eChapters

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 10^o 10’ N to 11^o 50’ N latitudes and 79^o 45’ E to 80^o 00’ E longitudes. Nagappattinam coast has covered an area of 935 sq. km.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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 7^th 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

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

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 (A_C>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

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)