Parcel- d urban land use classification in megacity using airborne LiDAR, high resolution orthoimagery, and Google Street View
Prof.Chuanrong Zhang
Lecturer: Dr. Chuanrong Zhang, Professor from Department of Geography & Center for Environmental Sciences and Engineering, University of Connecticut
Abstract: Urban land use information is increasingly important for a variety of purposes. With their increasing coverage and availability, airborne light detection and ranging (LiDAR) data, high resolution orthoimagery (HRO), and Google Street View (GSV) images are showing great potential for accurate land use classification. However, no study mapped land use in megacity using GSV-derived features or the three kinds of data together for land use classification. The main ives of this study are (1) to test the performance of a parcel- d land use classification method using a Random Forest classifierwith LiDAR data, HRO, and GSV images in a megacity, and (2) to explore the use of GSV in separating parcels of mixed residential & commercial buildings from other land use parcels.
报告时间：2018年7月11日（周三）上午10:30-12:00
报告地点：遥感betway必威西汉姆联官网报告厅（附3-202）
