Developing an Integrated Remote Sensing Based Biodiversity Index for Predicting Animal Species Richness
نویسندگان
چکیده
منابع مشابه
Predicting microbial species richness.
Microorganisms are spectacularly diverse phylogenetically, but available estimates of their species richness are vague and problematic. For example, for comparable environments, the estimated numbers of species range from a few dozen or hundreds to tens of thousands and even half a million. Such estimates provide no baseline information on either local or global microbial species richness. We a...
متن کاملRemote sensing for biodiversity science and conservation
Remote-sensing systems typically produce imagery that averages information over tens or even hundreds of square meters – far too coarse to detect most organisms – so the remote sensing of biodiversity would appear to be a fool’s errand. However, advances in the spatial and spectral resolutions of sensors now available to ecologists are making the direct remote sensing of certain aspects of biod...
متن کاملPreface: Remote Sensing of Biodiversity
Since the 1992 Earth Summit in Rio de Janeiro, the importance of biological diversity in supporting and maintaining ecosystem functions and processes has become increasingly understood [1]. Biodiversity “connects the web of life,” that is, biodiversity represents the diversity of species in an ecosystem, landscape, region and globe. It is their combined interactions, with each other and their e...
متن کاملLow Cost UAV-based Remote Sensing for Autonomous Wildlife Monitoring
In recent years, developments in unmanned aerial vehicles, lightweight on-board computers, and low-cost thermal imaging sensors offer a new opportunity for wildlife monitoring. In contrast with traditional methods now surveying endangered species to obtain population and location has become more cost-effective and least time-consuming. In this paper, a low-cost UAV-based remote sensing platform...
متن کاملHyperspectral remote sensing for estimating aboveground biomass and for exploring species richness patterns of grassland habitats
A. PSOMAS*†‡, M. KNEUBÜHLER‡, S. HUBER§, K. ITTEN‡ and N. E. ZIMMERMANN† †Swiss Federal Research Institute WSL, Zuercherstrasse 111, 8903 Birmensdorf, Switzerland ‡Remote Sensing Laboratories (RSL), Department of Geography, University of Zürich, Winterthurerstrasse 190, 8057 Zürich, Switzerland §Department of Geography and Geology, University of Copenhagen, Øster Voldgade 10, 1350 Copenhagen, D...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Remote Sensing
سال: 2018
ISSN: 2072-4292
DOI: 10.3390/rs10050739