Multi-temporal remote sensing data of land use/land cover: Processing and accuracy assessment — A case of Wuhan Metropolitan

2009 ◽  
Author(s):  
Qun Zeng ◽  
Baoku Yin ◽  
Cheng Cai ◽  
Mingxiang Cai ◽  
Zheng Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Accuracy Assessment ◽  
Remote Sensing Data ◽  
Land Use Land Cover ◽  
Sensing Data ◽  
Multi Temporal

scholarly journals DISTRICT-WISE CHANGE ANALYSIS OF LAND USE-LAND COVER IN DELHI TERRITORY USING REMOTE SENSING & GIS

2017 ◽  
Vol 10 (2) ◽  
pp. 201-213
Author(s):  
Surya Prakash Pattanayak ◽  
Sumant Kumar Diwakar
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Land Use Changes ◽  
Remote Sensing Data ◽  
High Growth ◽  
Temporal Analysis ◽  
Land Use Land Cover ◽  
Change Analysis ◽  
Multi Temporal

Digital change detection is the process that helps in determining the changes associated with Land use and Land cover properties with reference to geo-referenced multi-temporal remote sensing data. It helps in identifying change between two or more dates that is uncharacterized of normal variation. This work is an attempt to assess the district-wise changes in land use/land cover in Delhi, India. The study made use of LISS -III imageries of 2008 and 2012 year. The images were classified using Maximum Likelihood classification method. The output can be useful in many applications such as Land use changes, habitat fragmentation, rate of deforestation, urban sprawl and other cumulative changes through spatial and temporal analysis. The study shows that Delhi land cover from 2008 to 2012 a major rapid changes in the landscape as there is high growth in the fallow and built up area. Agriculture land and forest area has reduced marginally and water body is showing almost stagnant condition over time.

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.

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.

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