Evaluation of Landsat 8 image pansharpening in estimating soil organic matter using multiple linear regression and artificial neural networks-Reference-Cited by-同舟云学术

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Evaluation of Landsat 8 image pansharpening in estimating soil organic matter using multiple linear regression and artificial neural networks

Published:2022-02-15 Issue:3 Volume:25 Page:353-364
ISSN:1009-5020
Container-title:Geo-spatial Information Science
language:en
Short-container-title:Geo-spatial Information Science

Author:

Bouasria Abdelkrim¹²^ORCID,Ibno Namr Khalid¹,Rahimi Abdelmejid¹,Ettachfini El Mostafa¹,Rerhou Badr²³

Affiliation:

1. Faculty of Sciences, Chouaib Doukkali University, El Jadida, Morocco

2. Agricultural Development Department, Doukkala Regional Agricultural Development Office, El Jadida, Morocco

3. Soil Science Department, Hassan II Agronomic and Veterinary Institute, Rabat, Morocco

Publisher

Informa UK Limited

Subject

Computers in Earth Sciences,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10095020.2022.2026743

Reference73 articles.

1. Land use change effects on soil quality and biological fertility: A case study in northern Iran

2. Land Resources Monitoring, Modeling, and Mapping with Remote Sensing

3. MODTRAN4 radiative transfer modeling for atmospheric correction

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1. Applications and challenges of digital soil mapping in Africa;Geoderma;2024-09

2. Development of an Imaging Spectrometer with a High Signal-to-Noise Ratio Based on High Energy Transmission Efficiency for Soil Organic Matter Detection;Sensors;2024-07-05

3. Soil organic carbon exchange due to the change in land use;Environmental and Ecological Statistics;2024-06-07

4. Synergistic Use of Multi-Temporal Radar and Optical Remote Sensing for Soil Organic Carbon Prediction;Remote Sensing;2024-05-24

5. Mapping Soil Organic Matter Under Field Conditions;IEEE Transactions on AgriFood Electronics;2024-03

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