Understanding wheat lodging using multi-temporal Sentinel-1 and Sentinel-2 data
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Mirco Boschetti | Roshanak Darvishzadeh | Andrew Nelson | Sugandh Chauhan | Yi Lu | R. Darvishzadeh | M. Boschetti | S. Chauhan | A. Nelson | Yi Lu
[1] David P. Roy,et al. The Global Availability of Landsat 5 TM and Landsat 7 ETM+ Land Surface Observations and Implications for Global 30m Landsat Data Product Generation , 2013 .
[2] T. Faurtyot. Vegetation water and dry matter contents estimated from top-of-the-atmosphere reflectance data: A simulation study , 1997 .
[3] Francisco Ceballos,et al. The Feasibility of Picture-Based Insurance (PBI): Smartphone Pictures for Affordable Crop Insurance , 2018, Development Engineering.
[4] C. W. Wood,et al. Relationships between chlorophyll meter readings and leaf chlorophyll concentration, N status, and crop yield: A review 1 , 1993 .
[5] Thomas W. MacFarland,et al. Kruskal–Wallis H-Test for Oneway Analysis of Variance (ANOVA) by Ranks , 2016 .
[6] Mirco Boschetti,et al. Estimation of crop angle of inclination for lodged wheat using multi-sensor SAR data , 2020 .
[7] W. Kruskal,et al. Use of Ranks in One-Criterion Variance Analysis , 1952 .
[8] Mirco Boschetti,et al. Remote sensing-based crop lodging assessment: Current status and perspectives , 2019, ISPRS Journal of Photogrammetry and Remote Sensing.
[9] A. R. Ennos,et al. Understanding and Reducing Lodging in Cereals , 2004 .
[10] Maurice Borgeaud,et al. The use of ERS-1/2 Tandem interferometric coherence in the estimation of agricultural crop heights , 2001, IEEE Trans. Geosci. Remote. Sens..
[11] Ghislain Picard,et al. A Multiple Scattering Model for C-Band Backscatter of Wheat Canopies , 2002 .
[12] R. Todd Ogden,et al. Functional regression in crop lodging assessment with digital images , 2002 .
[13] Clive H. Bock,et al. Plant Disease Severity Estimated Visually, by Digital Photography and Image Analysis, and by Hyperspectral Imaging , 2010 .
[14] Andrew K. Skidmore,et al. Effects of Canopy Structural Variables on Retrieval of Leaf Dry Matter Content and Specific Leaf Area From Remotely Sensed Data , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[15] Guijun Yang,et al. Monitoring model of corn lodging based on Sentinel-1 radar image , 2017, 2017 SAR in Big Data Era: Models, Methods and Applications (BIGSARDATA).
[16] T. Alberda. Crop photosynthesis : methods and compilation of data obtained with a mobile field equipment , 1977 .
[17] Hong Sun,et al. [The spectral characteristics and chlorophyll content at winter wheat growth stages]. , 2010, Guang pu xue yu guang pu fen xi = Guang pu.
[18] Daniela Stroppiana,et al. WHEAT LODGING ASSESSMENT USING MULTISPECTRAL UAV DATA , 2019, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences.
[19] Marco Heurich,et al. Mapping leaf chlorophyll content from Sentinel-2 and RapidEye data in spruce stands using the invertible forest reflectance model , 2019, Int. J. Appl. Earth Obs. Geoinformation.
[20] Irena Hajnsek,et al. On the potential of Polarimetric SAR Interferometry to characterize the biomass, moisture and structure of agricultural crops at L-, C- and X-Bands , 2018 .
[21] Brian O'Connor,et al. Analysis of Sentinel-2 and RapidEye for Retrieval of Leaf Area Index in a Saltmarsh Using a Radiative Transfer Model , 2019, Remote. Sens..
[22] N. Bunnik. The multispectral reflectance of shortwave radiation by agricultural crops in relation with their morphological and optical properties , 1978 .
[23] Donald G. Bullock,et al. Evaluation of the Minolta SPAD-502 chlorophyll meter for nitrogen management in corn , 1998 .
[24] Camilla Brekke,et al. Effect of wind direction and incidence angle on polarimetric SAR observations of slicked and unslicked sea surfaces , 2018, Remote Sensing of Environment.
