The characterization of the marine environment plays an important role in the understanding of the dynamics affecting the transport, fate and persistence (TFP) of Persistent Organic Pollutants (POPs). This work is part of a project funded by the Ministero dell’Istruzione, dell’Università e della Ricerca. The aim of the project is the assessment of the TFP of POPs in the Mediterranean sea. The analysis will be carried out at regionalmesoscale (central Mediterranean), and at local spatial scale considering different Italian test sites (the Delta of the Po River, the Venice Lagoon and the estuary of the Rio Nocella). The first step of this work involves the implementation of GIS geodatabases for the definition of the input dataset. The geodatabases were populated with MERIS and MODIS level 2 and level 3 products of Chlorophyll-a (CHL-a), Chromophoric Dissolved Organic Matter (CDOM), Aerosol Optical Thickness (AOT), Diffuse Attenuation Coefficient (DAC), Particulate Inorganic Carbon (PIC), Particulate Organic Carbon (POC) and Sea Surface Temperature (SST). The spatial scale (central Mediterranean sea) and the reference system (Plate Carrée projection) have been imposed as a constraint for the geodatabases. Four geodatabases have been implemented, two for MODIS and two for MERIS products with a monthly, seasonal and climatological temporal scale (2002 -2013). Here, we present a first application of a methodology aimed to identify vulnerable areas to POPs accumulation and persistence. The methodology allowed to assess the spatial distribution of the CHL-a in the central Mediterranean sea. The chlorophyll concentration is related to the amount of nutrients in the water and therefore provides an indicator of the potential presence of POPs. A pilot area of 300 x 200 km located in the North Adriatic sea has been initially considered. The seasonal and climatological MODIS and MERIS CHL-a variability were retrieved and compared with in-situ forcing parameters, i.e. Po River discharge rates and wind data. Study outlooks include a better accuracy of the distribution of the vulnerable areas achieved through the use of additional parameters (CDOM, SST, POC), and an assessment of the contribution of the contaminants by atmospheric dry deposition to the marine environment.
Recent remote sensing applications require sensors that provide both high spatial and spectral resolution, but this is often not possible for economic and constructive reasons. The "fusion" of images at different spatial and spectral resolution is a method widely used to solve this problem. Pan-sharpening techniques have been applied in this work to simulate PRISMA images. The work presented here is indeed part of the Italian Space Agency project “ASI-AGI”, which includes the study of a new platform, PRISMA, consisting of an hyperspectral sensor with a spatial resolution of 30 m and a panchromatic sensor with a spatial resolution of 5 m, for monitoring and understanding the Earth's surface. Firstly, PRISMA images have been simulated using images from MIVIS and Quickbird sensors. Then several existing fusion methods have been tested in order to identify the most suitable for the platform PRISMA in terms of spatial and spectral information preservation. Both standard and wavelet algorithms have been used: among the former there are Principal Component Analysis and Gram-Schmidt transform, and among the latter are Discrete Wavelet Transform and the “à trous” wavelet transform. Also the Color Normalized Spectral Sharpening method has been used. Numerous quality metrics have been used to evaluate spatial and spectral distortions introduced by pan-sharpening algorithms. Various strategies can be adopted to provide a final rank of alternative algorithms assessed by means of a battery of quality indexes. All implemented statistics have been standardized and then three different methodologies have been used to achieve a final score and thus a classification of pan-sharpening algorithms. Currently a new protocol is under development to evaluate the preservation of spatial and spectral information in fusion methods. This new protocol should overcome the limitations of existing alternative approaches and be robust to changes in the input dataset and user-defined parameters.
Satellite images are a tool increasingly used in environmental monitoring and in recent years have become also strongly used in the field of archaeology. In this study it was conducted an experimental analysis on the identification of wetlands from satellite images in order to identify sites of interest from the archaeological point of view because probable sites of ancient settlements. The studied area is the Plan de la Limagne which is located in North-East of the French city of Clermont-Ferrand. For wet areas identification were used two ASTER satellite images and pre-existing carthography. Different indexes have been used to identify wet areas. First of all, it was used the NDVI (Normalized Difference Vegetation Index) to discriminate bare soils. Secondly, through the Tasseled Cap transform, other indexes were obtained, such as the Greeness Index, the Brightness Index (SBI – Soil Brightnes Index) and the Wetness Index. Then it has been used the ATI index (Apparent Thermal Inertia) that provides information on the thermal inertia of soils. Through these indexes, visual inspection and the study of spectral signatures, it has been tried not only to identify wetlands within the images, but also to find repeatable processes for the detection of these areas. Some “anomalous” areas, that are probably wet areas, have been identified with this procedure. The identification of wet areas has been carried out in a raw way, this is surely a first approximation analysis. Certainly the in situ analysis would provide the possibility of a better evaluation, in fact field measurements could be used to calibrate the model and then find an effective and repeatable procedure for identifying wetlands.
The Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) data retrieved at 0:55 μm with spatial resolutions of 10 km and 1 km AOD have been considered in this work. The 10 km resolution of MODIS AOD product is from the MODIS Collection 5:1 dark target retrieval and the 1 km resolution retrieval is from the new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. We evaluate ability of these two products to characterize the spatial distribution of aerosols in urban areas through comparison with surface PM<sub>10</sub> measurements. The Po Valley area (northern Italy) is considered in this study since urban air pollution is an important concern. Population and industrial activities are located in a large number of urban areas distributed within the valley. The 10 km spatial resolution of MODIS AOD product is considered too large for air quality studies at the urban scale. Using MAIAC data at 1 km, we examine the relationship between PM<sub>10</sub> concentrations, AOD, and AOD normalized by Planetary Boundary Layer (PBL) depths obtained from NCEP global analysis, for year 2012 over the Po Valley. Results show that the MAIAC retrieval provides a high resolution depiction of the AOD within the Po Valley and performs nearly as well in a statistical sense as the standard MODIS retrieval during the time period considered. Results also show that normalization by the analyzed PBL depth to obtain an estimate of the mean boundary layer extinction is needed to capture the seasonal cycle of the observed PM<sub>10</sub> over the Po Valley.
