Preface With the recent advancements in imaging spectroscopy, application potential of Hyperspectral Remote Sensing Technique has witnessed a quantum leap not only in Earth observation, but also in Planetary Remote Sensing. Availability of very high and contiguous spectral information from the airborne/space borne systems help in resolving of Hyperspectral Remote Sensing is crucial in several application areas such as mineral exploration in geology, species decimation in agriculture and forestry, pollutant dispersion in environmental monitoring. Conventional remote sensing techniques often fail to address the above said issues by virtue of its handicap in addressing sub-pixel/ mix-pixel related problems. This volume documents the state of research developments pertaining to Hyperspectral Remote Sensing and Spectral Signature Applications in India. This volume is also an extension of research papers presented during the National Seminar on “Hyperspectral Remote Sensing and Spectral Signature Database Management System - Hyperspec 2008” held between 14 and 15 February, 2008 at Annamalai University, Tamil Nadu, India. It also includes few contributions in high resolution and multispectral data applications. It is our great hope that the research articles presented in this volume offer readers with a broad view of hyperspectral signal and image processing. In particular, this volume is also very useful for practitioners and engineers working in this area. Last but not least, I would like to thank all the contributors for their participation in this National Seminar and share their experience with the readers. The success of bringing this volume is primarily by their kind co-operation.

ABSTRACT Multispectral imagery has been used as the data source for natural resource mapping and land observational remote sensing from airborne and satellite systems since the early 1960s. Over the past two decades, advances in sensor technology have made it possible for the collection of several hundred spectral bands. This is commonly refe rred to as hyperspectral imagery. Thus it is possible to construct a complete reflectance spectrum of every pixel in the scene. This review highlights the hyperspectral remote sensing system development, hyper spectral data processing and difference between multispectral and hyperspectral data; spatial and spectral resolutions and focuses on the application of hyperspectral imagery in natural resource studies and, in particular the classification and mapping of land resources.

ABSTRACT Remote sensing has undergone tremendous development in past decades. Hyperspectral imaging refers to the imaging of a scene over a large number of discrete, narrow contiguous spectral bands in the visible through thermal infrared portion of the spectrum. Thus it is possible to construct a complete reflectance spectrum of every pixel in the scene. Classification of hyperspectral image requires thorough understanding of surface material properties, sensor characteristics and atmospheric absorption spectra. The reflectance spectra of most materials on the Earth's surface contain diagnostic absorption features. Remote sensors, capable of acquiring complete reflectance spectra over large areas, offer a powerful tool to study of the Earth and the environment. Methods are being developed to extract information from remote sensing data using image-processing approaches. Specific absorption features of reflectance spectrum can be used to identify a number of important rock forming minerals, and have been used by geologists for geologic mapping and studies of volcanoes. The present discussion includes an application of thermal characteristics of near- IR bands of Landsat TM to estimate the temperature of over and around the crater of Barren Island volcano in 1991. A method using dual band temperature characteristics related to radiant source of sub-pixel size was developed and utilized to prepare temperature contour map of the Island using unsaturated pixels of band 5 and 7.

ABSTRACT Over the last decade, hyperspectral remote sensing has become a powerful analysis tool for applications in environment and ecology, aquaculture, forestry, agriculture, and geoscience. A hyperspectral imagers advantage over broadband sensors, such as Landsat Thematic Mapper (TM) and the SPOT Haute Resolution Visible (HRV) sensor series, is its ability to detect molecular absorption and particle scattering signatures of constituents. The finer spectral resolution of a hyperspectral imager allows detection of surface materials and their abundances, as well as inferences of biological and chemical processes. This review highlights the vast extent to which hyperspectral technology and their application with special reference to ocean have been discussed.

ABSTRACT This paper reviews the various application of hyperspectral remote sensing data carried out by the scientists of India emphasizing its advantages. 1. INTRODUCTION The most significant recent breakthrough in remote sensing has been the development of hyperspectral sensors. The ‘Hyper’ in hyperspectral means ‘too many’ and refers to the large number of measured wavelength bands. Hyperspectral images are spectrally over determined, which means that they provide ample spectral information to identify and distinguish spectrally unique materials. Hyperspectral imagery provides the potential for more accurate and detailed information, extraction than is possible with any other type of conventional remotely sensed data. Imaging spectroscopy (Goetz et al., 1985) in hyperspectral imaging is concerned with the measurement, analysis, and interpretation of spectra acquired from a given scene (or specific object) at a short, medium or long distance by an airborne or satellite sensor. The concept of imaging spectroscopy originated in the 1980's, when A. F. H. Goetz and his colleagues at NASA's Jet Propulsion Laboratory began a revolution in remote sensing by developing new instruments such as the Airborne Imaging Spectrometer (AIS), then called AVIRIS, for Airborne Visible Infra-Red Imaging Spectrometer (Green et al., 1998). This system is now able to cover the wavelength region from 0.4 to 2.5 μm using more than two hundred spectral channels, at nominal spectral resolution of 10 nm. The special characteristics of hyperspectral datasets pose different processing problems, which must be necessarily tackled under specific mathematical formalisms, such as classification and segmentation (Jia et al., 1999, Green, R 1998) and spectral mixture analysis (Adams et al., 1986; Smith et al., 1990a, b).

