Abstract
Spatio-temporal fusion of MODIS and Landsat data aims to produce new data that have simultaneously the Landsat spatial resolution and MODIS temporal resolution. It is an ill-posed problem involving large uncertainty, especially for reproduction of abrupt changes and heterogeneous landscapes. In this paper, we proposed to incorporate the freely available 250 m MODIS images into spatio-temporal fusion to increase prediction accuracy. The 250 m MODIS bands 1 and 2 are fused with 500 m MODIS bands 3-7 using the advanced area-to-point regression kriging approach. Based on a standard spatio-temporal fusion approach, the interim 250 m fused MODIS data are then downscaled to 30 m with the aid of the available 30 m Landsat data on temporally close days. The 250 m data can provide more information for the abrupt changes and heterogeneous landscapes than the original 500 m MODIS data, thus increasing the accuracy of spatio-temporal fusion predictions. The effectiveness of the proposed scheme was demonstrated using two datasets.
Original language | English |
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Article number | 7934036 |
Pages (from-to) | 4116-4123 |
Number of pages | 8 |
Journal | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Volume | 10 |
Issue number | 9 |
DOIs | |
Publication status | Published - 1 Sept 2017 |
Keywords
- Downscaling
- geostatistics
- image fusion
- Landsat
- MODIS
- spatio-temporal fusion
ASJC Scopus subject areas
- Computers in Earth Sciences
- Atmospheric Science