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Radar Vegetation Index for Estimating the Vegetation Water Content of Rice and Soybean

Yihyun Kim, T. Jackson, R. Bindlish, Hoonyol Lee, Sukyoung Hong
2012 IEEE Geoscience and Remote Sensing Letters  
Here, the radar vegetation index (RVI) was evaluated for estimating VWC.  ...  Index Terms-Leaf area index (LAI), microwave remote sensing, normalized difference vegetation index (NDVI), polarimetric scatterometer, radar vegetation index (RVI), vegetation water content (VWC).  ...  ACKNOWLEDGMENT This work was carried out with the support of "Cooperative Research Program for Agriculture Science and Technology Development (Project No.  ... 
doi:10.1109/lgrs.2011.2174772 fatcat:jeskt2qxyre4lfvtc6uzlwpzoe

CROP SPECIES RECOGNITION AND DISCRIMINATION PADDY-RICE-GROWINGFIELDS FROM REAPED-FIELDS BY THE RADAR VEGETATION INDEX (RVI) OF ALOS-2/PALSAR2

Y. Yamada
2016 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Kim,Y. and van Zyl, J.J. proposed a kind of Radar Vegetation Index (RVI) as RVI = 8 * σ<sup>0</sup><sub>hv</sub> / (σ<sup>0</sup><sub>hh</sub> + σ<sup  ...  Their report showed the L-band was the most promising wave length for estimating LAI and NDVI from RVI.  ...  Further research should be desired.Kim,Y., Jackson,T., et al., 2012,Radar Vegetation Index for Estimating the Vegetation Water Content of Rice and Soybean, IEEE Geo. Remote Sens.  ... 
doi:10.5194/isprsarchives-xli-b8-1083-2016 fatcat:3tougvg5zndnznzvufqbtg7fgm

CROP SPECIES RECOGNITION AND DISCRIMINATION PADDY-RICE-GROWINGFIELDS FROM REAPED-FIELDS BY THE RADAR VEGETATION INDEX (RVI) OF ALOS-2/PALSAR2

Y. Yamada
2016 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Kim,Y. and van Zyl, J.J. proposed a kind of Radar Vegetation Index (RVI) as RVI = 8 * σ<sup>0</sup><sub>hv</sub> / (σ<sup>0</sup><sub>hh</sub> + σ<sup>0</sup><sub>vv</sub> + 2* σ<sup>0</sup><sub>hv</sub  ...  Their report showed the L-band was the most promising wave length for estimating LAI and NDVI from RVI.  ...  Further research should be desired.Kim,Y., Jackson,T., et al., 2012,Radar Vegetation Index for Estimating the Vegetation Water Content of Rice and Soybean, IEEE Geo. Remote Sens.  ... 
doi:10.5194/isprs-archives-xli-b8-1083-2016 fatcat:2ibw6m3qx5fzlpbi6neays3zvy

Preliminary Study on the Radar Vegetation Index (RVI) Application to Actual Paddy Fields by ALOS/PALSAR Full-polarimetry SAR Data

Y. Yamada
2015 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Kim and van Zyl (2001) proposed a kind of radar vegetation index (RVI).  ...  They applied it into rice crop and soybean. (Y.Kim, T.Jackson et al., 2012) They compared RVI for L-, C- and X-bands to crop growth data, LAI and NDVI.  ...  And they reported that the RVI is effective to estimate VWC, vegetation water content. Their VWC is useful for the estimation of soil moisture or drought, according to Kim and Jackson, et al.  ... 
doi:10.5194/isprsarchives-xl-7-w3-129-2015 fatcat:vo7v25qbarbn3gn5qnuouste6u

Radar Remote Sensing of Agricultural Canopies: A Review

Susan C. Steele-Dunne, Heather McNairn, Alejandro Monsivais-Huertero, Jasmeet Judge, Pang-Wei Liu, Kostas Papathanassiou
2017 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
If 397 multiple radar measurements are used, inversion of the WCM allows estimates of vegetation 398 parameter(s), for example LAI and/or vegetation water content, as well as underlying soil  ...  They found 210 that at L-band, HV backscatter was the best estimator for vegetation water content (VWC).  ... 
doi:10.1109/jstars.2016.2639043 fatcat:6w5qd3dg2jd7ncdod7nn2un7gi

