A comprehensive review of hyperspectral data fusion with lidar and sar data

被引:50
作者
Kahraman, Sevcan [1 ]
Bacher, Raphael [2 ]
机构
[1] Istanbul Gelisim Univ, Elect & Elect Engn, TR-34315 Istanbul, Turkey
[2] Univ Grenoble Alpes, CNRS, Grenoble INP, GIPSA Lab, F-38000 Grenoble, France
关键词
hyperspectral (HS) image; Light Detection And Ranging (LiDAR); Synthetic Aperture Radar (SAR); multi-modal data fusion; review; LAND-COVER CLASSIFICATION; REMOTE-SENSING DATA; FEATURE-LEVEL FUSION; HIGH-RESOLUTION; WAVE-FORM; EXTINCTION PROFILES; FEATURE-EXTRACTION; DECISION FUSION; CLOUD-SHADOW; RGB DATA;
D O I
10.1016/j.arcontrol.2021.03.003
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the development of remote sensing techniques, the fusion of multimodal data, particularly hyperspectralLight Detection And Ranging (HS-LiDAR) and hyperspectral-SAR, has become an important research field in numerous application areas. Multispectral, HS, LiDAR, and Synthetic Aperture Radar (SAR) images contain detailed information about the monitored surface that are complementary to each other. Thus, data fusion methods have become a promising solution to obtain high spatial resolution remote-sensing images. The main point of this review paper is to classify hyperspectral-LiDAR and hyperspectral-SAR data fusion with approaches. Moreover, recent achievements in the fusion of hyperspectral-LiDAR and hyperspectral-SAR data are highlighted in terms of faced challenges and applications. Most frequently used data fusion datasets that include IEEE GRSS Data Fusion Contests are also described.
引用
收藏
页码:236 / 253
页数:18
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