scholarly journals GIS and Remote Sensing Based Physical Land Suitability Analysis for Culitivation OF Selected Cool Weather Cereal Crops, Misha District, Hadiya Zone, South Central Ethiopia

2020 ◽  
Author(s):  
Solomon Abebe
Keyword(s):  
Land Suitability ◽  
Cereal Crops ◽  
Climatic Data ◽  
Suitability Analysis ◽  
Weighted Overlay ◽  
Land Suitability Analysis ◽  
Central Ethiopia ◽  
South Central ◽  
Suitability Map ◽  
Hadiya Zone

This study to assess the Physical Land Suitability Analysis for Cultivation of Selected Cool Weather Cereal Crops, Misha District, Hadiya Zone, South Central Ethiopia of major cereal crops of barley and teff in Misha district. Each of the criteria was separately reclassified and analyzed for their suitability for supporting barley and teff crops based on the FAO crop requirements specified for them. The major data sources were climatic data, soil, LGP and topographic data as well as key informant interview, questioner observation of crop requirements which have been considered to undertake suitability assessments of the study area. The factor maps like land use /land cover, temperature, rain fall, soil type and altitude were classified based on suitability evaluation methods of FAO and experts’ opinion. At final stage these were reclassified and standardized in GIS software extension tools, which led to the preparation of suitability analysis map of the major crops plant suitability classes. As part of spatial MCDM, AHP pair wise comparison module was used to derive internal and external weights for each individual factors and parameters respectively. Consequently, suitability analysis was done and weighted overlay suitability map was visualized with integration of GIS. The findings show that among total area of land suitability maps for both barley and teff cops were using weighted overlay techniques. The suitability map of teff crop shows that 12,038.22 hectare of the investigated area are highly suitable (S1), 19,646.07 hectare moderately suitable (S2) and 4,501.71 hectare marginally suitable (S3) and 112 hectare not suitable. On the other hand, the suitability map of barley crop shows that 7,898.52 hectare of the investigated area are highly suitable (S1), 22,830.08 hectare moderately suitable (S2), and 5,466.4 hectare marginally suitable (S3) and 103 hectare not suitable for economic reasons (N1). This was done for barley and Teff crops separately. Results of the study revealed that most of the lands in the study area are suitable for the cultivation of the selected crops and other crops. Based on finding, it could be recommended that this work would be used as policy guide for planners; investment could be successful in the District, further suitability research works should be carried out in order to optimize the major crop cultivation and production.

Multi-Criteria Land Suitability Analysis for Plantation in Upper Mula and Pravara Basin: Remote Sensing and GIS Approach

2018 ◽  
Vol 2 (1) ◽  
pp. 12-21 ◽  
Author(s):  
Rajendra Zolekar ◽  
Vijay Bhagat
Keyword(s):  
Pairwise Comparison ◽  
Field Work ◽  
Land Suitability ◽  
Suitability Analysis ◽  
Analytic Hierarchy ◽  
Pairwise Comparison Matrix ◽  
Weighted Overlay ◽  
Land Suitability Analysis ◽  
Final Output ◽  
Hierarchy Process

Assessment of land suitability potentials is an important step to detect the environmental limit for sustainable land management (SLM). Land suitability analysis (LSA) is more suitable, beneficial and environmentally acceptable for SLM. It deals with the assessment of land performances for the specific use like agriculture, plantation, etc. The main objective of the present study was to determine the suitable areas for plantation in the Upper Mula and Pravara Basin. GIS based Analytic Hierarchy Process (AHP) was used to analyze land suitability for plantation. Criterion like slope, LULC, depth, texture, moisture, SOC, MWHC, pH, EC and primary nutrients were used. Pairwise comparison matrix was used for calculation of weights for criterion and scores were assigned to sub-criterion using field work, experts’ opinions and literature review. Weighted overlay analysis was used for final output raster map. Then cell values of raster map were divided into four classes i.e. 9, 7, 4 and 1. Finally, these classes have reclassified into four suitability levels according to FAO. About 5% of reviewed land is highly suitable, 23% moderately suitable, 14% marginally suitable and 58% not suitable for plantation in the region.

