Propose of a new Vegetation Index is purposes. Ordinal vegetation Index can show intensity of vegetation on the ground. It can not show structure of vegetation surface or texture. Proposed vegetation index utilizes BRF property. It is generated from data from 2 orbit of satellite and be able to show structure of vegetation surface or texture. Principles of this index is coming from field observation using RC helicopter. Each vegetation canopy has different texture and roughness. New index, named BSI (Bi-directional reflectance Structure Index) shows difference of vegetation canopy. It is calculated by using the data of NOAA/AVHRR, ADEOS OCTS. ADEOS-II GLI can derive BSI.
This project used hyperspectral data set to classify land cover using remote sensing techniques. Many different earth-sensing satellites, with diverse sensors mounted on sophisticated platforms, are currently in earth orbit. These sensors are designed to cover a wide range of the electromagnetic spectrum and are generating enormous amounts of data that must be processed, stored, and made available to the user community. The Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) collects data in 224 bands that are approximately 9.6 nm wide in contiguous bands between 0.40 and 2.45 mm. Hyperspectral sensors acquire images in many, very narrow, contiguous spectral bands throughout the visible, near-IR, and thermal IR portions of the spectrum. The unsupervised image classification procedure automatically categorizes the pixels in an image into land cover classes or themes. Experiments on using hyperspectral remote sensing for land cover classification were conducted during the 2003 and 2004 NASA Summer Faculty Fellowship Program at Stennis Space Center. Research Systems Inc.'s (RSI) ENVI software package was used in this application framework. In this application, emphasis was placed on: (1) Spectrally oriented classification procedures for land cover mapping, particularly, the supervised surface classification using AVIRIS data; and (2) Identifying data endmembers.
The Leica ADS40 is a line scanning sensor that collects stereo panchromatic imagery and 4 discrete multispectral bands in a 12,000 pixel-wide swath. The Z/I Imaging DMC is a frame based sensor that produces 13,824x7,680 pixel panchromatic images and 3072x2048 pixel multispectral images, which are normally pan sharpened to produce high resolution RGB and color infrared products. The suitability of the two systems for multispectral remote sensing and photogrammetric applications are compared, and contrasted with other film and digital alternatives. Results indicate that the DMC has an advantage for large scale photogrammetry applications, and the ADS40 is superior for remote sensing applications.
The Cross-track Infrared Sounder (CrIS), an interferometric sounder, is one of the instruments within the National Polar-orbiting Operational Environmental Satellite System (NPOESS) suite. CrIS measures earth radiances at high spectral resolution providing accurate and high-resolution pressure, temperature and moisture profiles of the atmosphere. These profiles are used in weather prediction models to track storms, predict levels of precipitation etc. Each CrIS instrument contains three Focal Plane Array Assemblies (FPAAs): SWIR [λc(98 K) ~ 5 mm], MWIR [λc(98 K) ~ 9 mm], and LWIR [λc(81 K) ~ 16 mm]. Each FPAA consists of nine large (850-mm-diameter) photovoltaic detectors arranged in a 3 x 3 pattern, with each detector having an accompanying cold preamplifier. This paper describes the selection methodology of the detectors that constitute the FPAAs and the performance of the CrIS SWIR, MWIR and LWIR proto-flight FPAAs.
The appropriate bandgap n-type Hg1-xCdxTe was grown on lattice-matched CdZnTe. 850-mm-diameter photodiodes were manufactured using a Lateral Collection Diode (LCD) architecture. Custom pre-amplifiers were designed and built to interface with these large photodiodes. The LWIR, MWIR and SWIR detectors are operated at 81 K, 98 K and 98 K respectively. These relatively high operating temperatures permit the use of passive radiators on the instrument to cool the detectors. Performance goals are D* = 5.0 x 1010 cm-Hz1/2/W at 14.0 mm, 9.3 x 1010 cm-Hz1/2/W at 8.0 mm and 3.0 x 1011 cm-Hz1/2/W at 4.64 mm. Measured mean values for the nine photodiodes in each of the LWIR, MWIR and SWIR FPAAs are D* = 5.3 x 1010 cm-Hz1/2/W at 14.0 mm, 1.0 x 1011 cm-Hz1/2/W at 8.0 mm and 3.1 x 1011 cm-Hz1/2/W at 4.64 mm. These compare favorably with the following BLIP D* values calculated at the nominal flux condition: D* = 8.36 x 1010 cm Hz1/2/W at 14.0 mm, 1.4 x 1011 cm-Hz1/2/W at 8.0 mm and 4.1 x 1011 cm-Hz1/2/W at 4.64 mm.
