Department of Forest Management and Applied Geoinformatics

The department has long tradition as one of the founding departments of the University of Agriculture in Brno (1919). Its predecessors are the Department of Forest Management (1920, separately since 1951) and the Geodetic Department (1921). In the present, the department is focused on the area of precision forestry, which synthesizes elements of forest management with applied geoinformatics in a number of forestry activities, that are complemented by modern geoinformation technologies (GIT). Precision forestry on a GIT platform is multidisciplinary approach with numerous overlaps that are further advanced upon by:

• traditional and noncontact methods for detecting state of forest stands,
• mathematical and statistical processing of biometric data,
• theory of the growth and production of a forest,
• differentiated adaptive forest management.

The main objective is to improve coordination and management processes at different spatiotemporal scales of forest management.

The department disposes of two auditoriums, specialized computer lab with 20 seats, specialized geodetic lab with 40 seats, one laboratory for work with analogue and digital spatial data for diploma and Ph.D. students, and one biometric laboratory designed for gathering information from various types of image inputs. There are also two specialized libraries at the department.

Research is particularly focused on the analysis of the landscape and forest stands with respect to risks caused by natural and human sources and subsequent management of the landscape and forest stands. The department actively cooperates with other departments of the faculty and of the whole university as well as with external institutions (e.g. Forest Management Institute, Silva Tarouca Research Institute, CzechGlobe).

Geoengineering and planning documentation:

• surveying work in relation to planning documents of land consolidation in various forms and goals,
• usage of accurate digital terrain models for analysis and planning,
• applications of GIS  for land suitability mapping and spatial decision support.

Classical and noncontact methods for detecting forest and vegetation condition in the landscape:

• detection of dendrometric variables and optimization of methods in relation to the shape and character of the forest,
• application of methods for scalable monitoring (microchips, sensor networks),
• use of airborne laser scanning and unmanned aerial vehicles (UAV),
• application of methods based on Object-Based Image Analysis (OBIA) – Artificial neural network(ANN), vegetation indices.

Biometric data processing, environmental and economic production of the forest:

• modelling of growth and development of the forest and its use for forecasting,
• the use of growth simulators for evaluation and assessment of management strategies,
• application of ecophysiological principles to determine stability and to ensure production of mixed stands,
• calculation of economic effectiveness of production with regard to socio-economic conditions.