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Thursday, May 7, 2020 | History

1 edition of Remote sensing and modeling of ecosystems for sustainability VI found in the catalog.

Remote sensing and modeling of ecosystems for sustainability VI

Wei Gao

Remote sensing and modeling of ecosystems for sustainability VI

5-6 August 2009, San Diego, California, United States

by Wei Gao

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  • 8 Currently reading

Published by SPIE in Bellingham, Wash .
Written in English


Edition Notes

Includes bibliographical references and author index.

StatementWei Gao, Thomas J. Jackson, editors ; sponsored and published by SPIE
SeriesProceedings of SPIE -- v. 7454, Proceedings of SPIE--the International Society for Optical Engineering -- v. 7454.
ContributionsSPIE (Society)
Classifications
LC ClassificationsS494.5.S86 R465 2009
The Physical Object
Pagination1 v. (various pagings) :
ID Numbers
Open LibraryOL24430213M
ISBN 100819477443
ISBN 109780819477446
LC Control Number2010459293
OCLC/WorldCa463298790

  Remote Sensing and Modeling of Ecosystems for Sustainability XI 18 August | San Diego, California, United States Remote Sensing and Modeling of Ecosystems for Sustainability X. Remote Sensing for Sustainability introduces the current state of the art remote sensing knowledge integral for monitoring the world’s natural resources and environments, managing exposure to natural disasters and man-made risks, and helping understand the sustainability and productivity of natural ecosystems. Bridging the gap between remote.

KEYWORDS: Remote sensing, Reflectivity, Data modeling, Infrared radiation, Sensors, Solar radiation models, Thermal modeling, Infrared imaging, Agriculture, Absorption Read Abstract + Fuel moisture content (FMC), an important variable for predicting the occurrence and spread of wildfire, is the ratio of foliar water content and foliar dry. Remote Sensing of Ecosystem Services: An Opportunity for Spatially Explicit Assessment Article (PDF Available) in Chinese Geographical Science 20(6) December with 1, Reads.

Remote sensing, with the high variety of spectral ranges and the fine spatial and temporal resolution currently available, is a tool of great value for various applications in agriculture. The availability of robust inverse methods that allow surface biophysical variables to be assessed, combined with modeling approaches, makes it a high. Get this from a library! Remote sensing and modeling of ecosystems for sustainability III: August, , San Diego, California, USA. [Wei Gao; Susan L Ustin; Society of Photo-optical Instrumentation Engineers.; USDA UVB Monitoring and Research Program.;].


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Remote sensing and modeling of ecosystems for sustainability VI by Wei Gao Download PDF EPUB FB2

Remote sensing instrumentation consists of an imaging spectrometer measuring surface reflectance over the continuous wavelength range from to nm with 10 nm resolution, a scanning, small footprint waveform LiDAR for 3-D canopy structure measurements and a high resolution airborne digital camera.

Remote Sensing and Modeling of Ecosystems for Sustainability II Editor(s): Wei Gao ; David R. Shaw *This item is only available on the SPIE Digital Library. Remote Sensing for Sustainability introduces the current state of the art remote sensing knowledge integral for monitoring the world’s natural resources and environments, managing exposure to natural disasters and man-made risks, and helping understand the sustainability and productivity of natural ecosystems.

Bridging the gap between remote Cited by: 3. Remote Sensing and Modeling of Ecosystems for Sustainability VI: Authors: Gao, Wei; Jackson, Thomas J. Publication: Remote Sensing and Modeling of Ecosystems for Sustainability VI.

Edited by Gao, Wei; Jackson, Thomas J. Proceedings of the SPIE, Volume (). (SPIE Homepage) Publication Date: 08/ Origin: AIP: Bibliographic Code. Remote Sensing and Modeling of Ecosystems for Sustainability VIII: Authors: Remote Sensing and Modeling of Ecosystems for Sustainability VIII.

Edited by Gao, Wei; Jackson, Thomas J.; Wang, Jinnian; Chang, Ni-Bin. Proceedings of the SPIE, Volume (). adshelp[at] The ADS is operated by the Smithsonian Astrophysical Observatory under NASA Cooperative Agreement NNX16AC86A. Request PDF | Remote Sensing for Ecosystem Sustainability | An ecosystem is a system formed by the interaction of a community of organisms with their environment within a geographic unit or region.

