Rice Crop Analysis, Production, Detection, Health, Change

Chapter Contents (Back)
Classification. Rice Classification. Rice Yield.

Song, S.[Shalei], Gong, W.[Wei], Zhu, B.[Bo], Huang, X.[Xin],
Wavelength selection and spectral discrimination for paddy rice, with laboratory measurements of hyperspectral leaf reflectance,
PandRS(66), No. 5, September 2011, pp. 672-682.
Elsevier DOI 1110
Hyperspectral data; Wavelength selection; Spectral discrimination; Rice BibRef

Sakamoto, T.[Toshihiro], Shibayama, M.[Michio], Kimura, A.[Akihiko], Takada, E.[Eiji],
Assessment of digital camera-derived vegetation indices in quantitative monitoring of seasonal rice growth,
PandRS(66), No. 6, November 2011, pp. 872-882.
Elsevier DOI 1112
Crop phenology; Active sensing; Flashlight BibRef

Lopez-Sanchez, J.M., Cloude, S.R., Ballester-Berman, J.D.,
Rice Phenology Monitoring by Means of SAR Polarimetry at X-Band,
GeoRS(50), No. 7, July 2012, pp. 2695-2709.

Hosoi, F.[Fumiki], Omasa, K.[Kenji],
Estimation of vertical plant area density profiles in a rice canopy at different growth stages by high-resolution portable scanning lidar with a lightweight mirror,
PandRS(74), No. 1, November 2012, pp. 11-19.
Elsevier DOI 1212
Estimating Vertical Leaf Area Density Profiles of Tree Canopies Using Three-Dimensional Portable Lidar Imaging,
Laser09(152). 0909
Laser beam coverage index; Plant area density; Portable scanning lidar; Rice; Three-dimensional imaging; Voxel-based canopy profiling BibRef

Gnyp, M.L.[Martin Leon], Yu, K.[Kang], Aasen, H.[Helge], Yao, Y.K.[Yin-Kun], Huang, S.Y.[Shan-Yu], Miao, Y.X.[Yu-Xin], Bareth, G.[Georg],
Analysis of Crop Reflectance for Estimating Biomass in Rice Canopies at Different Phenological Stages,
PFG(2013), No. 4, 2013, pp. 351-365.
DOI Link 1309

Gnyp, M.L., Yao, Y.K., Yu, K., Huang, S.Y., Aasen, H., Lenz-Wiedemann, V.I.S., Miao, Y.X., Bareth, G.,
Hyperspectral Analysis Of Rice Phenological Stages In Northeast China,
AnnalsPRS(I-7), No. 2012, pp. 77-82.
HTML Version. 1209

Yu, K.[Kang], Li, F.[Fei], Gnyp, M.L.[Martin L.], Miao, Y.X.[Yu-Xin], Bareth, G.[Georg], Chen, X.P.[Xin-Ping],
Remotely detecting canopy nitrogen concentration and uptake of paddy rice in the Northeast China Plain,
PandRS(78), No. 1, April 2013, pp. 102-115.
Elsevier DOI 1304
Hyperspectral index; Nitrogen status; Rice; Heading stage; N dilution effect; Stepwise multiple linear regression; Lambda by lambda band-optimized algorithm BibRef

Son, N.T., Chen, C.F., Chen, C.R., Chang, L.Y.,
Satellite-based investigation of flood-affected rice cultivation areas in Chao Phraya River Delta, Thailand,
PandRS(86), No. 1, 2013, pp. 77-88.
Elsevier DOI 1312

Son, N.T.[Nguyen-Thanh], Chen, C.F.[Chi-Farn], Chen, C.R.[Cheng-Ru], Duc, H.N.[Huynh-Ngoc], Chang, L.Y.[Ly-Yu],
A Phenology-Based Classification of Time-Series MODIS Data for Rice Crop Monitoring in Mekong Delta, Vietnam,
RS(6), No. 1, 2013, pp. 135-156.
DOI Link 1402

Maki, M.[Masayasu], Homma, K.[Koki],
Empirical Regression Models for Estimating Multiyear Leaf Area Index of Rice from Several Vegetation Indices at the Field Scale,
RS(6), No. 6, 2014, pp. 4764-4779.
DOI Link 1407

