Prediction of soil properties using imaging spectroscopy: Considering fractional vegetation cover to improve accuracy-Reference-Cited by-同舟云学术

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Prediction of soil properties using imaging spectroscopy: Considering fractional vegetation cover to improve accuracy

Published:2015-06 Issue: Volume:38 Page:358-370
ISSN:0303-2434
Container-title:International Journal of Applied Earth Observation and Geoinformation
language:en
Short-container-title:International Journal of Applied Earth Observation and Geoinformation

Author:

Franceschini M.H.D.,Demattê J.A.M.,da Silva Terra F.,Vicente L.E.,Bartholomeus H.,de Souza Filho C.R.

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Earth-Surface Processes,Global and Planetary Change

Reference66 articles.

1. Köppen’s climate classification map for Brazil;Alvares;Meteorol. Z.,2013

2. Determining iron content in Mediterranean soils in partly vegetated areas, using spectral reflectance and imaging spectroscopy;Bartholomeus;Int. J. Appl. Earth Observ. Geoinf.,2007

3. Soil organic carbon mapping of partially vegetated agricultural fields with imaging spectroscopy;Bartholomeus;Int. J. Appl. Earth Observ. Geoinf.,2011

4. Reflectance properties of soils;Baumgardner;Adv. Agron.,1985

5. Carbon sequestration in two Brazilian cerrado soils under no-till;Bayer;Soil Till. Res.,2006

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2. Adapting Prediction Models to Bare Soil Fractional Cover for Extending Topsoil Clay Content Mapping Based on AVIRIS-NG Hyperspectral Data;Remote Sensing;2024-03-18

3. Using Machine-Learning Algorithms to Predict Soil Organic Carbon Content from Combined Remote Sensing Imagery and Laboratory Vis-NIR Spectral Datasets;Remote Sensing;2023-08-30

4. Estimation of soil and crop residue parameters using AVIRIS-NG hyperspectral data;International Journal of Remote Sensing;2023-03-19

5. Improving soil organic carbon predictions from a Sentinel–2 soil composite by assessing surface conditions and uncertainties;Geoderma;2023-01

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