杨凌农业示范区经济作物种植结构多源多时相遥感数据集

A dataset of multi-source and multi-temporal remote sensing data of cash crop planting structure in Yangling Agricultural Demonstration Zone

卫星遥感能够及时获取大尺度下的地物分布,为经济作物种植结构的信息获取提供良好的数据与技术支撑。本数据集以杨凌农业示范区为研究区域,由遥感数据、地面真值数据、杨凌边界以及分类结果 4部分组成。遥感数据由2021年4月到9月的哨兵2号、高分1号(包括高分1号C星)、高分2号以及高分6号等卫星数据构成,经过辐射校正、大气校正、正射校正、图像融合以及影像配准等遥感影像处理。通过实地调查、Google Earth目视解译、小区域的无人机近地遥感等多种方式,建立地面真实分布验证区。在质量控制方面,遥感数据整体含云量很少、颜色均匀、空间分辨率为2 m;地面真值图通过实地调查进行绘制,真实可靠。本数据集采用随机森林算法验证,总体分类精度为86.17%。本数据集可为相关算法在经济作物种植结构获取方面的研究及应用提供训练样本,也可为杨凌示范区的土地利用分类及变化、农作物长势监测等方面提供数据支撑。

Satellite remote sensing technology can obtain the distribution of ground objects on a large scale in a timely manner,and provide great data and technical support for the acquisition of information on the planting structure of cash crops.Taking Yangling Agricultural Demonstration Area as the research area,this dataset is composed of four parts:remote sensing data,ground truth data,Yangling boundary and classification results.The remote sensing data consist of satellite data,such as Sentinel-2,Gaofen-1(including Gaofen-1C satellite),Gaofen-2,and Gaofen-6 from April to September in 2021 after radiation correction,atmospheric correction,and remote sensing image processing such as orthorectification,image fusion,and image registration.Through on-the-spot investigation,visual interpretation of Google Earth,and near-ground remote sensing of UAVs in small areas,we established the ground truth distribution verification area.In terms of quality control,the remote sensing data are characteristic of little overall cloud content,uniform color,and a spatial resolution of 2m;the ground truth map,authentic and reliable,is drawn through field surveys.The dataset has been verified by random forest algorithm,and the overall classification accuracy is 86.17%.It can provide training samples for the research and application of related algorithms in the acquisition of cash crop planting structure,and can also provide data support for land use classification and changes as well as crop growth monitoring in Yangling Demonstration Zone.