Monitoring & analysis of wastelands and its dynamics using multi-resolution and temporal satellite data in part of Indian state of Bihar (original) (raw)
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International Journal of Engineering Research and Technology (IJERT), 2013
https://www.ijert.org/a-comparative-study-of-sodic-wastelands-and-water-logged-area-using-irs-p6-liss-iii-and-liss-iv-data-through-the-gis-techniques https://www.ijert.org/research/a-comparative-study-of-sodic-wastelands-and-water-logged-area-using-irs-p6-liss-iii-and-liss-iv-data-through-the-gis-techniques-IJERTV2IS90588.pdf Sodic land and Water logging are the twin evils for agriculture in arid and semi-arid areas on many continents, which reduce the productivity of agricultural crops adversely. The extent & nature of these problems depend on climatic condition, geologic, topographic, hydrologic factors and human activities, such as population pressure and over grazing. Water logged area is affected by excessive logging of water for quite some period and affects the productivity of land and cultivation pattern. Remote sensing and GIS techniques offer several advantages for management of the salt-affected and waterlogged areas by studying various aspects of spatial data on soil, land cover, geology and hydrogeology along with implementing reclamation activities such as site selection, soil monitoring etc. This paper describes a comparative study of sodic wastelands and water logged area using IRS P6 LISS-III (spatial resolution 23.5m) and LISS-IV (spatial resolution 5.8 m) data through the GIS applications This encompasses spatial analysis of sodic land and waterlogged area by satellite data. The study area is located in the District of Hardoi in Uttar Pradesh. Waterlogged areas are distinctly seen in satellite image (FCC) as light to dark blue colour of varying size and shapes. Remote sensing and GIS has capability to map & spatially analyse sodic and water logged area in a particular district or region. The satellite images were visually interpreted for three classes, these are sodic wasteland, water logged area and degraded forest.
International Journal of Geomatics and Geosciences
Voluminous increase in population has created an excessive demand for productive land. At the same time land degradation because of desertification, soil salinity, waterlogging, floods/droughts, excessive soil erosion and unscientific agricultural practices has resulted in the creation of vast stretches of wastelands. This has necessitated adoption of scientific measures for increasing land productivity and bringing more areas under cultivation/forests. In the present study, the multi-temporal satellite images of IRS P6 LISS-III were used to map wastelands dynamics over different seasons. An attempt has also been made to evaluate the potential of high spatial resolution LISS IV (5.8 m) data over moderate spatial resolution LISS-III data (23.5 m) from the Indian Remote Sensing Satellite for delineation of wastelands in a portion of the Indo-Gangetic plains of northern India. Visual interpretation based on image characteristics and a prior knowledge of the study area was used to delineate wasteland classes. Using LISS III data, 1372.92 and 605.90 hectares of land areas are identified as affected by seasonal and permanent waterlogged respectively, and using LISS IV, 1113.33 and 105.84 hectares of land areas are identified as affected by seasonal and permanent waterlogged respectively. Wasteland classes such as seasonal and permanent waterlogged could be further separated into wasteland classes such as land with dense scrub, land with open scrub, degraded pastures/grazing lands and degraded land under plantation using higher resolution satellite data.
Decadal changes in land degradation status of India
Current Science, 2021
Robust data on the spatial distribution of land degradation is important for resource conservation planning. Spatial land degradation status of India was mapped using multi-temporal Linear Imaging Self Scanning Sensor (LISS-III) data acquired from Resourcesat-1/2 during 2005-2006 and 2015-2016 under the Natural Resources Census programme of the Indian Space Research Organisation. Heads-up on-screen visual interpretation of multi-season satellite data was carried out, supported by digital elevation model and other historical maps available. Visual interpretation cues were developed and employed across various partner institutions to achieve consistency in mapping. The outputs were subjected to two-stage quality check. Results indicate that the total land degradation of India was 91.2 M ha (27.77% of the geographical extent of the country) during 2015-2016 against 91.3 M ha during 2005-2006. During the ten-year period, there was an overall decrease of around 0.1 M ha in degraded land. However, noticeable intra-and inter-class changes were observed in land degradation during the ten-year period. Major reclamation was noticed in sand dunes which were converted into crop lands by levelling them. Substantial decrease in severity and extent of salt-affected soils was noticed in Uttar Pradesh.
IRJET, 2020
Land degradation is seen as a phenomenon or more that reduces current and/or potential soil capacity to produce goods. This means a decline from a higher to a lower state due to a decline in land capacity, productivity, and biodiversity loss. The aim of the present study is to prepare baseline data to combat land degradation and conserve land resources in an efficient manner. To assess land degradation with the help of Remote Sensing (RS) and Geographical Information System (GIS)-in Maitha Block of Kanpur Dehat district, Uttar Pradesh. Different levels of analysis were performed to estimate the extent of land. Degradation to assess saline or salt-free soils and calcareous or sodium soils and to compare this knowledge with satellite studies the spatial variability of these soil parameters was shown in soil maps created in a GIS environment. The findings showed that the soil in the study region was vulnerable to salt infiltration and water erosion that could be traced primarily to irrigation practices in the Maitha Block of Kanpur district. A temporary study of the 2013 and 2016 LISS III satellite datasets was also done to find the parameters that are responsible for land degradation, respectively.