ABSTRACT Mineral composition and their distribution on planetary surfaces provides important clues to the evolutionary processes that the planetary bodies have undergone since their formation. For distant and inaccessible planets, remote sensing, either from Earth-based telescopes or from an orbiter around the planetary body, using reflectance spectroscopy over a wide range of the electromagnetic spectrum (UV-Visible-IR), can provide surface distribution of minerals. With advances in technology, a high-resolution hyperspectral imager onboard an orbiter has developed into a powerful tool for compositional mapping of planetary surfaces. Interpretation of the signals from these distant and relatively unknown destinations is a challenging task due to scarcity of available ground truth. Here, we describe the technique with its applicability to airless bodies, such as Moon, in the context of the Indian Moon mission, Chandrayaan-1, and, the intricacies involved in the data analyses. Keywords : Reflectance spectroscopy, hyperspectral data, remote sensing, planets, moon 1. INTRODUCTION The primary goal of planetary exploration is to understand the mechanism by which planetary objects (planets, dwarf planets, satellites and small solar system bodies) have evolved with time. The information gathered from the study of individual bodies is integrated to comprehend the development of our solar system. The present understanding envisages our solar system to have formed from the solar nebula, produced as a consequence of the collapse of a molecular cloud. While the central mass gravitated and formed the sun, the gas and dust surrounding it condensed to form grains and formed the proto-planetary disk. These grains, through a series of processes, finally aggregated to form of the various planetary bodies. Existing Astronomical, chemical and mineralogical evidences from studies of lunar samples, meteorites and, remote sensing observations suggest that the planetary bodies are heterogeneous and possess extreme compositional and morphological diversity. The internal energy of a planetary body, a function of its size, is responsible for the differences in the degree of differentiation a body has undergone leading to the variations in their surface composition. Large planets like the Earth and Venus are still evolving whereas the small asteroids have barely evolved after their formation and are considered primitive. The wide variety of planetary bodies in our solar system is therefore reminiscent of the various stages of evolution that our solar system went through. The degree of melting and cycling through episodes of differentiation determine the mineral inventory on a planetary body. Therefore, distribution and composition of various minerals can be used to understand various stages of chemical evolution of a planetary body. Mineral mapping of planetary surfaces is thus useful in understanding the petrogenetic history.

ABSTRACT Spectral signatures are the specific combination of reflected and absorbed electromagnetic radiation at varying wavelengths which can uniquely identify an object. The “Spectral signature” of an object is a function of 1) incidental EM wavelength and material interaction with that section of the electromagnetic spectrum. The measurements can be made with various instruments, including a task specific spectrometer, although the most common method is separation of the Red, Green, Blue and Near Infrared portion of the EM spectrum as acquired by digital cameras. The spectral signatures serve as diagnostic tools in understanding the composition and structure of the materials. The present paper highlights the usefulness of the spectral signatures in rock and mineral discrimination and mineral exploration and stresses the need for creation of a spectral data base in India for various applications. 1. INTRODUCTION Objects at the Earth's surface emit and reflect many wavelengths of radiation. In principle, each object has a unique spectral signature, which could be used for identification much like a finger print. Remotely sensed spectral signatures could be utilized for recognizing and mapping for all kinds of features. This can be done to a limited extent with conventional multispectral scanners that operate in a few broad bands of visible and infrared energy. However, broad spectral bands often do not distinguish between similar features. To overcome this limitation, a more sophisticated approach toward spectral signatures has arisen during the past few years. This approach is called image spectroscopy or hyperspectral analysis, which is based on scanning hundreds of closely spaced and very narrow spectral bands. With this technique, it is possible to create continuous spectral response curves, which may be used to identify many objects positively.

ABSTRACT A study was conducted to compare inter-sensor variability by computing vegetation indices, NDVI & SR. The two sensors compared were Hyperion and ALI (Advanced Land Imager) present on EO-1 satellite. Hyperion is a hyperspectral sensor having a spectral range of 400-2500nm with 10nm bandwidth. ALI is a multispectral sensor with 10 bands of 100nm bandwidth. Hyperion and ALI data were acquired at the same time for two different seasons, dry (April) and wet (October) seasons over Shoolpaneshwar Wildlife Sanctuary, Gujarat, India. Vegetation indices such as SR “ Simple Ratio and NDVI -Normalized Differential Vegetation Index were performed. Seasonal variations were observed in both the data sets. For SR index, Hyperion performed well using October month data. In comparison with ALI, Hyperion showed high NDVI for both deciduous and evergreen species using October month data. The highest NDVI value is assumed to represent the maximum vegetation “greenness” during that period. Results clearly indicated the superiority of Hyperion in vegetation analysis using NDVI & SR indices. Keywords : Hyperion data (EO-1), ALI (Advance Land Imager),Shoolpaneshwar Wildlife Sanctuary, NDVI, Simple Ratio (SR)

ABSTRACT The Mumbai region of Maharashtra has been witnessing very rapid urbanization development in terms of industrial, commercial and residential establishments. This has resulted in reclamation of tidal flats and estuarine regions. The ‘marine clay', characteristic of this environment has high swelling potential and consequently affects the performance of the structures. This will have a serious negative impact on the urbanization expansion. In this study, an attempt is made to map the spatial distribution of these expansive clays using the state of art Hyperion data. Reflectance spectra of representative samples collected from the field is used to map marine clays using Spectral Angle Mapper (SAM) technique. Laboratory analyses of these foundation soils (reflectance spectroscopy, mineralogy and Atterberg limits) indicate that they have significant amount of montmorrilonite and has good swelling potential (AC>1.4). The derived expansive clay abundance map will be of use while planning appropriate remedial measure and future development. Key Words : Swelling clay, Spectral characters, Geotechnical properties

ABSTRACT In the present paper, study of spectral reflectance measurements has been carried out for different type of snow and other ambient objects in snowbound areas of Indian Himalaya using Spectroradiometer (350-2500nm). The observations suggest that there are significant changes in the spectral radiances and reflectance values of snow and other ambient objects, which can be discriminated using satellite multi-spectral bands, however for characterizing the snow using satellite sensor, spectral bands having maximum radiances values should be greater than snow radiances and suitable spectral bandwidth are to be identified. The detail analysis of field collected reflectance suggest that, due to aging and grain size variation in snow, the maximum variations in reflectance was observed in the NIR region i.e. around 1040-1050nm. For contamination and snow depth, the maximum variation was observed in the visible region i.e. around 470nm and 590nm respectively. For the moisture changes, the maximum variations observed around 980 and 1160nm. The study also suggests, normalized difference snow index (NDSI) increases with the increase of aging, grain size and moisture content. This study can be helpful in selection of suitable spectral bands for snow cover applications using satellite remote sensing and developing the algorithms for seasonal snow cover characteristics using multi-spectral and hyper-spectral data.

