Losses in biodiversity critically impact the ability of ecosystems to provide critical services ranging from carbon sequestration and food production to the maintenance of soil fertility. The maintenance of biodiversity is thus essential for human well-being and a sustainable future. Since landscape diversity often relates to species biodiversity, considering several ecological levels from species community diversity to genetic diversity, measuring landscape heterogeneity, is an efficient and relatively cheap way of providing biodiversity estimates over large geographical areas. In this study we will demonstrate the power of using remotely sensed data to estimate landscape heterogeneity and locate diversity hotspots, allowing effective management and conservation of the landscape
Rocchini, D.; Olteanu Raimond, A.M.; Delucchi, L.; Pareeth, S.; Neteler, M.G.; Nagendra, H. (2014). Sensing technologies and their integration with maps: mapping landscape heterogeneity by satellite imagery. In: Thematic Cartography for the Society (editor(s) Bandrova, T.; Konecny, M.; Zlatanova, S.): Springer: 259-273. ISBN: 978-3-319-08179-3 doi: 10.1007/978-3-319-08180-9_19. handle: http://hdl.handle.net/10449/23650
Sensing technologies and their integration with maps: mapping landscape heterogeneity by satellite imagery
Rocchini, Duccio;Delucchi, Luca;Pareeth, Sajid;Neteler, Markus Georg;
2014-01-01
Abstract
Losses in biodiversity critically impact the ability of ecosystems to provide critical services ranging from carbon sequestration and food production to the maintenance of soil fertility. The maintenance of biodiversity is thus essential for human well-being and a sustainable future. Since landscape diversity often relates to species biodiversity, considering several ecological levels from species community diversity to genetic diversity, measuring landscape heterogeneity, is an efficient and relatively cheap way of providing biodiversity estimates over large geographical areas. In this study we will demonstrate the power of using remotely sensed data to estimate landscape heterogeneity and locate diversity hotspots, allowing effective management and conservation of the landscapeFile | Dimensione | Formato | |
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