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Article: ICESat GLAS data for urban environment monitoring

TitleICESat GLAS data for urban environment monitoring
Authors
KeywordsBuilding density
Laser altimetry
Urban growth
Global change
Building height
Issue Date2011
Citation
IEEE Transactions on Geoscience and Remote Sensing, 2011, v. 49, n. 3, p. 1158-1172 How to Cite?
AbstractAlthough the Geoscience Laser Altimeter System (GLAS) onboard the NASA Ice, Cloud and Land Elevation Satellite was not designed for urban applications, its 3-D measurement capability over the globe makes it a nice feature for consideration in monitoring urban heights. However, this has not been previously done. In this paper, we report some preliminary assessment of the GLAS data for building height and density estimation in a suburb of Beijing, China. Building heights can be directly calculated from a GLAS data product (GLA14). Because GLA14 limits height levels to six in each ground footprint, we developed a new method to remove this restriction by processing the raw GLAS data. The maximum heights measured in the field at selected GLAS footprints were used to validate the GLAS measurement results. By assuming a constant incident energy and surface reflectance within a GLAS footprint, the building density can be estimated from GLA14 or from our newly processed GLAS data. The building density determined from high-resolution images in Google Earth was used to validate the GLAS estimation results. The results indicate that the newly developed method can produce more accurate building height estimation within each GLAS footprint ( R2 = 0.937, rmse = 6.4 m, and n = 26) than the GLA14 data product (R2 = 0.808, rmse = 11.5m, and n = 26). However, satisfactory estimation results on building density cannot be obtained from the GLAS data with the methods investigated in this paper. Forest cover could be a challenge to building height and density estimation from the GLAS data. It should be addressed in future research. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/296932
ISSN
2023 Impact Factor: 7.5
2023 SCImago Journal Rankings: 2.403
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorGong, Peng-
dc.contributor.authorLi, Zhan-
dc.contributor.authorHuang, Huabing-
dc.contributor.authorSun, Guoqing-
dc.contributor.authorWang, Lei-
dc.date.accessioned2021-02-25T15:17:00Z-
dc.date.available2021-02-25T15:17:00Z-
dc.date.issued2011-
dc.identifier.citationIEEE Transactions on Geoscience and Remote Sensing, 2011, v. 49, n. 3, p. 1158-1172-
dc.identifier.issn0196-2892-
dc.identifier.urihttp://hdl.handle.net/10722/296932-
dc.description.abstractAlthough the Geoscience Laser Altimeter System (GLAS) onboard the NASA Ice, Cloud and Land Elevation Satellite was not designed for urban applications, its 3-D measurement capability over the globe makes it a nice feature for consideration in monitoring urban heights. However, this has not been previously done. In this paper, we report some preliminary assessment of the GLAS data for building height and density estimation in a suburb of Beijing, China. Building heights can be directly calculated from a GLAS data product (GLA14). Because GLA14 limits height levels to six in each ground footprint, we developed a new method to remove this restriction by processing the raw GLAS data. The maximum heights measured in the field at selected GLAS footprints were used to validate the GLAS measurement results. By assuming a constant incident energy and surface reflectance within a GLAS footprint, the building density can be estimated from GLA14 or from our newly processed GLAS data. The building density determined from high-resolution images in Google Earth was used to validate the GLAS estimation results. The results indicate that the newly developed method can produce more accurate building height estimation within each GLAS footprint ( R2 = 0.937, rmse = 6.4 m, and n = 26) than the GLA14 data product (R2 = 0.808, rmse = 11.5m, and n = 26). However, satisfactory estimation results on building density cannot be obtained from the GLAS data with the methods investigated in this paper. Forest cover could be a challenge to building height and density estimation from the GLAS data. It should be addressed in future research. © 2006 IEEE.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Geoscience and Remote Sensing-
dc.subjectBuilding density-
dc.subjectLaser altimetry-
dc.subjectUrban growth-
dc.subjectGlobal change-
dc.subjectBuilding height-
dc.titleICESat GLAS data for urban environment monitoring-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TGRS.2010.2070514-
dc.identifier.scopuseid_2-s2.0-79952042461-
dc.identifier.volume49-
dc.identifier.issue3-
dc.identifier.spage1158-
dc.identifier.epage1172-
dc.identifier.isiWOS:000287658000023-
dc.identifier.issnl0196-2892-

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