Naiman Banner is one of the most typical semi‐arid vulnerable ecological zones that is characterized by vegetation degradation and severe desertification. Previous studies mostly utilized a single feature space or only the linear correlation model to monitor desertification. In this study, the optimal monitoring model that fully considers the multiple feature spaces and the nonlinear relationship between surface parameters in Naiman Banner was determined, and then the spatial–temporal evolution patterns of the desertification from 1989 to 2017 were analyzed. The results showed that: (a) The albedo–normalized difference vegetation index point‐to‐point model was applicable to areas with high‐vegetation coverage, whereas the albedo–modified soil‐adjusted vegetation index (MSAVI) linear model had better applicability in areas with relatively low vegetation coverage. Considering the surface cover, the desertification monitoring index based on albedo‐MSAVI linear model had the best applicability. (b) During 1989–2017, the total desertification area percentage of Naiman County decreased from 90.85% in 1989 to 63.35% in 2017, showing a significant downward trend. (c) During the past 30 years, the desertification process was significantly influenced by human activities, such as ‘Three‐North’ Shelterbelt, Returning Farmland to Forestry, and Returning Farmland to Grassland (d) The desertification levels of unused land and grassland with low coverage was relatively high, whereas the desertification degree of cultivated and forest lands was low. These results can be used as an effective reference for the remote sensing monitoring and evaluation of desertification and can provide data and decision support for the ecological restoration of the region.

中文翻译：

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基于具有典型地面参数的LANDSAT影像特征空间模型的奈曼旗沙漠化动态监测

奈曼旗是最典型的半干旱脆弱生态区之一，其特征是植被退化和严重的荒漠化。先前的研究大多利用单个特征空间或仅使用线性相关模型来监测荒漠化。在本研究中，确定了充分考虑多个特征空间和奈曼旗地表参数之间非线性关系的最优监测模型，然后分析了1989年至2017年荒漠化的时空演变模式。结果表明：（a）反照率归一化差异植被指数点对点模型适用于植被覆盖率较高的地区，反照率修正的土壤调整植被指数（MSAVI）线性模型在植被覆盖率相对较低的地区具有更好的适用性。考虑到地表覆盖，基于反照率-MSAVI线性模型的荒漠化监测指标具有最佳的适用性。（b）在1989-2017年期间，奈曼县的总荒漠化面积百分比从1989年的90.85％下降到2017年的63.35％，显示出明显的下降趋势。（c）在过去30年中，荒漠化进程受到人类活动的重大影响，例如``三北''防护林带，退耕还林，退耕还草（d）未利用土地和草地的荒漠化程度低覆盖率相对较高，而耕地和林地的荒漠化程度较低。