Crop type classification using a combination of optical and radar remote sensing data: a review

被引:183
作者
Orynbaikyzy, Aiym [1 ]
Gessner, Ursula [1 ]
Conrad, Christopher [2 ,3 ]
机构
[1] German Remote Sensing Data Ctr DFD, German Aerosp Ctr DLR, Dept Land Surface Dynam, Wessling, Germany
[2] Univ Wurzburg, Inst Geog & Geol, Dept Remote Sensing, Wurzburg, Germany
[3] Univ Halle, Inst Geosci & Geog, Halle, Germany
关键词
MULTISENSOR IMAGE FUSION; LANDSAT TM; IN-SEASON; SAR DATA; RICE FIELDS; INTEGRATION; INFORMATION; ALGORITHMS; PALSAR; AREAS;
D O I
10.1080/01431161.2019.1569791
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Reliable and accurate crop classification maps are an important data source for agricultural monitoring and food security assessment studies. For many years, crop type classification and monitoring were focused on single-source optical satellite data classification. With advancements in sensor technologies and processing capabilities, the potential of multi-source satellite imagery has gained increasing attention. The combination of optical and radar data is particularly promising in the context of crop type classification as it allows explaining the advantages of both sensor types with respect to e.g. vegetation structure and biochemical properties. This review article gives a comprehensive overview of studies on crop type classification using optical and radar data fusion approaches. A structured review of fusion approaches, classification strategies and potential for mapping specific crop types is provided. Finally, the partially untapped potential of radar-optical fusion approaches, research gaps and challenges for upcoming future studies are highlighted and discussed.
引用
收藏
页码:6553 / 6595
页数:43
相关论文
共 132 条
[1]   Enhancing land use classification with fusing dual-polarized TerraSAR-X and multispectral RapidEye data [J].
Abdikan, Saygin ;
Bilgin, Gokhan ;
Sanli, Fusun Balik ;
Uslu, Erkan ;
Ustuner, Mustafa .
JOURNAL OF APPLIED REMOTE SENSING, 2015, 9
[2]   COMPARISON OF DIFFERENT FUSION ALGORITHMS IN URBAN AND AGRICULTURAL AREAS USING SAR (PALSAR AND RADARSAT) AND OPTICAL (SPOT) IMAGES [J].
Abdikan, Saygin ;
Sanli, Fusun Balik .
BOLETIM DE CIENCIAS GEODESICAS, 2012, 18 (04) :509-531
[3]  
AHERN F.J., 1978, Canadian Journal of Remote Sensing, V4, P127
[4]  
[Anonymous], 2017, World population projected to reach 9.8 billion in 2050
[5]  
[Anonymous], 2007 IEEE INT GEOSC
[6]   Fusion of Quickbird MS and RADARSAT SAR data for urban land-cover mapping: object-based and knowledge-based approach [J].
Ban, Yifang ;
Hu, Hongtao ;
Rangel, I. M. .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2010, 31 (06) :1391-1410
[7]   A global reference database of crowdsourced cropland data collected using the Geo-Wiki platform [J].
Bayas, Juan Carlos Laso ;
Lesiv, Myroslava ;
Waldner, Francois ;
Schucknecht, Anne ;
Duerauer, Martina ;
See, Linda ;
Fritz, Steffen ;
Fraisl, Dilek ;
Moorthy, Inian ;
McCallum, Ian ;
Perger, Christoph ;
Danylo, Olha ;
Defourny, Pierre ;
Gallego, Javier ;
Gilliams, Sven ;
Akhtar, Ibrar ul Hassan ;
Baishya, Swarup Jyoti ;
Baruah, Mrinal ;
Bungnamei, Khangsembou ;
Campos, Alfredo ;
Changkakati, Trishna ;
Cipriani, Anna ;
Das, Krishna ;
Das, Keemee ;
Das, Inamani ;
Davis, Kyle Frankel ;
Hazarika, Purabi ;
Johnson, Brian Alan ;
Malek, Ziga ;
Molinari, Monia Elisa ;
Panging, Kripal ;
Pawe, Chandra Kant ;
Perez-Hoyos, Ana ;
Sahariah, Parag Kumar ;
Sahariah, Dhrubajyoti ;
Saikia, Anup ;
Saikia, Meghna ;
Schlesinger, Peter ;
Seidacaru, Elena ;
Singha, Kuleswar ;
Wilson, John W. .
SCIENTIFIC DATA, 2017, 4
[8]  
Betbeder J., 2014, 2014 IEEE GEOSC REM
[9]   Efficiency of crop identification based on optical and SAR image time series [J].
Blaes, X ;
Vanhalle, L ;
Defourny, P .
REMOTE SENSING OF ENVIRONMENT, 2005, 96 (3-4) :352-365
[10]  
Brisco B., 1989, CAN J REMOTE SENS, V15, P44