ABSTRACT Greenseeker is a handheld computer mounted sensor for observing normalized difference vegetation Index [NDVI= (NIR “R)/(NIR+R)], which may be used to estimate site specific amount of fertilizer nitrogen depending up on the crop condition. The sensor can be used for yield estimation and developing remote sensing based growth models. It is an active sensor with a built in light source for illuminating the target and records reflected light from vegetation at wavelength of 670 nm (red region) and 780 nm (near infrared region) of electromagnetic spectrum. The swath covered by the Sensor is 0.75 m when sensor is placed about 1.0 m above crop canopy. The sensor was used to record NDVI in wheat- sugarcane intercropping system wherein wheat was grown on raised beds of 1.04 m width with six rows of wheat and sugarcane in furrows at row spacing of 1.38 m. The wheat variety PBW 343 was sown with nitrogen levels @ 0, 30, 60, 90, 120, 150, 180 and 210 kg N ha-1 (all basal) and sugarcane variety CoSe 92423 was planted in furrows on 7th November, 2006 in a medium textured loam soil. The NDVI was recorded in wheat at 17, 41, 59, 73, 88, 113 and 129 DAS using Greenseeker and Spectroradiometer (UNISPEC TM of PP system, USA) simulating normal satellite bands i.e. NIR: 770-860 nm, Red: 620-680 nm, Green: 520-580 nm. The maximum NDVI (recorded at 88 DAS) was used to develop INSEY “ yield relationship in wheat. The NDVI recorded by Greenseeker was integrated with NDVI recorded by Spectroradiometer. The Greenseeker was also used to monitor crop growth in sugarcane. The NDVI was correlated with shoot population, plant height, LAI and total biomass during formative and crop elongation phase of sugarcane till end of November 2007. Highly significant (at 1%) correlation was observed between GS- NDVI and shoot population till mid August and LAI in sugarcane for entire crop cycle. An exponential model (R2 = 0.9017) was developed to estimate LAI of sugarcane from NDVI. The NDVI was significantly (at 5 %) was correlated with plant height till mid August. However, the correlation between total crop biomass in sugarcane and NDVI remained non-significant.

ABSTRACT Satellite-based hyperspectral imaging became areality in November 2000 with the successful launch and operation of the Hyperion system on board the EO-1 platform. Hyperion is a push broom imager with 220 spectral bands in the 400-2500 nm wavelength range, a 30 meter pixel size and a 7.5 km swath. Prelaunch characterization of Hyperion measured low signal to noise (SNR<40:1) for the geologically significant shortwave infrared (SWIR) wavelength region (2000- 2500 nm). The impact of this low SNR on Hyperion's capacity to resolve spectral detail is studied for the Musiri and Tattayyangarpettai regions of part of Namakkal and Tiruchirapalli districts of Tamil Nadu state, India which comprises a diverse range of minerals with narrow, diagnostic absorption bands in the SWIR. Following radiative transfer correction of the Hyperion radiance at sensor data to surface radiance (apparent reflectance), diagnostic spectral signatures were clearly apparent including: green vegetation; talc; dolomite; crystalline limestone, chlorite; white mica and sericite. Though the derived surface composition maps generated from these image endmembers were noisy (both random and column), the spatially coherent and correlated well with the known geology. The interpreted and processed mineral map is given below. In addition, the Hyperion data were used to measure and map spectral shifts of <10 nm in the SWIR related to white mica chemical variations.

ABSTRACT Hyperspectral data are generally noisier compared to broadband multispectral data. Therefore, it is desirable to smoothen the reflectance spectra. Smoothing needs to preserve an absorption feature while simultaneously removing noise. It is very essential to optimize the smoothing filter to minimize disturbances to the statistical properties of the original data. This study was carried out to see the effect of Fast-Fourier Transform (FFT) based smoothing technique on the statistical properties of vegetation spectral response and to see the effect of the filter size. The data used for the present study is the reflectance spectra data obtained from space borne EO-1 onboard Hyperion sensor. Filter sizes were varied between 3 and 15 with the increment of 2, i.e. 3, 5, 7..........15. Paired t-test was carried out between the original and the smoothed data (for the selective bands) for all the filter sizes in order to see the extent of distortion with changing filter sizes. Our study revealed that the distortion in the spectra increases with the increase in the filter size. Beyond filter size 11, the number of locations within the spectra where the smooth spectra were statistically different from its original counterpart increased to 14 and reaches 21 at the filter size 15.

ABSTRACT Leaf N and chlorophyll (Chl) concentration of crop are important indicators of plant nitrogen status. Laboratory determination of plant tissue N is time consuming and costly. Also remote sensing is quickly becoming recognized as a valuable tool that has the potential to asses a wide variety of physiological properties over a large area in a short amount of time. This study examined the relationship of sorghum and bajra canopy reflectance spectral response to its nitrogen and chlorophyll content. The study consisted of two nitrogen level (N0 : no nitrogen and N1: recommended dose of nitrogen for each crop) for two crops (sorghum and bajra) . Chlorophyll and N content were measured throughout the growing season for both crops. Reflectance at increased significantly as N fertilizer rate decreased. Chl and N were strongly related to canopy reflectance for either individual wavelength or for spectral vegetative indices or ratios. Sorghum nitrogen fertilizer rate mainly affected leaf reflectance at 575 and 623 nm, while bajra at 565 and 657nm. The reflectance values at 581 and 603 nm had the highest correlation with sorghum leaf N concentration. Similarly, bajra leaf N concentration was highly correlated with 619 and 696 nm. Sorghum and bajra leaf N concentrations were highly correlated with reflectance ratio of R581/ R381 (r2= 0.44*) and R619/R462 (r2= 0.78***) respectively with greatest r2 value. Similarly, Sorghum and bajra leaf Chl concentrations were highly correlated with R677/R527 (r2= 0.63**) andR688/R409 (r2= 0.71***) or R615/R411 (r2=0.71***), respectively. Thus our results suggest that spectral reflectance measurements hold promise for the assessment of some physiological parameter at the leaf level real time monitoring of sorghum and bajra N status and N fertilizer management.

