基于Google Earth高分辨率影像的2018-2020年浙江杭州湾亚米级耕地提取数据集

该数据包含了杭州湾的农业地块，主要覆盖了杭州、宁波、绍兴、嘉兴、舟山、湖州、上海等多个城市，总面积为5.2万平方公里。影像采用Google earth下载的高分辨卫星影像 ，空间分辨率为0.5m左右，数据获取时间是2018-2020年。采用深度学习模型BDCN对该数据进行了地块 提取，利用团队自主研制的矢量化算法，提取了农田，每个封闭的边界合围区域表示一个农业地块。

This dataset contains agricultural parcels in the Hangzhou Bay region, which covers multiple cities including Hangzhou, Ningbo, Shaoxing, Jiaxing, Zhoushan, Huzhou and Shanghai, with a total area of 52,000 square kilometers. The imagery consists of high-resolution satellite images downloaded from Google Earth, with a spatial resolution of approximately 0.5 meters, and the data was acquired between 2018 and 2020. Parcels were extracted from this dataset using the deep learning model BDCN, and farmland parcels were extracted via a vectorization algorithm independently developed by the research team. Each closed boundary-enclosed area represents a single agricultural parcel.

搜集汇总

背景与挑战

背景概述

该数据集提供了2018-2020年浙江杭州湾及周边城市的高分辨率耕地提取数据，覆盖面积广、分辨率高，适用于农业地块分析和研究。