Virginia Access (VAccess) is a regional, remote sensing and Geographical Information Sciences project among several educational institutions. It is a prototype for regional projects in other states and other countries, and is funded by NASA's applications program. The user communities VAccess serves are the Commonwealth of Virginia and State of Maryland, local and regional users represented in a Technical Advisory Committee. Remote sensing data include global NASA and NOAA data tailored for regional applications as well as high-resolution multispectral (Landsat, MODIS, etc.), hyperspectral, LIDAR and SAR data sets. Broad beam LIDAR technology can provide canopy structure as well as other information for environmental concerns such as the state of wetlands. The data information system is based on a distributed architecture to serve remote sensing and GIS data to a variety of users via the WWW. Several remote sensing and GIS-based environmental and Earth systems science applications projects are discussed here, including flood and fire hazard mitigation, forestry, land use/land cover and epidemiology projects; as well as innovative data fusion, data access and analysis and various tools serving the users and their applications.

Desertification is a land degradation problem of major importance in the arid regions of the world. Deterioration in soil and plant cover have adversely affected nearly 70 percent of the drylands as mainly the result of human mismanagement of cultivated and range lands. Overgrazing, woodcutting, cultivation practices inducing accelerated water and wind erosion, improper water management leading to salinisation, are all causes of land degradation. In addition to vegetation deterioration, erosion, and salinisation, desertification effects can be seen in loss of soil fertility, soil compaction, and soil crusting. Combating desertification involves having an accurate knowledge on a current land degradation status and the magnitude of the potential hazard. We present here a new project that aims at deriving a global simplified Land Degradation Index (LDI) from hyperspectral remote sensing data. Indeed, specific soil properties directly linked to soil degradation status, such as chemical properties, organic matter content, mineralogical content, soil crusting, and runoff, as well as vegetation content and degradation status, could be derived from high-spectral resolution imagery. Then, global maps assessing drylands desertification status could be routinely developed. This paper, after a brief review of land degradation processes and assessment, discusses the capabilities of hyperspectral imagery for land degradation assessment.

Based on previous studies that showed significant correlation between crusted soil and their reflectance properties, we applied a systematic study over Loess soil from Israel using Hyperspectral (or Imaging Spectroscopy) technology. A simulation for rain events under laboratory conditions, using the selected soil and varying rain energy treatments was conducted and reflectance properties of the crusted soils were measured. A spectral parameter defined as a Normalized Spectral Area (NSA) was used to assess for the crust status (based on the area under a ratio spectrum relative to a known non-crusted soils' plot). The NSA laboratory parameter was applied to the AISA data using ground controlled soil plots (crusted and non crusted). A reasonable agreement was obtained between the two data sets (laboratory and air) suggesting that infiltration rates values can be estimated remotely. It is strongly suggested that future study, will use the full optical range (VIS-NIR-SWIR-TIR) in the IS technology to map the crust status in a better precise way.

A remote sensing campaign was performed in September 2001 at night-time in order to assess the level of optical pollution due artificial illumination due to cities and industries. Two hyperspectral sensors, namely the MIVIS and the VIRS-200, which provide a spectral coverage from the visible up to the thermal infrared, were flown over the Tuscany coast (Italy) on board of a Casa 220 airplane. The acquired images showed a maximum scene brightness almost equal to that observed during similar day-time measurements, while their average luminosity was three orders of magnitude lower. The measurements, performed under clear-sky conditions during a moonless night, confirmed that artificial illumination produces noticeable effects even at great distance from the considered sources.

Remote Sensing provides a diversity of data from the superficial environmental, which can be manipulated and analyzed by Geographic Information Systems (GIS) to extract information relevant to the understanding of environmental hazards. This applies especially to the study of desert conditions, desertification monitoring, assessment and mapping. This contribution utilizes remote sensing data and techniques to evaluate the biological and physical parameters related to land degradation and desertification, such as water, vegetation, geomorphology, drainage system, soil moisture, etc. Multi-temporal analysis of Landsat TM images is used to monitor the effects on vegetation of the increase in areas of irrigation during the period of 1983-1997. The analysis clearly demonstrates a net decrease in vegetation cover. This situation exemplifies the deterioration of the natural vegetation cover. A Geographic Information System was used to combine and interpret a range of parameters (land use, soil type, topography, climate, etc.). A result of this GIS analysis is the provision of maps showing water erosion, wind erosion, vegetation degradation and salinization. A final stage of this research was the construction of a

The 'Tenuta di Castelporziano' (Castelporziano Presidential Estate) is an important area for the study of Mediterranean coastal and dune ecosystems. The need of providing a new and detailed Vegetation Map rose for the environmental monitoring of that area and its efficient management. All activities were developed using remote sensing images acquired by a new 12 band DAEDALUS sensor, in the course of a specific monitoring aero-campaign organized by ENEA. The realization of the map, lasted one year, can be divided into two blocks: (1)remote sensing image processing methodologies, developed at the ENEA-Casaccia Research Center (Rome), by experts of Remote Sensing Department; and (2) 'in situ' work, realized by ecologists and botanical experts of University of Rome 'La Sapienza'. Image processing steps were organized as follows: (i) geometric correction and georeferencing of the images; (ii) classification; (iii) mosaicking; (iv) conversion into vector layer and editing. As concerns image processing, ERDAS/IMAGINE system was used, while ARC/INFO system was used for vector layers management and map printing. At the end of all activities the map accuracy was tested by a statistical procedure: the global accuracy was about of 88%. The map is integrated in a information system (SITAC), a GIS realized by ENEA.

Environment preservations of the forest become world-widely close-up. The remote sensing technologies by satellite have been used for observation of the forest. However, the observation system on the ground is also needed because the remote sensing by satellite is seriously hindered by atmospheric phenomena and detailed data are necessary for precise analysis of the state of forest. Therefore we developed a multispectral infrared camera system for plant healthiness monitoring. The infrared camera system has five infrared bandpass filters. A hue is defined from the five infrared images. We performed several experiments to confirm that the hue changes according as the plant healthiness decline. In this paper, we propose a plant healthiness evaluation method by detecting hue changes with time. Experimental results of observation of hue changes of a plant through a day using the multispectral infrared camera system are shown. The results show that hue in healthiness parts of plants are more stable than in weak parts when the circumambient conditions such as the sunshine condition are changed.

Almeria, holding the only dessert area of continental Europe, is a semiarid province located southeast the Iberian Peninsula. The development status of the different counties of the province is widely different. Near the coast, greenhouse growing and tourism have generated an extremely active economic area. On the other side, inner areas of the province have gone down economically, with the reduction of mining and classic grows. In order to analyze new development alternatives, we built ESTIARA-Sig for the Ministry of Agriculture of Andalusia; our main objective developing this GIS was to catalog the different resources of the whole province to support development decisions. It includes four types of information: a) alphanumeric data (36 groups/tables, relative to statistics and resources), b) vectorial data (including the cartography), c) raster geographical data (obtained from satellite images, they let us to differentiate specifically greenhouse growing, populated and other areas), and d) photographic images (including types of constructions or special locations). A dynamic user interface was added to facilitate its use. In this work, we present main characteristics of the system and analyze their use along last six years, presenting as conclusions the experience obtained in order to develop a new version.

Urban green is recognized as an important functional element of the city, which affects directly the standard of living. The present paper is concerned with the study of urban green by means of object-oriented image analysis of high-resolution IKONOS data. More specifically, the potential for detecting urban green and quantitatively assessing it was explored. The analysis included two levels of segmentation and classification. On the first level, objects to which the image was segmented were subsequently classified according to a vegetation index (Scaled MSAVI) to areas with dense, thin or no vegetation. On the second level the image was classified in larger areas that simulated building blocks according to the relative area of vegetation, in order to create a thematic map of urban green density. The evaluation of the results indicated that detection and quantitative assessment of urban green was achieved with satisfactory accuracy. The use of additional data (DEM, hyperspectral, GIS) will allow a more detail study of the urban green from high resolution data by means of object-oriented image analysis

The Virescence Separator of Beijing, the capital city of China, is a virescence zone between the central area and the edge group as well as the zone among different edge groups, within irregular shape and the total area of 240 square kilometers. The construction of the Virescence Separator is a big and difficult project, an effective information system for planning and development with satisfactory performance is therefore essential. In this paper, the applications of remote sensing and GIS (Geographical Information System) technologies in BJVSIS (planning and development Information System for Beijing Virescence Separator), including three dimensional (3D) visualization, integrated databases management and multi-media technologies, were presented. The initial pilot project of BJVSIS was finished successfully in 2001, and up to now this information system runs very well and plays a great role in the construction of the Virescence Separator. Just depended on the applications of so many high-tech like GIS, remote sensing, 3D visualization, and databases integration, BJVSIS can manage all kinds of relevant geographic data, such as vector graphics, DEM (Digital Elevation Model), image and multi-media attributes. And BJVSIS also provides many GIS functions, such as spatial query, 2D/3D display, spatial analysis, statistic calculation, form report and map output.

