five

Habitat mapping of coastal wetlands using expert knowledge and Earth observation data

收藏
DataONE2020-06-24 更新2024-06-08 收录
下载链接:
https://search.dataone.org/view/sha256:0289ba2af2f4d2e515dd0037da2af36e5559c21f9ffe1fbb024aa7483bd42333
下载链接
链接失效反馈
官方服务:
资源简介:
Long-term habitat mapping and change detection are essential for the management of coastal wetlands as well as for evaluating the impact of conservation policies. Earth observation (EO) data and techniques are a valuable resource for long-term habitat mapping. Although the use of EO data is well developed for the automatic production of land cover (LC) maps, this is not the same for habitat maps, which are highly related to biodiversity. In a previous paper, we used the Food and Agricultural Organization (FAO) Land Cover Classification System (LCCS) environmental attributes (e.g. water quality, lithology, soil surface aspect) for LC-to-habitat class translation. However, these environmental attributes are often not openly available, not updated or are missing. This paper offers an alternative, knowledge-based solution to automatic habitat mapping. When only expert rules and EO data are used, the final overall map accuracy, which is obtained by comparing reference ground truth patches ...
创建时间:
2025-04-15
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作