scholarly journals INTEGRATED REMOTE SENSING AND GIS FOR MODELING ECONOMIC REHABILITATION DEVELOPMENT OF EX-MINE SITES

2017 ◽  
Vol 25 (2) ◽  
pp. 177-190
Author(s):  
Junaidi Junaidi ◽  
Eric K.H. Goh
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
World Wide ◽  
Land Development ◽  
Remote Sensing And Gis ◽  
Production Costs ◽  
Modeling Tool ◽  
Mine Sites ◽  
Site Rehabilitation ◽  
Efficient Modeling

The potential environmental impacts of mining, increasing environmental legislation and public awareness have received increased attention world-wide in the last two decades. The focus of concern by the industry, environmental regulatory agencies and members of the public is the systematic rehabilitation of ex-mine sites to improve the quality at site for potential future commercial land use. The minerals extracted from these mine/quarry sites are essential in the construction, semiconductor, high-technology, ceramic and other manufacturing sectors for further industrial development. However, efficient engineering design and systematic economic evaluation of mine sites for site rehabilitation are required in maintaining the expected standards of environmental compliance.  With escalating production costs and the keen competitiveness of the mining industry world-wide, the necessity to increase the efficiency in site rehabilitation is getting more prominence.  A coordinated environmental protection and rehabilitation programme is essential if the environmental awareness of the community and the demands of the respective planning authorities are to be accommodated. There is thus a need to increase the base of knowledge for efficient planning in the systematic and progressive rehabilitation of current and future ex-mine sites. An efficient modeling tool is required for the systematic planning and design of potential economic land development of ex-mine sites. The applicability of Remote Sensing and Geographic Information System (GIS) technology is a useful tool to acquire spatial information for the systematic design and planning of potential development of ex-mine sites. This research was conducted to detect the trends in the suitability of land cover changes via land cover change detection of ex-mine sites and validated with reality. The findings are useful to assist in the development of a tool for efficient modeling and design of potential economic development of ex-mine sites. The aim of this research is to quantify, model and map the economic potential of the ex-mine sites for built up areas such as housing and other urban infrastructures. Land cover classes were interpreted into maps and the accuracy of the maps were validated to reference data and actual ground scenarios. The study for validation of the proposed modeling tool was carried out using the large prominent mining area in Malaysia namely the Kinta District. Results from the validation study carried out indicate that the correlation of the results obtained from this Integrated Remote Sensing and GIS tool for modeling to field data is in the range of 0.87-0.92 which is acceptable and close to reality.

scholarly journals Impact of Land Cover Change on Soil Erosion Hazard in Northern Jordan Using Remote Sensing and GIS

2013 ◽  
Vol 19 ◽  
pp. 912-921 ◽  
Author(s):  
M.Minwer Alkharabsheh ◽  
T.K. Alexandridis ◽  
G. Bilas ◽  
N. Misopolinos ◽  
N. Silleos
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Land Cover ◽  
Land Cover Change ◽  
Remote Sensing And Gis ◽  
Erosion Hazard ◽  
Northern Jordan

scholarly journals Application of remote sensing and GIS in land use/land cover mapping and change detection in Shasha forest reserve, Nigeria

2014 ◽  
Vol XL-8 ◽  
pp. 613-616 ◽  
Author(s):  
O. S. Olokeogun ◽  
K. Iyiola ◽  
O. F. Iyiola
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Sustainable Forest Management ◽  
Cost Effective ◽  
Remote Sensing And Gis ◽  
Clear Understanding ◽  
Forest Reserve ◽  
Landsat Satellite

Mapping of LULC and change detection using remote sensing and GIS techniques is a cost effective method of obtaining a clear understanding of the land cover alteration processes due to land use change and their consequences. This research focused on assessing landscape transformation in Shasha Forest Reserve, over an 18 year period. LANDSAT Satellite imageries (of 30 m resolution) covering the area at two epochs were characterized into five classes (Water Body, Forest Reserve, Built up Area, Vegetation, and Farmland) and classification performs with maximum likelihood algorithm, which resulted in the classes of each land use. <br><br> The result of the comparison of the two classified images showed that vegetation (degraded forest) has increased by 30.96 %, farmland cover increased by 22.82 % and built up area by 3.09 %. Forest reserve however, has decreased significantly by 46.12 % during the period. <br><br> This research highlights the increasing rate of modification of forest ecosystem by anthropogebic activities and the need to apprehend the situation to ensure sustainable forest management.

scholarly journals Land Use/Land Cover Mapping of Sambar Watershed by Using Remote Sensing and GIS

2021 ◽  
Vol 10 (9) ◽  
pp. 578-585
Author(s):  
B. Varpe Shriniwas D. Payal Sandip
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Remote Sensing And Gis ◽  
Rapid Expansion ◽  
Water Bodies ◽  
Land Cover Mapping ◽  
Fallow Land ◽  
Land Use Land Cover ◽  
Barren Land

In the present study, an effort has been made to study in detail of Land Use/Land Cover Mapping for Sambar watershed by using Remote Sensing and GIS technique was carried out during the year of 2020-2021 in Parbhani district. In this research the Remote Sensing and Geographical Information system technique was used for identifying the land use/land cover classes with the help of ArcGIS 10.8 software. The Sambar watershed is located in 19º35ʹ78.78˝ N and 76º87ʹ88.44˝ E in the Parbhani district of Marathwada region in Maharashtra. It is covered a total area 97.01 km2. The land use/land cover map and its classes were identified by the Supervised Classification Method in ArcGIS 10.8 software by using the Landsat 8 satellite image. Total six classes are identified namely as Agricultural area, Forest area, Urban area, Barren land, Water bodies and Fallow land. The Agricultural lands are well distributed throughout the watershed area and it covers 4135 ha. (43 per cent). Forest occupies 502 ha area and sharing about 5 per cent of the total land use land cover of the study area. The Urban land occupies 390 ha. area (4 per cent) and there was a rapid expansion of settlement area. Barren land occupies 3392 ha. area (35 per cent). A water bodies occupy 630 ha. area (6 per cent) and the Fallow land occupies 650 ha (7 per cent) but well-developed dendritic drainage pattern and good water availability is in the Sambar watershed.

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