The ESF-LSF 1997 flight campaign conducted by the German Aerospace Center (DLR) recorded several transects across the island of Naxos using the airborne hyperspectral scanner DAIS. The geological targets cover all major litho-tectonic units of a metamorphic dome with the transition of metamorphic zonations from the outer meta-sedimentary greenschist envelope to the gneissic amphibolite facies and migmatitic core. Mineral identification of alternating marble-dolomite sequences and interlayered schists bearing muscovite and biotite has been accomplished using the airborne hyperspectral DAIS 7915 sensor. Data have been noise filtered based on maximum noise fraction (MNF) and fast Fourier transform (FFT) and converted from radiance to reflectance. For mineral identification, constrained linear spectral unmixing and spectral angle mapper (SAM) algorithms were tested. Due to their unsatisfying results a new approach was developed which consists of a linear mixture modeling and spectral feature fitting. This approach provides more detailed and accurate information. Results are discussed in comparison with detailed geological mapping and additional information. Calcites are clearly separated from dolomites as well as the mica-schist sequences by a good resolution of the mineral muscovite. Thereon an outstanding result represents the very good resolution of the chlorite/mica (muscovite, biotite)-transition defining a metamorphic isograde.

ASTER sensor aboard NASA's Terra satellite has the capability of measuring multispectral thermal infrared (TIR) emission from the earth's surface to space. The author proposed indices by the combination of ASTER-TIR bands for detecting quartz and carbonate minerals, and another index to estimate the abundance of bulk SiO₂ content in the surface silicate rocks, applied them to the low level ASTER radiance at the sensor data without atmospheric corrections, and showed a potential ability of the indices in a rock type mapping. This paper tries to apply the proposed method into the practical case studies using ASTER-TIR data. The study sites include ophiolitic belt zones in Oman and along Yarlun Zangbo River in Tibet. The applied results are compared with the geology of the study areas. It indicates that the new remote sensing approach proposed here would improve the quality and the cost of the geological mapping in arid and semi-arid regions.

The identification of active faults (faults potentially capable to trigger an earthquake) is important for a seismically active country like Greece. Remote sensing techniques and GIS analysis were used in order to detect, map and characterize the tectonic structures of Psachna town and the surrounding area in central Evoia, Greece. Geometrically corrected and processed Landsat ETM+ data are used for the lineament analysis. The expert knowledge for the interpretation of the lineaments was used against algorithm and other automatic methods in order to increase the qualitative accuracy of the method. The refined lineament map, the seismic data of about the last 40 years, the Quaternary formations map, and the drainage anomalies map were integrated in a GIS. The proposed model examines and classifies every lineament based on a set of predefined criteria. The classification system is in accordance with the official regulations for neotectonic mapping in Greece and consists of four classes: active fault, possible active fault, inactive fault and lineaments. Further analysis of the active and possible active faults shows two sets of directions, NW-SE and ENE-WSW striking. Both directions are in accordance with the extensional tectonic regime in the central Evoia in Pliocene and Middle - Upper Pleistocene, respectively.

This paper discusses the recognition of geological lineaments seen in multispectral images of the Earth collected at optical wavelengths. The possibility of discerning jointing of rocks from natural and artificial image objects is thoroughly discussed. This problem is addressed by using an original image classification algorithm that enables us to detect urban areas and rivers. Once that a reliable sub image freed from possible artefact causes is isolated the true analysis of linear features is performed. This analysis takes advantage from the use of the Hough transform, in order to carry out the automatic identification of linear features and their analysis. The performance of the algorithm has been investigated by processing high resolution aerial photogrammetry and Thematic Mapper images. Tests as far executed have shown a good ability of the algorithm to accurately map image spatial features with linear morphology, and very rare occurrence of mix-up with different image objects.

This paper illustrates the results of an experiment carried out using a fluorescence imaging lidar system with an Optical Parametric Oscillator (OPO) system as the excitation source. Fluorescence spectra of various samples of limestones, sandstones and mortars typically used in the building of historical monuments were investigated exciting at five different wavelengths in the UV region. The spectra were analyzed to produce thematic maps by using multivariate analysis. Besides giving the possibility to identify the optimal excitation wavelength for each specific lithotype or material, the experiment offers prospects for an improved method for the characterization of different materials based on a combined multivariate analysis of fluorescence spectra obtained at different excitation wavelengths.

The primary mission objective of a new small Bi-spectral InfraRed Detection (BIRD) satellite, which was put in a 570 km circular sun-synchronous orbit on 22 October 2001, is detection and quantitative analysis of high-temperature events (HTE) like fires and volcanoes. A unique feature of the BIRD mid- and thermal infrared channels is a real-time adjustment of their integration time that allows a HTE observation without sensor saturation, preserving a good radiometric resolution of 0.1-0.2 K for pixels at normal temperatures. This makes it possible: (a) to improve false alarm rejection capability and (b) to estimate HTE temperature, area and radiative energy release. Due to a higher spatial resolution, BIRD can detect an order of magnitude smaller HTE than AVHRR and MODIS. The smallest verified fire that was detected in the BIRD data had an area of ~12 m². The first BIRD HTE detection and analysis results are presented including bush fires in Australia, forest fires in Russia, coal seam fires in China, and a time-varying thermal activity at Etna.

Clouds and the Earth's Radiant Energy system (CERES) sensors provide accurate measurements for the long-term monitoring of the Earth's radiation budget components such as reflected shortwave and emitted longwave radiances. CERES instruments has three scanning thermistor bolometers that measure broadband radiances in the shortwave (0.3 to 5.0 micrometer), total (0.3 to >100 micrometer) and in 8 - 12 micrometer water vapor window regions. Two of the CERES instruments (Flight Models 1 and 2(FM1&2)) are part of ESE Terra mission and has been successfully making Earth radiance measurements for the past two years. The CERES sensors are calibrated in flight using the on-board blackbody sources and a tungsten lamp known as internal calibration module (ICM) as well as a solar diffuser plate known as the Mirror Attenuator Mosaic (MAM). The ICM calibrations is used to determine the sensor measurement precisions during the ground, ground to orbit, and the on-orbit phases of the sensor calibrations. The MAM calibrations define on-orbit shifts or drifts in shortwave and total sensor responses. The traditional validation studies conducted to understand the stability of the sensors' performance include the analysis of Tropical Mean (TM) value using nadir tropical ocean measurements and three channel intercomparison between sensors of the same instrument. With two CERES instruments on the same platform, an additional study utilizing direct comparison of similar sensor measurements viewing the same geolocation is also conducted. The ICM results have shown that total sensors on both instruments have shown a variation of 0.25 and 0.5 percent respectively, whereas the shortwave sensors show a minimal change of 0.2 percent each. With high variability during the initial year, the MAM results have stabilised within the 0.5 percent precision range in the second year. The validation studies have shed additional light into the behaviour of total sensors in the shortwave and longwave spectral regions. The TM longwave day night difference (DN) derived from longwave sensors of each CERES instrument indicate that the FM1 sensors have varied about 0.25 watts m^-2sr^-1, whereas the total sensor in FM2 has a gradual rise of 1.4 watts m^-2sr^-1 in a 30 month period. This paper discusses briefly the contribution of each calibration and validation study in understanding the CERES sensors' behavior and the results from both Terra instruments' sensors. It also discusses how the various analyses are put together in understanding the rise seen in the total sensor of FM2 instrument.