This paper analyzed the damaged forest by tomicus piniperda using multiple types of remote sensing data such as TM, CBERS-1, AVHRR and MODIS data. It selected a typical region including heavy damaged and healthy forest. The region was located by GPS (Global Position System). Then the spectral features of the above remote sensing data (March, 2001) were given. It indicates that the values of healthy forest of TM NIR band (0.76-0.9 ) and SWIR band (1.55-1.75 ) are distinctly greater than those of damaged forest. The values of CBERS-1 NIR bands (0.77-0.89 ), AVHRR bands (0.725-1.0 ) and MODIS bands (0.841-0.876 ) behave in the same pattern with TM. Otherwise, the values of MODIS thermal bands (3.929-3.89 , 10.78-11.28 and 11.77-12.27 ) of damaged forest are distinctly greater than those of healthy forest. The AVHRR thermal bands are not so. Finally, two detection models were put forward according to the spectral changing characteristics. One was named Difference Rate (DR) model with NIR and VIR data, which applied for TM, CBERS-1, AVHRR and MODIS. DR is greater, the forest grow healthily. Basis on the typical sample, the different guidelines distinguished healthy and damaged forests are obtained. The other model was named Disaster Index (DI) model with thermal and NIR data, only suitable for MODIS. The guidelines of healthy and damaged forest are determined too. DI is greater the forest is stricken more badly. In conclusion, it will help monitoring and assessing the vermin occurrence and impact by remote sensing detection model.
A long wave infrared (LWIR) hyperspectral imager, the University of Hawaii's Airborne Hyperspectral Imager (AHI), was used to relate systematic changes in LWIR spectral features to weathering trajectories on the surfaces of basaltic rocks. Kahle and others proposed that in relation to the LWIR spectra, that devitrification of chilled glassy margins dominate the first stages of weathering, followed by the accretion of silicate coatings and the oxidation of iron[1-3]. We are using the AHI's higher spectral and special resolution to better constrain this relationship between the LWIR and weathering trajectories. The main study area was along the northern flank of Mauna Loa on the Island of Hawai'i. We collected samples ranging from a few decades to over 8000 years old. Samples a few hours to a few days old were collected from Kilauea. A Nicolet FTIR spectrometer was used to acquire reference spectra in the range of 5 to 15 μm. Three features are readily identifiable: two narrow features (A: ~8.1μm and B: 9.1μm) and one broad feature (C: 9.5 to 13 μm). The most striking change is in the C feature which changes from a large and dominant feature in the fresh Kilauea pahoehoe, to a subtle feature in the 1935 Mauna Loa flow. The only overall age related spectral change observed is the reduction of relative spectral feature intensity with increasing age. We also noted that within samples of the same age, there are some striking differences in the spectral shape.
This study was to develop the time-specific and time-critical method to overcome the limitations of traditional field sampling methods for variable rate fertilization. Farmers, agricultural managers and grain processing enterprises are interested in measuring and assessing soil and crop status in order to apply adequate fertilizer quantities to crop growth. This paper focused on studying the relationship between vegetation index (OSAVI) and nitrogen content to determine the amount of nitrogen fertilizer recommended for variable rate management in precision agriculture. The traditional even rate fertilizer management was chosen as the CK. The grain yield, ear numbers, 1000-grain weight and grain protein content were measured among the CK, uniform treatments and variable rate fertilizer treatments. It indicated that variable rate fertilization reduced the variability of wheat yield, ear numbers and dry biomass, but it didn't increased crop yield and grain protein content significantly and did not decrease the variety of 1000-grain weight, compared to traditional rate application. The nitrogen fertilizer use efficiency was improved, for this purpose, the variable rate technology based on vegetation index could be used to prevent under ground water pollution and environmental deterioration.