Improvement of Clustering Methods for Modelling Abrupt Land Surface Changes in Satellite Image Fusions
A key challenge in developing models for the fusion of surface reflectance data across multiple satellite sensors is ensuring that they apply to both gradual vegetation phenological dynamics and abrupt land surface changes. To better model land cover spatial and temporal changes, we proposed previou...
Main Authors: | Detang Zhong, Fuqun Zhou |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-07-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | https://www.mdpi.com/2072-4292/11/15/1759 |
Similar Items
-
A Prediction Smooth Method for Blending Landsat and Moderate Resolution Imagine Spectroradiometer Images
by: Detang Zhong, et al.
Published: (2018-08-01) -
Integration of One-Pair Spatiotemporal Fusion With Moment Decomposition for Better Stability
by: Yaobin Ma, et al.
Published: (2021-10-01) -
A Land Product Characterization System for Comparative Analysis of Satellite Data and Products
by: Kevin Gallo, et al.
Published: (2017-12-01) -
A Comprehensive and Automated Fusion Method: The Enhanced Flexible Spatiotemporal DAta Fusion Model for Monitoring Dynamic Changes of Land Surface
by: Chenlie Shi, et al.
Published: (2019-09-01) -
STAIR 2.0: A Generic and Automatic Algorithm to Fuse Modis, Landsat, and Sentinel-2 to Generate 10 m, Daily, and Cloud-/Gap-Free Surface Reflectance Product
by: Yunan Luo, et al.
Published: (2020-10-01)