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There are new algorithms recently available.
1. FSDAF
2. Fmask
3. SADFAT
4. DELTA








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flexible_spatiotemporal_data_fusion_fsdaf_model

Flexible Spatiotemporal DAta Fusion (FSDAF) model

This algorithm was developed by Dr. Xiaolin Zhu at Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University.

Email address of primary contact: Xiaolin.zhu@polyu.edu.hk. The download link is here.

Language of computer code: IDL
Input data: two coarse-resolution satellite images at time t1 and t2 and one fine-resolution satellite image at t1.
Output: one fine-resolution satellite image at t2.
Descriptions of the computer code by the author:
FSDAF was developed to generate synthesized frequent high spatial resolution images through blending two types of data, i.e., frequent coarse spatial resolution data, such as that from MODIS, and less frequent high spatial resolution data such as that from Landsat. It has the following strengths: (1) it needs minimum input data; (2) it is suitable for heterogeneous landscapes; and (3) it can predict both gradual change and land cover type change. It cannot capture tiny changes in land cover type which could be further improved through brining more available fine-resolution images into the process.

Relevant publications:

Zhu, X., Helmer E., Liu, D., Chen, J., Gao, F., and Lefsky M. 2016. A flexible spatiotemporal method for fusing satellite images with different resolutions. Remote Sensing of Environment, 172, 165-155.

Remote sensor the algorithm is primarily applied to

Coarse spatial resolution (> 100 m) optical sensor
Medium spatial resolution (10-100 m) optical sensor
High spatial resolution (< 10 m) optical sensor

Application Area

Hydrology and water resources
Land surface modeling
Forestry
Agriculture
Soils
Wetland
Ecology
Geography and land information
Urban


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