Wang Guangxing, Gertner George, Howard Heidi, Anderson Alan
Department of Natural Resources and Environmental Sciences, University of Illinois, W503 Turner Hall, 1102 S. Goodwin Avenue, Urbana, IL, USA.
J Environ Manage. 2008 Sep;88(4):1088-98. doi: 10.1016/j.jenvman.2007.05.014. Epub 2007 Jul 12.
Military training activities disturb ground and vegetation cover of landscapes and increases potential soil erosion. To monitor the dynamics of soil erosion, there is an important need for an optimal sampling design in which determining the optimal spatial resolutions in terms of size of sample plots used for the collection of ground data and the size of pixels for mapping. Given a sample size, an optimal spatial resolution should be cost-efficient in both sampling costs and map accuracy. This study presents a spatial variability-based method for that purpose and compared it with the traditional methods in a study area in which a soil erosion cover factor was sampled and mapped with multiple plot sizes and multi-sensor images. The results showed that the optimal spatial resolutions obtained using the spatial variability-based method were 12 and 20 m for years 1999 and 2000, respectively, and were consistent with those using the traditional methods. Moreover, the most appropriate spatial resolutions using the high-resolution images were also consistent with those using ground sample data, which provides a potential to use the high-resolution images instead of ground data to determine the optimal spatial resolutions before sampling. The most appropriate spatial resolutions above were then verified in terms of cost-efficiency which was defined as the product of sampling cost and map error using ordinary kriging without images and sequential Gaussian co-simulation with images to generate maps.
军事训练活动会干扰地貌的地面和植被覆盖，并增加潜在的土壤侵蚀。为了监测土壤侵蚀的动态变化，迫切需要一种优化的采样设计，其中要确定用于收集地面数据的样地大小以及用于制图的像素大小方面的最佳空间分辨率。在给定样本量的情况下，最佳空间分辨率在采样成本和地图精度方面都应具有成本效益。本研究为此提出了一种基于空间变异性的方法，并在一个研究区域中将其与传统方法进行了比较，在该区域中，采用多种样地大小和多传感器图像对土壤侵蚀覆盖因子进行了采样和制图。结果表明，使用基于空间变异性的方法在1999年和2000年分别获得的最佳空间分辨率为12米和20米，与使用传统方法获得的结果一致。此外，使用高分辨率图像得出的最合适空间分辨率也与使用地面样本数据得出的结果一致，这为在采样前使用高分辨率图像而非地面数据来确定最佳空间分辨率提供了可能。然后根据成本效益对上述最合适的空间分辨率进行了验证，成本效益定义为使用无图像的普通克里金法和使用图像的序贯高斯协同模拟生成地图时的采样成本与地图误差的乘积。