This paper presents a new approach aiming to build an intelligent sensor exploiting a statistical model, discovered by the application of the radiative transfer theory and its use in the remote sensing domain. Its purpose is to interpret inhomogeneous scenes, particularly in mountainous regions covered by snow.

The objective of the present research effort was the investigation of expert system classification techniques for land use mapping from very high resolution images for a typical Greek landscape. Data used included an IKONOS image of the Arkadi area in Crete acquired on September 2000, and a digital terrain model. Photointerpretation was carried out using color composites, band ratios and maps of scale 1:5.000 and 1:50.000. Maximum likelihood was used for per pixel supervised classification and its accuracy was 72%. A knowledge base containing 51 rules, 44 hypotheses and 12 variables was developed in the Expert Classifier module of ERDAS Imagine. A hierarchical organization of thematic classes was developed in four levels through photointerpretation and study of the spectral reflectance diagrams and thematic class histograms. The image was first classified into three general categories: water-like, vegetation-like and soil-like materials. These were then separated into sub-classes. Classification rules were enriched with ancillary data such as the slopes, the road network, the NDVI vegetation index, the results of a spatial model computing texture, and indices reflecting the polygon shape and perimeter. Overall accuracy of the classification with the expert system was 82%.

Atmospheric correction is a complex process, which requires substantial modelling and computation, and a major difficulty is to obtain appropriate input parameters for the models. Numerous investigators have dealt with the development of simple or sophisticated approaches for the atmospheric correction of satellite images. However there is uncertainty about the effectiveness of such techniques especially when dealing with historical datasets in which input parameters for atmospheric models prove difficult to be obtained. The use pseudo-invariant targets in conjunction with radiative transfer calculations is an alternative atmospheric correction technique which offers a relatively simple mean of removing atmospheric effects in multi-temporal series of image data; providing that suitable pseudo-invariant targets can be easily identified on the satellite images and records on the their spectral characteristics are available. The spectral data of the proposed pseudo-invariant targets can be easily found in the literature from other studies. Indeed, this paper explores the need for identifying suitable pseudo-invariant targets, which are large in size, distinctive in shape and common in many geographical areas. This paper presents an application of use pseudo-invariant targets for removing atmospheric effects from Landsat TM and ETM+ satellite imagery acquired over different geographical areas such as in UK, Cyprus, Kazakhstan and Greece for environmental applications.

For some years sensor systems have been available providing digital images of a new quality. Especially aerial stereo scanners acquire digital multispectral images with an extremely high ground resolution of about 0.10 - 0.15m and provide in addition a Digital Surface Models (DSM). These imaging products both can be used for a detailed monitoring at scales up to 1:500. The processed georeferenced multispectral orthoimages can be readily integrated into GIS making them useful for a number of applications. The DSM, derived from forward and backward facing sensors of an aerial imaging system provides a ground resolution of 0.5 m and can be used for 3D visualization purposes. In some cases it is essential, to store the ground elevation as a Digital Terrain Model (DTM) and also the height of 3-dimensional objects in a separated database. Existing automated algorithms do not work precise for the extraction of DTM from aerial scanner DSM. This paper presents a new approach which combines the visible image data and the DSM data for the generation of DTM with a reliable geometric accuracy. Already existing cadastral data can be used as a knowledge base for the extraction of building heights in cities. These elevation data is the essential source for a GIS based urban information system with a 3D visualization component.

C-band SAR interferometry using ERS data has been shown to be potential for urban areas studies. This work illustrates the application of Principal Components Analysis (PCA) to a multi-temporal set of ERS coherence images to detect urban areas and their features. In particular Principal Component Transformation was applied on sets of one-day and long-term coherence images for urban mapping applications in the area of Naples, Italy. Two main classes, urban and non-urban, which then included two classes each, were considered in this study. Dense built-up areas and residential areas formed the urban class. Water bodies and vegetated areas (fields and woods) were grouped in the non-urban class. The first principal component was found to be more suitable than higher order components for detection of urban areas. Moreover, a simple algorithm based on distance between the first principal component of a pixel and the value representative for each class was tested for intra-urban mapping. Results showed that the first principal component could discriminate reasonably well between dense built-up and residential areas.

A 3-dimensional virtual landscape has been produced of Al-Madinah Al-Munwwarah in Saudi Arabia. A Triangular Irregular Network (TIN) interpolation method has been used to create a digital elevation model (DEM) from digital topographic maps at 1:1000 scale. High resolution aerial photography has been merged with satellite imagery to drape over the DEM. The resultant DEM, and fused overlay images, has been imported into Internet Space Builder software in order to add several attributes to the scene and to create an interactive virtual reality modelling language (VRML) model to support walk-throughs of the scene.

The multi-spectral, multi-line and muliti-stereo HRSC airborne pushbroom imager provides digital ortho-images and digital surface models with a position accuracy of 10 to 20cm. Since the first experiments carried out in 1997, coverage of more than 150 cities and large areas have been acquired and processed in Europe and the USA.The spatial resolution and ground coverage of the HRSC-A, HRSC-AX, HRSC-AXW models of the imager can be varied due to flight altitude during operational airborne flights to give images from 10cm to 100cm in terms of spatial resolution and from 1km to 10km swath width, depending on the particular model of the HRSC that is used for the flight.

The international EU-funded SIBERIA project (1998-2000) aimed at the production of an extensive forest map using spaceborne SAR data acquired by the ERS and JERS satellites. For a large geographical region (900.000 km2) located in the Central Siberian Plateau, one-day ERS coherence and JERS backscatter were used to retrieve growing stock volume. A classification algorithm based on peaks in the coherence and backscatter histograms was used. Four volume classes, water and open land were considered. An independent test in 10 areas showed an accuracy above 80%. The produced forest map serves as a tool for the sustainable management of Siberian natural resources and for a better understanding of the role of boreal forests in climate change. The objective of the international EU-funded SIBERIA-II project (2002-2005) is to demonstrate the viability of full carbon accounting, including all greenhouse gasses, with a multi-sensor approach over a 2 million-km2 area in Siberia. Having recently started, a general overview of the aims and the objectives of the project is given. Using several satellite observations available and the SIBERIA database, the first step consists in the generation of several Earth Observation (EO) products (such as biomass, phenological parameters, soil moisture, snow cover etc). Together with land-cover information from local institutions, these products will be input to two dynamic vegetation models for full regional carbon accounting. To increase knowledge, additional products such as Afforestation-Reforestation-Deforestation and fire scars maps are planned.

At present, gas pipeline networks in Europe are routinely monitored by vehicle and air patrols to protect them against damage by soil movement and third part interference. Because of the expenses, pipeline operators are investigating the possibilities to replace these traditional monitoring methods by remote sensing from space. A preliminary analysis shows that considerable savings can be achieved by deploying a user network of ground stations to receive the Synthetic Aperture Radar (SAR) data of the ENVISAT, RADARSAT-2, ALOS and TerraSAR satellites.

In SAR images, direct geocoding accuracy is affected by the input parameters, such as orbit data, height values introduced in the ellipsoid equation, and approximate geodetic coordinates. Specifically, the approximate coordinates, required for every pixel in the image by direct geocoding, contain errors due to pixel misidentifications on the map, to topographic maps, DEM and gravimetric to orthometric model. This paper describes a method, which evaluates the accuracy of the approximate coordinates introduced in the direct geocoding method for any pixel in the image, without the 'true' geodetic values being known. The method is based on the 'pseudo-errors' produced by the subtraction of the calculated by the direct geocoding method coordinates, from the approximate input coordinates introduced in the method. Evaluation of the above method is performed using three test points and four reflectors. It is shown that for the pixels of the SAR image, the corresponding evaluated geodetic coordinates when introduced as control points in the indirect geocoding process may produce geocoding results of accuracy higher than 1.4 ERS pixels. The method is useful if no reflector is located in the study area, because it produces four times better accuracies, compared to those usually produced by indirect geocoding.

