Recent Progress in Quantitative Land Remote Sensing in China

dc.contributor.authorLiang, Shunlin
dc.contributor.authorShi, Jiancheng
dc.contributor.authorYan, Guangjian
dc.date.accessioned2023-11-20T19:44:45Z
dc.date.available2023-11-20T19:44:45Z
dc.date.issued2018-09-18
dc.description.abstractDuring the past forty years, since the first book with a title mentioning quantitative and remote sensing was published [1], quantitative land remote sensing has advanced dramatically, and numerous books have been published since then [2,3,4,5,6] although some of them did not use quantitative land remote sensing in their titles. Quantitative land remote sensing has not been explicitly defined in the literature, but we consider it as a sub-discipline of remote sensing including the following components (see Figure 1): radiometric preprocessing, inversion, high-level product generation, and applications. Many inversion algorithms rely on physical models of radiation regimes of landscapes, which link with remotely-sensed data. Generating high-level satellite products of land surface biophysical and biochemical variables create the key bridge between remote sensing science and applications. Conducting in situ measurements for validation of inversion algorithms and satellite products is also a critical component. Application of satellite products to address scientific and societal relevant issues will ultimately decide the future of quantitative land remote sensing.
dc.description.urihttps://doi.org/10.3390/rs10091490
dc.identifierhttps://doi.org/10.13016/dspace/m5aq-5n3a
dc.identifier.citationLiang, S.; Shi, J.; Yan, G. Recent Progress in Quantitative Land Remote Sensing in China. Remote Sens. 2018, 10, 1490.
dc.identifier.urihttp://hdl.handle.net/1903/31451
dc.language.isoen_US
dc.publisherMDPI
dc.relation.isAvailableAtCollege of Behavioral & Social Sciencesen_us
dc.relation.isAvailableAtGeographyen_us
dc.relation.isAvailableAtDigital Repository at the University of Marylanden_us
dc.relation.isAvailableAtUniversity of Maryland (College Park, MD)en_us
dc.titleRecent Progress in Quantitative Land Remote Sensing in China
dc.typeArticle
local.equitableAccessSubmissionNo

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