Artificial intelligence and remote sensing for spatial prediction of daily air temperature: case study of Souss watershed of Morocco-Reference-Cited by-同舟云学术

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Artificial intelligence and remote sensing for spatial prediction of daily air temperature: case study of Souss watershed of Morocco

Published:2022-01-07 Issue:2 Volume:25 Page:244-258
ISSN:1009-5020
Container-title:Geo-spatial Information Science
language:en
Short-container-title:Geo-spatial Information Science

Author:

Meliho Modeste¹,Khattabi Abdellatif²,Zejli Driss¹,Orlando Collins Ashianga³,Dansou Caleb E.⁴

Affiliation:

1. Ecole Nationale des Sciences Appliquées Kénitra- Laboratoire Ingénierie des Systèmes Avancés (ISA), Université Ibn Tofail, Kenitra, Morocco

2. Ecole Nationale Forestière d’Ingénieurs, Salé, Morocco

3. Salé, Morocco

4. Sciences de données, École des sciences de l’information (ESI), Rabat, Morocco

Publisher

Informa UK Limited

Subject

Computers in Earth Sciences,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10095020.2021.2014765

Reference34 articles.

1. Performance of multi-model ensembles for the simulation of temperature variability over Ontario, Canada

2. A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales

3. Barry, R., and R. Chorley. 1987. Atmosphere, Weather and Climate, 536. 1st ed. Abingdon, UK: Taylor & Francis.

4. MODIStsp : An R package for automatic preprocessing of MODIS Land Products time series

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