2020_Book_RemoteSensingOfPlantBiodiversi.pdf

This Open Access volume aims to methodologically improve our understanding of biodiversity by linking disciplines that incorporate remote sensing, and uniting data and perspectives in the fields of biology, landscape ecology, and geography. The book provides a framework for how biodiversity can be d...

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Γλώσσα:English
Έκδοση: Springer Nature 2020
Διαθέσιμο Online:https://www.springer.com/9783030331573
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spelling oapen-20.500.12657-399862021-07-21T03:39:38Z Remote Sensing of Plant Biodiversity Cavender-Bares, Jeannine Gamon, John A. Townsend, Philip A. Biodiversity Remote Sensing/Photogrammetry Plant Sciences Ecosystems Plant Ecology Monitoring/Environmental Analysis Plant Science Environmental Monitoring Remote detection of biodiversity Retrieving functional traits from spectra Community assembly Spectral diversity Leaf optical properties Hyperspectral field data collection and processing Spatial resolution and integration across scales Micro and macroscopic structure of leaves Detection of disease and decline in forests Ocean and aquatic biodiversity Open Access Geographical information systems & remote sensing Botany & plant sciences Ecological science, the Biosphere Environmental monitoring bic Book Industry Communication::R Earth sciences, geography, environment, planning::RN The environment::RNC Applied ecology::RNCB Biodiversity bic Book Industry Communication::R Earth sciences, geography, environment, planning::RG Geography::RGW Geographical information systems (GIS) & remote sensing bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences::PST Botany & plant sciences bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences::PSA Life sciences: general issues::PSAF Ecological science, the Biosphere bic Book Industry Communication::P Mathematics & science::PS Biology, life sciences::PST Botany & plant sciences::PSTS Plant ecology bic Book Industry Communication::T Technology, engineering, agriculture::TQ Environmental science, engineering & technology::TQD Environmental monitoring This Open Access volume aims to methodologically improve our understanding of biodiversity by linking disciplines that incorporate remote sensing, and uniting data and perspectives in the fields of biology, landscape ecology, and geography. The book provides a framework for how biodiversity can be detected and evaluated—focusing particularly on plants—using proximal and remotely sensed hyperspectral data and other tools such as LiDAR. The volume, whose chapters bring together a large cross-section of the biodiversity community engaged in these methods, attempts to establish a common language across disciplines for understanding and implementing remote sensing of biodiversity across scales. The first part of the book offers a potential basis for remote detection of biodiversity. An overview of the nature of biodiversity is described, along with ways for determining traits of plant biodiversity through spectral analyses across spatial scales and linking spectral data to the tree of life. The second part details what can be detected spectrally and remotely. Specific instrumentation and technologies are described, as well as the technical challenges of detection and data synthesis, collection and processing. The third part discusses spatial resolution and integration across scales and ends with a vision for developing a global biodiversity monitoring system. Topics include spectral and functional variation across habitats and biomes, biodiversity variables for global scale assessment, and the prospects and pitfalls in remote sensing of biodiversity at the global scale. 2020-07-14T07:18:50Z 2020-07-14T07:18:50Z 2020 book ONIX_20200714_9783030331573_21 https://library.oapen.org/handle/20.500.12657/39986 eng application/pdf n/a 2020_Book_RemoteSensingOfPlantBiodiversi.pdf https://www.springer.com/9783030331573 Springer Nature Springer 10.1007/978-3-030-33157-3 10.1007/978-3-030-33157-3 6c6992af-b843-4f46-859c-f6e9998e40d5 Springer 581 open access
institution OAPEN
collection DSpace
language English
description This Open Access volume aims to methodologically improve our understanding of biodiversity by linking disciplines that incorporate remote sensing, and uniting data and perspectives in the fields of biology, landscape ecology, and geography. The book provides a framework for how biodiversity can be detected and evaluated—focusing particularly on plants—using proximal and remotely sensed hyperspectral data and other tools such as LiDAR. The volume, whose chapters bring together a large cross-section of the biodiversity community engaged in these methods, attempts to establish a common language across disciplines for understanding and implementing remote sensing of biodiversity across scales. The first part of the book offers a potential basis for remote detection of biodiversity. An overview of the nature of biodiversity is described, along with ways for determining traits of plant biodiversity through spectral analyses across spatial scales and linking spectral data to the tree of life. The second part details what can be detected spectrally and remotely. Specific instrumentation and technologies are described, as well as the technical challenges of detection and data synthesis, collection and processing. The third part discusses spatial resolution and integration across scales and ends with a vision for developing a global biodiversity monitoring system. Topics include spectral and functional variation across habitats and biomes, biodiversity variables for global scale assessment, and the prospects and pitfalls in remote sensing of biodiversity at the global scale.
title 2020_Book_RemoteSensingOfPlantBiodiversi.pdf
spellingShingle 2020_Book_RemoteSensingOfPlantBiodiversi.pdf
title_short 2020_Book_RemoteSensingOfPlantBiodiversi.pdf
title_full 2020_Book_RemoteSensingOfPlantBiodiversi.pdf
title_fullStr 2020_Book_RemoteSensingOfPlantBiodiversi.pdf
title_full_unstemmed 2020_Book_RemoteSensingOfPlantBiodiversi.pdf
title_sort 2020_book_remotesensingofplantbiodiversi.pdf
publisher Springer Nature
publishDate 2020
url https://www.springer.com/9783030331573
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