2005年和2015年蒙古30m空间分辨率土地覆盖分类数据集

Juanle Wang, Shuxing Xu, Fei Yang, Kai Li, Yating Shao
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引用次数: 0

摘要

蒙古高原位于东北亚内陆,极易受到气候变化和人类活动的有害影响。蒙古国是蒙古高原的重要组成单元,其资源、环境和生态问题与中国北方的生态屏障和资源安全以及中蒙俄走廊的可持续发展密切相关。然而,目前仍缺乏适合蒙古国区域特点的高精度土地覆盖数据产品。本研究根据蒙古国的景观格局,构建了适合蒙古国的土地覆盖分类体系;并基于面向对象的遥感解译方法,采用分场景解译方法选择了多种指标。根据一定的规则和分类阈值,我们获得了2005年和2015年蒙古国空间分辨率为30m的土地覆盖分类数据集。蒙古国的土地覆盖分类包括11类:森林、草甸草原、真草原、沙漠草原、裸地、沙地、沙漠、冰雪、水、农田和建筑区。基于多源验证点信息和高分辨率谷歌地球图像,我们完成了蒙古土地覆盖分类结果的整体质量评估和单一分类质量评估。2005年,总体分类准确率为78.85%,Kappa系数为0.77。2015年,总体分类准确率为80.49%,Kappa系数为0.78。年均分类准确率为79.67%,符合精度要求。该数据集可以直接反映蒙古国土地覆盖格局和趋势的变化,为支持蒙古国的可持续发展提供基础科学数据。
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A dataset of land cover classifications with a spatial resolution of 30m in Mongolia in 2005 and 2015
The Mongolian Plateau is in the interior of Northeast Asia, and is extremely vulnerable to climate change and the deleterious effects of human activities. Mongolia is an important component unit of the Mongolian Plateau, and its resources, environment and ecological problems are closely related to the ecological barrier and resource security in northern China and the sustainable development of the China-Mongolia-Russia Corridor. However, there is still a lack of high-precision land cover data products suitable for the regional characteristics of Mongolia. In this study, according to the landscape pattern of Mongolia, we constructed a land cover classification system suitable for Mongolia; and based on the object-oriented remote sensing interpretation method, we adopted the split-scene interpretation to select a variety of indexes. According to certain rules and classification thresholds, we obtained a dataset of land cover classifications with a spatial resolution of 30m in Mongolia in 2005 and 2015. The land cover classifications of Mongolia includes 11 categories: forest, meadow steppe, real steppe, desert steppe, bare land, sand, desert, ice and snow, water, cropland and built areas. Based on multi-source validation point information and high-resolution Google Earth images, we completed an overall quality assessment and a single classification quality assessment of land cover classification results in Mongolia. In 2005, the overall classification accuracy is 78.85% and the Kappa coefficient is 0.77. In 2015, the overall classification accuracy is 80.49% and the Kappa coefficient is 0.78. The average annual classification accuracy is 79.67%, which meets the accuracy requirements. The dataset can directly reflect the changes of land cover pattern and trend in Mongolia and provide basic scientific data to support the sustainable development of Mongolia.
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