ABSTRACT Pests and diseases cause serious economic losses in yield and quality of many cultivated crops. Detection and assessment of their damage symptoms is very crucial to initiate timely control interventions. The conventional scouting technique adopted for assessment of pest and disease in field crops is very laborious and time consuming. Remote sensing may provide a better means to objectively quantify disease stress than visual methods and it can be used to repeatedly collect sample measurements non-destructively and non-invasively. In this paper we report the changes in the reflectance spectra due to pest and disease incidence in three crops viz., groundnut, castor and rice. Canopy reflectance measurements were made with a hand held multispectral radiometer (MSR 16-R, CropScan Inc) which records incoming radiation and light reflectance with up looking and down looking sensors, respectively in 16 pass bands. Data of percent reflectance at each pass band were processed subsequently using the calibration and correlation constants through a mini computer connected to the sensor. A total of 10 samples were selected for each level of pest/disease. At each sampling, six measurements were recorded and the resulting data were averaged. The reflectance spectra varied for different biotic stresses in the three test crops. Higher absorption in the NIR region between 760-1240 nm was observed for healthy plants compared to the diseased plants in all the three crops tested. The spectral signatures from severely defoliated (by semilooper pest) castor crop showed that the percent reflectance in the visible region between 560-710 nm was higher in the defoliated crop compared to healthy and reverse is true in the NIR region between 810-1100 nm. In case of rice, spectral reflectance in the region between 760-1100 nm could differentiate the healthy and brown plant hopper affected plants. Decrease in reflectance in this region was proportion to the number of hoppers per plant. This could be due to collapse of leaf tissues by hopper damage. The higher reflectance in the visible region (560-710 nm) was observed only when the damage is very severe (hopper burn). Different spectral indices viz., SR (simple ratio), NDVI (normalized difference vegetation index), NPCI (normalized total pigment to chlorophyll index), DWSI (disease water stress index) and WBI (water band index) were compared to distinguish healthy and diseased plants. NDVI was found useful in distinguishing semilooper damaged (defoliated) castor crop from healthy castor. All the indices tested were useful to differentiate the rice plants damaged by sap-sucking pest, BPH at different levels of infestation. Incase of groundnut, the differences in the spectral indices between different disease incidence levels were not significant. Results of the present study demonstrated that by comparing the reflectance spectra generated using ground based high-resolution radiometer, it is possible to distinguish healthy and pest/disease affected crops.

ABSTRACT This paper is an attempt to highlight the problems of coastal environmental impact assessment owing to logistic constraints, costs of analytical data generation, time gap between data generation and interpretation, quantum of physical and chemical data required for assessment of environmental data through conventional methods and to examine the potential of hyperspectral remote sensing as an alternative for conventional methods. As hyperspectral remote sensing is non-destructive, offers repetitivity and high resolution (spatial and spectral) and hyper-sensitive to many physical and chemical properties of coastal soils and minerals, we recommend use of hyperspectral remote sensing for reduction of cost and man-hours in coastal environmental assessment, without compromising the quality of data.

ABSTRACT Of late, the importance of integrated study of multi-theme data is being realised in geological mapping and mineral exploration programmes. The usefulness of such a study lies in the fact that data integration and interpretation in a conjunctive mode enables to infer more information than the sets can separately provide. The present paper presents several case studies, illustrating the usefulness of multi-theme data integration in geological mapping and mineral exploration. 1. INTRODUCTION Integrated study of multi-theme data is being practiced in the recent times in the geological mapping and mineral exploration campaigns. Such a study, in a synergetic fashion, helps to extract more meaningful information than from the study of individual datasets. It not only helps in deciphering regional geological picture, but also in the precise location of drilling targets, thereby yielding rich dividends for the expenditure incurred in the mapping and mineral investigations. Besides, the success ratio of the mineral investigations has also shown a significant increase, resulting in the discovery of more mineral deposits. Hence the integration of multi-theme data is of paramount importance for the success of geological mapping and mineral investigations.

ABSTRACT In earth system about 60% of the world's population live within 60 km of coastline and use the coastline for their livelihood. Environmental pollution of the coast, inshore water and deep ocean is one of the important topical issues in the context of human health and global warming. To combat this natural and man made problem, we have to rely on qualitative analysis quantitatively. In the recent advancement in information and technology field, spectral data plays a major dominant role in the environmental studies. This could provide more powerful and accessible means to exploit the enormous wealth of data available in the system. The high-resolution imaging spectrometry (hyperspectral imagery) will help to analyze the data for mapping and other environmental modeling applications. This could attain advanced approaches to deduce surface characteristics and extract features from hyperspectral images. The current capabilities are in which, the prototype system can classify pixels according to surface type. The classification process employs neural network analysis of inputs which include pixel spectra and a variety of processed image metrics, including image “texture spectra” derived from fractal signatures computed for sub image tiles at each wavelength. Thus, this kind of technical analysis can prove to achieve coastal area studies well in advance in the ongoing environmental changes more precisely.

ABSTRACT The Remote Sensing data volume is vast, so high processing capacity is required. It is impossible to update spatial data without the support of high performance of RS image management, retrieval, and change detection and pattern discovery. After introducing some background information including significance of SDI updating, feasibility and advantages of satellite RS imagery used to update spatial data, the framework of updating spatial and attribute information based on RS image is proposed. In the process, the integrated processing of raster data and vector data is very important, so some functions of RS image processing and GIS software should be fused. In order to extract the anticipated images from vast image database, effective retrieval technique is vital. RS image data mining and knowledge discovery is the synergy of Spatial Data Mining (SDM) and Image Data Mining (IDM). Oriented to the demands of SDI updating to intelligent information processing, some primary issues on RSDM are analysed. It is pointed out that updating SDI by satellite RS imagery will be potential advantageous in the future. RS Data Mining and Knowledge Discovery are very important and will play important roles in the future. Keywords: Spatial Data Infrastructure (SDI), Remote Sensing Data Mining, Spatial Data Mining, Image Data Mining.

