1
数据介绍
Using 335,709 Landsat images on the Google Earth Engine, we built the first Landsat-derived annual land cover product of China (CLCD) from 1985 to 2019. We collected the training samples by combining stable samples extracted from China's Land-Use/Cover Datasets (CLUD), and visually-interpreted samples from satellite time-series data, Google Earth and Google Map. Several temporal metrics were constructed via all available Landsat data and fed to the random forest classifier to obtain classification results. A post-processing method incorporating spatial-temporal filtering and logical reasoning was further proposed to improve the spatial-temporal consistency of CLCD.
译文(谷歌翻译出来的,仅供参考):
使用GEE上的 335,709 张 Landsat 图像,我们构建了 1985-2019 年中国第一个 Landsat 衍生的年度土地覆盖产品(CLCD)。我们通过结合从中国土地利用/覆盖数据集中提取的稳定样本收集了训练样本( CLUD),以及来自卫星时间序列数据、谷歌地球和谷歌地图的视觉解释样本。通过所有可用的 Landsat 数据构建了几个时间指标,并将其馈送到随机森林分类器以获得分类结果。进一步提出了一种结合时空滤波和逻辑推理的后处理方法,以提高 CLCD 的时空一致性。
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数据获取
生态遥感笔记微信公众号后台回复CLCD,即可弹出百度云盘链接。