This study modeled wild edible mushroom yields in Mediterranean forests using Planet satellite imagery, LiDAR, climate data, and field measurements. Results show that seasonal NDVI differences, precipitation, and forest structure are key predictors. Integrating high-resolution intra-annual remote sensing significantly improves yield prediction and ecological understanding.