Understanding root-zone soil moisture in agricultural regions of Central Mexico using the ensemble Kalman filter, satellite-derived information, and the THEXMEX-18 dataset-Reference-Cited by-同舟云学术

Understanding root-zone soil moisture in agricultural regions of Central Mexico using the ensemble Kalman filter, satellite-derived information, and the THEXMEX-18 dataset

Published:2022-02-04 Issue:1 Volume:15 Page:52-78
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Huerta-Bátiz Héctor Ernesto¹^ORCID,Constantino-Recillas Daniel Enrique¹²³^ORCID,Monsiváis-Huertero Alejandro¹^ORCID,Hernández-Sánchez Juan Carlos¹²^ORCID,Judge Jasmeet⁴^ORCID,Aparicio-García Ramón Sidonio¹^ORCID

Affiliation:

1. Escuela Superior de Ingeniería Mecánica y Eléctrica Unidad Ticomán, Instituto Politécnico Nacional, Mexico City, Mexico

2. Escuela Superior de Ingeniería Mecánica y Eléctrica Unidad Zacatenco, Instituto Politécnico Nacional, Mexico City, Mexico

3. Tecnológico Nacional de México-TESE, Ecatepec, Mexico

4. Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, USA

Funder

Consejo Nacional de Ciencia y Tecnología and the Mexican Space Agency

Instituto Politécnico Nacional

National Aeronautics and Space Administration

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,Computer Science Applications,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2021.2012534

Reference73 articles.

1. The agroecology of corn production in Tlaxcala, Mexico

2. Assessing SMAP Soil Moisture Scaling and Retrieval in the Carman (Canada) Study Site

3. Soil moisture prediction with the ensemble Kalman filter: Handling uncertainty of soil hydraulic parameters

4. The Texas Soil Observation Network:A Comprehensive Soil Moisture Dataset for Remote Sensing and Land Surface Model Validation

5. Estimation of energy and moisture fluxes for dynamic vegetation using coupled SVAT and crop-growth models

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