scholarly journals Analysis of Land Use/Land Cover Changes Using Remote Sensing Data and GIS at an Urban Area, Tirupati, India

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Praveen Kumar Mallupattu ◽  
Jayarama Reddy Sreenivasula Reddy
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Area ◽  
Geographical Information Systems ◽  
Remote Sensing Data ◽  
Geographical Information ◽  
Land Use Land Cover ◽  
Rapid Urbanization ◽  
Sensing Data

Land use/land cover (LU/LC) changes were determined in an urban area, Tirupati, from 1976 to 2003 by using Geographical Information Systems (GISs) and remote sensing technology. These studies were employed by using the Survey of India topographic map 57 O/6 and the remote sensing data of LISS III and PAN of IRS ID of 2003. The study area was classified into eight categories on the basis of field study, geographical conditions, and remote sensing data. The comparison of LU/LC in 1976 and 2003 derived from toposheet and satellite imagery interpretation indicates that there is a significant increase in built-up area, open forest, plantation, and other lands. It is also noted that substantial amount of agriculture land, water spread area, and dense forest area vanished during the period of study which may be due to rapid urbanization of the study area. No mining activities were found in the study area in 1976, but a small addition of mining land was found in 2003.

scholarly journals INTEGRATION OF REMOTE SENSING DATA AND BASIC GEODATA AT DIFFERENT SCALE LEVELS FOR IMPROVED LAND USE ANALYSES

2015 ◽  
Vol XL-3/W3 ◽  
pp. 85-89 ◽  
Author(s):  
G. Waldhoff ◽  
S. Eichfuss ◽  
G. Bareth
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Spatial Resolution ◽  
Geographical Information Systems ◽  
High Spatial Resolution ◽  
Regional Scale ◽  
Remote Sensing Data ◽  
Geographical Information ◽  
Sensing Data ◽  
Very High Spatial Resolution

The classification of remote sensing data is a standard method to retrieve up-to-date land use data at various scales. However, through the incorporation of additional data using geographical information systems (GIS) land use analyses can be enriched significantly. In this regard, the Multi-Data Approach (MDA) for the integration of remote sensing classifications and official basic geodata for a regional scale as well as the achievable results are summarised. On this methodological basis, we investigate the enhancement of land use analyses at a very high spatial resolution by combining WorldView-2 remote sensing data and official cadastral data for Germany (the Automated Real Estate Map, ALK). Our first results show that manifold thematic information and the improved geometric delineation of land use classes can be gained even at a high spatial resolution.

scholarly journals Estimating the Volume of Sediments and Assessing the Water Balance of the Badra Basin, Eastern Iraq, Using Swat Model and Remote Sensing Data

2021 ◽  
Vol 54 (2C) ◽  
pp. 88-99
Author(s):  
Awad A. Sahar
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Water Balance ◽  
Assessment Tool ◽  
Remote Sensing Data ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
Sensing Data ◽  
Water Assessment

The primary objective of this study is to employ the remote sensing data and Soil & Water Assessment Tool model to estimate sediment volume and assess the water balance of the Badra Basin (2,615km2) in eastern Iraq. Remote sensing data was utilized as the main input with the Soil & Water Assessment Tool model. These data involved a land use-land cover map that was constructed by the classification of the Landsat-8 satellite imagery for the year 2020, STMR digital elevation model, soil map was acquired from the Food and Agriculture Organization and climatic data were sourced from the NASA-funded prediction of Worldwide Energy Resource The results discovered that about 40 % and 18% of the yearly rainfall are losing by evapotranspiration and filtration. The average amount of annual sediment transported was predicted at 120.47 tons /ha, 2018 recorded the highest value of transported sediment which is about 360 tons /ha. The volume of annual runoff was assessed at about 340.74 million m3. These results proved that the Soil & Water Assessment tool model has the ability to estimation the sediment and runoff volume. The climatic elements, especially rainfall, in addition to soil classes, topography, and land use-land cover had a significant impact on the amount of transported sediments and the volume of runoff.

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