ABSTRACT The improvement of spatial resolution of satellite remote sensing (RS) imagery, it is possible to update spatial data infrastructure efficiently by satellite RS images. But the RS data volume is vast, so high processing capacity is required. In order to extract the anticipated images from vast image database, effective retrieval technique is vital. The rapid development of Earth Observation System (EOS), the spatial resolution, temporal resolution and spectral resolution of Remote Sensing (RS) image have been improved greatly. Based on contentbased image retrieval, content-based RS image retrieval is put forward and some topics including retrieval pattern, useful image content, feature extraction and similarity measure are researched. After related images are retrieved from vast image database, it is necessary to discover those change areas, so change detection from multitemporal RS images are discussed further. RS image data mining and knowledge discovery is the synergy of Spatial Data Mining (SDM) and Image Data Mining (IDM). It is pointed out that content based RS image retrieval will be potential advantageous in the future and all the techniques discussed in this paper including retrieval modes, content-useful in RS image retrieval. Content-based image retrieval (CBIR) is one of the hot issues in image retrieval, and it can be used to RS image retrieval. That lead to a new area: content-based RS imagery retrieval. Keywords : Remote Sensing, content based RS image Retrieval, Earth Observation System, Spatial Data Mining, Image Data Mining.

ABSTRACT Hyperspectral image reduction processes use only information drawn from knowledge related to the surface reflectance properties. The chemical composition and crystal structure control the shape of spectral curve, position and amplitude of absorption bands. Spectral database provide a source of reference spectra useful in classification of hyperspectral images. An attempt has been made to put all such available data on a structured database for easy access and visualization. A Web-based interface for reference spectra of natural surfaces facilitates data sharing and increases access to reference material for classification. 1. INTRODUCTION Hyperspectral imaging refers to the imaging of a scene over a large number of discrete, narrow contiguous spectral bands in the visible through thermal infrared portion of the spectrum. Thus it is possible to construct a complete reflectance spectrum of every pixel in the scene. Field spectroscopy is a nondestructive way to collect information on natural resources and is becoming a common exercise in remote sensing field campaigns. Specific absorption features of reflectance spectrum can be used to identify a number of important rock forming minerals, and have been used by geologists for geologic mapping and studies of volcanoes. Spectral database provide a source of reference spectra useful in classification of hyperspectral images.

ABSTRACT This paper demonstrates the ability of FTIR for analyzing compositional structures of naturally occurring crystals namely gypsum and calcite. As these two crystals occur in a wide variety of geological environments and are susceptible to compositional and structural changes influenced by pressure, temperature, crystallization fluids and so many other factors, these are extensively studied by geoscientists for interpretation of paleoenvironment, modeling diagenesis of sediments and deducing sediment maturity for hydrocarbon exploration, study of these two crystals is important. Naturally occurring gypsum and calcite crystals collected from Cretaceous marine deposits of Ariyalur area were chosen for the present study as extensive occurrences of hydrocarbons are reported from offshore region of Cauvery basin and exploratory works are going on in the onland region. It is observed that the vibrational spectra of studied crystals show specific patterns in terms of stretching patterns of O-H, C-O, C=O, SO4 and CO2. As FTIR offers fast, cost-effective, non-destructive method of analyses of natural compounds, as it is proven useful, it can be utilized extensively in academic research and commercial exploration activities by geoscientists. Keywords : Spectral characterization, calcite, gypsum, diagenesis, paleoclimate, hydrocarbon exploration.

ABSTRACT The purpose of this paper is to utilize thermal infra red remote sensing data to find the location of heat processing units which contribute to high temperatures. These industries occur as anomalous pixels in urban area on the temperature map derived from the thermal remote sensing data. The night scenes of ASTER thermal infra red data were used for this study. It is concluded that analysis of temporal thermal remote sensing data can be used as a tool in environmental impact assessment and management. The temperature maps can be helpful in decision making process of siting / relocation of heat producing industries in and around cities. 1. INTRODUCTION For sustainable industrial development, management and regular monitoring of the industries is needed. Knowledge of industrial impacts on the environment is an essential for environmental impact assessment and management. Thermal remotes sensing techniques can be applied for this.

ABSTRACT The purpose of this paper is to map the diversity of Formicoidea, richness and habitat preferences with respective to the different forest cover, classified based on the NDVI from LANDSAT TM imagery with the help of remote sensing and GIS. The study is carried out in Sirumalai hills region of Dindigul District, Tamil Nadu state, India recorded a total of 26 species with 15 genera belonging to four sub-families by a taxonomical basis. The NDVI based forest classification results that the area has disturbed dry deciduous forest (SA), undisturbed dry deciduous forest (SB), disturbed mixed deciduous forest (SC), undisturbed semi evergreen forest (SD), undisturbed grassland (SE) and undisturbed dry evergreen forest (SF) types of forest covers. The results of diversity studies, statistical analyses and field study reveals that the tropical semi evergreen forest and tropical dry evergreen forest have yielded more number of species, genera than the mixed deciduous forest and dry deciduous forest which are most disturbed by human beings in establishment of estates, management strategies by the government and land use by the local farmers.