Speckle noise is a common phenomenon in SAR images. The reduction of Speckle is necessary for any further processing of SAR image such as segmentation, classification and other procedures for information extraction. In this paper, after a brief review of conventional filters for SAR speckle reduction, a wavelet-based soft-thresholding filter for SAR speckle reduction is presented. To evaluate the performance of this filter, the adaptive local statistics filters, which include Lee, Frost, Enhanced Lee, Enhanced Frost, Kuan, and the Gamma-Map filter are applied to the speckle reduction for a same typical SAR image. The performances are compared in several aspects including Radiometric preservation, feature preservation, speckle reduction in extended uniform regions and the absence of artifacts. The results show that the wavelet-based speckle reduction filter performs better in every aspect in evaluation than the conventional filters do.

Thematic maps are increasingly derived from satellite imagery using automatic classification methods. However, whereas most classification algorithms operate at the pixel level, map users usually are interested in information at the landscape unit with minimum mapping unit of several hectares. Consequently, most land cover mapping operational programs with satellite images (e.g. CORINE Land Cover) are still based on visual analysis. In this paper, we present a methodology developed by the Remote Sensing Group of the Portuguese Geographic Institute (IGP) to automatically generalize satellite-derived land cover maps using priority rules. Operations include exaggeration, merging, aggregation and amalgamation. The initial map may have any number of information classes, with the user assigning the priority of each class according to the purpose of the final map within a table. This priority table is used to define a cost-distance map for the aggregation of different classes. Generalization is accomplished by integrating existing spatial analysis functions using map algebra. The methodology was implemented in a well known commercial GIS software and allows the production of land cover maps at different minimum mapping units by operating on a raster map resulting from per pixel classification of satellite imagery. The methodology was successfully tested in a study area in Central Portugal.

With the increasing maturity of distributed object technology, CORBA, .NET and EJB are universally used in traditional IT field. However, theories and practices of distributed spatial database need farther improvement in virtue of contradictions between large scale spatial data and limited network bandwidth or between transitory session and long transaction processing. Differences and trends among of CORBA, .NET and EJB are discussed in details, afterwards the concept, architecture and characteristic of distributed large-scale seamless spatial database system based on J2EE is provided, which contains GIS client application, web server, GIS application server and spatial data server. Moreover the design and implementation of components of GIS client application based on JavaBeans, the GIS engine based on servlet, the GIS Application server based on GIS enterprise JavaBeans(contains session bean and entity bean) are explained.Besides, the experiments of relation of spatial data and response time under different conditions are conducted, which proves that distributed spatial database system based on J2EE can be used to manage, distribute and share large scale spatial data on Internet. Lastly, a distributed large-scale seamless image database based on Internet is presented.

A systematic plan of building Web Geographic Information System (WebGIS) using ActiveX technology is proposed in this paper. In the proposed plan, ActiveX control technology is adopted in building client-side application, and two different schemas are introduced to implement communication between controls in users¡¯ browser and middle application server. One is based on Distribute Component Object Model (DCOM), the other is based on socket. In the former schema, middle service application is developed as a DCOM object that communicates with ActiveX control through Object Remote Procedure Call (ORPC) and accesses data in GIS Data Server through Open Database Connectivity (ODBC). In the latter, middle service application is developed using Java language. It communicates with ActiveX control through socket based on TCP/IP and accesses data in GIS Data Server through Java Database Connectivity (JDBC). The first one is usually developed using C/C++, and it is difficult to develop and deploy. The second one is relatively easy to develop, but its performance of data transfer relies on Web bandwidth. A sample application is developed using the latter schema. It is proved that the performance of the sample application is better than that of some other WebGIS applications in some degree.

Nisyros is a poorly known Quarternary volcano, south-east of the Agean volcanic arc. It is characterized by periods of intense seismic activity and paucity in reruptive episodes, sometimes accompanied by hydrothermal explosions. The most recent unrest episode lasted from 1995 to 1998, without eruption. Radar interferometry has been applied in order to study the evolution of the deformation from 1995 to 2000. Observations show a continuous uplift of 140mm during 1995-1997. At mid 1998, the movement trend changes into a slower surface deflation til 2000. Maximum crust deformation is constantly observed at the north-west part of the island, where most earthquake epicenters are located and in agreement to three GPS campaigns conducted between mid 1997 and mid 1998. We solve for the best-fit Mogi point source and best-fit Okada rectangular dislocation of the observed deformation field. Mogi model indicates a source at 5km depth beneath the north-west edge of the island, with a maximum deformation amplitude at surface of 0.14 plus or minus 0.02m and a total volume change of 26 plus or minus 4 × 10⁶ m³, during 1995-1997. The Okada model indicats a dike solution 2km long, 2.2km wide, wiht a 4m opening and a 30° dip. The upper center is at 6.4km depth and the volume change, also during 1995-1997, is 17.6 × 10⁶ m³. Each solution is discussed on the potential controlling mechanism resulting to the volcano's inflation/deflation sequence.

Ground-based Synthetic Aperture Radar (GB-SAR) interferometry is used to monitor the Tessina landslide. This is a complex mass movement in the Italian Eastern Alps. Radar data, acquired during a 10-day campaign, are interferometrically processed. Image couples taken at the same position but at different times are used to estimate terrain slope deformations on a short temporal scale of a few hours. In addition, SAR images acquired with a baseline are processed to extract information on the current topography of the landslide area. Comparison with the terrain morphology of the scene at earlier times allows to evaluate the landslide activity on a long time scale spanning a few years.

This work assessed the suitability of hyperspectral data for estimating mudflat surface characteristics related to stability. Due to the inaccessibility of intertidal areas, precise ground-based measurements of mudflat stability are difficult to conduct. Remote sensing can provide full spatial coverage and non-intrusive measurement. As stability changes on mudflats are linked to subtle differences in mudflat surface characteristics, they can potentially be mapped by hyperspectral data. Hyperspectral images were collected along with near contemporary ground measurements. An unsupervised classification gave a map which confirmed that a channel bar was mainly sand whereas soft mud dominated an adjacent embayment. Multiple regression analysis was used to relate surface characteristics to hyperspectral data to construct regression equations. Erosion shear stress was estimated directly from the hyperspectral data and also by a relationship with the surface characteristics. The results of the thematic class map matched well with the known situation at the site during image acquisition. The maps of surface characteristics highlighted the additional information that can be extracted from hyperspectral data. Stability maps, based on the erosion shear stress, can be used as a basis for predicting the likely future behaviour in this dynamic environment and will be of use for coastal zone management.

The problems associated with the selection of the optimum band combination have been recognised since the early days of the Landsat MSS. Although this instrument consists of only four bands, it was soon realised that the number of bands would increase as the technology advanced. Obviously, to generate and analyse every combination of bands is potentially time-consuming. Various statistical methods of choosing the band combination containing the most information for environmental and geological studies such as optimum index factor, maximum variance-covariance determinant, and principal component analysis have been introduced. In order to evaluate the applicability of these methods to landslide studies, the eleven band Airborne Thematic Mapper (ATM) imagery of the inland slopes of Stonebarrow Hill in West Dorset, England was used. These slopes are extensively mantled with relict landslide features. The best band combination results obtained from these methods are evaluated against the visually checked imagery, where all possible bands are generated and classified in terms of texture and colour. The ability to express the texture and colour in the composite imagery that might be related to the landslide features are crucial in landslide studies.The results showed that all these statistical methods are not suitable to be used in landslides study. However, from early visual classification results showed that two combinations of three bands from three different wavelengths produced the best composite image.

