埃塞俄比亚Didessa流域利用地理空间技术进行玉米生产的土地适宜性分析

IF 8.2 Q1 AGRICULTURE, MULTIDISCIPLINARY
Mitiku Badasa Moisa , Firdissa Sadeta Tiye , Indale Niguse Dejene , Dessalegn Obsi Gemeda
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引用次数: 17

摘要

自然土地适宜性评价是提高产量的先决条件,并使农业社区能够在适当的地方种植适当的作物。玉米是埃塞俄比亚稳定的粮食作物之一,在高地、中部和低地三个农业生态区种植。尽管如此,由于缺乏关于土地适宜性的知识和信息缺口,玉米产量非常低。玉米种植的自然土地适宜性对于尽量减少粮食安全问题至关重要。本研究旨在利用多标准评价(MCE)和地理空间技术确定埃塞俄比亚西部Didessa流域玉米生产的潜在土地适宜性。玉米土地适宜性评价考虑了土地利用、土地覆被变化、气候、地形、土壤和基础设施等因素。应用基于MCE的两两比较矩阵对玉米作物种植的土地适宜性进行了评价。结果表明:研究区高度适宜种植面积为977.7 km2(14.1%),中度适宜种植面积为4794.9 km2(69.1%),边缘适宜种植面积为1118.8 km2(16.1%),不适宜种植面积为51.5 km2(0.7%)。该研究为决策机关和农业社区利用玉米种植潜力提供了重要信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Land suitability analysis for maize production using geospatial technologies in the Didessa watershed, Ethiopia

Physical land suitability assessment is a prerequisite for enhancing yield production and enables the agricultural communities to use the right place for the right crops. Maize is one of stable one food crops of Ethiopia and cultivated in three agroecological zones: highland, midland and lowlands. Despite these facts, maize yield is very low due to a lack of knowledge and information gaps on land suitability. Physical land suitability for maize cultivation is essential to minimize the problem of food security. The present study aims to identify the potential land suitability for maize production in the Didessa watershed, Western Ethiopia using Multi-Criteria Evaluation (MCE) and geospatial technologies. Land use land cover (LULC) change, climate, topography, soil, and infrastructure facilities were considered for maize land suitability assessment. The MCE based pairwise comparison matrix was applied to estimate land suitability for maize crop cultivation. The results showed that, about 977.7 km2 (14.1%) is highly suitable, 4794.9 km2(69.1%) is moderately suitable while 1118.8 km2 (16.1%), and 51.5 km2 (0.7%) of the study area were categorized under marginally and not suitable for maize production, respectively. This research provides crucial information for decision making organs and the farming community to utilize potential areas for maize cultivation.

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来源期刊
Artificial Intelligence in Agriculture
Artificial Intelligence in Agriculture Engineering-Engineering (miscellaneous)
CiteScore
21.60
自引率
0.00%
发文量
18
审稿时长
12 weeks
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