Multi-criteria land suitability analysis for agriculture in hilly zone: Remote sensing and GIS approach

2015 ◽  
Vol 118 ◽  
pp. 300-321 ◽  
Author(s):  
Rajendra Bhausaheb Zolekar ◽  
Vijay Shivaji Bhagat
Keyword(s):  
Remote Sensing ◽  
Remote Sensing And Gis ◽  
Land Suitability ◽  
Suitability Analysis ◽  
Land Suitability Analysis

scholarly journals Land Suitability Analysis for UrbanPlan Preparation Using Remote Sensing and GIS A Case of Anand-Vidyanagar-Karamsad Development Plan

10.29007/xcm1 ◽  
2018 ◽  
Author(s):  
Mehul Darshak ◽  
Rajan Zala ◽  
Manthan Bhandari ◽  
Dr. Shashikant Kumar
Keyword(s):  
Remote Sensing ◽  
Urban Development ◽  
Remote Sensing And Gis ◽  
Land Suitability ◽  
Development Plan ◽  
Gis Analysis ◽  
Suitability Analysis ◽  
Land Utilization ◽  
Land Suitability Analysis ◽  
Selection Of

Land Suitability analysis is important for preparation of Development Plan. The planning requires undertaking study of topography, water resources, land utilization, and development needs. The RS & GIS techniques offers suitable analytical opportunity to study variables required for selection of sites for various uses. This paper presents process adopted for the preparation of development plan of Anand Vidyanagar Karamsad Urban Development Authority (AVKUDA), regarding the land suitability analysis. The location and types of land to be protected were identified using RS Data and GIS analysis. Keywords— AVKUDA; Land Suitability; Planning; RS & GIS

scholarly journals Change Detection and Land Suitability Analysis for Extension of Potential Forest Areas in Indonesia Using Satellite Remote Sensing and GIS

Forests ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 398 ◽  
Author(s):  
Nety Nurda ◽  
Ryozo Noguchi ◽  
Tofael Ahamed
Keyword(s):  
Remote Sensing ◽  
Change Detection ◽  
Satellite Remote Sensing ◽  
Land Suitability ◽  
Landsat 8 ◽  
Suitability Analysis ◽  
Land Suitability Analysis ◽  
Expert Opinions ◽  
Detection Analysis ◽  
The Government

The objective of this research was to detect changes in forest areas and, subsequently, the potential forest area that can be extended in the South Sumatra province of Indonesia, according to the Indonesian forest resilience classification zones. At first, multispectral satellite remote sensing datasets from Landsat 7 ETM+ and Landsat 8 OLI were classified into four classes, namely urban, vegetation, forest and waterbody to develop Land Use/Land Cover (LULC) maps for the year 2003 and 2018. Secondly, criteria, namely distance from rivers, distance from roads, elevation, LULC and settlements were selected and the reclassified maps were produced from each of the criteria for the land suitability analysis for forest extension. Thirdly, the Analytical Hierarchy Process (AHP) was incorporated to add expert opinions to prioritize the criteria referring to potential areas for forest extension. In the change detection analysis, Tourism Recreation Forest (TRF), Convertible Protection Forest (CPF) and Permanent Production Forest (PPF) forest zones had a decrease of 20%, 13% and 40% in area, respectively, in the forest class from 2003 to 2018. The Limited Production Forest (LPF) zone had large changes and decreased by 72% according to the LULC map. In the AHP method, the influential criteria had higher weights and ranked as settlements, elevation, distance from roads and distance from rivers. CPF, PPF and LPF have an opportunity for extension in the highly suitable classification (30%) and moderately suitable classification (41%) areas, to increase coverage of production forests. Wildlife Reserve Forests (WRFs) have potential for expansion in the highly suitable classification (30%) and moderately suitable classification (52%) areas, to keep biodiversity and ecosystems for wildlife resources. Nature Reserve Forests (NRFs) have an opportunity for extension in the highly suitable classification (39%) and moderately suitable classification (48%) areas, to keep the forests for nature and biodiversity. In case of TRF, there is limited scope to propose a further extension and is required to be managed with collaboration between the government and the community.

scholarly journals Remote Sensing and Land Suitability Analysis to Establish Local Specific Inputs for Paddy Fields in Subang, West Java

2016 ◽  
Vol 33 ◽  
pp. 94-107 ◽  
Author(s):  
Widiatmaka ◽  
Wiwin Ambarwulan ◽  
Paulus B.K. Santoso ◽  
Supiandi Sabiham ◽  
Machfud ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Suitability ◽  
Paddy Fields ◽  
Suitability Analysis ◽  
West Java ◽  
Land Suitability Analysis

scholarly journals THE UTILIZATION OF REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEMS FOR ANALYSIS OF LAND SUITABILITY FOR THE GROWING OF CIPLUKAN (PHYSALIS ANGULATA L.)

2019 ◽  
Vol 16 (1) ◽  
pp. 1
Author(s):  
Nur Adliani ◽  
Nirmawana Simarmata ◽  
Heriansyah Heriansyah
Keyword(s):  
Remote Sensing ◽  
Information Systems ◽  
Geographic Information Systems ◽  
Remote Sensing Data ◽  
Geographic Information ◽  
Land Suitability ◽  
Suitability Analysis ◽  
Land Suitability Analysis ◽  
Sensing Data ◽  
Physalis Angulata

Remote sensing data and geographic information systems are widely used for land suitability analysis for crops such as coffee and corn. This study aims to analyze and map suitable land for the plant known locally as ciplukan (Physalis angulata L.).  As the cultivation of this plant is expected to be developed by the Institute of Technology of Sumatra, analysis of this type is needed. The parameters used in this study were slope, land use, rainfall and soil type. Information extraction from remote sensing data was carried out via visual interpretation of aerial photography used to create land-cover maps. Shuttle RADAR Topographic Mission (SRTM) data was converted from digital surface model (DSM) to digital terrain model (DTM) to provide elevation information. Land suitability analysis was performed using a scoring method and overlay analysis. The results obtained from the analysis identified several classes of land suitability for Physalis angulata L., categorized as suitable, less suitable, and not suitable. The less suitable class, scored at 9 to 11, comprised a total area of 180.96 ha, while the suitable area, scored at 12, comprised a total area of 49.1 ha.

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