ABSTRACT Remote Sensing and Geographical Information System play major role in the water planning of river basins. Varahanadhi is one of the 17 major river basins of Tamilnadu, bounded in North by Palar basin, East by Bay of Bengal and West & South by Ponnaiyar basin. It drains through Thiruvannamalai and Villupuram districts. There are three sub basins viz., Ongur, Nallavur and Varahanadhi sub basins. From Survey of India top sheets, Basin boundary, sub basin boundary maps were generated. Administrative map with district, block boundaries was prepared. GIS software - Arc view, was utilized for this purpose. By using ERDAS IMAGINE, Digital Image processing software, satellite image mosaic of Varahanadhi Basin, Geomorphology, Land use, Wasteland, Structural-Lineament maps were generated. IRS P 6 RESOURCESAT, LISS III and PAN data were used for the thematic map preparation. From the collateral data collected, the thematic maps on Geology, Soil, and annual north east, south west. summer, winter rainfall, irrigation system, pre monsoon and post monsoon groundwater levels, ground water quality were prepared using ARC GIS Software. Relief and Drainage map were also generated in GIS environment. The surface water potential was assessed by rainfall run off method for which geomorphology map interpreted by remote sensing and GIS was utilized. Based on geomorphology and land use maps, draft for irrigation was estimated. Geology, geomorphology, depth to bedrock, rainfall pattern, water level maps were used to asses groundwater potential and draft. Sectoral demand on power, industry and domestic were made based on collected collateral data. Environmental Impact Assessment was assessed using land use maps and ground water quality maps interpreted from remote sensing data for years 1998 and 2004 were prepared and compared. Wasteland map was prepared to know the extent of wastelands and their types as per National Waste Land Board norms. Remedial measures to convert waste lands into productive lands were also suggested. By superimposing geomorphology and lineament maps upon the wastelands, sites suitable for groundwater development in the waste lands were identified. In the same way by using GIS overlay analysis developmental and action plan maps were also prepared with technical recommendations. By applying remote sensing and GIS techniques the basin water resources assessment, draft to meet out sectoral demands and balance of water available for future use can be decided. Varaganadhi basin is a surplus basin as per the study.

ABSTRACT Presence of mangrove ecosystems on coastline, save lives and property during natural hazards such as cyclones, storm surges and erosion. This study is undertaken to assess the distribution of mangroves in Tamil Nadu. Geographical Information System, Remote Sensing and GPS (Global Positioning System) were used for mapping the mangrove forests. Mangrove wetland map and species zonation maps have been done using didital analysis of Remote Sensing data and ground truth information. The total area of mangroves found in Tamil Nadu and in Puducherry is around 4100ha. 1. INTRODUCTION Mangroves are typical, tropical specialized trees growing in the saline and brackish water system. Mangrove plants live in muddy and wet saline soils. They are trees associated with shrubs, growing both on the sheltered coast and inland, lining the bank of estuaries and rivers. They are an ecological group of evergreen plant species, belonging to different families, but possessing marked similarities in their physiological characteristics and structural adaptations. Mangrove areas are associated with high leaf production and leaf fall and rapid decomposition of the litter. Mangrove forests perform multiple ecological functions: They produce woody trees, provide habitat and detritus food for fish and shellfish and act as spawning ground for a variety of fishes, prawns and shellfishes. They harbour a variety of valuable fauna, including migratory birds. They also protect the coasts from storms and tidal waves and help in the formation of land by trapping sediments brought by the coastal community.There are many threats to mangroves. Deforestation is one of the major threats.

ABSTRACT A satellite based earth observation system enhances our understanding of the entire earth as an integrated system. Remotely sensed data gives accuracy and complete data. To study the coastal zone or area remote sensing is on of the best technology to monitor the regular changes over the time. Here satellite data used to understand the distribution of prawn farms along the Nagappattinam coast. It has stretched from River Coleroon in the north to Point Calimer in south. Nagappattinam coast rocked by tsunami in 2004 and it damaged the whole life of coastal and fishing people. This paper has attempted to analyse the distribution of prawn farms and impact of tsunami in the Nagappattinam coast using remote sensing. 1. INTRODUCTION Nagappattinam coast is located on the eastern part of Nagappattinam. It is a unique immemorial for its agricultural activities and lying in the deltaic region of Cauvery River. Nagappattinam coast (Fig 1) is peninsular delta area bounded by Bay of Bengal on the east, Palk Strait on the south, and Thiruvarur and Thanjavur districts on the west and Cuddalore on the north. The study area is located between 10o 10’ N to 11o 50’ N latitudes and 79o 45’ E to 80o 00’ E longitudes. Nagappattinam coast has covered an area of 935 sq. km.

ABSTRACT Petroleum exploration is the art of searching hydrocarbon reserves in unknown regions by geological, geophysical and geochemical methods. The selection of effective exploration targets is an important step to achieve success in oil exploration and its selection also dependents on study of basic petroleum geological conditions. Petroleum geologists generally consider basins to be a basic geological unit for petroleum exploration and their main task is to find and determine various sedimentary basins. The remote sensing images have characteristics of really and macroscopic to provide accurate and visualization data for directly determining geometric shapes of sedimentary basins. Remote sensing techniques are more effective in understanding the study of basins in an out-of-the-way about mountains and remote deserts. Key words: Petroleum Exploration, Sedimentary basin, geology, basin, geometry.

ABSTRACT Coastal resources represents highly productive ecosystems and are under pressure on account of increased anthropogenic activity on the coast. There is an urgent need to protect coastal resources aiming at sustainable development. Management of coastal resources requires spatial information on land and water resources, processes, water quality in a repetitive basis. Availability of high resolution and very high resolution data made the spatial tools indispensable in planning and management of resources such as mangroves and coral reefs. Monitoring mangrove degradation and aquaculture development, land use pattern, site selection for developmental activities adhering to coastal regulation zone notification requires highly accurate spatial information that can be extracted from IRS, IKONOS data. Extensive applications of remote sensing were hindered by cost, lack of familiarity and expertise in the developing countries. A national frame work must be established involving all available spatial datasets to build up the technical capabilities and ensure sustained support.