Monitoring soybean growth using L-, C-, and X-band scatterometer data

Yihyun Kim, Thomas Jackson, Rajat Bindlish, Hoonyol Lee, Sukyoung Hong
2013 International Journal of Remote Sensing  
Acknowledgements This study was funded by the research project (Project No. PJ009367012013) of National Academy of Agricultural Science, Rural Development Administration, Republic of Korea.  ...  expressed in units of dB. y x Regression equation RMSE Leaf area index L-HH y = 0.23x + 5.0395 0.1045 Vegetation water content L-HH y = 0.1939x + 4.0276 0.0796 kg m −2 .  ...  Figure 6 . 6 (L-HH, dB) Relationship between backscattering coefficients (L-band HH-polarization) and soybean growth parameters: (a) LAI and (b) vegetation water content (VWC).  ... 
doi:10.1080/01431161.2013.772309 fatcat:f2z3yyirm5bmfb6dsbmoyhorpe

Research advances of SAR remote sensing for agriculture applications: A review

Chang-an LIU, Zhong-xin CHEN, Yun SHAO, Jin-song CHEN, Tuya Hasi, Hai-zhu PAN
2019 Journal of Integrative Agriculture  
under the condition of high vegetation coverage, the integrations of SAR remote sensing retrieval information with hydrological models and/or crop growth models, and so on, still need to be improved.  ...  yield estimation.  ...  Acknowledgements This work was supported in part by the National Natural Science Foundation of China (61661136006 and 41371396). Allain S, Ferro-Famil L, Pottier E. 2003.  ... 
doi:10.1016/s2095-3119(18)62016-7 fatcat:a4v7kcn3lvfxza7z4d4hfwdeau

Synergistic Use of Radar and Optical Satellite Data for Improved Monsoon Cropland Mapping in India

Qadir, Mondal
2020 Remote Sensing  
We adapted a synergistic approach of combining Sentinel-1 Synthetic Aperture Radar (SAR) data with Normalized Difference Vegetation Index (NDVI) derived from Sentinel-2 optical data using the Google Earth  ...  The proposed agriculture mask, ROM, has high potential to support the global agriculture monitoring missions of Geo Global Agriculture Monitoring (GEOGLAM) and Sentinel-2 for Agriculture (S2Agri) project  ...  and water content.  ... 
doi:10.3390/rs12030522 fatcat:crviyeabwfe7rlw5s7u7awfyfa

Irrigated Grassland Monitoring Using a Time Series of TerraSAR-X and COSMO-SkyMed X-Band SAR Data

Mohammad Hajj, Nicolas Baghdadi, Gilles Belaud, Mehrez Zribi, Bruno Cheviron, Dominique Courault, Olivier Hagolle, François Charron
2014 Remote Sensing  
, height, and the Vegetation Water Content (VWC) [12] .  ...  Some studies have used another index known as the Normalized Difference Water Index (NDWI), which is computed using the NIR (near infra-red) and the SWIR (short wave infrared), to estimate vegetation water  ...  We also wish to thank the EMMAH unit (INRA) for providing meteorological data and the technical teams of ASI and DLR for providing answers regarding the performances of CSK and TSX.  ... 
doi:10.3390/rs61010002 fatcat:c22z5vomffeynmjlafc6iyf2w4

Application of Ground-Based Remote Sensing in Identifying Biotic Stress: A Review

Jitendra Kumar, Ananta Vashisth, Nishant K. Sinha, M. Mohanty, Alka Rani, R. S. Chaudhary
2021 Research Biotica  
Therefore, this article aims to present an overview of the quantification of different biotic and abiotic stress by remote sensing techniques and focuses on future directions for researchers.  ...  Hyperspectral remote sensing has also been used in discrimination of crops and their cultivars, assessing abiotic and biotic stresses, quantitative estimation of crop nutrient status and soil health.  ...  + + Dimensions/height + + + + + Canopy water content ++ ++ ++ Leaf Water content +++ + + Temperature ++++ + Table 2 : 2 Vegetation index and indicator stress Index Name Formula Association with Relevant  ... 
doi:10.54083/resbio/3.1.2021.28-32 fatcat:j6zypsvdj5akzgzd6aqyb4bbhu

