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Author: Quiróz, R.

  • Author: Mares, V.
  • Author: Carbajal, M.
  • Author: Rolando, J.L.
  • Author: Zorogastua, P.
  • Author: Dubeux, J.C.
  • Author: Ruíz Moreno, M.
  • Author: Arya, S.
  • Author: Chamorro, A.
  • Author: Comerford, N.
  • Author: De Mendiburu, F.
  • Author: García, S.
  • Author: Gumucio, Tatiana
  • Author: Haan, Nicoline C. de
  • Author: Kadian, M.S.
  • Author: Konkel, J.
  • Author: Kumar, S.
  • Author: Mango, Nelson
  • Author: Mapedza, Everisto D.
  • Author: Martínez Barón, Deissy
  • Author: Mendiburu, F. de
  • Author: Monerris, J.
  • Author: Ninanya, J.
  • Author: Pérez, W.
  • Author: Quiroz, R.
  • Author: Rana, R.K.
  • Author: Rinza, J.
  • Author: Schaeffer, S.
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  • Explore related channels
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    Remote Sensing and Artificial Intelligence for Soil Organic Carbon Geospatial Modeling
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    Key ecosystem services and ecological intensification of agriculture in the tropical high-Andean Puna as affected by land-use and climate changes
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    Soil organic carbon stocks and fractionation under different land uses in the Peruvian high-Andean Puna
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    SWOT analysis of potato cultivation under arid conditions in western Rajasthan (India).
  • Quick Look
    Land use effects on soil fertility and nutrient cycling in the Peruvian High-Andean puna grasslands

Author: Ramírez, D.

  • Author: Mares, V.
  • Author: Carbajal, M.
  • Author: Rolando, J.L.
  • Author: Zorogastua, P.
  • Author: Dubeux, J.C.
  • Author: Ruíz Moreno, M.
  • Author: Arya, S.
  • Author: Chamorro, A.
  • Author: Comerford, N.
  • Author: De Mendiburu, F.
  • Author: García, S.
  • Author: Gumucio, Tatiana
  • Author: Haan, Nicoline C. de
  • Author: Kadian, M.S.
  • Author: Konkel, J.
  • Author: Kumar, S.
  • Author: Mango, Nelson
  • Author: Mapedza, Everisto D.
  • Author: Martínez Barón, Deissy
  • Author: Mendiburu, F. de
  • Author: Monerris, J.
  • Author: Ninanya, J.
  • Author: Pérez, W.
  • Author: Quiroz, R.
  • Author: Rana, R.K.
  • Author: Rinza, J.
  • Author: Schaeffer, S.
  • Show items as search results
  • Explore related channels
  • Quick Look
    Remote Sensing and Artificial Intelligence for Soil Organic Carbon Geospatial Modeling
  • Quick Look
    From Rangelands to Cropland, Land-Use Change and its impact on soil organic carbon variables in a Peruvian Andean Highlands: A Machine Learning Modeling approach
  • Quick Look
    Key ecosystem services and ecological intensification of agriculture in the tropical high-Andean Puna as affected by land-use and climate changes
  • Quick Look
    Soil organic carbon stocks and fractionation under different land uses in the Peruvian high-Andean Puna
  • Quick Look
    Land use effects on soil fertility and nutrient cycling in the Peruvian High-Andean puna grasslands

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    From rangelands to cropland, land-use change and its impact on soil organic carbon variables in a Peruvian Andean highlands: a machine learning modeling approach
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    Modelling the impacts of organic matter quality on soil carbon turnover and storage
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    Remote sensing of soil salinity mapping: status and potential
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    Irrigation performance using hydrological and remote sensing modeling
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    Utilizing Artificial Intelligence and Remote Sensing to Detect Prosopis juliflora Invasion: Environmental Drivers and Community Insights in Rangelands of Kenya
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    Integrating spatial statistics and remote sensing
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    An artificial neural network model for simulating streamflow using remote sensing data
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    Watershed scale soil moisture estimation model using machine learning and remote sensing in a data-scarce context
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    Evaluating the impacts of watershed rehabilitation and irrigation interventions on vegetation greenness and soil erosion using remote sensing and biophysical modelling in Feresmay watershed in Ethiopia
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    An equivalent soil mass procedure for monitoring soil organic carbon in multiple soil layers
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    Modelling the role of algae in rice crop nutrition and soil organic carbon maintenance
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    Vulnerability of landscape patterns from a multidisciplinary approach based on remote sensing and GIS in two agroecologies of Mali
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    Multicriteria evaluation and remote sensing approach to identifying degraded soil areas in northwest Peru

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    Digital soil mapping of metals and metalloids in croplands using multiple geospatial data and machine learning, implemented in GEE, for the Peruvian Mantaro Valley
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    An unmanned aerial vehicle (UAV) technology for estimating leaf N content in rice crops, from multispectral imagery
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    Comparative analysis of modified partial least squares regression and hybrid deep learning models for predicting protein content in Perilla (Perilla frutescens L.) seed meal using NIR spectroscopy
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    Integrating Earth Observation, Machine Learning and Citizen Science to Map Prosopis juliflora Invasion in Semi-Arid Rangelands of Kenya
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    Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands
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    Tracking Rangeland Degradation from Prosopis Invasion in Kenyan Rangeland: A Multi-Source Approach Combining Remote Sensing, Machine Learning and Citizen Science
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    Data-driven hydrological discharge simulation in the Limpopo River Basin for transboundary water management
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    Artificial neural network model for forecasting future ainfall scenario of Jharkhand state of India
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    ​​Configuration of the deep neural network hyperparameters for the hypsometric modeling of the Guazuma crinita Mart. in the Peruvian Amazon​
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    MusaDeepMosaic: Development of a machine learning genomic mosaic classifier tool.
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