LISS-III Satellite Images Research Articles

LWAMNNet: A novel deep learning framework for surface water body extraction from LISS-III satellite images

LWAMNNet: A novel deep learning framework for surface water body extraction from LISS-III satellite images

Impact of agrarian land use and land cover practices on survival and conservation of nilgai antelope (Boselaphus tragocamelus) in and around the Abohar wildlife sanctuary, northwestern India

ABSTRACTThere is an information gap on biodiversity effects of land use and land cover (LULC) dynamics of agrarian landscapes. Such data are essential for policy making and species management in agro-ecosystems. Thus, changes in LULC inside the Abohar wildlife sanctuary and its eco-sensitive zone were investigated using LISS-III satellite images from 2003 to 2016. The area under cropland witnessed a 3.6% increase, whereas wastelands significantly declined by 4.3%. Further, the impact of LULC dynamics on nilgai (Boselaphus tragocamelus) was determined through mortality distribution in the sanctuary from 2012 to 2017. The spatio-temporal distribution pattern of mortality revealed that a total of 336 nilgai died during the six years studied. Free-ranging feral dogs, in conjunction with fencing and road accidents, were the major factors involved in nilgai casualty. Fatalities were clustered in regions with significant LULC change. The results confirmed that intensified development and reuse of derelict agricultural fields disturbed nilgai ecology and habitat use pattern. Human-wildlife conflicts in agrarian landscapes are an increasing concern and should be managed following identification of sensitive areas.

Enhanced classification of LISS-III satellite image using rough set theory and ANN

Land use and land cover classification are one of the major aspects to detect land coverage in particular area. Same goes for water, forest, and mangroves. So by keeping these parameters in mind, our objective is to identify water, land, forest, and mangroves from a LISS-III satellite image by using rough set theory and artificial neural network. LISS-III is multi-spectral camera operating in four different bands. There are many problems related to the classification of the satellite image i.e., universal classifiers, parameter setting of classifiers and features. The classification accuracy is one of the major issues related to classification of satellite image therefore in this paper rough set-based artificial neural network is used for classification of the satellite image. The rough set theory is used to reduce the number of the feature vector for improved classification of satellite image using the artificial neural network.

Enhanced classification of LISS-III satellite image using rough set theory and ANN

Enhanced classification of LISS-III satellite image using rough set theory and ANN

Study of land use classification in an arid region using multispectral satellite images

Rapid urbanization and deforestation have led to increased areas of wasteland in the northern region of the Akola district of Maharashtra, India. This study investigates land use variations in the arid region with the help of multi-temporal images. Land use maps were employed for analysis of different classes using image classification tools in ArcGIS software. Multispectral satellite imagery data were used to create land cover variation maps and land use forecast maps for the study area. The land use classification change maps were produced from LISS-III satellite images and Landsat Enhanced Thematic Mapper Plus (2008 and 2015) using supervised classification techniques. Land use was divided into five major classes, i.e. agricultural land, developed land, wasteland, water bodies, and forestland. We observed significant changes in agricultural and forestland as a result of many factors including population growth, drought conditions, road infrastructure development, flooding, and soil erosion in the arid area. The overall accuracy of the supervised classification was 94.10% for 2008 and 88.14% for 2015, using the kappa method, which was a satisfactory result. The analysis of land use maps in the arid region revealed different patterns of use between 2008 and 2015. The results of this study may be useful for developing and implementing valuable management strategies for resource protection in the study area. These results show the potential for land use planning and development in arid regions using remote sensing and GIS technology.