Mosleh, M.K.[Mostafa K.], Hassan, Q.K.[Quazi K.],
Development of a Remote Sensing-Based 'Boro' Rice Mapping System,
RS(6), No. 3, 2014, pp. 1938-1953.
DOI Link 1404

Karila, K.[Kirsi], Nevalainen, O.[Olli], Krooks, A.[Anssi], Karjalainen, M.[Mika], Kaasalainen, S.[Sanna],
Monitoring Changes in Rice Cultivated Area from SAR and Optical Satellite Images in Ben Tre and Tra Vinh Provinces in Mekong Delta, Vietnam,
RS(6), No. 5, 2014, pp. 4090-4108.
DOI Link 1407

Gumma, M.K.[Murali Krishna], Thenkabail, P.S.[Prasad S.], Maunahan, A.[Aileen], Islam, S.[Saidul], Nelson, A.[Andrew],
Mapping seasonal rice cropland extent and area in the high cropping intensity environment of Bangladesh using MODIS 500 mu-m data for the year 2010,
PandRS(91), No. 1, 2014, pp. 98-113.
Elsevier DOI 1404
Seasonal rice mapping BibRef

Lopez-Sanchez, J.M., Vicente-Guijalba, F., Ballester-Berman, J.D., Cloude, S.R.,
Polarimetric Response of Rice Fields at C-Band: Analysis and Phenology Retrieval,
GeoRS(52), No. 5, May 2014, pp. 2977-2993.
Backscatter BibRef

Inoue, Y.[Yoshio], Sakaiya, E.[Eiji], Wang, C.[Cuizhen],
Potential of X-Band Images from High-Resolution Satellite SAR Sensors to Assess Growth and Yield in Paddy Rice,
RS(6), No. 7, 2014, pp. 5995-6019.
DOI Link 1408

Zhou, K.[Kai], Guo, Y.J.[Yong-Jiu], Geng, Y.[Yanan], Zhu, Y.[Yan], Cao, W.X.[Wei-Xing], Tian, Y.C.[Yong-Chao],
Development of a Novel Bidirectional Canopy Reflectance Model for Row-Planted Rice and Wheat,
RS(6), No. 8, 2014, pp. 7632-7659.
DOI Link 1410

Rossi, C., Erten, E.,
Paddy-Rice Monitoring Using TanDEM-X,
GeoRS(53), No. 2, February 2015, pp. 900-910.
crops BibRef

Nelson, A.[Andrew], Setiyono, T.[Tri], Rala, A.B.[Arnel B.], Quicho, E.D.[Emma D.], Raviz, J.V.[Jeny V.], Abonete, P.J.[Prosperidad J.], Maunahan, A.A.[Aileen A.], Garcia, C.A.[Cornelia A.], Bhatti, H.Z.M.[Hannah Zarah M.], Villano, L.S.[Lorena S.], Thongbai, P.[Pongmanee], Holecz, F.[Francesco], Barbieri, M.[Massimo], Collivignarelli, F.[Francesco], Gatti, L.[Luca], Quilang, E.J.P.[Eduardo Jimmy P.], Mabalay, M.R.O.[Mary Rose O.], Mabalot, P.E.[Pristine E.], Barroga, M.I.[Mabel I.], Bacong, A.P.[Alfie P.], Detoito, N.T.[Norlyn T.], Berja, G.B.[Glorie Belle], Varquez, F.[Frenciso], Wahyunto, Kuntjoro, D.[Dwi], Murdiyati, S.R.[Sri Retno], Pazhanivelan, S.[Sellaperumal], Kannan, P.[Pandian], Mary, P.C.N.[Petchimuthu Christy Nirmala], Subramanian, E.[Elangovan], Rakwatin, P.[Preesan], Intrman, A.[Amornrat], Setapayak, T.[Thana], Lertna, S.[Sommai], Minh, V.Q.[Vo Quang], Tuan, V.Q.[Vo Quoc], Duong, T.H.[Trinh Hoang], Quyen, N.H.[Nguyen Huu], Kham, D.V.[Duong Van], Hin, S.[Sarith], Veasna, T.[Touch], Yadav, M.[Manoj], Chin, C.[Chharom], Ninh, N.H.[Nguyen Hong],
Towards an Operational SAR-Based Rice Monitoring System in Asia: Examples from 13 Demonstration Sites across Asia in the RIICE Project,
RS(6), No. 11, 2014, pp. 10773-10812.
DOI Link 1412

