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Original Articles

Sensitivity of vegetation indices to spatial degradation of RapidEye imagery for paddy rice detection: a case study of South Korea

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Pages 1-17 | Received 05 Mar 2014, Accepted 18 Dec 2014, Published online: 29 Jan 2015

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Read on this site (11)

Shuang Zhao, Xiangnan Liu, Chao Ding, Shuyuan Liu, Changshan Wu & Ling Wu. (2020) Mapping Rice Paddies in Complex Landscapes with Convolutional Neural Networks and Phenological Metrics. GIScience & Remote Sensing 57:1, pages 37-48.
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Rei Sonobe, Yuki Yamaya, Hiroshi Tani, Xiufeng Wang, Nobuyuki Kobayashi & Kan-ichiro Mochizuki. (2017) Assessing the suitability of data from Sentinel-1A and 2A for crop classification. GIScience & Remote Sensing 54:6, pages 918-938.
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Mijeong Kim, Jonghan Ko, Seungtaek Jeong, Jong-min Yeom & Hyun-ok Kim. (2017) Monitoring canopy growth and grain yield of paddy rice in South Korea by using the GRAMI model and high spatial resolution imagery. GIScience & Remote Sensing 54:4, pages 534-551.
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Huanxue Zhang, Qiangzi Li, Jiangui Liu, Jiali Shang, Xin Du, Longcai Zhao, Na Wang & Taifeng Dong. (2017) Crop classification and acreage estimation in North Korea using phenology features. GIScience & Remote Sensing 54:3, pages 381-406.
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Articles from other publishers (12)

Yi-Shin Chou & Cheng-Ying Chou. (2023) Deep Learning Approach for Paddy Field Detection Using Labeled Aerial Images: The Case of Detecting and Staging Paddy Fields in Central and Southern Taiwan. Remote Sensing 15:14, pages 3575.
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Bernardo Galeote-Leyva, José René Valdez-Lazalde, Gregorio Ángeles-Pérez, Héctor Manuel De los Santos-Posadas & Juan Manuel Romero Padilla. (2022) Inventario forestal asistido por LIDAR: efecto de la densidad de retornos y el diseño de muestreo sobre la precisión. Madera y Bosques 28:2.
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Seyit Kerimkhulle, Zhandos Kerimkulov, Dias Bakhtiyarov, Nazerke Turtayeva & Jong Kim. (2021) In-Field Crop-Weed Classification Using Remote Sensing and Neural Network. In-Field Crop-Weed Classification Using Remote Sensing and Neural Network.
Zhengdong Deng, Zhao Lu, Guangyuan Wang, Daqing Wang, Zhibin Ding, Hongfei Zhao, Haoli Xu, Yue Shi, Zijian Cheng & Xiaoning Zhao. (2021) Extraction of fractional vegetation cover in arid desert area based on Chinese GF-6 satellite. Open Geosciences 13:1, pages 416-430.
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Xueqin Jiang, Shenghui Fang, Xia Huang, Yanghua Liu & Linlin Guo. (2021) Rice Mapping and Growth Monitoring Based on Time Series GF-6 Images and Red-Edge Bands. Remote Sensing 13:4, pages 579.
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Eugene G. Yu & Zhengwei Yang. 2021. Agro-geoinformatics. Agro-geoinformatics 175 203 .
Toshihiro Sakamoto, David S. Sprague, Katsuo Okamoto & Naoki Ishitsuka. (2018) Semi-automatic classification method for mapping the rice-planted areas of Japan using multi-temporal Landsat images. Remote Sensing Applications: Society and Environment 10, pages 7-17.
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Seonyoung Park, Jungho Im, Seohui Park, Cheolhee Yoo, Hyangsun Han & Jinyoung Rhee. (2018) Classification and Mapping of Paddy Rice by Combining Landsat and SAR Time Series Data. Remote Sensing 10:3, pages 447.
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Kyalo Richard, Elfatih M. Abdel-Rahman, Sevgan Subramanian, Johnson O. Nyasani, Michael Thiel, Hosein Jozani, Christian Borgemeister & Tobias Landmann. (2017) Maize Cropping Systems Mapping Using RapidEye Observations in Agro-Ecological Landscapes in Kenya. Sensors 17:11, pages 2537.
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Onisimo Mutanga, Timothy Dube & Omer Galal. (2017) Remote sensing of crop health for food security in Africa: Potentials and constraints. Remote Sensing Applications: Society and Environment 8, pages 231-239.
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Fengfei Xin, Xiangming Xiao, Bin Zhao, Akira Miyata, Dennis Baldocchi, Sara Knox, Minseok Kang, Kyo-moon Shim, Sunghyun Min, Bangqian Chen, Xiangping Li, Jie Wang, Jinwei Dong & Chandrashekhar Biradar. (2017) Modeling gross primary production of paddy rice cropland through analyses of data from CO2 eddy flux tower sites and MODIS images. Remote Sensing of Environment 190, pages 42-55.
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Eunsong Oh, Jinsuk Hong, Sug-Whan Kim, Young-Je Park & Seong-Ick Cho. (2016) Novel ray tracing method for stray light suppression from ocean remote sensing measurements. Optics Express 24:10, pages 10232.
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