Land Use Land Cover Classification Analysis in Chamarajanagara Taluk, Southern Tip of Karnataka State, India using Geo-informatics

Earth’s land pattern is one of the natural resources which being pressurized across the globe due to various factors. Rapid increase in population, its rises agricultural activities, urbanization, significant mining for growing economic minerals were the major anthropogenic factors impacting the Land Use/ Land Cover (LU/LC) patterns. The present aim is to map the LU/LC classification on LISS-III Satellite images in conjunction with Google Earth image through GIS software’s. An attempt have been made to delineate the level-I, level-II and level-III LU/LC classification system through NRSC guidelines (1995) using both Digital Image Processing (DIP) and Visual Image Interpretation Techniques (VIIT) with limited Ground Truth Checks (GTC). Level-III classification has been carried out in detail on agricultural to study the cropping pattern. More accurate classifications were observed in case of DIP as compared to that of VIIT in terms of area statistics. The final results highlight the capability of geo-informatics in classifying the LU/LC patterns around Chamarajanagara taluk of Karnataka, in Natural Resource Mapping (NRM) and its sustainability.

Evaluation of course change detection of Ramganga river using remote sensing and GIS, India

Abstract Visibility of Ramganga river course change detection was made using Remote Sensing and GIS in study area among period of forty-one years from 1972 to 2013. Landsat MSS, TM, ETM+, LISS-III satellite images from 1972, 1989, 2000, 2006, and 2013 respectively were used to delineate the historical changes of the river course. This study shows that for a long time this area has been suffering due to erosion problem and shifting characteristics of the Ramganga River. The Ramganga river course has been shifting and the overall shifting is towards the south-west direction in different places which leads to the village erosion. The area has remained undeveloped due to infrastructure damaged by flood, changing course. This study may be helpful for the overall river management and planning for future prevention of food, changing coursing, loss of properties.

Automatic Shoreline Detection and Change Detection Analysis of Netravati-GurpurRivermouth Using Histogram Equalization and Adaptive Thresholding Techniques

The shoreline change extraction and change detection analysis is an important task that has application in different fields such as development of setback planning, hazard zoning, erosion-accretion studies, regional sediment budgets and conceptual or predictive modeling of coastal morphodynamics. Shoreline delineation is difficult, time consuming, and sometimes impossible for entire coastal system when using traditional ground survey techniques. Recent advances in remote sensing and geographical information system (GIS) techniques are overcoming the difficulties in extraction of shoreline position and detection of shoreline changes. In the present paper, an automatic shoreline detection method using histogram equalization and adaptive thresholding techniques is developed. The shoreline of Netravati-Gurpur rivermouth area along Mangalore coast, West Coast of India have been extracted from Indian Remote Sensing Satellite (IRS P6) LISS-III (2005, 2007 and 2010) and IRS R2 LISS-III (2013) satellite images using developed automatic shoreline detection method. The delineated shorelines have been analyzed using Digital Shoreline Analysis System (DSAS), a GIS Software tool for estimation of shoreline change rates through two statistical techniques such as, End Point Rate (EPR) and Linear Regression Rate (LRR). The Bengre spit, Northern sector of Netravati-Gurpur river mouth is under accretion an average of 2.95 m/yr (EPR) and 3.07 m/yr (LRR) and maximum accretion obtained is 8.51 m/yr (EPR) and 8.69 m/yr (LRR). Southern sector, the Ullal spit is under erosion an average of -0.56 m/yr (EPR) and -0.59 m/yr (LRR).

Land use land cover change detection of Patani micro-watershed of Madhya Pradesh using remote sensing data