Asilo, S.[Sonia], de Bie, K.[Kees], Skidmore, A.[Andrew], Nelson, A.[Andrew], Barbieri, M.[Massimo], Maunahan, A.[Aileen],
Complementarity of Two Rice Mapping Approaches: Characterizing Strata Mapped by Hypertemporal MODIS and Rice Paddy Identification Using Multitemporal SAR,
RS(6), No. 12, 2014, pp. 12789-12814.
DOI Link 1412

Zhao, Q.Y.[Quan-Ying], Lenz-Wiedemann, V.I.S.[Victoria I.S.], Yuan, F.[Fei], Jiang, R.F.[Rong-Feng], Miao, Y.X.[Yu-Xin], Zhang, F.[Fusuo], Bareth, G.[Georg],
Investigating Within-Field Variability of Rice from High Resolution Satellite Imagery in Qixing Farm County, Northeast China,
IJGI(4), No. 1, 2015, pp. 236-261.
DOI Link 1502

Tornos, L.[Lucia], Huesca, M.[Margarita], Dominguez, J.A.[Jose Antonio], Moyano, M.C.[Maria Carmen], Cicuendez, V.[Victor], Recuero, L.[Laura], Palacios-Orueta, A.[Alicia],
Assessment of MODIS spectral indices for determining rice paddy agricultural practices and hydroperiod,
PandRS(101), No. 1, 2015, pp. 110-124.
Elsevier DOI 1503
Agriculture BibRef

Yu, K.[Kang], Gnyp, M.L.[Martin Leon], Gao, L.[Lei], Yuxin, M.[Miao], Xinping, C.[Cheng], Bareth, G.[Georg],
Estimate Leaf Chlorophyll of Rice Using Reflectance Indices and Partial Least Squares,
PFG(2015), No. 1, 2015, pp. 45-54.
DOI Link 1503

Wang, J.[Jing], Huang, J.F.[Jing-Feng], Zhang, K.[Kangyu], Li, X.[Xinxing], She, B.[Bao], Wei, C.[Chuanwen], Gao, J.[Jian], Song, X.D.[Xiao-Dong],
Rice Fields Mapping in Fragmented Area Using Multi-Temporal HJ-1A/B CCD Images,
RS(7), No. 4, 2015, pp. 3467-3488.
DOI Link 1505

Qin, Y.W.[Yuan-Wei], Xiao, X.M.[Xiang-Ming], Dong, J.W.[Jin-Wei], Zhou, Y.T.[Yu-Ting], Zhu, Z.[Zhe], Zhang, G.[Geli], Du, G.M.[Guo-Ming], Jin, C.[Cui], Kou, W.[Weili], Wang, J.[Jie], Li, X.P.[Xiang-Ping],
Mapping paddy rice planting area in cold temperate climate region through analysis of time series Landsat 8 (OLI), Landsat 7 (ETM+) and MODIS imagery,
PandRS(105), No. 1, 2015, pp. 220-233.
Elsevier DOI 1506
Rice paddy BibRef

Zhang, G.[Geli], Xiao, X.M.[Xiang-Ming], Dong, J.W.[Jin-Wei], Kou, W.[Weili], Jin, C.[Cui], Qin, Y.W.[Yuan-Wei], Zhou, Y.T.[Yu-Ting], Wang, J.[Jie], Menarguez, M.A.[Michael Angelo], Biradar, C.[Chandrashekhar],
Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data,
PandRS(106), No. 1, 2015, pp. 157-171.
Elsevier DOI 1507
Paddy rice fields BibRef

Guo, Y.J.[Yong-Jiu], Zhang, L.[Ling], Qin, Y.[Yehui], Zhu, Y.[Yan], Cao, W.X.[Wei-Xing], Tian, Y.C.[Yong-Chao],
Exploring the Vertical Distribution of Structural Parameters and Light Radiation in Rice Canopies by the Coupling Model and Remote Sensing,
RS(7), No. 5, 2015, pp. 5203-5221.
DOI Link 1506