Remote sensing estimating net primary productivity of temperate deciduous forest in Northeast China using satellite data: approach and preliminary results Author(s): Chaozong Xia. SESSION 4 MODELS AN D MODEL APPLICATIONS, ENVIRONMENTAL APPLICATIONS J Remote sensing and geospatial modeling for monitoring invasive plant species (Invited Paper) [] E.

Hunt, Jr., USDA-ARS Hydrology and Remote Sensing Lab. (USA) K A spatial model for restoration of the upper Mississippi River ecosystems []. Ecosystem respiration (R e) is rarely quantified from remote sensing data because satellite technique is incapable of observing the key processes associated with soil this study, we develop a Remote Sensing Model for R e (ReRSM) by assuming that one part of R e is derived from current photosynthate with the respiratory rate coupling closely with gross primary production (GPP Cited by: Remote sensing and other advanced geospatial data acquisition and processing techniques are critical for the measurement of sustainable ecosystems.

This special issue includes the latest advancements in remote sensor systems and computing platforms that have made it possible to collect data on ecosystems quickly and : Yichun Xie, Zongyao Sha, Victor Mesev.

Remote Sensing and Modeling of Ecosystems for Sustainability IX: Authors: Gao, Wei; Jackson, Thomas J. Publication: Remote Sensing and Modeling of Ecosystems for Sustainability IX, Edited by Wei Gao and Thomas J. Jackson.

ISBN:SPIE Vol. (SPIE Homepage) Publication Date: 10/ Origin: SPIE: Bibliographic Code: SPIE. Remote Sensing for Landscape Ecology book. New Metric Indicators for Monitoring, Modeling, and Assessment of Ecosystems.

Remote Sensing for Landscape Ecology book. New Metric Indicators for Monitoring, Modeling, and Assessment of Ecosystems. By Robert C. Frohn. Edition 1st Edition.

First Published eBook Published 4 May Cited by: Remote Sensing for Sustainability introduces the current state of the art remote sensing knowledge integral for monitoring the world’s natural resources and environments, managing exposure to natural disasters and man-made risks, and helping understand the sustainability and productivity of.

This is in accordance with the GEO strategies planned for – period and the attainment of SDG 15 for preserving biodiversity and ecosystem sustainability. Remote sensing data and techniques offer significant opportunities for long-term habitats monitoring because of the availability of a large amount of multi-temporal data from past.

Advances in the areas of remote sensing and modeling have allowed the integration of these two approaches and the use of multiple sensors and variables simultaneously to better understand the spatial and temporal dynamics of the water cycle and the available water resources at various scales.

Remote Sensing and Modeling of Ecosystems for Sustainability XI: Authors: Gao, Wei; Chang, Ni-Bin: Publication: Remote Sensing and Modeling of Ecosystems for Sustainability XI. Edited by Wei Gao, Ni-Bin Chang.

ISBN:SPIE Proceedings, Vol. (SPIE Homepage) Publication Date: 10/ Origin: ADS: Bibliographic Code: SPIE. In recent years, remote sensing (RS)-based models have provided efficient tools for agricultural hydrology and water resources modeling in irrigation districts, including soil moisture and salinity retrieval, evapotranspiration estimation, agro-hydrological modeling, irrigation efficiency and crop water productivity assessments, optimal allocation of irrigation water, and impact of irrigation practices on ecosystems.

Further, the quantitative calculation of ecosystem services based on remote sensing can provide a scientific basis for enhancing land use optimization and sustainable development.

This Special Issue aims to disseminate and share findings on national or regional ecosystem service assessment and its environmental stresses using remote sensing data, and the coupling of ecosystem services with. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is CHF (Swiss Francs). Book Description. Highlighting new technologies, Remote Sensing of Natural Resources explores advanced remote sensing systems and algorithms for image processing, enhancement, feature extraction, data fusion, image classification, image-based modeling, image-based sampling design, map accuracy assessment and quality control.

It also discusses their applications for evaluation of natural.5 Remote Sensing and Modeling of Coral Reef Resilience Mapping the Seafloor Both the three-d imension al structur e of the seafloor an d the biological co mpositio n of.Get this from a library!

Remote sensing and modeling of ecosystems for sustainability VI: AugustSan Diego, California, United States. [Wei Gao; T J Jackson; SPIE (Society);].