scholarly journals Land suitability analysis for rice cultivation using a GIS-based fuzzy multi-criteria decision making approach: central part of Amol District, Iran

2017 ◽  
Vol 12 (No. 1) ◽  
pp. 29-38 ◽  
Author(s):  
Z. Maddahi ◽  
A. Jalalian ◽  
M.M. Kheirkhah Zarkesh ◽  
N. Honarjo
Keyword(s):  
Decision Making ◽  
Climatic Conditions ◽  
Land Suitability ◽  
Rice Cultivation ◽  
Multi Criteria Decision Making ◽  
Suitability Analysis ◽  
Analytical Hierarchical Process ◽  
Land Suitability Analysis ◽  
Suitability Map ◽  
Land Use Maps

Land suitability analysis and preparing land use maps is one of the most beneficial applications of the Geographic Information System (GIS) in planning and managing land recourses. The main objective of this study was to develop a fuzzy multi-criteria decision making technique integrated with the GIS to assess suitable areas for rice cultivation in Amol District, Iran. Several suitability factors including soil properties, climatic conditions, topography, and accessibility were selected based on the FAO framework and experts’ opinions. A fuzzy analytical hierarchical process (FAHP) was used to determine the weights of the various criteria. The GIS was used to overlay and generate criteria maps and a land suitability map. The study area has been classified into four categories of rice cultivation suitability (highly suitable, suitable, moderately suitable, and unsuitable). The present study has attempted to introduce and use the FAHP method to land suitability analysis and to select lands in order to be used as best as possible. Areas that are classified as highly suitable and suitable for rice cultivation constitute about 59.8% of the total area of the region. The results of the present research indicate that the FAHP is an efficient strategy to increase the accuracy of the weight of the criteria affecting the analysis of land suitability.

scholarly journals Agroforestry land suitability analysis in the Eastern Indian Himalayan region

2021 ◽  
pp. 100199
Author(s):  
Arun Jyoti Nath ◽  
Rakesh Kumar ◽  
N. Bijayalaxmi Devi ◽  
Pebam Rocky ◽  
Krishna Giri ◽  
...  
Keyword(s):  
Land Suitability ◽  
Himalayan Region ◽  
Suitability Analysis ◽  
Indian Himalayan Region ◽  
Land Suitability Analysis

scholarly journals Kajian Kesesuaian Lahan Perkebunan Kopi Rakyat Kawasan Lereng Gunung Arjuna Kabupaten Malang

2020 ◽  
Vol 4 (2) ◽  
pp. 108
Author(s):  
Dimas Prakoswo Widayani ◽  
Kresna Shifa Usodri
Keyword(s):  
Temperature Data ◽  
Land Suitability ◽  
Maximum Temperature ◽  
Cultivated Plants ◽  
Survey Method ◽  
Mountainous Area ◽  
Suitability Analysis ◽  
Arabica Coffee ◽  
Land Suitability Analysis ◽  
Coffee Plants

