Current state and challenges in producing large-scale land cover maps: review based on recent land cover products

被引:4
|
作者
Gilic, Frane [1 ]
Gasparovic, Mateo [2 ]
Baucic, Martina [1 ]
机构
[1] Univ Split, Fac Civil Engn Architecture & Geodesy, Split, Croatia
[2] Univ Zagreb, Fac Geodesy, Zagreb, Croatia
关键词
Land cover; classification; machine learning; challenges; accuracy assessment; PROBA-V MISSION; CLASSIFICATION; TIME; METAANALYSIS; COPERNICUS;
D O I
10.1080/10106049.2023.2242693
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Data about the land cover have already been for decades one of the most important sources for determining human impact on nature and the environment and possible backward effects of nature and the environment on humans. Images acquired by earth observation (EO) satellites enabled more or less automatic production of global and continental land cover maps, thus performing detailed analysis of land cover changes over time. Although EO images have been broadly used for producing land cover maps for more than 30 years, many challenges are still present in their production workflow. This research firstly briefly analyses characteristics of some of the recent land cover products and then identifies the main steps that are present in producing land cover maps. It further highlights some of the main existing challenges present in those steps as well as future research topics. These challenges are rarely addressed comprehensively, but rather individually, so this research also provides directions to other recent studies that grapple with the mitigation of a particular challenge. An overview of the EO satellite missions and classification algorithms that are most often used to produce moderate resolution (10-30 m) land cover maps is also given.
引用
收藏
页数:38
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