Land Use Land Cover of an Urban Area using Remote Sensing (Texture Analysis Applications) and GIS - A Case Study of Central Region of Almadinah Almunawarah, Saudi Arabia

2017 ◽  
Vol 6 (1) ◽  
pp. 2114-2123
Author(s):  
Saleh Daqamseh ◽  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Saudi Arabia ◽  
Land Cover ◽  
Texture Analysis ◽  
Urban Area ◽  
Central Region ◽  
Land Use Land Cover

Land Use/Land Cover Dynamic Monitoring and Analysis Using Remote Sensing and GIS Techniques: Case Study of Qingpu District, Shanghai

2012 ◽  
Vol 518-523 ◽  
pp. 5704-5709
Author(s):  
Yi Lin ◽  
Bing Liu ◽  
Feng Xie ◽  
Wen Wei Ren
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Remote Sensing Data ◽  
Dynamic Monitoring ◽  
Land Use Land Cover ◽  
Ecological Value ◽  
Barren Land

This paper illustrates almost twenty years (1986～2007) of Land use/land cover change (LULCC) in Qingpu-one district of Shanghai. Qingpu District is an area of Upper Huangpu Catchment for fresh water supply with considerable ecological value, but it is also experiencing urban sprawl from development. To reveal the trends underlie LULCC, we propose a novel procedure to quantify different land use/land covers and implement it in the case study. In this procedure, we first collect historical remote-sensing data and co-registered or corrected them to the same spatial resolution and radioactive level. Based upon preliminary interpretation or investigation, land use/land cover types in study area can be included in 5 categories, i.e. Water, Agricultural Land, Urban or Built-up Land, Forest Land, and Barren Land or others. Moreover, data is clipped via boundary of study area for reducing computation load, followed by FPCR-ISODATA classification to divide the data into k groups (k>the number of land types). After postprocessing, e.g., merge the same connoted subgroups and correct misclassified units accompany with validation and verification, the detailed land use/land cover results can be achieved accurately. The quantitative and regression analysis indicate that during the past twenty years the area of agricultural land of Qingpu decreased coupled with urban or built-up area increased linearly. The water area had the minimum change during the decades. Forests had the smallest average proportion (9.6%) of the total area. It occupied so small proportion of land that we can only find points of it in the maps. Barren land can be an indicator for monitoring uncompleted redevelopment or transition of land.

scholarly journals Evaluating Changes in Land Use Land Cover using Remote Sensing Satellite Data and GIS (A Case Study in Patna Municipal Corporation Area) Patna, Bihar

2020 ◽  
pp. 346-353
Author(s):  
Mohammad Ahmad ◽  
Nikhat Hassan Munim
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Image ◽  
Land Use Land Cover ◽  
Rural And Urban ◽  
Multi Temporal ◽  
Color Composite ◽  
Irs P6 Liss Iv

Evaluation of land use land cover (LULC) change is an essential aspect of development in rural and urban sectors. This paper investigates the changes in LULC aspects of an environmentally vulnerable Patna Municipal Corporation (PMC) area in the middle-Ganga Plain, India. We offer Remote Sensing (RS), and Geographic Information System (GIS) techniques delineated LULC types include water bodies, agriculture land, fallow land, wasteland, built-up land and vegetation of the study area. LULC mapping of the study area was done through False Color Composite (FCC) Satellite image Resourcesat-1 (IRS P6 LISS-IV) and Resourcesat 2A (IRS-R2A LISS-IV) with 5.8-meter spatial resolution data of the year 2007 and 2018 respectively. The supervised classification and maximum likelihood equation were used to classified two multi-temporal images. Then temporal changes were detected by comparison between two LULC classified maps of 2007 and 2018, which was produced independently. Patna Municipal Corporation (PMC) area, Patna is one of the environmentally vulnerable areas under the threat of environmental and ecological degradation as a result of human activities due to improper land cover management. The main objective of using change detection is an important technique to detect changes in LULC over time in PMC, Patna between 2007-2018, and it is significant for updating land cover or natural resource management. The interpretation of this study has substantial changes in LULC occurred in the Patna Municipal Corporation (PMC) area, Patna within the period 2007-2018, related to urbanisation and economic development. The analysis outcome indicates the most remarkable changes occurred an increase in Built-up, (+) 21.86 % between 2007-2018, whereas the area of cropland and vegetation decreased (-) 8.95 % and (-) 5.8% respectively between 2007-2018. In the spatial distribution pattern, other changes have also occurred. This study will give the benefit in future action plans in land use and urban development and avoid LULC changes without proper planning. It will be most significant for the natural environment.

scholarly journals Spatial change detections and inventory of wetlands in Yenagoa Urban Area: Bayelsa State, Nigeria

2021 ◽  
Vol 6 (6) ◽  
pp. 230-240
Author(s):  
Eze Promise I ◽  
Elemuwa IC ◽  
Lawrence Hart
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Area ◽  
Urban Expansion ◽  
Rate Of Change ◽  
Percentage Change ◽  
Annual Rate ◽  
Land Use Land Cover ◽  
Total Percentage

Yenegoa Town has in recent years witnessed rapid City growth and Urban development and much of these developments are unplanned and unregulated. This has seriously impacted on wetlands in several locations of the town as persistent Wetlands reclamations are being witnessed in study area. This prompted the need for the study which is aimed to map wetlands location in Yenagoa’s urban area using GIS and Remote Sensing approach. The study analyzes land use/land cover changes (LULC) using LANDSAT(5) TM, LANDSAT(5) ETM and LANDSAT(7) OLI satellite imageries of 1990, 2000, 2010 and 2020 respectively. Through this study, the pattern of urban expansion for Thirty years were been studied. The satellite imageries covering the area were acquired and analyzed using ArcGIS 10.1 and ENVI 5.0 software. The supervised image classification method was adopted and the classification results were validated using the Kappa Index of Agreement (KIA) yielding an accuracy of 0.69m for year 1990, 0.62m for year 2000, 0.58m for year 2010 and 0.73m for 2020. A total area of 13,741.4 hectares was delineated in the study area which is identified as Yenagoa’s urban area. After processing the imageries, four land use/land cover (LULC) classes where considered, and the results shows that Built-up area continuously increased in land area from 1990 -2020 with total percentage change of 273.31% (4,178.7ha) and total annual rate of change of 25.33. Vegetation have total percentage change of 38.55% (974.34Ha) and total annual rate of change of 3.85, wetland cover loss with total percentage Change of 61.96% (-51,44.99ha) and total annual rate of change of -6.19ha, and the water body have loss of total percentage of -2.16% (-8.05Ha) and total annual rate of change of -0.22ha wetland at Yenegwe loss by Total %change of -29.918% ( -197.95ha), and wetland at Igbogene loss by total percentage change of -36.028% (-358.7ha). The research findings also revealed that the wetlands in Anyama, Swali, Kpansia and Opolo Towns were completely lost from the third Epoch of 2010, this may be as a result of persistence reclamation of wetland in this parts of the study area. The Markov Chain predicted model were utilized for predicting the likely changes in land use land cover for a period of thirty years. The predicted results also indicates that wetland size of 32.47,%, 30.68% and 28.99% may likely be lost by the year 2030, 2040 and 2050 respectively in study area if no action is taking by concerned authorities to forestall the factors responsible for the lost in wetland. The study justified the dynamics of remote sensing and GIS techniques in modeling wetlands changees over these periods, wise use of wetland resources and improvement of institutional arrangement were recommended so that wetland policies can be fully integrated into the planning process across all disciplines.

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