2018-2021年新疆棉花10米高空间分辨率“一张图”

对新疆地区2018年至2021年新疆棉花分布进行分布制图。制图之前，实验团队每年（2018年至2021年）在新疆进行均匀的棉花样点采集，并针对样点数据采用根据时序遥感影像棉花识别精度的影响因子分析，选用 LSWI光谱指数构建以10天为周期的10米高分辨率时序影像，克服了大区域尺度下棉花光谱与物候特征的空间异质性的影响，从而对新疆的主要农作物（棉花）进行精确分类。

This study conducted distribution mapping of cotton cultivation in Xinjiang from 2018 to 2021. Prior to the mapping procedure, the experimental team performed systematic, uniform sampling of cotton plots across Xinjiang annually between 2018 and 2021. For the collected sampling data, the team conducted an analysis of factors influencing the accuracy of cotton recognition using time-series remote sensing imagery. Subsequently, the LSWI spectral index was adopted to construct 10-meter high-resolution time-series images with a 10-day cycle. This approach effectively overcomes the impacts of spatial heterogeneity in cotton spectral and phenological characteristics at large regional scales, enabling accurate classification of cotton, the dominant crop in Xinjiang.

搜集汇总

背景与挑战

背景概述

该数据集是2018-2021年新疆棉花10米高空间分辨率分布图，基于LSWI光谱指数构建时序遥感影像，以克服大区域尺度棉花光谱和物候特征的空间异质性，实现棉花、玉米和小麦的准确分类。数据来源于公开的Landsat、SPOT和Sentinel影像，处理采用GEE和ENVI等软件，适用于农业遥感监测和分析。