期刊
REMOTE SENSING OF ENVIRONMENT
卷 134, 期 -, 页码 266-275出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2013.03.006
关键词
Soil organic carbon; pH; Soil erosion; Land degradation; Agriculture; Mapping; Landsat; Ethiopia
资金
- Bill and Melinda Gates Foundation (BMGF)
- Wajibu MS (Kenya sites)
- Ghent University (DRC sites)
Agriculture is the basis of the Ethiopian economy, accounting for the majority of its employment and export earnings. Land degradation is, however, widespread and improved targeting of land management interventions is needed, taking into account the variability of soil properties that affect agricultural productivity and land degradation risk across landscapes. In the current study we demonstrate the utility of Landsat ETM + imagery for landscape-level assessments of land degradation risk and soil condition through a combination of systematic field methodologies, infrared (IR) spectroscopy and ensemble modeling techniques. The approaches presented allow for the development of maps at spatial scales that are appropriate for making spatially explicit management recommendations. Field data and soil samples collected from 38 sites, each 100 km(2), were used to develop predictive models that were applied as part of a case study to an independent dataset from four sites in Ethiopia. The predictions based on Landsat reflectance were robust, with R-squared values of 0.86 for pH and 0.79 for soil organic carbon (SOC), and were used to create predicted surfaces (maps) for these soil properties. Further, models were developed for the mapping of the occurrence of soil erosion and root depth restrictions within 50 cm of the soil surface (RDR50), with an accuracy of about 80% for both variables. The maps generated from these models were used to assess the spatial distribution of soil pH and SOC, which are important indicators of soil condition, and land degradation risk factors in order to target relevant management options. (C) 2013 Elsevier Inc. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据