Soil organic carbon mapping using remote sensing techniques and multivariate regression model-Reference-Cited by-同舟云学术

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Soil organic carbon mapping using remote sensing techniques and multivariate regression model

Published:2017-09-29 Issue:2 Volume:34 Page:215-226
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Bhunia Gouri Sankar¹,Kumar Shit Pravat²,Pourghasemi Hamid Reza³

Affiliation:

1. Aarvee Associates Architects, Engineers & Consultants Pvt Ltd, Hyderabad, India

2. Department of Geography, Raja N.L. Khan Women’s College, Medinipur, India

3. Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2017.1381179

Reference37 articles.

1. Digital soil mapping at pilot sites in the northwest coast of Egypt: A multinomial logistic regression approach

2. Linear Relationship between CO2 Emissions and Economic Variables: Evidence from a Developed Country and a Developing Country

3. Detection of soil crusting risks related to low soil organic carbon contents by using Discriminant analysis on thematic Mapper data

4. Comparison between detailed digital and conventional soil maps of an area with complex geology

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1. A Review Of Soil Organic Carbon (SOC) Prediction Techniques In Agricultural Lands Using Remote Sensing;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

2. Remote sensing, artificial neural networks, and spatial interpolation methods for modelling soil chemical characteristics;Modeling Earth Systems and Environment;2024-06-04

3. Soil organic carbon pool in diverse land utilization patterns in North-East India: an implication for carbon sequestration;Environment, Development and Sustainability;2024-05-27

4. Assessing uncertainties and discrepancies in agricultural greenhouse gas emissions estimation in China: A comprehensive review;Environmental Impact Assessment Review;2024-05

5. Downscaling SMAP soil moisture product in cold and arid region: Incorporating NDSI and BSI into the random forest algorithm;Vadose Zone Journal;2024-03-20

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