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

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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Bibliographic Details
Main Authors:	Mikko Strahlendorff, Anni Kröger, Golda Prakasam, Miriam Kosmale, Mikko Moisander, Heikki Ovaskainen, Asko Poikela
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2024-12-01
Series:	Frontiers in Remote Sensing
Subjects:	soil wetness forestry operations seasonal forecast quality XGBoost (Extreme gradient boosting) lightGBM ERA5-Land
Online Access:	https://www.frontiersin.org/articles/10.3389/frsen.2024.1360572/full
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