Mount Arjuna is a mountainous area with forests and several cultivated plants located in Malang Regency, East Java. The forest is a complex area that is used as a protected area, research and production forest for agricultural commodities. The complex is located in the forest resulted in highly varied environmental conditions. The forest consists of several areas, namely protected forest, production forest, coffee plantation, and seasonal plantations. The Arjuna mountain area has several stands including pine and mahogany, but most of it is filled with pines by 90% and mahogany trees around 10%. Most of the coffee plants found in the Arjuna mountain forest area are Arabica coffee, while the rest is robusta coffee. This research was conducted on the slopes of Mount Arjuna, located in Sumbersari Village, Karangploso District, Malang Regency, East Java. This research was conducted from July to October 2017. This research employed a survey method by taking several sample points that represent the coffee plants in the area. Several sampling plots for land suitability analysis were identified in the area: The observation stages were carried out by taking air temperature data using a thermohygrometer by taking the minimum and maximum temperature data, taking air humidity using a thermohigrometer as well as minimum and maximum data and light intensity data using lux meters, taking soil samples to measure nutrients and soil fertility, and measuring the height and slope of the land. The results of the observations that have been made will be analyzed using the land suitability analysis method, by adjusting the area's data with the land suitability level for robusta and arabica coffee plants.Gunung Arjuna merupakan kawasan pegunungan dengan hutan serta beberapa tanaman budidaya yang terletak di Kabupaten Malang, Jawa Timur. Hutan tersebut merupakan kawasan kompleks yang dimanfaatkan sebagai kawasan lindung, riset dan juga hutan produksi untuk komoditas pertanian. Kondisi hutan yang kompleks mengakibatkan kondisi lingkungan tersebut sangat bervariatif. Hutan terdiri dari beberapa kawasanya, yaitu hutan lindung, hutan produksi, perkebunan kopi serta kawasan tanaman semusim. Kawasan gunung Arjuna memiliki beberapa tegakan diantaranya pinus dan mahoni namun sebagian besar dipenuhi oleh pinus sebesar 90% dan pohon mahoni berkisar 10%. Sebagian besar tanaman kopi yang terdapat pada kawasan hutan gunung Arjuna adalah jenis kopi arabika sedangkan sisanya adalah kopi robusta. Penelitian ini dilakukan di kawasan lereng Gunung Arjuna, Terletak di Desa Sumbersari, Kecamatan Karangploso, Kabupaten Malang, Jawa Timur. Penelitian ini akan dilaksanakan pada bulan Juli–Oktober 2017. Penelitian ini menggunakan metode survei dengan mengambil beberapa titik sampel yang mewakili yang mewakili tanaman kopi di kawasan tesebut. Beberapa plot sampel pengambilan sampel untuk analisis kesesuaian lahan diidentifikasi pada kawasan: Adapun tahapan pengamatan yang dilakukanya itu pengambilan data suhu udara menggunakan termohigrometer dengan mengambil data suhu minimum dan maksimum, pengambilan kelembapan udara dengan alat termohigrometer juga data minimum dan maksimum serta data intensitas cahaya menggunakan lux meter, pengambilan sampel tanah untuk mengukur hara serta kesuburan tanah, mengukur ketinggian serta tingkat kelerengan lahan. Hasil pengamatan yang telah dilakukan akan dianalisis menggunakan metode analisis kesesuaian lahan, dengan menyesuaikan data kawasan tersebut dengan tingkat kesesuaian lahan untuk tanaman kopi robusta dan arabika.

Multi-criteria Land Suitability Analysis for Agriculture in Semi-Arid Region of Kadapa District, Southern India: Geospatial Approaches

2021 ◽  
Vol 5 (2) ◽  
pp. 59-72
Author(s):  
Rajasekhar M. ◽  
Sudarsana Raju G. ◽  
Nanabhau Kudnar ◽  
Ramachandra M. ◽  
Pradeep Kumar B.
Keyword(s):  
Agricultural Land ◽  
Pairwise Comparison ◽  
Land Suitability ◽  
Suitability Analysis ◽  
Environmental Pressures ◽  
Land Suitability Analysis ◽  
Agricultural Efficiency ◽  
Integrated Methodology ◽  
Low Efficiency ◽  
Semi Arid Region

This research proposes an integrated methodology for incorporating RS, GIS and AHP techniques for the assessment of agricultural land suitability. In Kadapa district, Andhra Pradesh, India, study is being done on how to best promote agriculture as a source of income to boost the economy of the region. A combined RS, GIS and AHP techniques has been utilized that incorporates organizing AHP hierarchy, criteria specification, pairwise comparison, and criterion map preparation. Land suitability comparison showed that an area of 4.42 km2 (2.62%) is appropriate for irrigation, while an area of 54.39 km2 (32.33%) is appropriate moderately suitable for rainfed agriculture and 95.76 km2 (56.93%) is marginally suitable for agricultural productions. About 13.64 km2 (8.11%) land is currently not suitable for agricultural production. Additionally, the analysis clearly shows the necessity of a decrease in irrigated agricultural land and an increase in dry farm agricultural land. This application of RS, GIS and AHP based agricultural land suitability analysis is helpful in referring agricultural activities to the areas with good physical and environmental conditions, allowing maximum agricultural efficiency in the countryside, increasing non-agricultural uses in areas with low efficiency, and avoiding the construction and environmental pressures on suitable farmland.

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.

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