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Traditional land use classification methods rely heavily on domain experts, which is both expensive and inefficient. In this paper, deep neural network-based approaches are presented to label urban land use at pixel level using high-resolution aerial images and ground-level street view images. We use a deep neural network to extract semantic features from sparsely distributed street view images and interpolate them in the spatial domain to match the spatial resolution of the aerial images, which are then fused together through a deep neural network for classifying land use categories. Our methods are tested on a large publicly available aerial and street view images dataset of New York City, and the results show that using aerial images alone can achieve relatively high classification accuracy, the ground-level street view images contain useful information for urban land use classification, and fusing street image features with aerial images can improve classification accuracy. Moreover, we present experimental studies to show that street view images add more values when the resolutions of the aerial images are lower, and we also present case studies to illustrate how street view images provide useful auxiliary information to aerial images to boost performances.<\/jats:p>","DOI":"10.3390\/rs10101553","type":"journal-article","created":{"date-parts":[[2018,9,28]],"date-time":"2018-09-28T02:54:54Z","timestamp":1538103294000},"page":"1553","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":144,"title":["Integrating Aerial and Street View Images for Urban Land Use Classification"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1440-4175","authenticated-orcid":false,"given":"Rui","family":"Cao","sequence":"first","affiliation":[{"name":"Shenzhen Key Laboratory of Spatial Smart Sensing and Services &amp; Key Laboratory for Geo-Environmental Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation, Shenzhen University, Shenzhen 518060, China"},{"name":"College of Information Engineering &amp; Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen 518060, China"},{"name":"International Doctoral Innovation Centre &amp; School of Computer Science, University of Nottingham Ningbo China, Ningbo 315100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiasong","family":"Zhu","sequence":"additional","affiliation":[{"name":"Shenzhen Key Laboratory of Spatial Smart Sensing and Services &amp; Key Laboratory for Geo-Environmental Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation, Shenzhen University, Shenzhen 518060, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0255-4037","authenticated-orcid":false,"given":"Wei","family":"Tu","sequence":"additional","affiliation":[{"name":"Shenzhen Key Laboratory of Spatial Smart Sensing and Services &amp; Key Laboratory for Geo-Environmental Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation, Shenzhen University, Shenzhen 518060, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingquan","family":"Li","sequence":"additional","affiliation":[{"name":"Shenzhen Key Laboratory of Spatial Smart Sensing and Services &amp; Key Laboratory for Geo-Environmental Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation, Shenzhen University, Shenzhen 518060, China"},{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6201-3251","authenticated-orcid":false,"given":"Jinzhou","family":"Cao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bozhi","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Information Engineering &amp; Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen 518060, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Zhang","sequence":"additional","affiliation":[{"name":"International Doctoral Innovation Centre &amp; School of Computer Science, University of Nottingham Ningbo China, Ningbo 315100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5877-5648","authenticated-orcid":false,"given":"Guoping","family":"Qiu","sequence":"additional","affiliation":[{"name":"College of Information Engineering &amp; Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen 518060, China"},{"name":"School of Computer Science, University of Nottingham, Nottingham NG8 1BB, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,9,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Tu, W., Hu, Z., Li, L., Cao, J., Jiang, J., Li, Q., and Li, Q. 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