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-->
| Autoři: | Xiaojiang Li, Chuanrong Zhang, Weixing Zhang, Wenjie Wang, Dean M. Hanink, Weidong Li |
|---|---|
| Zdroj: | Data in Brief Data in Brief, Vol 12, Iss C, Pp 175-179 (2017) |
| Informace o vydavateli: | Elsevier, 2017. |
| Rok vydání: | 2017 |
| Témata: | 0211 other engineering and technologies, 0507 social and economic geography, High resolution, 02 engineering and technology, lcsh:Computer applications to medicine. Medical informatics, 11. Sustainability, Research article, lcsh:Science (General), 021101 geological & geomatics engineering, Data Article, Multidisciplinary, Feature data, Google Street View, Light detection, 05 social sciences, Orthophoto, Urban land, Detected text, Megacity, Lidar, Geography, Urban land use classification, lcsh:R858-859.7, Parcel feature, 050703 geography, Cartography, lcsh:Q1-390 |
| Popis: | 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]. |
| Jazyk: | English |
| ISSN: | 2352-3409 |
| Přístupová URL adresa: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a5074f5725420a4d32ba6cfa0567ee9 http://europepmc.org/articles/PMC5397128 |
| Rights: | OPEN |
| Přírůstkové číslo: | edsair.doi.dedup.....0a5074f5725420a4d32ba6cfa0567ee9 |
| Autor: | Xiaojiang Li, Chuanrong Zhang, Weixing Zhang, Wenjie Wang, Dean M. Hanink, Weidong Li |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0211 other engineering and technologies
0507 social and economic geography High resolution 02 engineering and technology lcsh:Computer applications to medicine. Medical informatics 11. Sustainability Research article lcsh:Science (General) 021101 geological & geomatics engineering Data Article Multidisciplinary Feature data Google Street View Light detection 05 social sciences Orthophoto Urban land Detected text Megacity Lidar Geography Urban land use classification lcsh:R858-859.7 Parcel feature 050703 geography Cartography lcsh:Q1-390 |
| Zdroj: | Data in Brief Data in Brief, Vol 12, Iss C, Pp 175-179 (2017) |
| ISSN: | 2352-3409 |
| Popis: | 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]. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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