地理信息系统和遥感在绘制土地退化图方面的潜力:津巴布韦Manyame河流域

IF 1.6 Q3 WATER RESOURCES
H. Muhoyi, E. Muhoyi
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引用次数: 2

摘要

津巴布韦的Manyame河集水区正在经历严重的土地退化,这主要是由于合法和非法的土地耕作行为。这些做法对现有生态系统的可持续性产生了负面影响。土地的状况可以通过植被覆盖来推断,例如,标准化植被指数(NDVI)。在景观尺度上,与基于诸如沟壑等显著物理特征的土地退化有关的定量数据很少。本研究的重点是在Manyame河集水区土地退化的分布和程度。该研究使用残差趋势分析(RESTREND)方法绘制了人类引起的土地退化的轮廓。特别是,该研究使用遥感数据(NDVI和降水时间序列)来分析2000-2017年期间的变化。利用R统计软件包(RESTREND和Kendall)和地理信息系统(GIS)技术对退化趋势进行量化分析。研究结果表明,在研究期间,人类活动导致的土地退化程度较高的地区的提取物。采用Mann-Kendall评估RESTREND的有效性。本研究的结果可用于自然资源从业者使用GIS工具监测、评估和管理环境变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Potential of GIS and remote sensing in mapping land degradation: catchment of the Manyame River, Zimbabwe
The Manyame River Catchment area in Zimbabwe is experiencing severe land degradation mainly due to legal and illegal land husbandry practices. These practices are negatively impacting the sustainability of the existing ecosystems. The conditions of the land can be inferred using its vegetative cover, e.g., the Normalised Difference Vegetation Index (NDVI). Quantitative data relating to land degradation based on notable physical features such as gullies, for the Manyame River Catchment at landscape scales are poor. This study focused on the distribution and magnitude of land degradation in the Manyame River Catchment area. The study mapped out the contours of human-induced land degradation using a residual trend analysis (RESTREND) method. In particular, the study used remotely sensed data (NDVI and precipitation time series) to analyse the shifts over the period 2000–2017. The analysis used R statistical software packages (RESTREND and Kendall) and Geographic Information System (GIS) techniques to quantify the degradation trends. The results indicated extracts of those areas which experienced significant human-induced land degradation during the study period. RESTREND effectiveness was assessed using Mann–Kendall. The results of this study can be used by natural resource practitioners in monitoring, assessing, and managing environmental changes using GIS tools.
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来源期刊
CiteScore
2.30
自引率
6.20%
发文量
136
审稿时长
14 weeks
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