Boschetti, M.[Mirco], Nelson, A.[Andrew], Nutini, F.[Francesco], Manfron, G.[Giacinto], Busetto, L.[Lorenzo], Barbieri, M.[Massimo], Laborte, A.[Alice], Raviz, J.[Jeny], Holecz, F.[Francesco], Mabalay, M.R.O.[Mary Rose O.], Bacong, A.P.[Alfie P.], Quilang, E.J.P.[Eduardo Jimmy P.],
Rapid Assessment of Crop Status: An Application of MODIS and SAR Data to Rice Areas in Leyte, Philippines Affected by Typhoon Haiyan,
RS(7), No. 6, 2015, pp. 6535.
DOI Link 1507

Li, S.[Shuo], Ji, W.J.[Wen-Jun], Chen, S.C.[Song-Chao], Peng, J.[Jie], Zhou, Y.[Yin], Shi, Z.[Zhou],
Potential of VIS-NIR-SWIR Spectroscopy from the Chinese Soil Spectral Library for Assessment of Nitrogen Fertilization Rates in the Paddy-Rice Region, China,
RS(7), No. 6, 2015, pp. 7029.
DOI Link 1507

Teluguntla, P.[Pardhasaradhi], Ryu, D.[Dongryeol], George, B.[Biju], Walker, J.P.[Jeffrey P.], Malano, H.M.[Hector M.],
Mapping Flooded Rice Paddies Using Time Series of MODIS Imagery in the Krishna River Basin, India,
RS(7), No. 7, 2015, pp. 8858.
DOI Link 1506

Shi, J.J.[Jing-Jing], Huang, J.F.[Jing-Feng],
Monitoring Spatio-Temporal Distribution of Rice Planting Area in the Yangtze River Delta Region Using MODIS Images,
RS(7), No. 7, 2015, pp. 8883.
DOI Link 1506

Huang, S.[Shanyu], Miao, Y.X.[Yu-Xin], Zhao, G.M.[Guang-Ming], Yuan, F.[Fei], Ma, X.B.[Xiao-Bo], Tan, C.[Chuanxiang], Yu, W.F.[Wei-Feng], Gnyp, M.L.[Martin L.], Lenz-Wiedemann, V.I.S.[Victoria I.S.], Rascher, U.[Uwe], Bareth, G.[Georg],
Satellite Remote Sensing-Based In-Season Diagnosis of Rice Nitrogen Status in Northeast China,
RS(7), No. 8, 2015, pp. 10646.
DOI Link 1509

Yeom, J.M.[Jong-Min], Kim, H.O.[Hyun-Ok],
Comparison of NDVIs from GOCI and MODIS Data towards Improved Assessment of Crop Temporal Dynamics in the Case of Paddy Rice,
RS(7), No. 9, 2015, pp. 11326.
DOI Link 1511

Nguyen, D.B.[Duy Ba], Clauss, K.[Kersten], Cao, S.[Senmao], Naeimi, V.[Vahid], Kuenzer, C.[Claudia], Wagner, W.[Wolfgang],
Mapping Rice Seasonality in the Mekong Delta with Multi-Year Envisat ASAR WSM Data,
RS(7), No. 12, 2015, pp. 15808.
DOI Link 1601

Kwak, Y.J.[Young-Joo], Arifuzzanman, B.[Bhuyan], Iwami, Y.[Yoichi],
Prompt Proxy Mapping of Flood Damaged Rice Fields Using MODIS-Derived Indices,
RS(7), No. 12, 2015, pp. 15805.
DOI Link 1601

Guan, X.D.[Xu-Dong], Huang, C.[Chong], Liu, G.[Gaohuan], Meng, X.L.[Xue-Lian], Liu, Q.S.[Qing-Sheng],
Mapping Rice Cropping Systems in Vietnam Using an NDVI-Based Time-Series Similarity Measurement Based on DTW Distance,
RS(8), No. 1, 2016, pp. 19.
DOI Link 1602

Campos-Taberner, M.[Manuel], García-Haro, F.J.[Franciso Javier], Confalonieri, R.[Roberto], Martínez, B.[Beatriz], Moreno, Á.[Álvaro], Sánchez-Ruiz, S.[Sergio], Gilabert, M.A.[María Amparo], Camacho, F.[Fernando], Boschetti, M.[Mirco], Busetto, L.[Lorenzo],
Multitemporal Monitoring of Plant Area Index in the Valencia Rice District with PocketLAI,
RS(8), No. 3, 2016, pp. 202.
DOI Link 1604

