Estimating soil erosion intensity in susceptible areas based on a comprehensive stratified sampling system associated with the geographical information system
Estimating soil erosion intensity in susceptible areas based on a comprehensive stratified sampling system associated with the geographical information system
复制标题
基于地理信息系统综合分层采样系统估算易受影响地区水土流失强度
DOI：
10.1139/cjss-2019-0041
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发表时间：
2019-07
影响因子：
1.7
通讯作者：
Liu Xia
中科院分区：
文献类型：
--
作者：
Liang-Jie Wang;Hongda Zhang;Fei Qi;Liu Xia
一种准确、快速的土壤侵蚀强度区域动态识别方法对地方政府至关重要。在这项研究中，一个简单的方法相结合的植被覆盖，坡度和土地利用耦合指数（植被和坡度耦合指数）模型与现场采样单元计划，以估计1998年和2009年之间的SEI的面积变化。结果表明，不同土地利用类型样本单元的平均预测精度最低为94%，最高为98.5%。虽然不同土地利用类型的PA表现出差异，趋势清楚地描绘了较高的抽样单位率和较低的相对误差。基于不同的建议策略，采样单元的平均拟合精度（FA）分别为98.84%、97.92%和97.26%，而外推结果的FA分别为94.77%、87.57%和92.41%。此外，外推结果被认为是效率低于抽样单位。然而，考虑到实地观察的工作量和时间消耗，这是可以接受的。因此，本研究提供了一个有前途的方案，快速估计的区域动态的SEI，这将有助于估计在其他地区的SEI。
An error-free and fast approach for the identification of the area dynamics of soil erosion intensity (SEI) is essential for local governments. In this study, a simple method combination of the vegetation cover, gradient slope, and land use coupling index (vegetation and slope coupling index) model with field sampling unit schemes was explored to estimate the area variations of SEI between the years 1998 and 2009. The obtained results show that the minimum average prediction accuracy (PA) for sampling units was 94% among different land use types, whereas the maximum PA was 98.5%. Although PAs for different land use types showed discrepancies, the trend clearly depicted higher rates of sampling units and lower relative errors. The average fitting accuracies (FAs) of the sampling units were 98.84%, 97.92%, and 97.26%, respectively, based on different proposed strategies, whereas the FAs of the extrapolation results were 94.77%, 87.57%, and 92.41%, respectively. In addition, the extrapolation results were found to be less efficient than the sampling units. However, this is acceptable, considering the field observation workloads and time consumption. Therefore, this study provides a promising scheme for the rapid estimation of the area dynamics of SEI, which will be useful for estimating the SEI in other areas.
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影响因子：
6.2
作者：
Xiwang Zhang;Bingfang Wu;F. Ling;Y. Zeng;Nana Yan;C. Yuan
通讯作者：
Xiwang Zhang;Bingfang Wu;F. Ling;Y. Zeng;Nana Yan;C. Yuan
DOI：
--
发表时间：
1978
期刊：
--
影响因子：
--
作者：
W. H. Wischmeier;D. Smith
通讯作者：
W. H. Wischmeier;D. Smith
影响因子：
4.7
作者：
Biadgilgn Demissie;P. Billi;A. Frankl;M. Haile;J. Nyssen
通讯作者：
Biadgilgn Demissie;P. Billi;A. Frankl;M. Haile;J. Nyssen
影响因子：
6.1
作者：
Amiri, Mandis;Pourghasemi, Hamid Reza;Afzali, Sayed Fakhreddin
通讯作者：
Afzali, Sayed Fakhreddin
影响因子：
4.2
作者：
Guo, Bing;Zhang, Fei-Fei;Jiang, Lin
通讯作者：
Jiang, Lin