High-Resolution prediction of soil pH in European temperate forests using Sentinel-2 and ancillary environmental data.

Soil pH is a key indicator for understanding soil health status in forested ecosystems, yet high-resolution mapping of this variable, especially at a 30-m spatial resolution, remains limited. This study uses Sentinel-2 spectral data, in-situ soil pH measurements, topsoil physical properties from the Land Use/Cover Area Frame Survey (LUCAS) database, and elevation data to estimate soil pH across temperate forests in Europe using a Random Forest model. Despite challenges in signal penetration due to forest canopy cover, the model achieved high prediction accuracy (R² = 0.

Landscape-scale variation in the canopy mycobiome in temperate beech and spruce forest stands explained by leaf water content and elevation.

Unlabelled: Fungi represent a significant portion of Earth's biological diversity and are essential for ecosystem functions like organic matter decomposition and nutrient cycling. While fungi associated with plant roots have been extensively studied, our understanding of fungi in the forest canopies remains limited. To investigate the landscape-scale variation in the canopy mycobiome of temperate beech and spruce forest stands in the Bavarian Forest National Park (Germany), we examined the influence of geophysical conditions and host traits.

Mapping temperate old-growth forests in Central Europe using ALS and Sentinel-2A multispectral data.

Old-growth forests are essential to preserve biodiversity and play an important role in sequestering carbon and mitigating climate change. However, their existence across Europe is vulnerable due to the scarcity of their distribution, logging, and environmental threats. Therefore, providing the current status of old-growth forests across Europe is essential to aiding informed conservation efforts and sustainable forest management.

Precision Estimation of Crop Coefficient for Maize Cultivation Using High-Resolution Satellite Imagery to Enhance Evapotranspiration Assessment in Agriculture.

The estimation of crop evapotranspiration (ETc) is crucial for irrigation water management, especially in arid regions. This can be particularly relevant in the Po Valley (Italy), where arable lands suffer from drought damages on an annual basis, causing drastic crop yield losses. This study presents a novel approach for vegetation-based estimation of crop evapotranspiration (ETc) for maize.

Assessing how irrigation practices and soil moisture affect crop growth through monitoring Sentinel-1 and Sentinel-2 data.

This study authorizes processes and approaches using optical and microwave data to determine the availability of water in the study area at any given moment. This will aid in identifying the optimal time and location for irrigation to enhance crop growth. For this purpose, a set of spectral vegetation parameters (from Sentinel-2), soil moisture (from Sentinel-1), evapotranspiration, and surface temperature (from Landsat-8) were used, along with field data on water content and irrigation timing.