Clauss, K.[Kersten], Yan, H.[Huimin], Kuenzer, C.[Claudia],
Mapping Paddy Rice in China in 2002, 2005, 2010 and 2014 with MODIS Time Series,
RS(8), No. 5, 2016, pp. 434.
DOI Link 1606

Singha, M.[Mrinal], Wu, B.F.[Bing-Fang], Zhang, M.[Miao],
An Object-Based Paddy Rice Classification Using Multi-Spectral Data and Crop Phenology in Assam, Northeast India,
RS(8), No. 6, 2016, pp. 479.
DOI Link 1608

Du, L.[Lin], Shi, S.[Shuo], Yang, J.[Jian], Sun, J.[Jia], Gong, W.[Wei],
Using Different Regression Methods to Estimate Leaf Nitrogen Content in Rice by Fusing Hyperspectral LiDAR Data and Laser-Induced Chlorophyll Fluorescence Data,
RS(8), No. 6, 2016, pp. 526.
DOI Link 1608

Sun, J.[Jia], Yang, J.[Jian], Shi, S.[Shuo], Chen, B.[Biwu], Du, L.[Lin], Gong, W.[Wei], Song, S.[Shalei],
Estimating Rice Leaf Nitrogen Concentration: Influence of Regression Algorithms Based on Passive and Active Leaf Reflectance,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link 1711

Du, L.[Lin], Shi, S.[Shuo], Gong, W.[Wei], Yang, J.[Jian], Sun, J.[Jia], Mao, F.Y.[Fei-Yue],
Wavelength Selection Of Hyperspectral Lidar Based On Feature Weighting For Estimation Of Leaf Nitrogen Content In Rice,
ISPRS16(B1: 9-13).
DOI Link 1610

Liu, Y., Chen, K.S., Xu, P., Li, Z.L.,
Modeling and Characteristics of Microwave Backscattering From Rice Canopy Over Growth Stages,
GeoRS(54), No. 11, November 2016, pp. 6757-6770.
Agriculture BibRef

Dong, J.[Jinwei], Xiao, X.[Xiangming],
Evolution of regional to global paddy rice mapping methods: A review,
PandRS(119), No. 1, 2016, pp. 214-227.
Elsevier DOI 1610
Paddy rice mapping BibRef

Yang, Z.[Zhi], Li, K.[Kun], Shao, Y.[Yun], Brisco, B.[Brian], Liu, L.[Long],
Estimation of Paddy Rice Variables with a Modified Water Cloud Model and Improved Polarimetric Decomposition Using Multi-Temporal RADARSAT-2 Images,
RS(8), No. 10, 2016, pp. 878.
DOI Link 1609

Moharana, S.[Shreedevi], Dutta, S.[Subashisa],
Spatial variability of chlorophyll and nitrogen content of rice from hyperspectral imagery,
PandRS(122), No. 1, 2016, pp. 17-29.
Elsevier DOI 1612
Rice BibRef

Wang, J.[Jing], Huang, J.F.[Jing-Feng], Gao, P.[Ping], Wei, C.[Chuanwen], Mansaray, L.R.[Lamin R.],
Dynamic Mapping of Rice Growth Parameters Using HJ-1 CCD Time Series Data,
RS(8), No. 11, 2016, pp. 931.
DOI Link 1612
And: Correction: RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703

Lee, B.[Bora], Kwon, H.[Hyojung], Miyata, A.[Akira], Lindner, S.[Steve], Tenhunen, J.[John],
Evaluation of a Phenology-Dependent Response Method for Estimating Leaf Area Index of Rice Across Climate Gradients,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702

Naito, H.[Hiroki], Ogawa, S.[Satoshi], Valencia, M.O.[Milton Orlando], Mohri, H.[Hiroki], Urano, Y.[Yutaka], Hosoi, F.[Fumiki], Shimizu, Y.[Yo], Chavez, A.L.[Alba Lucia], Ishitani, M.[Manabu], Selvaraj, M.G.[Michael Gomez], Omasa, K.[Kenji],
Estimating rice yield related traits and quantitative trait loci analysis under different nitrogen treatments using a simple tower-based field phenotyping system with modified single-lens reflex cameras,
PandRS(125), No. 1, 2017, pp. 50-62.
Elsevier DOI 1703
Breeding BibRef

