来自VHR遥感的西 (西藏) 田地形状指标的土地块级耕地数据集
Chuya Wang1, Xiaoyan Wang1, Yi Jiang1
1Institute of Remote Sensing and Digital Agriculture, Sichuan Academy of Agricultural Sciences, Chengdu, 610066, China.
Scientific data
|November 14, 2025
概括
本研究介绍了中国西的第一个农田级农田数据集,该数据集来自深度学习和高分辨率图像. 经过验证的数据集为改善土地管理提供了对细度农业模式的关键见解.
科学领域:
- 农业科学 农业科学
- 地理空间分析是什么
- 遥感 遥感 遥感 遥感
背景情况:
- 准确的耕地数据对于区域农业研究至关重要,特别是在中国西.
- 在西的碎片化景观和复杂的作物系统需要精确的监测.
研究的目的:
- 创建第一个小块级耕地数据集Xizang.
- 为农业监测,产量估计和土地管理规划提供高分辨率数据.
主要方法:
- 采用了基于深度学习的现场提取模型.
- 高分辨率的谷歌地球图像被用于数据生成.
- 使用无人机 (UAV) 样本进行现场验证,并与现有数据集进行比较.
主要成果:
- 该数据集包括1,072,110个地块,占地面积约为290,721.35公.
- 现场验证实现了90%的面积匹配精度.
- 与现有的耕地产品发现了强烈的线性相关性 (R2 = 0.87 和 0.90).
结论:
- 块级耕地数据集为西的微型农业模式提供了关键的见解.
- 这一数据集是农业监测和土地利用规划的基础.
- 现场形状指标 (方向,规律性,连续性) 被纳入进一步分析.
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