福建省2000–2020年10 m分辨率茶园空间分布数据集

A dataset of spatial distribution of tea plantations at 10 m resolution in Fujian Province from 2000 to 2020

福建省作为中国的产茶大省,快速准确地获取茶园的空间分布对于福建省的农业经济发展以及生态环境建设具有重大的决策意义。本研究在GEE云平台调用与处理Sentinel-1(S1)雷达数据和Sentinel-2(S2)多光谱数据,结合地形数据从中提取光谱特征、纹理特征、地形特征等98个特征,利用递归消除支持向量机算法(SVM_RFE)对特征变量进行筛选,共设计4种特征组合方案,通过支持向量机分类器(SVM)进行茶园提取,并分别对4种分类方案进行精度评价,获得了福建省2020年10 m分辨率茶园空间分布数据。在此基础上,利用GEE云平台获取福建省2000–2020年植被干扰信息,以2020年茶园提取结果掩膜剔除2000–2015年影像中非茶园区域,得到2000–2020年每隔5年的福建省10 m分辨率茶园空间分布数据集。本数据集利用样本点对重点产茶县市进行人工验证,结果表明:2020年茶园提取精度在92%以上,利用干扰数据剔除法获得的2000年、2005年、2010年、2015年茶园提取精度均在80%以上。提取茶园精度较高,可为有关部门进行茶园管理提供支持。

Being a major tea producing province in China,Fujian Province is badly in need of quick and accurate spatial distribution of tea plantation for decision-making in both the agricultural economic development and the ecological environment construction for the province.This study retrieved and processed Sentinel-1(S1)radar data and Sentinel-2(S2)multispectral data on the GEE cloud platform;and it extracted 98 features,such as spectral features,texture features,and terrain features from the terrain data.The recursive elimination support vector machine algorithm(SVM RFE)is used to screen the characteristic variables,resulting in the creation of 4 feature combination schemes.Using a support vector machine(SVM)classifier to extract the distribution data of tea plantations and assessing the accuracy of the 4 feature combination schemes,we obtained the spatial distribution data of tea plantations at 10 m resolution in Fujian Province in 2020.On this basis,we used the GEE cloud platform to access the vegetation disturbance information in Fujian Province from 2000 to 2020.We finally obtained a dataset of spatial distribution of tea plantations at 10 m resolution in Fujian Province from 2000 to 2020 by excluding the non-tea plantation areas from the images between 2000 and 2015 with the mask generated from the 2020 tea garden extraction results.This dataset has been manually validated using sample points from key tea-producing counties and townships.The results indicate an extraction accuracy of over 92%for tea plantations in 2020.The extraction accuracy of tea plantations obtained using interference data removal method in 2000,2005,2010,and 2015 was all above 80%.The dataset with a high accuracy in tea plantation extraction can provide support for relevant departments in tea plantation management.