It is becoming increasingly recognized that computer methods such as models and Geographic Information Systems (GIS) can be valuable tools for analyzing a geographical area in terms of it's hazards vulnerability, Vulnerability is an important aspect of households' experience of poverty. The measurement and analysis of poverty, inequality and vulnerability are crucial for cognitive purposes (to know what the situation is), for analytical purposes (to understand the factors determining this situation), for policy making purposes (to design interventions best adapted to the issues), and for monitoring and evaluation purposes (to assess whether current policies are effective, and whether the situation is changing). Here vulnerability defined as the probability or risk today of being in poverty - or falling deeper into poverty - in the future. Vulnerability is a key dimension of well being since it affects individuals' behavior (in terms of investment, production patterns, coping strategies) and their perception of their own situation. This study has been conducted with the joint collaboration of World Food Programme (WFP) and International Water Management Institute (IWMI) in Sri Lanka for identifying regions and population which are food insecure, for analyzing the reasons for vulnerability to food insecurity in order to provide decision-makers with information to identify possible sectors of intervention and for identifying where and for whom food aid can be best utilized in Sri Lanka. This new approach integrates GIS and Remote sensing with other statistical packages to allow consideration of more spatial/physical parameters like accessibility to economic resources, particularly land and the assets of the built environment, creating employment, and attracting investment in order to improve the quality and quantity of goods and services for the analysis which leads the analysis to represent the real scenario. For this study a detailed topographic data are being used along with MODIS EVI (Enhanced Vegetation Index)

Many researchers consider coral reefs the 'rainforests of the oceans' because they cover such a small area and yet provide homes for literally thousands of unique marine species. A multispectral or hyperspectral remote sensing satellite, with its spectral coverage, offers iadvantages over traditional methodologies for coral reef surveying, monitoring, and mapping. This apper presents research into the suitabilty of spectral remote sensing for coral reed surveying, monitoring and mapping. This paper presents research into the suitability of spectral remote sensing for coral reef surveying, monitoring and mapping using the SeaWiFS multispectral ocean color data for illustration. We describe the information technology developed to support this research and provide an overview of the database driven web application, which was developed to allow live interaction with the data. A database of in situ observations from the ReefBase web site was used as validation data as part of this investigation. This discussion includes details on the XML representation of the satellite and in situ data and metadat. It also introduces a dynamic Java Visualization applet developed to allow the users to visually interact wiht the data. The paper concludes wiht a discussion of the suitability and additional advantages of using hyperspectral remote sensing technology for this application that exploits the full spectral characteristics of submerged coral reefs.

This paper is a preliminary study of an extensive project that will take place at Corfu island (Northern island of Ionian Sea), involving the municipality of Esperion and the Remote Sensing Laboratory (University of Athens). The project's purpose is to estimate the erosion progress at Sidari bay's (North part of Corfu island) coastal zone, due to wave activity. Sidari area consists of Neogene formations, which are extremely vulnerable. Moreover, wave impact is also of high energy, causing subsidence of the coastal line. Through this project, our team is developing a GIS database that holds information, deriving from existing maps, bibliographical references, and climatological logs, related to geology, geomorphology and environmental parameters. Apart from those data, aerial photography stereo-observation and extensive D-GPS fieldwork resulted to continual coastline monitoring and GIS database updating, for a period of 26 and 5 years, respectively. Project's conclusions are based on quantitative and spatial analysis through GIS, giving answers on the erosion's rate, the erosion's impact on human activities and structures, and finally an estimation on Sidari's coastal zone future morphology.

In this paper we study the coastal zone in the region of Acheloos' River mouth and delta. In recent yeras, this region has been subjected to a series of environmental changes, primarily due to intense human activity concerning large hydroelectric dams. These dams created between 1960 and 1986 are responsible for important changes of the river's flow. The purpose of this study is to record the changes that have occurred between those yeras and present time; to define and analyze their possible consequences on the coastal geomorphology of the region. For this reason we used topographical and geological maps, aerial photos and finally satellite photos. A geographical database has been created in a GIS with environmental, geological, geomorphological and anthropogenic features of the studied aera. All digital data were analyzed spatially and quantitative in order to describe the change of delta shape, size and finally the occupied land use. Finally different thematic maps were created showing the geomorphological and environmental changes during those years.

Danube delta, one of the largest European wetlands left, lies predominantly in Romania, being considered a Biosphere Reservation. Environmental impact assessment and detection of spatio-temporal changes is needed for protection, conservation and restoration of the biological diversity specific to this area. Danube Delta wetlands and aquatic ecosystem are increasingly endangered by global or regional environmental changes due to the discharges or deposition of excess nutrients and/or harmful substances, to the reclamation of lands for agriculture, forestry, and engineering of water flows. A multitemporal data set consisting of LANDSAT MSS, TM and SAR-ERS1 images for Romanian Danube River Delta was used for comparing and mapping landcover change via change detection. The main aim of this paper is to conduct a comprehensive analysis based on existing historical and more recent data to establish the link between phytoplankton bloom development and related harmful phenomena in the North-Western part of Black Sea and changes in the Danube watershed (landuse, fertilizer utilization, waste water treatments). Based on satellite data were analyzed some test areas in the vicinity of the Danube mouths where the nutrient concentration were highest, being assimilated with an expected oxygen depletion, sulfate reduction and methanogenesis in the bottom waters and the superficial sediments.

Remote sensing technologies are used to collect data that measure properties of materials that comprise the earth's surface, subsurface, and man-made features such as levees constructed of these materials. Scientists use, manipulate, and analyze these data to make inferences about levee materials as well as identify local areas where intensive field investigation resources might most efficiently be spent. In this current study, airborne LiDAR and electromagnetic (EM) conductivity data have been processed and integrated with other digital data to identify specific areas within a levee system where anomalies exist. Preliminary results support the idea that changes in material type and the presence of man-made, levee-perforating structures do cause recognizable effects on recorded EM conductivities. Planned site investigations at identified EM anomalous areas will focus the efforts of field crews to determine the causes and significance of anomalies. As the field season progresses and data from in situ testing of levee materials are analyzed, relationships between material types and the EM data will be represented in graphics. Results of the study will be used to calibrate a model with which levee systems can be assessed for compliance with certain design specifications as well as predicting performance during flood events.

In this paper we study Samaria gorge through recognition, recording and visualization of geomorphological characteristics. Geomorphological characteristics collected through Remote Sensing techniques, are compared with those collected through stereoscopic observation of aerial photos and fieldwork. At the first phase, the aerial photos of the studied area were scanned and through selected digital image processing algorithms, the geomorphological characteristics were stressed and recorded. At the second phase a geomorphological map was created based on data derived from stereoscopic observation of the area aerial photos and fieldwork. During fieldwork a GPS was used, which was connected with the GIS in order to immediately record and test the measured characteristic position. Finally the combination of two methods took place in order to develop a geomorphological map.

The aim of the present work was to implement and evaluate spatial filtering and automatic edge extraction techniques for assisting the geological lineament detection process. The selected study area was Alevrada in Central Greece, an area of sedimentary terrain with many faults and folds. A Landsat-7 ETM+ image of the study area was geometrically registered on the geological map, and then radiometrically corrected, to subtract the path radiance of the optical bands. Various linear and nonlinear spatial high pass operators (Laplacian, Ford, directional filters, Sobel, Kirsch) were applied and an interpretation of the lineaments was made. Certain edge detection algorithms introduced in medical imaging and scene analysis were applied and assessed, including the Canny multi-scale edge detector, the Rothwell edge detector based on edge topology and the Black's anisotropic diffusion edge detector, followed by morphological cleaning and pruning processes. The interpreted lineaments were qualitatively compared to the edge maps derived from the edge extraction algorithms, and a satisfactory matching was observed. This work provides a preliminary step towards lineament mapping automation.

Many of the known porphyry copper deposits are situated in the Central Iranian volcanic Belt. The area under study is located in the southern part of this belt and covers an area of about 2600 sq. kms. ETM+ images have been used for alteration mapping. Crosta method was found useful for enhancing the areas with hydroxyl and iron oxide minerals. However field checking has shown that this method is not able to enhance all the areas with hydrothermal alteration. In order to recognize such areas combination of remote sensing and geophysical data can be helpful. The Sar Cheshmeh mine is chosen as a control area. The data has been divided into two sets namely, explanatory and target variables. The target variables are rock geochemistry (Cu and Mo) and alteration data. The explanatory data are Landsat and airborne geophysical data (K and Th counts, and total magnetics). The data analysis is performed in two steps, (1) integration and analysis of target variables over the control area by principal component analysis method, and (2) transformation of explanatory variables by using the eigenvector loadings of the first step. This technique is found to be useful for the delineation of hydrothermaly altered areas with enough confidence.

