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 Increasing Sugar Production in Indonesia Through Land Suitability Analysis and Sugar Mill Restructuring

Land ◽  
2019 ◽  
Vol 8 (4) ◽  
pp. 61 ◽  
Author(s):  
Andi Amran Sulaiman ◽  
Yiyi Sulaeman ◽  
Novia Mustikasari ◽  
Dedi Nursyamsi ◽  
Andi Muhammad Syakir
Keyword(s):  
Agricultural Land ◽  
Arable Land ◽  
World Market ◽  
Land Suitability ◽  
Sugar Production ◽  
Suitability Analysis ◽  
Land Suitability Analysis ◽  
The World ◽  
Sugar Mills ◽  
Sugarcane Productivity

Indonesia is the fourth most populated country in the world with an annual population growth rate of 1.3%. This growth is accompanied by an increase in sugar consumption, which is occurring at an annual rate of 4.3%. The huge demand for sugar has created a large gap between sugar production and demand. Indonesia became the world’s largest sugar importer in 2017–2018. Sugarcane farmers have an important role in sugar production. They are facing problems with declining sugarcane productivity and arable land decreasing. We aimed to understand the sugar production issue in Indonesia and to examine options to increase sugar production. To achieve these aims, a framework consisting of four steps was developed: Analysis of the current situation; problems identification; resolution; and delivering programs; and strategies. The main problems in sugar production in Indonesia were identified, including a stagnation in sugarcane harvest area, low sugarcane productivity, lack of good varieties, and inefficient sugar mills. Based on the identified problems, strategies to increase production were created. Two approaches need to be executed simultaneously: An increase in sugarcane planting area, and an increase in productivity and sugar yield. The first approach in increasing sugar production is the exploration of new sugarcane planting areas outside of Java both on existing agricultural land and in new areas. A land suitability analysis for the whole country was conducted based on a semi-detailed soil map. The main priority for development was the existing agricultural area via an integration system or existing crop exchange. The second approach is restructuring sugar factories through the revitalization of existing sugar mills and investment in the construction of new mills. The challenges that need to be addressed include land availability, provision of high-yielding varieties, and improving the efficiency of sugar mills. General strategies and medium-term programs are presented and discussed. These efforts, if well-executed, will boost Indonesia’s sugar production to meet its domestic demand by 2025, achieving competitiveness in the world market by 2045.

GIS-based Land Suitability Analysis for Surface Irrigation Using Analytical Hierarchy Process Method in East and West Bellessa, Northwestern Ethiopia

2021 ◽  
Author(s):  
Azemeraw Wubalem
Keyword(s):  
Analytical Hierarchy Process ◽  
Pairwise Comparison ◽  
Study Finding ◽  
Land Suitability ◽  
Suitability Analysis ◽  
Surface Irrigation ◽  
Pairwise Comparison Matrix ◽  
Land Suitability Analysis ◽  
Natural Break ◽  
Hierarchy Process

Abstract Bellessa is found in central Gondar, which is affected frequently by drought thanks to spatial and temporal failure of rainfall. Therefore, the agriculture in this area has to be supported by surface irrigation. For this, land suitability analysis for surface irrigation is extremely important to scale back food security problem. GIS-based land suitability analysis was conducted using analytical hierarchy process methods. Eight factors like slope, elevation, distance to water source, land use, soil texture, type, depth, and drainage are considered and therefore the weight of every parameter was estimated using 8x8 pairwise comparison matrix. After all, final land suitability map was generated using weighted overlay method under GIS tool. the ultimate map was classified into four land suitable classes using natural break classification method as highly suitable (S1), moderately suitable (S2), marginally suitable (S3), and not suitable class (S4). The result showed that highly suitable, moderately suitable, marginally suitable and not suitable class are covered 13.9%, 46.9%, 26.9%, and 12.2% of the whole area, respectively. This study finding will features a vital role in conducting surface irrigation considering the input parameters and therefore the final demarcated suitable land classes.

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 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.

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