eChapters

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

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

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

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

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

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

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

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.