Open Access
Monitoring Vegetation Systems in the Great Plains with Erts
J. W. Rouse,R. H. Haas,J. A. Schell,D. W. Deering +3 more
- Vol. 351, pp 309
TLDR
In this paper, a method has been developed for quantitative measurement of vegetation conditions over broad regions using ERTS-1 spectral bands 5 and 7, corrected for sun angle, which is shown to be correlated with aboveground green biomass on rangelands.Abstract:
The Great Plains Corridor rangeland project utilizes natural vegetation systems as phenological indicators of seasonal development and climatic effects upon regional growth conditions. A method has been developed for quantitative measurement of vegetation conditions over broad regions using ERTS-1 MSS data. Radiance values recorded in ERTS-1 spectral bands 5 and 7, corrected for sun angle, are used to compute a band ratio parameter which is shown to be correlated with aboveground green biomass on rangelands.read more
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Use of UK-DMC 2 and ALOS PALSAR for studying the age of oil palm trees in southern peninsular Malaysia
TL;DR: In this article, the authors demonstrated some techniques for studying the age of oil palm trees Elaeis guineensis Jacq using the disaster monitoring constellation 2 from the UK UK-DMC 2 and Advanced Land Observing Satellite phased array L-band synthetic aperture radar ALOS PALSAR data at a private oil palm estate in southern peninsular Malaysia.
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Modeling the effect of photosynthetic vegetation properties on the ndvi–lai relationship
Heidi Steltzer,Jeffrey M. Welker +1 more
TL;DR: It is expected that including the effects of PV properties in NDVI-LAI models will improve prediction of LAI where species composition varies across space or changes over time.
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Multi-scale standardized spectral mixture models
TL;DR: In this article, a globally representative mixing space using a spectrally diverse collection of 100 Landsat E TM + (Thematic Mapper and Enhanced Thematic Mappers) subscenes was constructed.
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Regional Mapping of Plantation Extent Using Multisensor Imagery
TL;DR: New, multisensor imagery were evaluated and integrated to extract the strengths of each sensor for mapping plantation extent at regional scales and the mapping approach was scalable and transferred well across the different geographies and plantation types.