Soil salinization is a form of topsoil degradation due to the formation of soluble salts at deleterious levels.
This phenomenon can seriously compromise vegetation health and agricultural productivity, and represents a
worldwide environmental problem. Remote sensing is a very useful tool for soil salinization monitoring and
assessment. In this work we show some results of a study aimed to define a methodology for soil salinity
assessment in Iraq based on SPOT 5 imagery. This methodology allows the identification of salinized soils
primarily on bare soils. Subsequently some soil salinity assessment can be done on vegetated soils. On bare soil
the identification of salt is based on spectral analysis, using the Minimum Noise Fraction transformation and
several indexes found in literature. In case of densely vegetated soils the methodology for the discrimination of
salinized soils has been integrated with the results obtained from the classification of vegetation coverage.
Thermal mapping is an highly relevant tool for the assessment of the quality of coastal waters. Remote sensing
is an useful technique for monitoring large surfaces in near real time, nevertheless, spatial resolution represents
an important limiting factor. In this work it the spatial improvement, from 1km to 250m, of MODIS thermal
imagery on coastal water obtained with the SWTI (SharpeningWater Thermal Imagery) is shown. This algorithm
is applied, for the first time, to MODIS images acquired on the lagoon of Venice and on the delta of the Po
River. The performances of SWTI are evaluated taking as a reference a couple of ASTER images acquired
simultaneously to the MODIS images and on the same areas. Moreover, the water temperatures obtained with a
simple bilinear interpolation of the MODIS images is also considered. Several statistical parameters, as bias and
root mean square difference, are used to quantify the the difference between ASTER and MODIS/SWTI water
temperatures along coastlines. In all the the cases these differences are lower than 1K.
Since the 1970s, the Iraq Marshlands have been damaged significantly, but recently (May 2003-March 2004), more than
20% of the original marshland area has been re-flooded.
The goal of the work is to observe the evolution of the marshes in terms of extension and to evaluate the success of
wetland restoration on the base of multispectral and multitemporal MODIS images collected in 2007-2008.
MODIS (MODerate resolution Imaging Spectroradiometer) has a viewing swath width of 2,330 km and views the entire
surface of the Earth every one to two days. Its detectors measure 36 spectral bands between 0.405 and 14.385 μm, and it
acquires data at three spatial resolutions -- 250m, 500m, and 1,000m.
These data with their low spatial resolution but high time frequency are suitable for regional-scale time-series studies.
The satellite data have been corrected for atmospheric effects using an IDL (Interactive Data Language) procedure based
on MODTRAN and 6S radiative transfer codes. These radiative transfer codes require, in input, atmospheric vertical
profiles, aerosol optical thickness(AOT) and columnar water vapour content (WV). Vertical profiles are obtained from
the nearest meteorological station or by climatological data set. AOT and WV are retrieved either from the MODIS
MODATML2 atmospheric product, or from the AERONET (Aerosol robotic network).
Then different classifications (Pixel- and Object-Oriented) have been tested, compared and discussed to evaluate the best
approach to apply on regional-scale time-series studies.
Hyper/Multispectral data provide information about characteristic of natural and antropic surfaces. In order to retrieve
the mineralogical species composing the Castel Porziano Beach (CPB), remote sensed data needs to be atmospherically
corrected. In this work a new tool for the atmospheric correction for spaceborne EO data, based on MODTRAN and 6S
codes, and developed on IDL/ENVI platform will be proposed and tested using NASA HYPERION and ASTER data. In
this paper the capability to identify mineral association composing the sand of the CPB emerged beach, using
hyperspectral data is shown. In order to define the mineralogical composition of the collected sample, SEM EMPA
(Scanning Electron Microscopy and Electron MicroProbe Analyser) and optical polarizing microscopy analysis have
been done. Results have been compared with 300 measurements performed directly on the CPB sand and 300
measurement acquired in the laboratory, both using an ASD-Fieldspec.
The Project called Sistema Rischio Vulcanico (SRV) is funded by the Italian Space Agency (ASI) in the frame of the
National Space Plan 2003-2005 under the Earth Observations section for natural risks management. The SRV Project is
coordinated by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) which is responsible at national level for the
volcanic monitoring. The objective of the project is to develop a pre-operative system based on EO data and ground
measurements integration to support the volcanic risk monitoring of the Italian Civil Protection Department which
requirements and need are well integrated in the GMES Emergency Core Services program. The project philosophy is to
implement, by incremental versions, specific modules which allow to process, store and visualize through Web GIS tools
EO derived parameters considering three activity phases: 1) knowledge and prevention; 2) crisis; 3) post crisis. In order
to combine effectively the EO data and the ground networks measurements the system will implement a multi-parametric
analysis tool, which represents and unique tool to analyze contemporaneously a large data set of data in
"near real time". The SRV project will be tested his operational capabilities on three Italian Volcanoes: Etna,Vesuvio
and Campi Flegrei.