Data fusing can solve this problem, but it will lead to the redundant information. In this paper, we proposed a novel manifold learning approach to perform ...

This study presents a methodological framework for fusing optical and synthetic aperture radar (SAR) data at the pixel level with manifolds to improve ULC ...

Results show that multi-temporal SAR data from an area dominated by agriculture can be successfully classified using SVM. Classi-fication accuracy (78.2%) and ...

A MANIFOLD LEARNING APPROACH OF LAND COVER CLASSIFICATION FOR. OPTICAL AND SAR FUSING DATA. Xiangyu Tana, Shaobin Jiangb,c,d,e,f, Zezhong Zheng*b,c,d,e,f, ...

We improved urban land covers classification by fusing optical and radar data. We proposed a framework of fusing optical and radar data with manifold learning.

... In the Optical image, manifold learning is used to improve the performance of semantic segmentation [19]. The application of manifold learning in the SAR ...

Our experimental results showed that our proposed method obtained the best land cover classification results among these approaches for the fusing optical and ...

Sep 27, 2019 · SPOT-5 data were used as optical data to be fused with three different SAR datasets. Experimental results showed that 1) the most useful ...

This study proposes a framework, through various sampling strategies and three typical supervised classification methods, to quantify the ULC classification ...

Jun 22, 2017 · Paper Title: A MANIFOLD LEARNING APPROACH OF LAND COVER CLASSIFICATION FOR OPTICAL AND SAR FUSING DATA ; Authors: Xiangyu Tan; Yunnan Electric ...