Forestry climate adaptation with HarvesterSeasons service—a gradient boosting model to forecast soil water index SWI from a comprehensive set of predictors in Destination Earth

Soil wetness forecasts on a local level are needed to ensure sustainable forestry operations during summer when the soil is neither frozen nor covered with snow. Training gradient boosting models has been successful in predicting satellite observation-based products into the future using Numerical W...

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Vydáno v:	Frontiers in remote sensing Ročník 5
Hlavní autoři:	Strahlendorff, Mikko, Kröger, Anni, Prakasam, Golda, Kosmale, Miriam, Moisander, Mikko, Ovaskainen, Heikki, Poikela, Asko
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Frontiers Media S.A 20.12.2024
Témata:	ERA5-Land forestry operations lightGBM seasonal forecast quality soil wetness XGBoost (Extreme gradient boosting)
ISSN:	2673-6187, 2673-6187
On-line přístup:	Získat plný text
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