Spatio-temporal-spectral observation model for urban remote sensing
Taking cities as objects being observed, urban remote sensing is an important branch of remote sensing. Given the complexity of the urban scenes, urban remote sensing observation requires data with a high temporal resolution, high spatial resolution, and high spectral resolution. To the best of our...
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Online Access: | http://dx.doi.org/10.1080/10095020.2020.1864232 |
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doaj-27c603ec74294ec48380a45156cf77af2021-10-04T13:56:59ZengTaylor & Francis GroupGeo-spatial Information Science1009-50201993-51532021-07-0124337238610.1080/10095020.2020.18642321864232Spatio-temporal-spectral observation model for urban remote sensingZhenfeng Shao0Wenfu Wu1Deren Li2Wuhan UniversityWuhan UniversityWuhan UniversityTaking cities as objects being observed, urban remote sensing is an important branch of remote sensing. Given the complexity of the urban scenes, urban remote sensing observation requires data with a high temporal resolution, high spatial resolution, and high spectral resolution. To the best of our knowledge, however, no satellite owns all the above characteristics. Thus, it is necessary to coordinate data from existing remote sensing satellites to meet the needs of urban observation. In this study, we abstracted the urban remote sensing observation process and proposed an urban spatio-temporal-spectral observation model, filling the gap of no existing urban remote sensing framework. In this study, we present four applications to elaborate on the specific applications of the proposed model: 1) a spatio-temporal fusion model for synthesizing ideal data, 2) a spatio-spectral observation model for urban vegetation biomass estimation, 3) a temporal-spectral observation model for urban flood mapping, and 4) a spatio-temporal-spectral model for impervious surface extraction. We believe that the proposed model, although in a conceptual stage, can largely benefit urban observation by providing a new data fusion paradigm.http://dx.doi.org/10.1080/10095020.2020.1864232urban remote sensingspatio-temporal-spectral observation modelremote sensing data fusionearth observation programs |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhenfeng Shao Wenfu Wu Deren Li |
spellingShingle |
Zhenfeng Shao Wenfu Wu Deren Li Spatio-temporal-spectral observation model for urban remote sensing Geo-spatial Information Science urban remote sensing spatio-temporal-spectral observation model remote sensing data fusion earth observation programs |
author_facet |
Zhenfeng Shao Wenfu Wu Deren Li |
author_sort |
Zhenfeng Shao |
title |
Spatio-temporal-spectral observation model for urban remote sensing |
title_short |
Spatio-temporal-spectral observation model for urban remote sensing |
title_full |
Spatio-temporal-spectral observation model for urban remote sensing |
title_fullStr |
Spatio-temporal-spectral observation model for urban remote sensing |
title_full_unstemmed |
Spatio-temporal-spectral observation model for urban remote sensing |
title_sort |
spatio-temporal-spectral observation model for urban remote sensing |
publisher |
Taylor & Francis Group |
series |
Geo-spatial Information Science |
issn |
1009-5020 1993-5153 |
publishDate |
2021-07-01 |
description |
Taking cities as objects being observed, urban remote sensing is an important branch of remote sensing. Given the complexity of the urban scenes, urban remote sensing observation requires data with a high temporal resolution, high spatial resolution, and high spectral resolution. To the best of our knowledge, however, no satellite owns all the above characteristics. Thus, it is necessary to coordinate data from existing remote sensing satellites to meet the needs of urban observation. In this study, we abstracted the urban remote sensing observation process and proposed an urban spatio-temporal-spectral observation model, filling the gap of no existing urban remote sensing framework. In this study, we present four applications to elaborate on the specific applications of the proposed model: 1) a spatio-temporal fusion model for synthesizing ideal data, 2) a spatio-spectral observation model for urban vegetation biomass estimation, 3) a temporal-spectral observation model for urban flood mapping, and 4) a spatio-temporal-spectral model for impervious surface extraction. We believe that the proposed model, although in a conceptual stage, can largely benefit urban observation by providing a new data fusion paradigm. |
topic |
urban remote sensing spatio-temporal-spectral observation model remote sensing data fusion earth observation programs |
url |
http://dx.doi.org/10.1080/10095020.2020.1864232 |
work_keys_str_mv |
AT zhenfengshao spatiotemporalspectralobservationmodelforurbanremotesensing AT wenfuwu spatiotemporalspectralobservationmodelforurbanremotesensing AT derenli spatiotemporalspectralobservationmodelforurbanremotesensing |
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1716844032703856640 |