根据土壤理化特性分析评估农田是否适合种植谷类作物

Simeneh Gedefaw Abate, Mihret Bizuye Anteneh
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引用次数: 0

摘要

本研究旨在评估安贝什流域特定土地资源是否适合用于生产选定的雨养作物(麦芽大麦、小麦和茶叶)。研究还对适宜土地进行了量化,并将其划分为土地绘图单元(LMUs),同时绘制了土地适宜性地图。土地适宜性评估(LSA)以安贝什流域的气候条件、地形、土壤物理和化学特性为主要因素,并结合多标准决策制定(MCDM)分析。通过将流域划分为不同的土地绘图单元(LMU),采集了 14 个复合土壤样本,并在土壤实验室进行了分析。气候数据和降雨量来自研究区域附近的两个气象站。温度数据来自 Landsat 8 卫星热波段数据。从土壤实验室和其他地方获得的数据最后使用 ArcGIS 环境和优先级估算工具 (PriEsT) 软件进行分析。采用加权总和叠加法调查流域的最终 LSA 地图。结果显示,LMUs、VRe-LPq 和 LPK.Pq-FLc LMUs 对所有选定的雨水灌溉作物具有较高的总体适宜性。然而,LMU(VRe-NTu 和 NTu-VRe)的总体适宜性值较低,尤其是在 S1 适宜性等级中(分别为 0.05% 和 10.6%)。最不适宜的 LMU 是 VRe-NTu,其 S1 适宜性等级为 0.05%,99% 以上的土地属于中度适宜、略微适宜和不适宜所选土地利用类型的适宜性等级。此外,分别约有 219.06 公顷(17.76%)、217.6 公顷(17.64%)和 168.9 公顷(13.7%)的土地非常适合麦芽大麦、茶叶和小麦作物生产。总之,在麦芽制造与管理(MCDM)过程中,将土地划分为更接近的同质性(LMU)是土地退化评估与遥感和地理信息系统相结合的一项重要应用,有助于更好地做出决策。同时,流域内大部分(超过三分之二)土地属于中度和微度适宜土地,需要开展密集的土地管理活动,以提高土地质量并获得高产。建议在做出土地利用决定之前先进行土地退化评估。同样重要的是,将土地划分为 LMU,使其在取样时更加均匀,从而降低著名的土壤实验室分析成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessment of agricultural land suitability for cereal crops based on the analysis of soil physico-chemical characteristics
This research aimed at evaluation of a given land resource suitable for selected rain fed crops production (malt barley, wheat and teff) in Ambesh watershed. It also quantified suitable land and classified into the land mapping units (LMUs), and presents a land suitability map. Land suitability assessment (LSA) made using climatic condition, topography, soil physical and chemical properties as a major factor integrated with a multi criteria decision making (MCDM) analysis in Ambesh watershed. Fourteen composite soil samples were taken by categorizing the watershed into different land mapping units (LMUs) and analyzed in a soil laboratory. Climatic data, rainfall was obtained from two meteorological stations nearby to the study area. Temperature data derived from Landsat 8 satellite thermal bands data. Data obtained from the soil laboratory and others were finally analyzed using ArcGIS environment and priority estimation tool (PriEsT) software’s. Weighted Sum Overlay was implemented to investigate the final LSA map of the watershed. Results revealed that LMUs, VRe–LPq and LPK.Pq–FLc LMUs has higher overall suitability for all the selected rain fed crops. However, LMUs (VRe–NTu and NTu–VRe) has lower overall suitability values particularly for S1 suitability class (0.05% and 10.6%, respectively). The least suitable LMU is VRe–NTu with 0.05% S1 suitability class and above 99% of the land laid under the suitability classes of moderately suitable, marginally suitable and not suitable for the selected land utilization types. Moreover, about 219.06 ha (17.76%), 217.6 ha (17.64%), 168.9 ha (13.7%), of land are highly suitable for malt barley, teff and wheat crop production, respectively. In conclusion, during MCDM, classifying the land into closer homogeneities (LMU) an important application of LSA integrated with remote sensing and GIS for a better decision making. Meanwhile, majority (above two third’s) of the land in the watershed is under moderate and marginally suitable, it needs intensive land management activities to increase the land qualities and obtain high yields. LSA recommended before land utilization decision has to be made. It is also important to classifying the land into LMUs to make it more homogeneous for sample taking and reducing the prestigious soil laboratory analysis costs.
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