This study investigates Patani micro-watershed situated in Majhagawan block of Satna District (M.P.). The watershed characterization was carried out using RS and GIS techniques. The major aim of this study is to prepare land use land cover and their change detections. In this study IRS-P6 Sensor, LISS-III satellite images of the dates 19th October, 2008 and 5th January, 2008 were used to detect the seasonal (Kharif and Rabi) changes in land use land cover of the Patani Micro-watershed. First the images were geo-referenced and land use land cover maps were prepared by image processing techniques. To differentiate the changes in land covers, and vigour of the vegetation, Normalized Difference Vegetation Index (NDVI) was used as an important indicator, NDVI maps were generated for both images of the dates 19th October, 2008 (Rabi) and 5th January, 2008 (Kharif), values of NDVI in the watershed varies from -0.42 to 0.15 for 19th October, 2008 and 0.99 to 0.24 for 5th January, 2008 respectively. The land use land cover classes identified in the watershed were forest, wasteland, agricultural land, open (Currently fallow), and water body. Maximum area (69%) of the watershed was under forest, 2% under wasteland, most of which was at hill top; there were no seasonal changes exhibited in forest and wasteland. Changes were detected in water body, agricultural and open land. Agricultural land was decreased by 2.87% from Kharif to Rabi season and open land was increased by 3.28% respectively. Most of the agricultural land is under rainfed and land with higher slopes and poor soil depth is kept fallow during the Rabi season. Reduction was also observed in the water body by 0.41% in Rabi season; this is due to use of water from water harvesting ponds for irrigation and losses as evaporation and seepage. Key words: RS, GIS, land use land cover, NDVI, Change detection.

Geospatial Technologies for National Geomorphology and Lineament Mapping Project – A Case Study of Goa State

A three level classification system, based on the genesis of landforms, was used to map the geomorphology of the Goa state. The first level corresponds to the process that was responsible for landform generation, the second level or the intermediate level was assigned based on the morphography, and the third level corresponds to the individual landforms units identified based on the morphostructure. The mapping was carried out using IRS-P6 LISS-III (23.5 m) satellite image as the primary data source. Ancillary data such as geological map, topographic map, digital elevation model (DEM), field data collected by global positioning system (GPS) and web portals for image visualisation, were also used for the mapping purpose. A new software designed for mapping landforms based on the genesis, was used in this study to create a seamless geomorphology and lineament database of the Goa state in a GIS environment. A total of 58 landforms within six types of genetic classes were mapped in this area. Similarly, structural and geomorphic lineaments were also delineated using the satellite data. The database created has multi-purpose usability such as environmental studies, mining activity assessment, coastal zone management and wasteland development, since the classification system used is focused on processes, not theme specific.

Spatial Variability and Precision Nutrient Management in Sugarcane

Investigations were carried out to develop precision nutrient management techniques for sugarcane. The study area (800 ha) comprised of Bijapur, Bilgi and Jamakhandi talukas that lie between 16° 34′–28° 10′ N latitudes and 75° 33′–75° 37′ E longitudes and located around Nandi Sahakari Sakkare Karkhane (NSSK) Niyamit, Galagali. The soils are medium to deep black with pH and EC ranging from 7.32 to 8.36 and 0.17 to 1.13 dS/m, respectively. The soils are low to medium in available nitrogen, medium in available phosphorus and high in available potassium content. Crop condition assessment was made through analysis of LISS-III satellite images using Erdas Imagine software. Fertigation with 300 kg N and 195 kg K per ha at fortnightly interval and soil application of 32 kg P per ha as basal, recorded higher sugarcane yield (167 Mg ha−1) as compared to 124 Mg ha−1 obtained with soil application of 250 kg N, 32 kg P and 156 kg K per ha and flood irrigation as per the package recommended by the University(POP). Fertigation of N and K at weekly interval recorded highest NDVI value (0.354) and soil application of nutrients as per POP resulted in the lowest NDVI of 0.219.

RS-GIS Based Assessment of River Dynamics of Brahmaputra River in India

The Brahmaputra River is one of the largest alluvial rivers in the world characterized by frequent bank erosion leading to channel pattern changes and shifting of bank line. This study is aimed at quantifying the actual bank erosion/deposi- tion along the Brahmaputra River within India for a period of eighteen years (1990-2008). The entire course of Brah- maputra River in Assam from upstream of Dibrugarh up to the town Dhubri near Bangladesh border for a stretch of around 620 kms has been studied using an integrated approach of Remote Sensing and Geographical Information Sys- tem (GIS). The channel configuration of the Brahmaputra River has been mapped for the years 1990 and 2008 using IRS 1A LISS-I, and IRS-P6 LISS-III satellite images respectively. The analysis of satellite data has provided not only the information on the channel configuration of the river system on repetitive basis but also has brought out several sig- nificant facts about the changes in river morphology, stable and unstable reaches of the river banks and changes in the main channel. The results provide latest and reliable information on the dynamic fluvio-geomorphology of the Brah- maputra River for designing and implementation of drainage development programmes and erosion control schemes in the north eastern region of the country.