ABSTRACT This work presents the results of multispectral analysis of TM (Thematic Mapper) sensor images on board the satellite LANDSAT 5 for discrimination of selected features of a Nainarmalai region of part of Namakkal District, Tamil Nadu using hyperspectral tools. The spectral classification was carried out using hyperspectral tools namely, a) spectral reduction by the Minimum Noise Fraction (MNF) transformation, b) spatial reduction by the Pixel Purity Index (PPI) and c) manual identification of the end members using the N-dimensional visualizer. The results of study shows that the kinds of features such as magnetite quartzite, sand, harvested land and vegetation area are discriminated well (as given in the figure) and show a strong correlation with landscape. Keywords: Landsat TM Multispectral Images, MNF transformation, PPI, endmembers, Reflectance spectrum, ENVI software. 1. INTRODUCTION With a multispectral analysis of an images collected by radiometers and detectors embarked on a satellite, one can make: “spectroscopy by satellite imagery”. Imaging spectrometers or “multispectral sensors” are remote sensing instruments that combine the spatial presentation of an imaging sensor with the analytical capabilities of a spectrometer. With a radiometer such as AVIRIS ”Airborne Visible/Infrared Imaging Spectrometer” where the number of spectral bands exceeds the 200, and with a spectral resolution of the order of 10 nm or narrow, it can produce a complete spectrum for each pixel of the image. The case of this radiometer enters on the “Hyperspectral” field. In the case of our study, we are using the radiometer TM (Thematic Mapper), which is on board for the satellite Landsat 5, and which only has 7 multispectral bands, with a spectral resolution of the order of 100 nm. Like finale result, one using the spectroscopy by satellite imagery, we can identify the spectra of various materials which are on various terrestrial surfaces.

ABSTRACT Synthetic Aperture Radar (SAR) images are being used more extensively than ever before for geosciences Applications in the moist tropics. With SAR's side viewing geometry, longer wavelengths, and almost all-weather sensing capability, SAR imagery has been extensively useful mapping tool for coastal geomorphology in the moist tropics. The purpose of this study to assess the use of Multitemporal C-band ENVISAT- ASAR data for identification of different coastal geomorphology in part of Tamilnadu coast. The orbital ASAR data was digitally geometric corrected (ortho-rectified) and filtered for speckle noise, and linearly stretched in order to enhance contrast between the coastal environment features. By using the methods of crisp enhancement, linear stretching and PCA, to show the various Coastal geomorphological units. The information extraction is based on recognition of the mechanism interactions occurring between radar signal and the target on the ground, represented by shallow water morphology in the intertidal conditions, coastal dunes, mangroves, marshes and highland. In an application perspective, Orbital ASAR data proved to be a fundamental source of information for both geomorphological mapping and land use pattern in moist tropical environments. Key Words : ASAR, Geomorphology, Mangroves, Land Cover, Coastal mapping.

ABSTRACT Mangrove wetlands are well known as the dominant feature of the intertidal areas of the tropical and subtropical regions. Ecologically mangrove forests are important for their inherent biological productivity in the habitat and also by exporting organic matter produced into coastal waters. Apart from that mangroves act as bioshield against natural coastal hazards like cyclones, storms and tsunamis. Remote sensing coupled with GIS is an important tool in monitoring the coastal areas such as mangroves, where the physical survey is difficult and time consuming. Remote sensing has a wide range of products with higher spatial, spectral and temporal resolutions, the combination of which can be applied in different themes based on the requirement. The present study used multispectral, multi-temporal and high-resolution remote sensing data to map and monitor the distribution of mangrove forest of Pichavaram, south India over a period of 30 years. The study shows that the mangrove area had decreased from 628 ha to 411 ha from 1977 to 1994 and increased to 858 ha in 2006. The high resolution remote sensing data with 4 m spatial resolution was used to prepare the mangrove wetland map in 1:5000 scale. Keywords : Mangroves, remote sensing, visual interpretation, IRS, IKONOS

ABSTRACT Soil is the medium in which the plant growth and development occurs. Soil type might change with genesis of the parent material and with prevailing weather conditions. Dominant soils of Tamil Nadu are Black soil, Red soil, Laterite soil and Hill soils. Each soil type has an inherent potential to retain and release nutrients to plants. The availability of nutrients varies from place to place and hence spatial distribution of nutrients, quantity of nutrients along with plant available water determines phenological development of crops. Nutrients are broadly classified as Macro and Micro nutrients that are required for crops in large and small quantities respectively. Availability of both macro and micro nutrients and its spatial distribution has not been attempted so far at a regional level. Such regional level approach of nutrients would suffice the researchers and policy planners to employ these data as inputs to Crop Simulation Models (CSM) in forecasting productivity of crops. Thiruvannamalai district in Tamil Nadu is divided into 6 taluks, 18 blocks covering an area of 6,31,205 haof land. The district lies between 120 00’ to 120 55’ N latitude and 780 37'to 790 45’ E longitude. Red loamy soil is predominantly prevalent followed by black loamy soils. Generally paddy, groundnut, sugarcane, millets and pulses are cultivated during fasli season. This district was chosen as our study area. A study has been attempted to map micro nutrients of Thiruvannamalai district. Geo-referenced surface soil samples from eighteen blocks of Thiruvananmalai district covering maximum soil units of soil map were collected randomly as per procedure adopted by soil survey manual. Global Positioning System (GPS) were used to collect corresponding geographic coordinates from each soil sampling point covering the entire Thiruvananmalai district by using Rikaline Bluetooth GPS 6031- X7 model. Approximately one thousand five hundred surface soil samples were collected, air dried, powered and sieved as per standard conditions. Soil samples were analyzed for its physical, chemical and fertility properties. Fertility maps for Micro nutrients such as Zinc, Iron, Manganese, Copper and Boron were plotted in ARCGIS Desktop. Micronutrients maps form a part of base map in analyzing and preparing an aggregated fertility map of Thiruvannamalai district.

