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• W2342960223 abstract "This review provides a perspective of the current state of the art in remote sensing of anthropogenic land cover and human-modified landscapes at global scales. The fact that humans have adapted to almost all of Earth’s environments, yet remain strongly clustered within each of these environments influences both the nature of anthropogenic impact on Earth’s landscapes and the challenges of mapping it. Remote sensing provides a consistent synoptic view of these environments by mapping the land cover associated with the anthropogenic land uses of settlement and food production, as well as their complement in forest cover. We give brief descriptions and illustrative comparisons of several current land cover products representing the global extents of settlements, agriculture and forests derived from remote sensing. To accommodate the challenges inherent to mapping any land cover at widely varying scales, we compare size distributions of spatially contiguous land cover (rather than total area) for several global land cover products. Despite the use of different sensors and different mapping criteria, there is remarkable consistency in the size distributions of these products – both within and across land cover class. Rank-size distributions of settlements, agricultural areas and forests are all well-described by power laws spanning more than four orders of magnitude in both area and number. This consistency in the form of the distributions suggests fundamental similarities among different types of land cover. The observed similarities can be explained by depicting land cover mosaics as co-evolving spatial networks sharing common processes of nucleation, growth and connection." @default.
• W2342960223 created "2016-06-24" @default.
• W2342960223 creator A5025352897 @default.
• W2342960223 creator A5066696545 @default.
• W2342960223 date "2016-06-01" @default.
• W2342960223 modified "2023-10-02" @default.
• W2342960223 title "Humans on Earth: Global extents of anthropogenic land cover from remote sensing" @default.
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• W2342960223 doi "https://doi.org/10.1016/j.ancene.2016.04.003" @default.
• W2342960223 hasPublicationYear "2016" @default.
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