一种新的可分性指数及其在中国南方Sentinel-2冬油菜制图的应用

doi:10.1016/j.jia.2022.10.008

摘要/Abstract

摘要： 利用遥感数据进行大范围作物制图对于农业生产、粮食安全和人类可持续发展具有重要意义。冬油菜是中国重要的油料作物，主要分布在长江流域。传统的冬油菜制图方法主要利用冬油菜关键物候期的光谱特征，获取遥感数据的时间窗口有限，因而不能满足大范围应用的需要。本研究提出了一种新的基于物候特征的冬油菜指数(PWRI)来进行长江中游地区的冬油菜制图。PWRI扩大了冬油菜和冬小麦的区分时间窗口，在冬油菜整个花期具有良好的分离性。PWRI还扩大了两种冬季作物的可分离性。采用基于PWRI的方法，利用时间序列合成Sentinel-2数据，在Google Earth Engine平台上实现了对长江中游地区冬季油菜的制图。该方法取得了良好的结果，总体精度和kappa系数分别超过92%和0.85。基于PWRI的方法为大范围高空间分辨率冬油菜制图提供了一种新的解决方案。

Abstract: Large-scale crop mapping using remote sensing data is of great significance for agricultural production, food security and the sustainable development of human societies. Winter rapeseed is an important oil crop in China that is mainly distributed in the Yangtze River Valley. Traditional winter rapeseed mapping practices are insufficient since they only use the spectral characteristics during the critical phenological period of winter rapeseed, which are usually limited to a small region and cannot meet the needs of large-scale applications. In this study, a novel phenology-based winter rapeseed index (PWRI) was proposed to map winter rapeseed in the Yangtze River Valley. PWRI expands the date window for distinguishing winter rapeseed and winter wheat, and it has good separability throughout the flowering period of winter rapeseed. PWRI also improves the separability of winter rapeseed and winter wheat, which traditionally have been two easily confused winter crops. A PWRI-based method was applied to the Middle Reaches of the Yangtze River Valley to map winter rapeseed on the Google Earth Engine platform. Time series composited Sentinel-2 data were used to map winter rapeseed with 10 m resolution. The mapping achieved a good result with overall accuracy and kappa coefficients exceeding 92% and 0.85, respectively. The PWRI-based method provides a new solution for high spatial resolution winter rapeseed mapping at a large scale.

Key words: phenology-based winter rapeseed index , winter rapeseed mapping , Sentinel-2 , Google Earth Engine

TAO Jian-bin, ZHANG Xin-yue, WU Qi-fan, WANG Yun. 一种新的可分性指数及其在中国南方Sentinel-2冬油菜制图的应用[J]. Journal of Integrative Agriculture, 2023, 22(6): 1645-1657.

TAO Jian-bin, ZHANG Xin-yue, WU Qi-fan, WANG Yun. Mapping winter rapeseed in South China using Sentinel-2 data based on a novel separability index[J]. Journal of Integrative Agriculture, 2023, 22(6): 1645-1657.

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