2018–2020年广西甘蔗10 m分辨率种植分布数据集

A dataset of the sugarcane planting distribution with the spatial resolution of 10 m in Guangxi from 2018 to 2020

作物种植分布的提取是作物监测的基础,及时准确地提取出甘蔗种植分布对甘蔗监测及种植结构调整具有重要意义。本文基于Sentinel-1和Sentinel-2数据,采用主被动遥感协同方法和决策树分类方法,开展了广西甘蔗种植分布提取方法研究,并结合多年调查的地面样本数据进行验证,在此基础上提取了2018–2020年广西甘蔗种植分布。该方法利用遥感数据提取得到的2018年广西甘蔗种植分布总体精度达92%,Kappa系数为0.85;2019年广西甘蔗种植分布总体精度达94%,Kappa系数为0.88;2020年广西甘蔗种植分布总体精度达94%,Kappa系数为0.88。本数据集可作为广西甘蔗时空变化分析的基础数据,也可为广西甘蔗生产管理与种植结构优化调整等提供基础数据支撑。

The extraction of sugarcane planting distribution is the basis of crop monitoring.The extraction of timely and accurate sugarcane planting distribution is of great significance for monitoring sugarcane crops and making adjustments to the planting structure.Based on Sentinel-1 and Sentinel-2 data,in this paper,we adopted the active and passive remote sensing collaborative method and decision tree classification method to carry out research on the extraction method of sugarcane planting distribution in Guangxi.Then we verified the data by referring to multi-year survey ground sample data.On this basis,we produced dataset of the sugarcane planting distribution with the spatial resolution of 10 m in Guangxi from 2018 to 2020.The remote sensing extraction-based method yielded an overall accuracy of 92%for sugarcane planting distribution in Guangxi in 2018,with a Kappa coefficient of 0.8.The overall accuracy of sugarcane planting distribution in Guangxi in 2019 is 94%,with a Kappa coefficient 0.88;the overall accuracy of sugarcane planting distribution in Guangxi in 2020 is 94%,with a Kappa coefficient of 0.88.This dataset can be used as the basic data for the analysis of temporal and spatial changes of sugarcane in Guangxi.And it can also provide basic data support for the optimization and adjustment of sugarcane production management and planting structure in Guangxi.