Land cover classification using Landsat 8 Operational Land Imager data in Beijing,China |
| |
| Authors: | Kun Jia Xingfa Gu Yunjun Yao Xianhong Xie Bin Li |
| |
| Institution: | 1. State Key Laboratory of Remote Sensing Science, and College of Global Change and Earth System Science, Beijing Normal University, Beijing, China;2. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China |
| |
| Abstract: | The successful launch of Landsat 8 provides a new data source for monitoring land cover, which has the potential to significantly improve the characterization of the earth’s surface. To assess data performance, Landsat 8 Operational Land Imager (OLI) data were first compared with Landsat 7 ETM + data using texture features as the indicators. Furthermore, the OLI data were investigated for land cover classification using the maximum likelihood and support vector machine classifiers in Beijing. The results indicated that (1) the OLI data quality was slightly better than the ETM + data quality in the visible bands, especially the near-infrared band of OLI the data, which had a clear improvement; clear improvement was not founded in the shortwave-infrared bands. Moreover, (2) OLI data had a satisfactory performance in terms of land cover classification. In summary, OLI data were a reliable data source for monitoring land cover and provided the continuity in the Landsat earth observation. |
| |
| Keywords: | land cover classification Landsat 8 texture Operational Land Imager |
|
|