ABSTRACT Remote sensing, especially high resolution satellite data has a major role to play in locating (localizing) mineral targets. The present study is carried out on exploration and discrimination of magnetite ore deposits of Tirthamalai region of part of Dharmapuri district, Tamil Nadu, India, using IRS P6 LISS IV high resolution satellite data. The applicable image processing techniques and associated put forth of field knowledge is used in the present study. The image processing classifications namely band rationing, principal component analysis and contrast enhancement are carried out in visualizing images using ERDAS Imagine 8.7 software. The visual interpretation of FCC of digital data shows that the raw pixel values of iron ore bands in the blue ranges 95 to 120, green ranges 85 to 125 and red ranges 55 to 75 and provided better delineation for iron formations. The interpretation of satellite data shows that the iron ore band exhibits in dark color, linear shape, fine texture and sharp contact with associated rock types. To rectify and reduce misinterpretation all above image processing techniques are undertaken along with the detailed filed-check in the selected test sites using GPS 178 and delineated the in situ iron formations. The interpretations show that the occurrence of few more iron bands and weathered formations along with massive formations in the region traced on the imagery since the absorptions themselves are different. The availability spectral absorption of iron formation is inferred highly in visible and near infrared region (0.9-1 Ìm). Remote sensing high resolution satellite data proved that the satellite parameters are important criteria and play a vital role in mapping of low-grade iron ore deposits of the Tirthamalai region of Dharmapuri district of Tamil Nadu state.

ABSTRACT The present study reports shoreline changes at Gopalpur along east coast of India for 30 years during 1973-2003. In order to understand the trend of sediment transport, shoreline changes at the vicinity areas viz. Rushikulya and Bahuda estuaries are also discussed. Geomorphological investigation is also carried out to understand the processes acting on this system. One Landsat image (1973) and two IRS 1C/1D images (1993 and 2003) were used for the study. The data were subjected to digital analysis using ERDAS Imagine and management of information layers using ARC/INFO GIS software. The results of the study show that the changes occurred differently in three distinct spatial features namely, i) sand spit ii) beach and, (iii) channel zone. Changes documented in these imageries reveal that the lengths of NE spit and SW spit are increased and decreased respectively in thirty years. Areas of NE and SW spits are also showing the similar pattern. Beach is almost stabilised and a slight decrease of 0.28 km in length is observed. However, area has been increased in the southern beach. Towards north, the beach area is also increased over a period of thirty years. The change of width of the beach is not found to be significant. The mouth near channel zone is reduced to 70 meter from 135 meter during the period of study.

ABSTRACT Topsoil erosion, loss of fertile soil and subsequent deposition in the reservoir as well as in the low-lying region are one of the major problems in the tropical mountainous region. Knowledge of sediment yield from the river basin is a prerequisite to address such issues. Rivers from the Western Ghat region of Uttara Kannada district bring lot of sediments causing siltation in their mouth. In the present study, sediment yield from a Venkatapur river basin in Bhatkal Taluk of Uttara Kannada district is estimated by Universal Soil Loss equation (USLE). Morphometric characteristics of the river basins that reflect sediment yield potential of the river basin are used to constrain the data obtained. Various parameters for USLE is derived from the IRS 1D LISS III image and data are handled in GIS environment. Sediment yields in the basin 101 tons/yr. Morphometric characters of the basin such as drainage density, bifurcation ratio, basin circularity (0.6) and form factor (0.43) suggest its low potential of sediment yield.

ABSTRACT The study was aimed to identify and delineate the groundwater potable zone in and around Madurai region. The study area is composed of Charnockites and Khondalites of Archaean age. The information of lithology, geomorphology and land use/land cover was generated using the Resourcesat (IRS P6 LISS IV data) and Survey of India (SoI) toposheets of scale 1:50,000 and integrated them with GIS to identify the groundwater potable zones of the study area. On the basis of hydrogeomorphology, groundwater potential zones was identified and delineated. From the overlay analyses landuse and EC, it is inferred that, poor category groundwater is found in the scrub forest, current fallow, canal and scrub with land areas.

ABSTRACT Groundwater geochemistry is largely a function of mineral composition of aquifer through which water flows thus, differences in aquifer composition are reflected as differences in groundwater chemistry. To understand water quality and flow pattern multivariate statistical analysis are used due to its relative importance in combining chemical variables and organize voluminous data and group into variables of similar characters. R-mode factor analysis is used in the field of hydrogeochemistry to interpret complex hydrogeological process. A total of 216 samples representing complete lithology like peninsular gneiss, Charnockite and calc gneiss for four different seasons was collected and analyzed for major ions like Ca, Mg, Na, K, HCO3, Cl, SO4, NO3, PO4, F and H4SiO4. Correlation analysis reveals Mg, Cl and Na are spinal and others seasonal. Factor analysis indicates ascendancy of anthropogenic basis followed by lithological weight. Factor score superimpose indicate governing hydrogeochemical regimes spread in western and eastern part. In southern part the same has superior influence than northern part.

ABSTRACT The over extraction of water from the coastal environment, results in reduction of groundwater resources which has reflected in lowering of water level. In general, the depletion of water level enhances the landward migration of saltwater wedge. Pondicherry is one such region with recent alluvium as the major litho unit. A study has been attempted to calculate the extraction of water and to estimate the amount of recharge into this alluvial aquifer. The monthly water level fluctuation was observed for the study period in eighteen locations (20002002). The highest water level observed during 2000 was taken as the initial water level for the study and the subsequent decline in water level up to 2001 was monitored monthly until the rising trend was noted. This was taken as the fall in water level due to extraction. Keeping this as the initial value increasing trend was studied until there was a notice of decline in water level. This was taken as the rise in water level due to recharge. The spatial representation of these data in the above said eighteen locations were carried out by using GIS and the area occupied by different water level contours were calculated and the amount of water withdrawn was estimated. The maximum recharge was noted in the central and the northern part of the study area when compared to the other regions. Similarly, the maximum discharge was noted in the northern and the southern part of the study area. Keywords: Rainfall, Recharge, Groundwater Budget, GIS.