[25] R. J. Brown,et al. The effect of dew on the use of RADARSAT-1 for crop monitoring: Choosing between ascending and descending orbits , 2002 .
[26] J. Kong,et al. Theory of microwave remote sensing , 1985 .
[27] M. A. Moreira,et al. Hyperspectral field reflectance measurements to estimate wheat grain yield and plant height , 2006 .
[28] Yuri A. Gritz,et al. Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. , 2003, Journal of plant physiology.
[29] Stefano Pignatti,et al. Wheat lodging monitoring using polarimetric index from RADARSAT-2 data , 2015, Int. J. Appl. Earth Obs. Geoinformation.
[30] Guijun Yang,et al. Monitoring of maize lodging using multi-temporal Sentinel-1 SAR data , 2020 .
[31] Chunyan Li,et al. Effect of nitrogen levels and nitrogen ratios on lodging resistance and yield potential of winter wheat (Triticum aestivum L.) , 2017, PloS one.
[32] R. Clark,et al. Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications , 1984 .
[33] S. C. Tripathi,et al. Planting Systems on Lodging Behavior, Yield Components, and Yield of Irrigated Spring Bread Wheat , 2005 .
[34] B. Bouman,et al. Crop parameter estimation from ground-based x-band (3-cm wave) radar backscattering data , 1991 .
[35] Hong Chun Zhu,et al. The Extraction of Wheat Lodging Area in UAV’s Image Used Spectral and Texture Features , 2014 .
[36] Clement Atzberger,et al. Estimation of vegetation LAI from hyperspectral reflectance data: Effects of soil type and plant architecture , 2008, Int. J. Appl. Earth Obs. Geoinformation.
[37] Lingli Zhao,et al. Characterizing Lodging Damage in Wheat and Canola Using Radarsat-2 Polarimetric SAR Data , 2017 .
[38] Simonetta Paloscia,et al. The relationship between the backscattering coefficient and the biomass of narrow and broad leaf crops , 2001, IEEE Trans. Geosci. Remote. Sens..
[39] Mirco Boschetti,et al. Discriminant analysis for lodging severity classification in wheat using RADARSAT-2 and Sentinel-1 data , 2020, ISPRS Journal of Photogrammetry and Remote Sensing.
[40] R. A. Fischer,et al. Lodging effects on high-yielding crops of irrigated semidwarf wheat , 1987 .
[41] R. W. Leamer,et al. Reflectance of Wheat Cultivars as Related to Physiological Growth Stages1 , 1980 .
[42] Jai Singh Parihar,et al. Comparison of Two Data Smoothing Techniques for Vegetation Spectra Derived From EO-1 Hyperion , 2011 .
[43] Yann Kerr,et al. Comparison of ERS-2 SAR and Landsat TM imagery for monitoring agricultural crop and soil conditions , 2002 .
[44] R. Clark,et al. Spectroscopic Determination of Leaf Biochemistry Using Band-Depth Analysis of Absorption Features and Stepwise Multiple Linear Regression , 1999 .
[45] H.W.J. van Kasteren,et al. Ground-based X-band (3-cm wave) radar backscattering of agricultural crops. I. Sugar beet and potato; backscattering and crop growth , 1990 .
[46] Deborah Bentivoglio,et al. Technological clusters as a hub for the innovation: from the theoretical model to an Italian regional case study in the agrifood sector , 2017 .
[47] Luca Gatti,et al. Towards an Operational SAR-Based Rice Monitoring System in Asia: Examples from 13 Demonstration Sites across Asia in the RIICE Project , 2014, Remote. Sens..
[48] Paris W. Vachon,et al. Coherence estimation for SAR imagery , 1999, IEEE Trans. Geosci. Remote. Sens..
[49] R. Munns,et al. Factors affecting CO2 assimilation, leaf injury and growth in salt-stressed durum wheat. , 2002, Functional plant biology : FPB.
[50] Jinsong Chen,et al. Potential of RADARSAT-2 data on identifying sugarcane lodging caused by typhoon , 2016, 2016 Fifth International Conference on Agro-Geoinformatics (Agro-Geoinformatics).
[51] X. Chang,et al. Effect of dose and timing of application of different plant growth regulators on lodging and grain yield of a Scottish landrace of barley (Bere) in Orkney, Scotland , 2017 .