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​Parcel feature data derived from Google Street View images for urban land use classification in Brooklyn, New York Cityfor urban land use classification in Brooklyn, New York Cityretain-->

Authors :
Weixing Zhang
Weidong Li
Chuanrong Zhang
Dean M. Hanink
Xiaojiang Li
Wenjie Wang
Source :
Data in Brief, Vol 12, Iss C, Pp 175-179 (2017)
Publication Year :
2017
Publisher :
Elsevier, 2017.

Abstract

Google Street View (GSV) was used for urban land use classification, together with airborne light detection and ranging (LiDAR) data and high resolution orthoimagery, by a parcel-based method. In this data article, we present the input raw GSV images, intermediate products of GSV images, and final urban land use classification data that are related to our research article "Parcel-based urban land use classification in megacity using airborne LiDAR, high resolution orthoimagery, and Google Street View" (Zhang et al., 2017) [1]. More detail about other used data and our findings can be found in Zhang et al. (2017) [1].

Details

Language :
English
ISSN :
23523409
Volume :
12
Issue :
C
Database :
Directory of Open Access Journals
Journal :
Data in Brief
Publication Type :
Academic Journal
Accession number :
edsdoj.72fa95b957214b42b852289d7f832b07
Document Type :
article
Full Text :
https://doi.org/10.1016/j.dib.2017.04.002