Mapping of Lateritic Soils of Midlands in Kerala Using Resourcesat-1 LISS-III and SRTM DEM Data

Lateritic soils of Mathamangalam, Kannur District, located in midlands of Kerala, were morphologically studied, characterized, classified and mapped at 1:50,000 scale using remote sensing techniques. The terrain of the study area being hilly and covered with perennial vegetation, soil-landscape model was applied. For this purpose physiographic information was inferred from SRTM DEM, Resourcesat-1 LISS-III satellite image and topographical maps. The interpreted units were validated in the field and characterized through soil-site examination, soil profile study and soil analysis. The study indicated that the lateritic soils of midlands of Kerala vary in physical, chemical and morphological properties in relation to micro-relief. Soils developed on moderately steeply sloping side slopes (15–30% slope) are deep, moderately well drained with gravelly clay textured, where as the soils developed on moderately slopping side slope (10–15% slope) are very deep and well drained. The soils of valleys are very deep, moderately well drained with fine texture. Very gently sloping (1–3%) laterite plateau tops have extremely shallow soils associated with rock outcrops. These soils mainly belong to Order Ultisols followed by Inceptisols and Entisols. These were further grouped up to Family and Series level by tentatively establishing seven soil series. This study helps in understanding the behaviour of lateritic soils of midlands of Kerala, which can be useful in generation of interpretative maps and in optimizing the land use.

Quantitative modeling of groundwater in Satluj River basin of Rupnagar district of Punjab using remote sensing and geographic information system

Water is a fluctuating resource making it difficult to measure in time and in space. To demonstrate the efficiency of the geographic information system (GIS) for groundwater studies, information on the parameters controlling groundwater such as lithology, geomorphology and lineament analysis were analyzed. LISS-III and Landsat satellite image of the area was used to infer information on the geologic lineaments and geomorphology. To delineate linear features enhancement and direction, filtering was performed on single bands of Landsat images. Thematic maps for geology, slope, geomorphology and lineament were prepared and integrated in GIS by assigning the weights and ranking to various parameters controlling the occurrence of groundwater to generate the groundwater potential map for the study area. The results indicate that the floodplain of river and its adjoining areas have very good groundwater potential, whereas the steeply sloping area in the northern part having high relief and slope possesses poor groundwater potential.

Morphostructural prognostication of kimberlites in parts of eastern dharwar craton: Inferences from remote sensing and gravity signatures

The varied nature of geophysical signatures encountered in the identification of blocks with favorable setting for emplacement of kimberlites, the major geological hosts of diamonds, has resulted in the development of different criteria for their prognostication. This paper attempts to bring out the association of domal morpho-structural features with kimberlite occurrences. From analysis of an IRS-ID LISS-III satellite image of the Maddur-Narayanpet-Mahboobnagar-Gadwal-Raichur region (latitudes 16° N to 17°15’ N and longitudes 77° E to 78°15’ E) in the eastern Dharwar craton, the surface morphology and structural configuration were obtained. From observed surface correlation of reported kimberlite occurrences with intersecting lineaments within regions of domal morphology, regions with such configuration were delineated as potential kimberlite bearing zones. Using this observation as a criterion, six potential kimberlite zones were delineated: near Sedam, around Maddur, north of Mahbubnagar, north of Raichur, between Raichur and Gadwal and around Gadwal.