UAV Remote Sensing for Campus Monitoring: A Comparative Evaluation of Nearest Neighbor and Rule-Based Classification
Tóm tắt
UAV technology when aided with the unique data acquisition strategies, preprocessing techniques and analytical abilities of an established domain of remote sensing provide more affordable, customized and user-friendly option of “UAV-Remote Sensing”. This extended branch of remote sensing flourishes in both the mapping and measurement, if implemented in the ordered fashion to ensure remote sensing grade data. The current study integrates the potential of UAV technology to the high-resolution data classification approach of object-based image analysis. Department of Civil Engineering, Indian Institute of Technology-Roorkee, India, is selected as study area. In the first part of the study, a detailed UAV survey followed by UAV data processing was carried out to capture the VHR orthorectified image of the selected study area. In the second step, a comparative assessment of nearest neighbor (NN) and rule-based classifications were performed. Orthorectified image was segmented using a multi-resolution segmentation. The overall accuracy for NN and rule-based classifier were 95.13% and 93.87%, respectively. Detailed assessment of user accuracy and producer accuracy described that tree, road, solar panel and waterbody were more accurately classified with NN classifier, whereas building, grass land, open land and vehicle were more accurately classified with rule-based classifier.
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