Sensing Urban Land-Use Patterns By Integrating Google Tensorflow And Scene-Classification Models

no code implementations • 4 Aug 2017 • Yao Yao, Haolin Liang, Xia Li, Jinbao Zhang, Jialv He

To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features.

General Classification Scene Classification +1

Extracting urban impervious surface from GF-1 imagery using one-class classifiers

no code implementations • 13 May 2017 • Yao Yao, Jialv He, Jinbao Zhang, Yatao Zhang

In this study, we investigate several one-class classifiers, such as Presence and Background Learning (PBL), Positive Unlabeled Learning (PUL), OCSVM, BSVM and MAXENT, to extract urban impervious surface area using high spatial resolution imagery of GF-1, China's new generation of high spatial remote sensing satellite, and evaluate the classification accuracy based on artificial interpretation results.

General Classification Management