来自于塞尔维亚各种自然环境的高分辨率无人机土地覆盖地图的综合数据集
Bojana Ivošević1, Nina Pajević2, Sanja Brdar2
1BioSense Institute - Research and Development Institute for Information Technologies in Biosystems, University of Novi Sad, 21101, Novi Sad, Serbia. bojana.ivosevic@biosense.rs.
Scientific data
|January 14, 2025
概括
高分辨率的开源土地覆盖地图对于环境管理至关重要. 这项研究使用无人机图像和机器学习开发了详细的地图,为生物多样性和土地利用研究创造了宝贵的资源.
科学领域:
- 遥感 遥感 遥感 遥感
- 地理空间分析是什么
- 环境科学 环境科学
背景情况:
- 高分辨率 (HR) 土地覆盖地图对于粮食安全,土地利用规划和环境保护至关重要.
- 自由可用的HR土地覆盖数据集很少,这凸显了对多光谱空中图像的需求.
研究的目的:
- 为了比较基于对象的图像分析 (OBIA) 与随机森林和卷积神经网络 (CNN) 的准确性,用于土地覆盖的分类.
- 为27个多样化的塞尔维亚景观制作详细的土地覆盖地图和HR多光谱orthomosaics的宝贵数据集.
主要方法:
- 利用无人机 (UAV) 技术捕获厘米级的形图像.
- 采用基于对象的图像分析 (OBIA),与随机森林和CNN算法集成用于土地覆盖分类.
- 确定了九个不同的土地覆盖类别,并评估了人类对各种生态区自然息地的影响.
主要成果:
- 为塞尔维亚的27个不同景观生成了详细的土地覆盖地图.
- 创建了一个有价值的数据集,包括HR多光谱正方形,土地覆盖分类以及相关指标和培训数据.
- 评估研究区域内人类对自然息地的影响.
结论:
- 开发的数据集是为息地绘制,生物多样性监测以及在土地覆盖分类中推进机器学习技术的关键资源.
- 该研究表明,将无人机遥感与先进的机器学习相结合,可以有效地创建准确和详细的土地覆盖地图.
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