Torbick, N.[Nathan], Chowdhury, D.[Diya], Salas, W.[William], Qi, J.[Jiaguo],
Monitoring Rice Agriculture across Myanmar Using Time Series Sentinel-1 Assisted by Landsat-8 and PALSAR-2,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703

Huang, S.[Shanyu], Miao, Y.[Yuxin], Yuan, F.[Fei], Gnyp, M.L.[Martin L.], Yao, Y.[Yinkun], Cao, Q.[Qiang], Wang, H.[Hongye], Lenz-Wiedemann, V.I.S.[Victoria I. S.], Bareth, G.[Georg],
Potential of RapidEye and WorldView-2 Satellite Data for Improving Rice Nitrogen Status Monitoring at Different Growth Stages,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704

Campos-Taberner, M.[Manuel], García-Haro, F.J.[Francisco Javier], Camps-Valls, G.[Gustau], Grau-Muedra, G.[Gonçal], Nutini, F.[Francesco], Busetto, L.[Lorenzo], Katsantonis, D.[Dimitrios], Stavrakoudis, D.[Dimitris], Minakou, C.[Chara], Gatti, L.[Luca], Barbieri, M.[Massimo], Holecz, F.[Francesco], Stroppiana, D.[Daniela], Boschetti, M.[Mirco],
Exploitation of SAR and Optical Sentinel Data to Detect Rice Crop and Estimate Seasonal Dynamics of Leaf Area Index,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704

Mansaray, L.R.[Lamin R.], Huang, W.[Weijiao], Zhang, D.[Dongdong], Huang, J.[Jingfeng], Li, J.[Jun],
Mapping Rice Fields in Urban Shanghai, Southeast China, Using Sentinel-1A and Landsat 8 Datasets,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704

Arii, M., Yamada, H., Kobayashi, T., Kojima, S., Umehara, T., Komatsu, T., Nishimura, T.,
Theoretical Characterization of X-Band Multiincidence Angle and Multipolarimetric SAR Data From Rice Paddies at Late Vegetative Stage,
GeoRS(55), No. 5, May 2017, pp. 2706-2715.
geophysical techniques, radar polarimetry, synthetic aperture radar, vegetation, Japan, MIMP SAR observation, Niigata City, Pi-SAR2, SAR, X-band multiincidence angle, X-band polarimetric-interferometric SAR 2, discrete scatterer model, late vegetative stage, multiincidence angle-multipolarimetric, multipolarimetric SAR data, polarimetric decomposition techniques, radar backscatter, rice paddies, scattering mechanism, synthetic aperture radar, vegetation structure, volume scattering, Backscatter, Radar polarimetry, Scattering, Spaceborne radar, Synthetic aperture radar, Vegetation mapping, Multiincidence angle and multipolarimetric synthetic aperture radar (MIMP SAR), rice paddies BibRef

Yuzugullu, O.[Onur], Marelli, S.[Stefano], Erten, E.[Esra], Sudret, B.[Bruno], Hajnsek, I.[Irena],
Determining Rice Growth Stage with X-Band SAR: A Metamodel Based Inversion,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link 1706

Zhou, G.X.[Gao-Xiang], Liu, X.[Xiangnan], Zhao, S.[Shuang], Liu, M.[Ming], Wu, L.[Ling],
Estimating FAPAR of Rice Growth Period Using Radiation Transfer Model Coupled with the WOFOST Model for Analyzing Heavy Metal Stress,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link 1706

Yang, M.D.[Ming-Der], Huang, K.S.[Kai-Siang], Kuo, Y.H.[Yi-Hsuan], Tsai, H.P.[Hui Ping], Lin, L.M.[Liang-Mao],
Spatial and Spectral Hybrid Image Classification for Rice Lodging Assessment through UAV Imagery,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706

Zhou, X., Zheng, H.B., Xu, X.Q., He, J.Y., Ge, X.K., Yao, X., Cheng, T., Zhu, Y., Cao, W.X., Tian, Y.C.,
Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery,
PandRS(130), No. 1, 2017, pp. 246-255.
Elsevier DOI 1708
UAVs BibRef

Granell, C.[Carlos], Miralles, I.[Ignacio], Rodríguez-Pupo, L.E.[Luis E.], González-Pérez, A.[Alberto], Casteleyn, S.[Sven], Busetto, L.[Lorenzo], Pepe, M.[Monica], Boschetti, M.[Mirco], Huerta, J.[Joaquín],
Conceptual Architecture and Service-Oriented Implementation of a Regional Geoportal for Rice Monitoring,
IJGI(6), No. 7, 2017, pp. xx-yy.
DOI Link 1708

