Prediction of topsoil properties at field-scale by using C-band SAR data
暂无分享,去创建一个
Marisa B. Domenech | Nilda M. Amiotti | José Luis Costa | Mauricio Castro Franco | J. Costa | N. M. Amiotti | Marisa B. Domenech | M. C. Franco
[1] P. Levelt,et al. ESA's sentinel missions in support of Earth system science , 2012 .
[2] Victor O. Sadras,et al. Quantification of grain yield response to soil depth in Soybean, Maize, Sunflower, and Wheat , 2001 .
[3] Christoph Rüdiger,et al. Sensitivity of Sentinel-1 Backscatter to Vegetation Dynamics: An Austrian Case Study , 2018, Remote. Sens..
[4] Á. Cabrera,et al. Flora de la Provincia de Buenos Aires , 1972 .
[5] Kenneth A. Sudduth,et al. Comparison of sensors and techniques for crop yield mapping , 1996 .
[6] Philippe Lagacherie,et al. Digital soil mapping : an introductory perspective , 2007 .
[7] Yang Song,et al. Mapping Winter Wheat Planting Area and Monitoring Its Phenology Using Sentinel-1 Backscatter Time Series , 2019, Remote. Sens..
[8] Armando Apan,et al. Identifying the spatial variability of soil constraints using multi-year remote sensing , 2011 .
[9] José Luis Costa,et al. Sampling scheme optimization to map soil depth to petrocalcic horizon at field scale , 2017 .
[10] P. Diggle,et al. Model‐based geostatistics , 2007 .
[11] Gustavo A. Slafer,et al. Wheat production systems of the Pampas. , 1999 .
[12] R. Alvarez. Predicting average regional yield and production of wheat in the Argentine Pampas by an artificial neural network approach , 2009 .
[13] Dennis L. Corwin,et al. Characterizing soil spatial variability with apparent soil electrical conductivity , 2005 .
[14] Rémy Fieuzal,et al. Estimation of soybean yield from assimilated optical and radar data into a simplified agrometeorological model , 2015, 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
[15] Michael Dixon,et al. Google Earth Engine: Planetary-scale geospatial analysis for everyone , 2017 .
[16] Mehrez Zribi,et al. Retrieval of Both Soil Moisture and Texture Using TerraSAR-X Images , 2015, Remote. Sens..
[17] Gilbert Wooding Robinson,et al. A new method for the mechanical analysis of soils and other dispersions , 1922, The Journal of Agricultural Science.
[18] L. S. Pereira,et al. Crop evapotranspiration : guidelines for computing crop water requirements , 1998 .
[19] J. Campbell,et al. Remote sensing of crop residue and tillage practices: Present capabilities and future prospects , 2014 .
[20] B. Brisco,et al. The effect of soil and crop residue characteristics on polarimetric radar response , 2002 .
[21] U. Grömping. Dependence of Variable Importance in Random Forests on the Shape of the Regressor Space , 2009 .
[22] D. Corwin,et al. Application of Soil Electrical Conductivity to Precision Agriculture , 2003 .
[23] R. D. Ramsey,et al. Landsat Spectral Data for Digital Soil Mapping , 2008 .
[24] Alexandre Bouvet,et al. Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications , 2017 .
[25] Alfred E. Hartemink,et al. Digital Soil Mapping with Limited Data , 2008 .
[26] B. Huwe,et al. Uncertainty in the spatial prediction of soil texture: Comparison of regression tree and Random Forest models , 2012 .
[27] Farshid Vahedifard,et al. Investigating the correlation between radar backscatter and in situ soil property measurements , 2017, Int. J. Appl. Earth Obs. Geoinformation.
[28] Alfred E. Hartemink,et al. Digital Soil Mapping: Bridging Research, Production, and Environmental Application , 2010 .
[29] Andy Liaw,et al. Classification and Regression by randomForest , 2007 .
[30] M. Barral,et al. Land-use planning based on ecosystem service assessment: A case study in the Southeast Pampas of Argentina , 2012 .
[31] G. Gee,et al. Particle-size Analysis , 2018, SSSA Book Series.
[32] J. Wolf,et al. Yield gap analysis with local to global relevance—A review , 2013 .
[33] Shoba Periasamy,et al. Significance of dual polarimetric synthetic aperture radar in biomass retrieval: An attempt on Sentinel-1 , 2018, Remote Sensing of Environment.
[34] Mehrez Zribi,et al. Soil Texture Estimation Over a Semiarid Area Using TerraSAR-X Radar Data , 2012, IEEE Geoscience and Remote Sensing Letters.
[35] Budiman Minasny,et al. A conditioned Latin hypercube method for sampling in the presence of ancillary information , 2006, Comput. Geosci..
[36] Claude R. Duguay,et al. Defining the Sensitivity of Multi-Frequency and Multi-Polarized Radar Backscatter to Post-Harvest Crop Residue , 2001 .
[37] Heather McNairn,et al. A Review of Multitemporal Synthetic Aperture Radar (SAR) for Crop Monitoring , 2016 .
[38] Nahuel Raúl Peralta,et al. Prediction of Soil Properties at Farm Scale Using a Model-Based Soil Sampling Scheme and Random Forest , 2015 .
[39] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[40] Shaun Quegan,et al. High-resolution measurements of scattering in wheat canopies-implications for crop parameter retrieval , 2003, IEEE Trans. Geosci. Remote. Sens..
[41] Thuy Le Toan,et al. Multitemporal C-band radar measurements on wheat fields , 2003, IEEE Trans. Geosci. Remote. Sens..
[42] Pierre Roudier,et al. A conditioned Latin hypercube sampling algorithm incorporating operational constraints , 2012 .
[43] Heather McNairn,et al. Early season monitoring of corn and soybeans with TerraSAR-X and RADARSAT-2 , 2014, Int. J. Appl. Earth Obs. Geoinformation.
[44] Andrej Ceglar,et al. Detecting flowering phenology in oil seed rape parcels with Sentinel-1 and -2 time series , 2020, Remote sensing of environment.
[45] D. Lobell,et al. A scalable satellite-based crop yield mapper , 2015 .
[46] José Luis Costa,et al. A spatial dataset of topsoil texture for the southern Argentine Pampas , 2018 .
[47] David Clifford,et al. The Australian three-dimensional soil grid: Australia’s contribution to the GlobalSoilMap project , 2015 .
[48] R. Lavado,et al. Climate, organic matter and clay content relationships in the Pampa and Chaco soils, Argentina , 1998 .
[49] Jean-Michel Poggi,et al. Variable selection using random forests , 2010, Pattern Recognit. Lett..
[50] F. J. Kriegler,et al. Preprocessing Transformations and Their Effects on Multispectral Recognition , 1969 .
[51] Fernando R. Momo,et al. Changes in Average Annual Precipitation in Argentina’s Pampa Region and Their Possible Causes , 2015 .