We use satellite images and remote sensing data to record the health of the plants. This includes the detection of drought damage and the analysis of vegetation indices to identify early symptoms of stress. Our system takes into account changes in the spectral signature of the vegetation, particularly in the near-infrared (NIR) range, which indicate drought stress at an early stage. In addition, factors such as heat, soil properties and exposure are integrated to obtain a holistic picture of drought development on agricultural land and in forests. Historical data analyses and AI-supported forecasts allow future drought risks to be assessed at an early stage so that you can act proactively.

Using relevant vegetation indices such as NBR, NBRT, NDVI and NDWI, we analyze fire hazards and combine these findings with information on existing tree species as required. Using high-resolution remote sensing technologies, we identify potential fire hotspots long before critical situations develop. Our analyses take into account factors such as vegetation condition, soil moisture and historical fire events in order to precisely assess the fire risk in individual regions. Based on these detailed findings, we develop tailor-made recommendations for action to make areas sustainably fire-resistant and effectively implement preventive strategies.

We use remote sensing to identify potential flood risks. Our models take topographical features and historical weather data into account in order to accurately forecast the risk of flood events. The data obtained makes it possible to set up early warning systems that inform you of impending dangers in good time.

We analyze the risk of windthrow in existing tree complexes on an individual tree basis to assess the stability of individual trees and entire stands. Our precise risk models support forest managers in the planning and implementation of forest conversion measures to increase the resilience of forests. The results of our analyses flow directly into strategic measures that promote a resilient forest structure in the long term.

Through detailed soil analyses, we identify signs of soil erosion, humus loss and degradation processes such as desertification, salinization and sodification at an early stage. These findings serve as the basis for targeted measures to maintain soil fertility and long-term productivity. Continuous monitoring of soil parameters enables us to recognize changes in soil quality and resilience in good time. This allows us to assess impending yield losses at an early stage and derive suitable countermeasures. With the help of precise risk assessments, we model soil-related climate risks in order to minimize potential damage in agriculture and forestry. Our analyses support forward-looking planning and help to increase the resilience of soils to climatic challenges. Our scientifically sound methods provide a reliable basis for decision-making for sustainable and future-oriented soil management.

We analyze disease and pest infestation at plant level and model potential high-risk areas based on environmental stress factors such as drought, heat and nutrient deficiency. So we identify pest infestations and diseases at an early stage. Our precise risk models enable early detection of areas at risk and support you in implementing sustainable plant protection strategies to ensure healthy and robust vegetation in the long term.