Updating Landsat-based forest cover maps with MODIS images using multiscale spectral-spatial-temporal superresolution mapping |
| |
| Affiliation: | 1. Key laboratory of Monitoring and Estimate for Environment and Disaster of Hubei province, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China;2. Lancaster Environment Centre, Faculty of Science and Technology, Lancaster University, Lancaster LA1 4YQ, UK;3. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;4. University of Chinese Academy of Sciences, Beijing 100049, China;1. CETEMAS, Forest and Wood Technology Research Centre, Sustainable Forest Management Area, Finca Experimental “La Mata” s/n, 33820 Grado, Asturias, Spain;2. E.T.S.I. Montes, Technic University of Madrid, Ciudad Universitaria, s/n, 28040 Madrid, Spain;1. School of Computer and Information Technology, Shanxi University, No. 92 Wuchen Road, Taiyuan, Shanxi 030006, China;2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, A11 Datun Road, Chaoyang District, Beijing 100101, China;3. Institute of Earth Surface Dynamics (IDYST), School of Civil and Environmental Engineering, University of Lausanne, Mouline, Geopolis, office 3337, 1015 Lausanne, Switzerland;1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;2. Laboratory of Geo-information Science and Remote Sensing, Wageningen University, Wageningen, The Netherlands;3. Soil Geography and Landscape group, Wageningen University, Wageningen, The Netherlands |
| |
| Abstract: | With the high deforestation rates of global forest covers during the past decades, there is an ever-increasing need to monitor forest covers at both fine spatial and temporal resolutions. Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat series images have been used commonly for satellite-derived forest cover mapping. However, the spatial resolution of MODIS images and the temporal resolution of Landsat images are too coarse to observe forest cover at both fine spatial and temporal resolutions. In this paper, a novel multiscale spectral-spatial-temporal superresolution mapping (MSSTSRM) approach is proposed to update Landsat-based forest maps by integrating current MODIS images with the previous forest maps generated from Landsat image. Both the 240 m MODIS bands and 480 m MODIS bands were used as inputs of the spectral energy function of the MSSTSRM model. The principle of maximal spatial dependence was used as the spatial energy function to make the updated forest map spatially smooth. The temporal energy function was based on a multiscale spatial-temporal dependence model, and considers the land cover changes between the previous and current time. The novel MSSTSRM model was able to update Landsat-based forest maps more accurately, in terms of both visual and quantitative evaluation, than traditional pixel-based classification and the latest sub-pixel based super-resolution mapping methods The results demonstrate the great efficiency and potential of MSSTSRM for updating fine temporal resolution Landsat-based forest maps using MODIS images. |
| |
| Keywords: | Forest cover mapping MODIS Landsat Updating Spectral-spatial-temporal Super-resolution mapping |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