Our paper describes an operational application of NOAA-AVHRR satellite imagery in combination with satellite-based land cover data for comprehensive observation and follow-up of 10 000 fire outbreak and of their consequences in Greece during summer 2000. At a first stage, we acquired and processed satellite images on a daily basis and we interpreted them in view to smoke-plume tracking and fire-core detection at national level. Information was acquired eight times per day and derived from all AVHRR spectral channels. At a second stage, we assessed the consequences of the fires by producing burnt-area maps on the basis of multi-annual normalised vegetation indexes using again AVHRR data but this time in combination with the European CORINE Land Cover database (CLC). The derived burnt-area maps compared successfully to the in-situ inventories available for that year. Our results showed burnt area estimates with an accuracy ranging from 88% to 95%, depending on the predominant land-cover type. These results, along with the very low cost and hi-acquisition frequency of AVHRR satellite imagery, suggest that the combination of moderate resolution satellite data with harmonised CLC data can be applied operationally for forest fire and post-fire assessments at national and at pan-European levels.

In this study, the design and implementation of a GIS based tool for the support of technological risk management is presented. This Decision Support Tool is based on the detection and space-time monitoring of plumes caused by technological accidents, by integrating moderate and high-resolution satellite imagery and in-situ spatial data. The Advanced Very High Resolution (AVHRR) on board the NOAA satellites has been used for the detection of fire as well as for the detection and monitoring of plumes. The detection algorithms have been presented in previous studies for past accidents in Europe. AVHRR images, were adjusted to the broader area of Athens in order to develop a major technological accident scenario based on real plumes. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on board the EOS AM-1 satellite has been used for the extraction of topographic information, land cover and spatial distribution of vegetation, as well as for the depiction of urban areas, road network and major industrial installations. The scenario was used to present the functionality of the developed GIS tool for the support of decision making during the crisis, as well as for the assessment of the accident's impact to natural and human environment.

The development of techniques for the detection of water leaks from underground pipelines is seen as a high profile activity by water companies and regulators. This is due to increasing water demands and problems with current leak detection methods. In this paper optical reflectance and microwave backscatter models (SAIL + PROSPECT and RT2) were used to try and identify optimal indices for detecting water leaks amongst a variety of different land cover types at different growth stages. Results suggest that red/near infrared and red/middle infrared ratios show potential for leak detection. Given the sensitivity of L-band radar to moisture, and the ability to separate contributions from canopy and ground surface, it is possible to detect saturated soils through vegetation canopies. The results of both approaches are used to infer limits of detection in terms of season and meteorological conditions for a range of land covers. Preliminary findings suggest that leaks may be optimally detected when canopy height is low, surrounding soil is dry, and the leak has been present for more than 14 days. The modelled data is compared with L - band fully polarimetric E-SAR data, and 200 channel HYMAP hyperspectral airborne data which were acquired over an 8km section of the Vrynwy aqueduct (UK), which included a high concentration of leaks. Data was acquired as part of the British National Space Centre (BNSC) and Natural Environmental Research Council (NERC), SAR and Hyperspectral Airborne Campaign (SHAC) in June 2000. The results from this work suggest that remote sensing is both an effective and feasible tool for leak identification.

The traditional approach to delineating and extracting features from remotely sensed images relies predominantly on manual interpretation, a procedure that is often time consuming and expensive. Automation offers the potential for reduced costs and wider utilization of remote sensing within the business community, but involves difficulty in representing the expertise of remote sensing scientists within a series of decision rules. The objectives of this paper are two-fold: firstly, to produce a system for automated feature discrimination in remotely sensed images, using leaks from water supply networks as a case study; and secondly, to test whether the system is suitable for use with the next generation of satellite sensors. The automated system was calibrated by integrating HyMap and Airborne Thematic Mapper (ATM) images with context data from a variety of sources (such as ambient irradiance environment; topography; land use, and field boundaries). The automated system was assessed for its applicability to satellite remote sensing by testing the system on airborne data that were degraded to the resolutions of satellite images. It is proposed in this paper that automation, particularly with respect to satellite remote sensing, makes leak detection from water supply networks commercially viable.

Satellite gaging reaches are polygonal land areas encompassing river and floodplain reaches where total surface water area expands and contracts as river discharge varies. Traditional gaging stations measure water level, or stage, as a surrogate for discharge. Such stations are commonly located where discharge changes are primarily accommodated by stage and not width changes. In contrast, we identify for testing purposes 191 gaging reaches distributed worldwide where multi-temporal remote sensing demonstrates significant water surface area variability. Typical reach lengths are 30 km and reach widths average 10-30 km. The gaging reaches are sufficiently wide to accommodate the largest floods. Measured water surface areas using the MODIS sensor 250 m resolution bands are converted to river characteristic widths (water area/river length) and, in the U.S., are compared to adjacent gaging station data. Preliminary results indicate that, along many U.S. gaging reaches, MODIS-derived widths are robust predictors of discharge. As is the case for in situ gaging stations, local width/discharge relations vary, and some reaches record discharge changes with greater precision than others. Time series of MODIS river characteristic widths can provide hydrologists and water resource managers with a geographically extensive and economical river monitoring capability

Remote sensing technologies with high spatial and spectral resolution show a great deal of promise in addressing critical environmental monitoring issues, but the ability to analyze and interpret the data lags behind the technology. Robust analytical methods are required before the wealth of data available through remote sensing can be applied to a wide range of environmental problems for which remote detection is the best method. In this study we compare the classification effectiveness of two relatively new techniques on data consisting of leaf-level reflectance from plants that have been exposed to varying levels of heavy metal toxicity. If these methodologies work well on leaf-level data, then there is some hope that they will also work well on data from airborne and space-borne platforms. The classification methods compared were support vector machine classification of exposed and non-exposed plants based on the reflectance data, and partial east squares compression of the reflectance data followed by classification using logistic discrimination (PLS/LD). PLS/LD was performed in two ways. We used the continuous concentration data as the response during compression, and then used the binary response required during logistic discrimination. We also used a binary response during compression followed by logistic discrimination. The statistics we used to compare the effectiveness of the methodologies was the leave-one-out cross validation estimate of the prediction error.

There has been a rapid growth of shrimp farm around Kung Krabaen Bay in the past decade. This has caused enormous rise in generation of domestic and industrial wastes. Most of these wastes are disposed in the Kung Krabaen Bay. There is a serious need to retain this glory by better water quality management of this river. Conventional methods of monitoring of water quality have limitations in collecting information about water quality parameters for a large region in detailed manner due to high cost and time. Satellite based technologies have offered an alternate approach for many environmental monitoring needs. In this study, the high-resolution satellite data (LANDSAT TM) was utilized to develop mathematical models for monitoring of chlorophyll-a. Comparison between empirical relationship of spectral reflectance with chl-a and band ratio between the near infrared (NIR) and red was suggested to detect chlorophyll in water. This concept has been successfully employed for marine zones and big lakes but not for narrow rivers due to constraints of spatial resolution of satellite data. This information will be very useful in locating point and non-point sources of pollution and will help in designing and implementing controlling structures.

We present test data for a solid ZnSe air gapped etalon with free spectral range 3 cm^-1 and finesse >70 (i.e., spectral resolution <0.043 cm^-1). We present an instrument concept, the Tropopsheric Ozone Sounding (TOS) Dual Etalon Cross Tilt Order Sorting Spectrometer (DECTOSS), that would use an etalon like this to acquire nadir data at resolution <0.06 cm^-1 and signal to noise the order 1000 on a range from 1036 to 1071 cm^-1 in footprints with crosstrack dimension selectable (e.g., the order tens to hundreds of km), and with along track dimension the order 17 km. Instrument accommodation is the order 25 kg, 110 W and 1 mbps. We present linear error analysis for retrieval of tropospheric ozone from the data acquired by the TOS-DECTOSS. Indication is that more than 2.5 vertical layers of information on tropospheric information are retrievable. An example of the deployment of the TOS-DECTOSS would be as an instrument of opportunity (IOO) add on to the US National Polar-orbiting Operational Environmental Satellite System (NPOESS). The huge advantage of the TOS-DECTOSS as compared with UV techniques for tropospheric ozone measurement is that it the can be used both day and night, the latter is not possible in the UV. The considerable advantage in signal to noise compared with a Fourier Transform Spectrometer (FTS) for tropospheric ozone measurement, on considering that for a given footprint the DECTOSS and FTS integration times are comparable, is that the DECTOSS noise per spectral sample is dominated by statistical fluctuations of signal photons that are passed through its narrow 0.06 cm-1 bandpass, while for a similar FTS spectral sample the noise is due to fluctuations of the signal photons through the FTS bandpass of tens of cm^-1. The TOS-DECTOSS signal to noise advantage on the FTS is also enhanced in that the spectral sample density of the TOS-DECTOSS data is more than one hundred times larger than for the FTS.