Recent Advancement of Synthetic Aperture Radar (SAR) Systems and Their Applications to Crop Growth Monitoring [chapter]

Jiali Shang, Jiangui Liu, Zhongxin Chen, Heather McNairn, Andrew Davidson
2022 Remote Sensing [Working Title]  
parameter estimation, and change detection; and (3) summary and perspectives for future application development.  ...  Synthetic aperture radars (SARs) propagate and measure the scattering of energy at microwave frequencies.  ...  Radar backscattering models have been used for estimation of crop parameters such as Leaf Area Index (LAI), canopy water content, and biomass [7] [8] [9] [10] , and soil parameters such as soil moisture  ... 
doi:10.5772/intechopen.102917 fatcat:alc4lsj5ofa37os4ij6sptn6qm

Rice Mapping and Monitoring Using ENVISAT ASAR Data

Shenbin Yang, Shuanghe Shen, Bingbai Li, Thuy Le Toan, Wei He
2008 IEEE Geoscience and Remote Sensing Letters  
In this paper, ENVISAT Advanced Synthetic Aperture Radar (ASAR) alternative polarization VV/HH data was used for rice monitoring in Xinghua rice experiment site in the middle of Jiangsu Province.  ...  Radar remote sensing technology has become an important method for stable and long-time rice monitoring for its capability to operate in all weather conditions.  ...  Other plants are also grown during the rice season, such as soybeans, cotton and various garden vegetables.  ... 
doi:10.1109/lgrs.2007.912089 fatcat:qhvuy5h3yrezjcsibzzxcsgblq

Monthly composites from Sentinel-1 and Sentinel-2 images for regional major crop mapping with Google Earth Engine

Chong LUO, Huan-jun LIU, Lü-ping LU, Zheng-rong LIU, Fan-chang KONG, Xin-le ZHANG
2021 Journal of Integrative Agriculture  
Adding common vegetation indices and Sentinel-1 data to the crop classification improved the overall classification accuracy and the OA by 0.2 and 0.6%, respectively, compared to using only the Sentinel  ...  We obtained Sentinel-1 and Sentinel-2 images from all the covered study areas in the critical period for crop growth in 2018 (May to September), combined monthly composite images of reflectance bands,  ...  Acknowledgements The paper was funded by the National Key R&D Program of China (2017YFD0201803) and the Talent Recruitment Project of Northeast Institute of Geography and Agroecology, Chinese Academy of  ... 
doi:10.1016/s2095-3119(20)63329-9 fatcat:khazabk3frbohf4246ce7t2pjq

Measuring Rice Yield from Space: The Case of Thai Binh Province, Viet Nam

Kaiyu Guan, Ngo The Hien, Zhan Li, Lakshman Nagraj Rao
2018 Social Science Research Network  
Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten  ...  Rice is different from corn and soybean in that corn and soybean both have their final grains below the canopy, while rice grains mostly locate at top of the canopy.  ...  0.01 for croplands, 0.05 for barren, 0.05 for built-ups, 0.02 for water, 0.05 for wetlands, and 0.10 for other vegetation.  ... 
doi:10.2139/ssrn.3188560 fatcat:dr5lryfvmfaj7jmu7i5bsre7my

Prediction of Soil Water Content and Electrical Conductivity using Random Forest Methods with UAV Multispectral and Ground-coupled Geophysical Data

Yunyi Guan, Katherine Grote, Joel Schott, Kelsi Leverett
2022 Remote Sensing  
The volumetric water content (VWC) of soil is a critical parameter in agriculture, as VWC strongly influences crop yield, provides nutrients to plants, and maintains the microbes that are needed for the  ...  In this study, the best estimates of these properties were obtained when the agriculture parameters in a field were fairly homogeneous (one crop type and the same type of drainage throughout the field)  ...  Acknowledgments: Our sincere gratitude is extended to Kelly Nelson, who provided site access, maps, and invaluable site guidance. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs14041023 fatcat:vxxp7ddunvcprcmkaxluz7lciy
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