Journal of Global Ecology and Environment, 2021
A wide range of applications requires a detailed mapping of wasteland changes at a regional scale. Data on wastelands in the form of maps and statistics are needed for spatial planning and management. In the present study, the extent and changes in wastelands are evaluated during 2006-2016 in Sri Potti Sriramulu (SPS) Nellore district. Indian Remote Sensing Satellite (IRS) data pertaining to Kharif, Rabi and Zaid seasons have been used for interpretation of wastelands during 2005-06, 2008-09, and 2015-16. Twelve wasteland categories were identified and delineated using on-screen visual image interpretation techniques in GIS environment. The geographical extent of wastelands was spread over constitute about 2433 sq. km (18.42%) in 2005-06, 2304 sq. km (17.44%) in 2008-09, and 2045 sq. km (15.48%) in 2015-16. It is observed that there is a reduction in the extent of wastelands during 2006-16 by an area of about 388 sq. km (2.93%). There is a considerable change in the extents of open scrub, dense scrub and scrub forest area; whereas little changes are observed in sands, barren rocky and other wasteland categories. The decreased in the district's wasteland areas can be attributed to the implementation of various developmental initiatives. They include watershed development, industrial development and the influence of the industrial corridors in the district.
Journal of Geography, Environment and Earth Science International
Increasing population worldwide has put tremendous pressure on the land. Recent studies reported that many areas covered by wastelands are decreasing because parts of wastelands are being converted into arable land. It is important to identify and monitor these changes in spatial planning and management. This paper adopts a remote sensing-based identification of culturable wastelands based on seasonal vegetation changes in Vadodara district, India. Supervised classification was applied on three MODIS images of 2016-17 of 3 different seasons. Separability analysis was applied to get the best data combination for image classification. Validation was done by ground referencing and Google earth images. The composite of winter season image with NDVI and EVI performed best with an overall accuracy of 78.2% with the kappa co-efficient of 0.7580. This method opens a possibility of using digital classification for identification of culturable wastelands in the study area which are so far mapped with visual interpretations only.
Forest is important source of biodiversity in the study area forest are spreading all over the area we are comparing to forest with wastelands we know that where the Granitic is present where wasteland is developed overall studying about forest in study area highest forest coming under the kanakapura region , North of Tumkur and southern part of Chitradurga Remote sensing (RS) is an efficient and cost-effective means of monitoring landscapes. One of the key challenges in the RS study is to improve the accuracy of classification. The present study aims to propose appropriate the Major identifiable wasteland categories are barren rocky; land with scrub; mining wasteland and salt affected area. The final result specifies each wasteland categories in the study area using GIS technique considering the environmental, biophysical and socio-economic factors.
Arabian Journal of Geosciences, 2014
The present study provides assessment of waste- land development in Bihar State based on satellite data. Wasteland covers 6.90 % (6,501 km2 ) of the state area and exhibits dominance of waterlogged areas in North Bihar (25.28 %) and scrubland (26.61 %) in South Bihar. The waterlogged areas in the state are dominantly associated with northern Bihar plains (94%) with minor development (6%) in southern Bihar plains. Such unequal distribution of water- logged land areas in northern and southern Bihar plains is largely governed by high cumulative discharge generated in the large catchment area in Himalayan mountain ranges in the upland areas of northern Bihar plains in contrast to low cumulative discharge generated within small catchments in the Chota Nagpur Plateau in the southern Bihar plains. It is evaluated that the relief and groundwater level define the primary controlling factors, whereas rainfall, watershed area, and upland/plain ratio exert secondary control. Lower relief areas with high rainfall exhibit high soil moisture thereby inducing conditions of waterlogging. The study signifies the potential of satellite image-based evaluation of waterlogging through the use of Digital Elevation Model, Tropical Rainfall Measuring Mission-based rainfall measurement, and temporal waterlogging assessment together with other terrain parameters for conceptual understanding of waterlogging in northern Bihar plains.
In this project, we studied land use and land cover classification of Nirmal Mandal, Adilabad district, Telenagna state by using Geographical Information system and Remote sensing techniques. LISS-IV satellite image resolution 5 m × 5 m provides quality information for identification of Land use/Land cover characteristics. The image accuracy shows 45.70% of Agricultural land, 9.10% Built-up land, Forest area is 7.90%, Barren land have 7.60% and Uncultivated land occupied 29.70%. National land use and land cover mapping report based on 5 divisions classified in the study area. The area land use and land cover classification provide reliable data to understand land, water, soil, forests , urban sprawl. This socio economic survey significantly shows the changes that so far have taken place. This will help the people/farmers for the future land use and land cover change detection. Regular monitoring of agriculture , forest and greening efforts for plantation at suitable area, schemes and limitations. Free ware browsing of land cover gives sufficient development to plenty resource.
Spatial Analysis of Land Use/Land Cover over India Using Satellite Based Remote Sensing Techniques
2000
Land use/land cover information is the basic prerequisite for land and water resource utilisation, conservation and management. The information on land use/land cover available today in form of thematic maps, published statistical figures in records and publications, are inadequate, inconsistent and do not provide up-to-date information on the changing land use patterns, processes and their spatial distribution in space and time. Efforts made by the State/Central Government departments and other institutions to bridge the information gaps and remove inconsistency in ground data collection, reporting and data compilation procedures, though encouraging, it is slow and time consuming. It is here, satellite remote sensing offers alternate, efficient and faster mode of data collection and updating of the land use/land cover information and helps to arrive at a standard classification and explanation to different land use/land cover classes. Realising the need for an up-to-date and accurate land use/land cover maps by several departments in the country, especially for agricultural land use planning, at the behest of Planning Commission, Government of India, National Remote Sensing Agency (NRSA)/Department of Space (DOS), Government of India, has carried out the land use/land cover mapping for the fifteen Agro-Climatic Zones (ACZ) covering all the 442 districts in the country on 1:250,000 scale using standardised IRS (LISS-II) satellite data of 1988-89 years. A land use/land cover classification system comprising twenty-two classes (upto Level-II) was developed.