Mapping North African landforms using continental scale unmixing of MODIS imagery
Mapping North African landforms using continental scale unmixing of MODIS imagery
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DOI：
10.1016/j.rse.2005.04.023
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发表时间：
2005-09
影响因子：
13.5
通讯作者：
J. A. Ballantine;G. Okin;D. Prentiss;D. Roberts
中科院分区：
文献类型：
--
作者：
J. A. Ballantine;G. Okin;D. Prentiss;D. Roberts
我们描述了利用中等分辨率的卫星图像和方法，适用于次大陆到全球尺度的地形测绘的地形图的北非。编制了非洲10° N以北的中分辨率成像光谱仪（MODIS）表观地表反射率图像镶嵌图。地貌图像端元被选择来表征10种不同类型的植被和无植被的沙漠表面：冲积复合体，沙丘，干燥和短暂的湖泊，开放水域，玄武岩火山和流动，山脉，岩石，剥离，低角度基岩表面，沙层，和萨赫勒植被。应用多光谱端元混合分析（MESMA）对MODIS影像进行了地形和植被端元组分的估算。在每个MODIS像元的主要地形确定的基础上，在两个或三个端元模型的大多数端元分数。使用两个数据源进行了准确性评估：北非历史地形图[Raisz，E。（1952年出版）。北非地形图。军需主任办公室环境保护分支。]和陆地卫星专题制图仪（TM）数据。与Raisz地形图相比，总体分类精度为54%，冲积表面和沙丘之间以及桑迪和粘土质表面和沙丘之间存在明显的混淆。第二次验证使用20个Landsat图像在分层抽样方案给出了70%的分类精度，沙丘和沙层之间的混乱。这两种准确性评估方案都表明，在萨赫勒边缘进行植被分类存在困难。与最小距离和最大似然监督分类的比较发现，MESMA方法产生了显着更高的分类精度。这张数字地形图质量很高，足以构成地貌研究的基础，包括全球和区域灰尘模型中的地表参数化。
We describe the production of a landform map of North Africa utilizing moderate resolution satellite imagery and a methodology that is applicable for sub-continental to global scale landform mapping. A mosaic of Moderate Resolution Imaging Spectroradiometer (MODIS) apparent surface reflectance imagery was compiled for Africa north of 10° N. Landform image endmembers were chosen to characterize ten different types of vegetated and unvegetated desert surfaces: alluvial complexes, dunes, dry and ephemeral lakes, open water, basaltic volcanoes and flows, mountains, regs, stripped, low-angle bedrock surfaces, sand sheets, and Sahelian vegetation. Multiple Endmember Spectral Mixture Analysis (MESMA) was applied to the MODIS mosaic to estimate landform and vegetation endmember fractions. The major landform in each MODIS pixel was identified based on the majority endmember fraction in two- or three-endmember models. Accuracy assessment was conducted using two data sources: the historic Landform Map of North Africa [Raisz, E. (1952). Landform Map of North Africa. Environmental Protection Branch, Office of the Quartermaster General.] and Landsat Thematic Mapper (TM) data. Comparison with the Raisz landform map gave an overall classification accuracy of 54% with significant confusion between alluvial surfaces and regs, and between sandy and clayey surfaces and dunes. A second validation using 20 Landsat images in a stratified sampling scheme gave a classification accuracy of 70%, with confusion between dunes and sand sheets. Both accuracy assessment schemes indicated difficulty in vegetation classification at the margin of the Sahel. A comparison with minimum distance and maximum likelihood supervised classifications found that the MESMA approach produced significantly higher classification accuracies. This digital landform map is of sufficiently high quality to form the basis for geomorphic studies, including parameterization of the surface in global and regional dust models.