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If you continue to use this site we will assume that you are happy with it. Ok Disclaimer. Characterization of habitats structures and functions and how these parameters could influence species. Variability in physical, behavioural,… properties of the biosphere that leaves traces in its reflected spectral signal at any point in space and time.

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For plants, like based on the spectral variation hypothesis 2 Applying environmental parameters primary productivity, climate data, and habitat structure or area derived from remotely sensed data as predictors for biodiversity. Remote sensing does not observe biodiversity per se i.

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Share This Paper. Figures from this paper. Citations Publications citing this paper. Responses of Amazonian ecosystems to climatic and atmospheric carbon dioxide changes since the last glacial maximum.

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Gosling , Mark B Bush. Temperature and rainfall interact to control carbon cycling in tropical forests. Philip G. Toward accounting for ecoclimate teleconnections: intra- and inter-continental consequences of altered energy balance after vegetation change Scott C.


Stark , David D. Protecting the Amazon with protected areas.

What If You Could See Every Wavelength Of The Electromagnetic Spectrum? - Answers With Joe

Robert D. Well-designed spectral databases are essential tools of scientific inquiry in ecological sciences for several reasons.

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  • 1. Linking people and ecosystems.
  • They provide:. Project Synopsis Our goal is to develop a working prototype of an effective spectral database system, with active community engagement.

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    Through these key actions, ESIS will yield a tangible outcome: a functioning prototype system for warehousing a rich, validated set of data , metadata standards , and analytical tools to facilitate synthesis studies and help identify critical gaps in our understanding of the spectral variation within ecosystems.

    We expect the ESIS approach to provide a systematic basis for evaluating the causes of spectral variability, including error.

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    ESIS will provide a quantitative framework for remote sensing of vegetation that is an essential foundation for future studies involving imaging spectroscopy. ESIS will be developed as a resource for the ecosystem spectroscopy community. It will be the foundation for new initiatives in collaboration and cooperation within the Earth Sciences community and lower access barriers by those outside the community. ESIS has long-term parallel and overlapping objectives, and an intended long lifespan as a repository for spectral and associated data: A.

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    Integrate community-provided spectral data into a scientifically robust and accessible ESIS repository and identify critical gaps in current spectroscopic knowledge. Any one set of lab, field, or imaging spectrometer data cover a limited range of functional types, geographic locations, and phenological conditions. By allowing ready review and comparison of spectra, ESIS will provide the capacity to assess the coverage of existing spectral data, determine where coverage is inadequate, and allow integration of new spectra to fill data gaps.

    ESIS will create data ingest standards and methods to assure the scientific validity, traceability, and description of data.

    For life, for the future: Biosphere reserves and climate change

    Establish spectral data collection standards and best practices. Methodologies for collecting lab and field spectral data will be documented and evaluated. Approaches that facilitate improved inter-comparison will be published, following efforts by Rivard et al.