Liu, L., Shao, Y., Pinel, N., Li, K., Yang, Z., Gong, H., Wang, Y.,
Modeling Microwave Backscattering From Parabolic Rice Leaves,
GeoRS(55), No. 11, November 2017, pp. 6044-6053.
Computational modeling, Mathematical model, Microwave FET integrated circuits, Spaceborne radar, Discrete dipole approximation (DDA), BibRef

Saberioon, M.M., Gholizadeh, A.,
Novel Approach For Estimating Nitrogen Content In Paddy Fields Using Low Altitude Remote Sensing System,
ISPRS16(B1: 1011-1015).
DOI Link 1610

Yamada, Y.,
Crop Species Recognition And Discrimination Paddy-rice-growingfields From Reaped-fields By The Radar Vegetation Index (rvi) Of Alos-2/palsar2,
ISPRS16(B8: 1083-1087).
DOI Link 1610

Kimura, A., Kondo, A., Mochizuki, K.,
A Study on the SAR Data Observation Time For The Classification Of Planting Condition Of Paddy Fields,
ISPRS16(B8: 927-930).
DOI Link 1610

Willkomm, M., Bolten, A., Bareth, G.,
Non-destructive Monitoring Of Rice By Hyperspectral In-field Spectrometry And Uav-based Remote Sensing: Case Study Of Field-grown Rice In North Rhine-westphalia, Germany,
ISPRS16(B1: 1071-1077).
DOI Link 1610

Wang, P., Huang, F., Liu, X.N.,
A Simple Interpretation Of The Rice Spectral Indices Space For Assessment Of Heavy Metal Stress,
ISPRS16(B7: 129-135).
DOI Link 1610

Chen, C.F., Son, N.T., Chen, C.R., Chang, L.Y., Chiang, S.H.,
Rice Crop Mapping Using Sentinel-1a Phenological Metrics,
ISPRS16(B8: 863-865).
DOI Link 1610

Son, N.T., Chen, C.F., Chen, C.R., Chang, L.Y., Chiang, S.H.,
Rice Yield Estimation Through Assimilating Satellite Data Into A Crop Simumlation Model,
ISPRS16(B8: 993-996).
DOI Link 1610

Elshorbagy, A.M., Imam, E.H., Nour, M.H.,
Rice Area Inter Annual Variation through a Remote Sensing Based Mapping Algorithm,
DOI Link 1402

Hashjin, S.S.[S. Sharifi], Darvishzadeh, R., Khandan, R.,
A Study toward the Evaluation of ALOS Images for LAI Estimation in Rice Fields,
HTML Version. 1311

Bendig, J., Willkomm, M., Tilly, N., Gnyp, M.L., Bennertz, S., Qiang, C., Miao, Y., Lenz-Wiedemann, V.I.S., Bareth, G.,
Very high resolution crop surface models (CSMs) from UAV-based stereo images for rice growth monitoring In Northeast China,
HTML Version. 1311

Tilly, N., Hoffmeister, D., Liang, H., Cao, Q., Liu, Y., Lenz-Wiedemann, V., Miao, Y., Bareth, G.,
Evaluation of Terrestrial Laser Scanning for Rice Growth Monitoring,
DOI Link 1209

Wu, L.[Ling], Liu, X.[Xiangnan], Liu, M.[Meiling],
Analysis of the fractal characteristic of the hyperspectral curves of the rice under plumbum pollution stress,

Sarkar, S.[Subrata], Bhattacharyya, N.[Nabarun], Mukherjee, S.[Subhankar],
Determination of Amylose content in rice using electronic tongue,

Zhou, Y.F.[Ying-Feng], Wang, Y.M.[Ya-Ming], Yao, Q.[Qing],
Segmentation of rice disease spots based on improved BPNN,

Li, M.W.[Ming-Wei], Zhang, W.[Wei],
Research and Implement of Head Milled Rice Detection High-Speed Algorithm Based on FPGA,

Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
Wheat Crop Analysis, Production, Detection, Health, Change .

Last update:Feb 26, 2018 at 13:41:56