PDF(Pubmed)
Abstract：
To address the increasing global demand for food, it is crucial to implement sustainable agricultural practices, which include effective soil management techniques for enhancing productivity and environmental conditions. In this regard, a study was conducted to assess the efficacy of utilizing phenological metrics derived from satellite data in order to map and identify suitable agricultural soil within a semi-arid region. Two distinct methodologies were compared: one based on physicochemical soil parameters and the other utilizing the phenological response of vegetation through the application of the Normalized Difference Vegetation Index (NDVI) Modis-time series. The study findings indicated that the NDVI-based approach successfully identified a specific class of soil suitability for agriculture (referred to as S1) that could not be effectively mapped using the multi-criteria analysis (MCAD) method relying on soil physicochemical parameters. This S1 class of soil suitability accounted for approximately 5 % of the total study area. These outcomes suggest that phenological-based approaches offer greater potential for spatio-temporal monitoring of soil suitability status compared to MCAD, which heavily relies on discrete observations and necessitates frequent updates of soil parameters. The approach developed to map the soil-suitability is a valuable tool for sustainable agricultural development, and it can play an effective role in ensuring food security and conducting a land agriculture assessment.
摘要：
为了应对全球日益增长的粮食需求，实施可持续农业实践至关重要，其中包括有效的土壤管理技术，以提高生产力和环境条件。在这方面,进行了一项研究，以评估利用卫星数据得出的物候指标的有效性，以便在半干旱地区绘制和确定合适的农业土壤。比较了两种不同的方法：一种基于土壤理化参数，另一种通过应用归一化植被指数（NDVI）Modis时间序列利用植被的物候响应。研究结果表明，基于NDVI的方法成功地确定了特定类别的农业土壤适宜性（称为S1），这些土壤适宜性无法使用依赖于土壤理化参数的多标准分析（MCAD）方法进行有效映射。这种S1类土壤适宜性约占总研究区域的5％。这些结果表明，与MCAD相比，基于物候的方法为时空监测土壤适宜性状态提供了更大的潜力，严重依赖离散观测，需要频繁更新土壤参数。为绘制土壤适宜性而开发的方法是可持续农业发展的宝贵工具，它可以在确保粮食安全和进行土地农业评估方面发挥有效作用。
