An inter-comparison of different PSO-optimized artificial intelligence algorithms for thermal-based soil moisture retrieval
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences
Link
https://link.springer.com/content/pdf/10.1007/s12145-021-00747-7.pdf
Reference32 articles.
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3. Azimi S, Dariane AB, Modanesi S, Bauer-Marschallinger B, Bindlish R, Wagner W, Massari C (2020) Assimilation of Sentinel 1 and SMAP – based satellite soil moisture retrievals into SWAT hydrological model: the impact of satellite revisit time and product spatial resolution on flood simulations in small basins. J Hydrol 581:1879–2707
4. Bartels GK, Castro NMR, Pedrollo O, Collares GL (2021) Soil moisture estimation in two layers for a small watershed with neural network models: assessment of the main factors that affect the results. CATENA 207:105631. https://doi.org/10.1016/j.catena.2021.105631
5. Bartsch A, Balzter H, George C (2009) The influence of regional surface soil moisture anomalies on forest fires in Siberia observed from satellites. Environ Res Lett 4(4):1–9
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