This study was submitted to access and report on land use changes in the prefecture of Heraclion in Crete. The period of interest is from 1995 to 2000, thne and July being the preferred months of study.

The objective of this research was the investigation of advanced image analysis methods for geomorphological mapping. Methods employed included multiresolution segmentation of the Digital Elevation Model (DEM) GTOPO30 and fuzzy knowledge based classification of the segmented DEM into three geomorphological classes: mountain ranges, piedmonts and basins. The study area was a segment of the Basin and Range Physiographic Province in Nevada, USA. The implementation was made in eCognition. In particular, the segmentation of GTOPO30 resulted into primitive objects. The knowledge-based classification of the primitive objects based on their elevation and shape parameters, resulted in the extraction of the geomorphological features. The resulted boundaries in comparison to those by previous studies were found satisfactory. It is concluded that geomorphological feature extraction can be carried out through fuzzy knowledge based classification as implemented in eCognition.

In this research work, an attempt has been made to study the ability of remote sensing data and some of the image processing techniques to map and monitor changes happened over a period of one year in an urban area. IRS 1B LISS II data pertaining to coastal city of Madras, India acquired in the month of April 93 and 94 were registered on each other using EASI/PACE image processing software. Band subtraction, PCA and fuzzy logic were then applied to create a new image showing changed and unchanged areas. MLC algorithm used to classify the images of 93 and this new image. To create change map, a simple procedural program was developed with modeling language of EASI/PACE image processing software. Based on the ground truth information the overall accuracy of classification was observed to be about 70 per cent. Results showed that in this urban area, major changes were observed to be from green areas to built-up area.

This paper proposes a geographical information system for terrain and obstacle awareness and alerting that extracts information from high-resolution satellite images. On-board terrain elevation databases are being increasingly used in aircraft terrain awareness and warning systems (TAWS), offering a step change in capability from the radar altimeter-based ground proximity warning system. However, to enhance the safety of flight of small aircraft and helicopters, in addition to pure topographic information a TAWS database should also contain significant man-made obstacles that present a collision hazard, such tall buildings and chimneys, communications masts and electrical power transmission lines. Another issue is keeping the terrain and obstacle database current, reflecting changes to features over time. High-resolution stereoscopic images remotely sensed from Earth orbit have great potential for addressing these issues. In this paper, some critical items are discussed and effective information processing schemes for extracting information relevant to flight safety from satellite images are proposed.

The most prominent artifact in line scanner images is a cross track brightness gradient, which is due to sensor optics, atmospheric and surface bidirectional effects. Those effects prevent a precise intra- and intercomparison of image scenes and affect spectral ratios. A method to improve the intra- and intercomparison of a set of images of the same surface type but from different times of the day by using a simultaneous correction of bidirectional effects is presented. It should be applied after sensor, atmospheric, and geometric correction, although all four effects interact with each other. But since the method is semi-empirical in nature it will also correct partly gradients from the other effects when applied solely. The method bases on the linear semi-empirical Ambrals model (Algorithm for MODIS Bidirectional Reflectance Anisotropy of the Land Surface, Lucht 2000). A ready-to-use software in IDL has been developed for line scanner images and is made available to the public for test. The adaptation to different sensor types is straightforward. As an example, images from the DAISEX'99 campaign in Barrax, taken with the wide FOV hyperspectral sensor HyMap from different flight directions and times of the day, are modeled and corrected. An intercomparison of the images and a validation is made.

A simple bio-optical model has been developed and used together with historical water quality measurements from Lake Mälaren, Sweden, to construct an algorithm for retrieval of chlorophyll concentrations from remote sensing data. The algorithm has previously been applied to CASI data from Lake Mälaren and the result was promising, but the model needed further validation on data from other lakes in order to investigate its generality. CASI data was also collected over the nearby Lake Erken and in this paper the same algorithm was applied to that data set and evaluated using ground truth measurements. The estimated chlorophyll concentrations were in average twice as high as the ground truth measurements. The CASI spectra were therefore compared to the reflectance spectra measured at lake level at all sampling stations in Erken during the campaign, and the correspondence was good. The overestimation of chlorophyll by the model derived algorithm can be explained by the fact that ground truth samples were taken below the surface, while the CASI measurements reflect the state on the surface, where accumulations were evident in the whole lake.

It is the GIS developing direction to integrate GIS with Internet. Internet GIS is not only used to publish distributed geographic information on line, but also to provide on line tools for distributed geographic information real-time analysis and processing. Internet GIS should make use of existing multi-sources and functions for geographic information analysis and processing. The distributed feature is inherent to geographic information, which needs distributed organization and processing approach. Internet GIS (Geographic Information System) is the integration of Internet and GIS, being used to implement publishing on line and distributed real-time analysis of geographic information. The problem of geographic information distributed management and processing should be solved by Internet GIS. This paper provides three approaches to the problem, especially the distributed component and Geo-Connector approach to Internet GIS. The distributed component method includes homogeneous, heterogeneous and conjoint methods, for the problem of distributed geographic information publishing and real - time analysis. With instance, the feasibility and practicability of distributed component method are interpreted in detail. The concept of Geo-connectors in GIS application server side for organization and management of distributed heterogeneous database is presented and a case of heterogeneous geo-data access and interoperability is studied

Linear unmixing of spectra from daytime Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images can be used to improve the spatial resolution of temperatures calculated for streams that are not fully resolved in the 90-m thermal infrared (TIR) data. We first examine ASTER 15-m Visible-Near Infrared (VNIR) data to select three endmembers using a simple automated technique. These endmembers correspond to vegetation, shade/water, and other scene components (e.g. urban/soil/non-photosynthetic vegetation). Then the 15-m VNIR data are unmixed into the three corresponding fraction images. Threshold and adjacency tests are used to separate the shade and water fractions creating a total of four fraction images that together are used to specify the amount of the scene components in each 90-m TIR pixel. The emitted thermal radiance (ETR) from each of the scene components can be estimated if we assume that it is the same as for a

Structures visible on soil profiles contain transport-relevant information (pedological horizons, boundaries between them, biopores, skeleton, and other macroscopic features). The knowledge of the shape and connectivity of such structures is a first order approximation for predicting flow and transport under given boundary conditions. We measure the spectral reflectance of exposed soil surfaces (e.g. on soil profiles, soil samples, or the horizontal soil surface) to map the geometry of such structural regimes. We make use of the fact, that reflectance of light by dense particulate media depends on complex refractive index, particle size, and porosity. We propose a light scattering model based on the four-flux approach of Maheu et al. to describe radiative transfer of visible light (VIS) and infrared radiation (IR) through soil slabs. Principal input parameters are wavelength, mean grain size, slab thickness, porosity and refractive index. In case of soil samples, where all parameters but one are known, the unknown can be estimated by comparing the measured and calculated reflectance and transmittance spectra. It follows for example, that the refractive index have to be known to solve the problem for the mean grain size. The refractive index for soils is rarely published. Therefore we demonstrate the variability of the refractive index for soils on the basis of three different soil materials. To test the model, we measured the reflectance and transmittance for soil samples as a function of particle size fraction and slab thickness. We found that the fitted complex refractive indices -- a constant of the material -- depend mainly on the type of soil material and less on particle size or slab thickness.

When we do aerial photography and an environmental research, a remote control helicopter (R/C helicopter) is excellent tool in the next point. For example, the cost of aerial photography and an environmental research work by R/C helicopter are low, also R/C helicopter pilot reservation fee are low price, and free from aviation law in Japan. But, R/C helicopter maneuvering and aerial photographing skills are necessary, and these are difficult to learn. Additionally, if the visibility of R/C helicopter is getting bad when it goes far away, operation is getting difficult. These problems are caused by the badness of autonomous stability on R/C helicopter system. In this study, we propose a new angle detection sensor for 3 axial rotations which is based on the development of the easy and safe steering system for the operation person.

The brightness temperature information by LANDSAT TM band 6 was analyzed and compared with the land cover information acquired from the high-resolution satellite, IKONOS, and the relationship between them examined.

