The project is funded by the Bulgarian National Science Fund under BG-175467353-2025-07, Call for Funding of Fundamental Scientific Research by Young Scientists and Postdoctoral Researchers – 2025, Contract No. KP-06-M96/4 dated 10 December 2025.
Project duration: 10 December 2025 – 10 December 2027
Contract value: EUR 30,677.51
Base organization: Institute of Forestry – Bulgarian Academy of Sciences
Project Manager: Senior Assistant Professor Elena Rumenova Todorova, Ph.D.
Correspondence address:
1756 Sofia
132 St. Kliment Ohridski Blvd.
Why?
Climate change is increasingly affecting the condition of forest ecosystems. Pine forests, particularly even-aged plantations, are among the most vulnerable, as droughts, extreme temperatures, and changes in soil moisture increase the risk of degradation and loss of ecosystem functions.
Photo credit: Leonid Todorov
What do we aim for?
The project investigates the relationship between soil moisture and the condition of forest vegetation under climate change. It applies an innovative and integrated approach that combines remote sensing and spatial analyses with IoT systems and forestry knowledge to generate new insights into the processes that determine the health and resilience of pine forests.
What exactly do we do?
Three experimental plots will be established and equipped with automated soil moisture sensors connected to an IoT system. In parallel, vegetation indices (NDVI, EVI, LAI, SMI) will be analyzed based on Sentinel-2 imagery, complemented by multispectral and thermal drone surveys, as well as LiDAR data for the creation of a detailed terrain model. Climate data collected for the period 2015–2025 will be integrated into a multifactor analysis to identify the relationships between climatic drivers, soil moisture, and forest condition, with a particular focus on vulnerable even-aged pine plantations.
What results do we expect?
he expected results include an open-access database, standardized methodologies, and practical recommendations for adaptive management. The newly acquired knowledge will have direct application in adaptive and sustainable forest management under climate change conditions. In the longer term, these findings may contribute to the development of a practically applicable model for monitoring and predicting the resilience of pine plantations in the Western Rhodopes..
Main tasks:
Task 1: Establishment of three experimental plots and installation of a soil moisture monitoring system.
Task 2: Parallel calculation of vegetation indices (NDVI, EVI, LAI, SMI) and compilation of a database for the monitoring period, as well as historical data from 2015 onwards. Drone surveys will be conducted to generate a high-resolution orthophoto map, a Digital Terrain Model (DTM), and a Digital Elevation Model (DEM).
Task 3: Collection of climate data for the monitoring period and from 2015 onwards.
Task 4: Multifactor analysis to track relationships and dependencies among the studied variables.
Hypotheses:
Within the framework of the project, the following hypotheses are examined:
Hypothesis 1:
There is a statistically significant correlation between soil moisture levels and the values of NDVI, EVI, and LAI in pine plantations. Under soil moisture deficit, vegetation closes its stomata, reducing photosynthesis and leading to lower LAI values. LAI often lags 1–2 weeks behind declines in soil moisture; this temporal pattern will be validated through regular measurements. Conversely, higher LAI is associated with increased evapotranspiration, which accelerates soil moisture depletion.
The hypothesis regarding the relationship between LAI and SMI is based on the fact that SMI is influenced by NDVI/LAI and land surface temperature. Accordingly, a high correlation with LAI is expected at the beginning of the growing season, while during drought conditions this correlation is expected to decrease.
Hypothesis 2:
Plots located at higher elevations and with northern exposure retain more soil moisture and maintain better vegetation condition.
Hypothesis 3:
The sensitivity of vegetation indices to soil moisture varies seasonally.
Team:
senior assistant Elena Rumenova Todorova, PhD
Project Leader
Dr. Todorova has 12 years of experience in the coordination, administration, and management of projects related to regional and local development, GIS, remote sensing, wildfires, floods, and biodiversity. For the past three years, she has been an Associate Professor at the Institute of Geography – Bulgarian Academy of Sciences (IG-BAS), where she actively participates in numerous projects, international initiatives, and COST Actions. Her work expands her experience and knowledge in spatial analysis and remote sensing, with a strong focus on transdisciplinary research with socio-ecological focus.
senior assistant Sevdalin Vergilov Belilov, PhD
Forest Resources Expert
Dr. Belilov works in the fields of forest entomology, biodiversity, and forest ecosystem monitoring. His doctoral dissertation focuses on xylophagous insects affecting species of the genus Pinus and their role in forest decline in the Ihtimanska Sredna Gora region. He has extensive practical experience in forest resource management and is expanding his work in remote sensing, exploring its applications for forest fires, pest outbreaks, and forest health monitoring.
senior assistant Leonid Todorov Todorov, PhD
GIS and Spatial Analysis Expert
Dr. Todorov is a lecturer at Sofia University “St. Kliment Ohridski,” working in the fields of geographic information systems, databases, spatial analysis, modeling, and remote sensing. He is involved in scientific and applied projects related to transport analysis, climate risks, flood management, drought assessment, ecosystem services, and biodiversity monitoring, including within the NATURA 2000 network.
Abstract of the project:
In the context of accelerating climate change and an increasing risk of forest ecosystem degradation, this project proposes an innovative, integrated approach to assessing the resilience of pine forests in the Western Rhodopes. By combining remote sensing and in-situ monitoring, we will establish a unique, high-frequency database covering key parameters of soil and vegetation dynamics. Three experimental plots will be equipped with TEROS 10 sensors and an IoT-based system for remote soil moisture monitoring. In parallel, vegetation indices (NDVI, EVI, LAI, SMI) will be derived from Sentinel-2 imagery, complemented by drone surveys using multispectral and thermal cameras for detailed terrain modeling and detailed spatial assessments of health status, physiological stress and structural dynamics of pine crops. Climatic datasets spanning 2015–2025 will be integrated into a multifactor analysis to explore linkages between climatic drivers, soil moisture, and forest condition, with a particular focus on vulnerable even-aged pine plantations. Expected outputs include an open-access database, standardized methodologies, and practical recommendations for adaptive forest management, with strong potential for follow-up within EU Framework Programmes and national scientific initiatives.