The acquisition and storage of large amount of data coming from distributed environmental sensors of different kind can be solved with the aid of a network between the acquisition subsystems, but problems can arise if they are not homogeneous. In this case the network should be as flexible as possible to ensure modularity and connectivity. In this work we describe the development and testing of a network based acquisition system. The network uses, where possible, commercial products, based on different standards, in order to increase the availability of its components, as well as its modularity. In addition it is completely independent from proprietary hardware and software products. In particular we tested an acquisition network based on multiple transmission protocol, like wireless and cabled RS232 and Fast Ethernet, which includes the acquisition, archiving and data analysis systems. Each acquisition subsystem can get time from satellite using GPS, and is able to monitor seismic activity, temperature, pressure, humidity and electromagnetic data. The sampling frequency and the dynamics of the acquired data can be matched to the characteristics of each probe. All the acquisition stations can use different platform as well as different operating systems. Tests have been performed to evaluate the capability of long acquisition periods and the fault tolerance of the whole system.

Laser interferometry is one of the most sensitive and versatile techniques for small relative displacements measurement. For these reasons it is used or it is being introduced in many different fields of research. One of its possible applications is seismic activity monitoring, obtained by fixing the mirrors of an interferometer to the ground. In order to obtain a preliminary experimental evaluation of the performances of such an instrument, we tested a simple Michelson interferometer in air as a seismic sensor and compared its sensitivity with a standard seismic sensor. We demonstrated that in the low frequency region the interferometric sensor is much more sensitive and therefore it can represent a valid alternative or replacement to a standard sensor. The optical elements needed to build the interferometer were fixed to the ground to couple the detector with seismic activity. The system were continuously monitored also to take into account of misalignments coming from abnormal air fluctuation and displacement of the mirrors. All data coming from this system are collected by a computer for the storage and are real-time pre-analyzed in order to convert the signal coming from the interference pattern into another describing the equivalent mirrors relative displacement.

To resolve the remote sensing problem of the surfaces by means of use of the synthesis aperture radar (SAR) with high resolution it is necessary to perform the multiparametric measurements. This could be achieved with the help of the multichannel scatterometers that could give the possibility to receive the signals in the different frequency bands, of different polarization, from different directions, etc. In this paper the algorithms of such a combined processing are examined. These algorithsm were synthesized by the solving of the optimization problems. They include the classical operations of the aperture synthesis and operations of the adaptive signal whitening, and statistical characteristic calculation of the Earth covers parameters, as well. Some results of the limits of the measurement errors for the electrophysical parameters such as permittivity, the root-mean-sqaure of the height and the correlation radius of irregularities, etc. within the wide range of reference values were studied.

It is commonly accepted that the spatial distribution of archaeological sites is largely dependent on the characteristics of the environment. Hence, during the last decades, many studies have been focused on selecting environmental characteristics that can be used successfully in predicting unknown site locations. In previous studies the authors, using experimental tests and ground surveys, analysed many environmental factors and identified the most important ones for defining the inclination of an area to settling. Some of these could be obtained from cartography and Digital Elevation Models (DEM), whereas others were extracted from remote sensing imagery. In this work, Landsat ETM and IKONOS-2 satellite data were used to obtain environmental information useful in predicting new archaeological sites using an expert euristic approach. The information obtained from satellite data, plus a few other environmental descriptors, was used to build a predictive archaeological model that characterised an inclination to settle in the test area (region of Lucania in Southern Italy). The map of settlement tendency thus obtained, which was verified during few ground surveys, led to the identification of more than one hundred new archaeological sites, with a prediction accuracy greater than 80%. The environmental characteristics of the new archaeological locations were then statistically analysed and their effectiveness was evaluated. The results demonstrated that the integration of remotely-sensed information within an archaeological model greatly enhanced the capabilities for searching out identifying new archaeological settlements.

The structural setting of the eastern sector of the Dezful Embayment of the Zagros Belt was interpreted using satellite data consisting of two multispectral Landsat 7 scenes, two panchromatic and stereoscopic Spot scenes and two digital orthoimages with a Digital Elevation Model obtained by processing Spot data. Both spectral and spatial characters of Landsat ETM+ were used to evaluate the lithological features of the are. The digital stereo Spot images and the DEM allowed identifying and measuring several geologic features. The achieved results were subsequently subjected to field controls and then integrated into a GIS. The tectonic structures affecting the area are folds, reverse faults and thrusts, NW-SE trending. They indicate a crustal shortening and a transport direction towards SW, with several back-thrusting phenomena. The age of the deformation in this sector of the belt ranges from Pliocene to present. The evaporitic Miocene Gachsaran Formation is a decoupling level interleaved between the upper clastic Incopmetent Group and the lower carbonate Competent Group; the folds and faults affecting this formation do not correspond in location and dimension to the structures affecting the lower carbonate succession.

A time series of satellite imagery of AVHRR sea surface temperature (SST) and SeaWiFS chlorophyll concentration (CHL) for Hellenic waters are analyzed for the mapping of anomaly distribution in these environmental parameters. The spatial distributions of these anomalies are compared using a Geographic Information System (GIS) in order to identify and map areas of persistent environmental anomaly. These spatial distributions describe areas, which are characterized by highSST/lowCHL and lowSST/highCHL values. Generally, the first pair of anomalies implies the spatial extent of persistent cyclonic gyres while the second pair implies the extent of persistent anticyclonic gyres and upwelling. Such oceanographic features (gyres and upwelling) are processes, which along with eddies and fronts, consist the main factors of water mass mixing, particularly in the upper layer euphotic zone. A seasonal classification of these anomalies is developed because SST anomaly, in particular, is widely accepted as the proxy factor for a variety of oceanic and atmospheric-meteorological phenomena. In addition, lowSST/highCHL areas indicate offshore feeding grounds for many commercially important species, such as small pelagic fish (sardine and anchovy) and pelagic cephalopods (squids). A preliminary comparison of surveyed catch data to lowSST/highCHL areas shows a remarkable relation between species distributions and environmental anomalies. However, the main purpose of this work is the combined mapping and classification of SST/CHL anomalies in SE Mediterranean waters.

Snow and ice play an important role in the earth`s radiation balance because of the high albedo in comparison to other natural surfaces. Furthermore ice and snow is the largest contributor to rivers and ground water over major parts of the middle and high altitudes. These are reasons why hydrological and climatological studies require estimates of snow covered areas. Most of such snow cover maps generated from satellite data include information of snow or not snow for each image pixel. In this study a linear spectral unmixing algorithm is used to calculate snow cover portions within each data cell. We examine the ability of this algorithm for operational and near-real time snow cover estimation at subpixel scale using medium spatial resolution satellite data from NOAA-AVHRR. The automated methodology is presented which produces snow cover fraction maps showing plausible distribution of snow in comparison to TERRA-ASTER data. The qualitative analysis of the results present how suitable the approach implemented in the preliminary processing chain is. Simplifying assumptions are made to the procedure which explains some variation between derived snow cover fraction map and reference data. Further work should include an accurate quantification of areal snow coverage comparison to traditional approaches.

Since the construction of a harbour, Port de l'Amitie, an important importation gate for Nouakchott in 1987, the previous coast dynamic equilibrium had been destroyed and thus a significant littoral geomorphological change has occurred, which has produced a severe degradation of the littoral and urban environment. Our research is focused on this coastal environmental change monitoring and its potential evolution estimation by remote sensing techniques using multi-temporal SPOT images and Markov chain analysis. The objectives of this study are to understand coastline evolution particularities, measure geomorphological change rates, evaluate life-span of the harbour, produce useful data for the government to control the environment degradation and provide reference for the future similar coastal engineering. According to our research, the north beach of the harbour has extended by 0.92km² (91.6ha) from 1989 to 2001 and the accretion will probably reach its maximum limit in about 13.4 ± 0.5 years (in 2014-2015) and the harbour will arrive at the end of service. The south sandbar has been eroded by 1.34km² (134ha) and the coastline has landward retreated at the maximum by 362m. Another 0.91km² of land will be nibbled by seawater in the next 10 years. This erosion has caused several times inundation into the suburb and urban areas, provoking a deterioration of the urban environment.