Conference Paper

New opportunities for forest management using Copernicus data Sentinels for Thuringian Information Systems

Authors:
Martyna Stelmaszczuk-Gorska at Friedrich Schiller University Jena
Martyna Stelmaszczuk-Gorska
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Abstract

In the Free State of Thuringia in Germany the forest inventory data are collected as part of the forest management and the forest biotope mapping only once every ten years. Additionally, the Forestry Environmental Monitoring in Thuringia with its three key elements, the forest condition survey (WZE) conducted every year, the soil condition survey (BZE) conducted once every fifteen years, and the intensive monitoring of forest at the measurement stations conducted from hourly measurements (weather information) to once every five years (forest growth, soil conditions, and ground vegetation) are designed to identify changes in the forest ecosystem. All mentioned information are available only for point measurements and are not updated frequently enough to capture the rapid changes in water supply. To develop necessary climate change adaptation strategies, it is essential to obtain continuous information on a regular basis on the total forest area. This kind of information can be provided from the Earth Observation (EO) data. Satellite data together with other remote sensing data and available reference data can support the monitoring of forested areas.

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Toward an Operational Forest Monitoring Using Copernicus Data: A Case Study in Central Germany
Conference Paper
  • Aug 2018
In the Free State of Thuringia, in Central Germany, the ThüringenForst develops new remote sensing products using open and free data. For this purpose, Copernicus data as well as LiDAR data, and Thuringian GIS database provided by the Agency for Surveying and Geodata (Federal State Thuringia) have been used. Copernicus services combined with auxiliary data can provide at no cost timely and objective information on forest resources that complement and update the existing forest geoinformation. Until now, three products have been available for operational use by ThüringenForst, namely afforestation monitoring, terrain accessibility maps, and tree height maps. Another important forest parameter to monitor is tree species. In this paper, a workflow for classifying tree species has been presented that can be utilized as a future remote sensing local forest product. Using the Sentinel-2 data, five dominant tree species were classified with an overall accuracy of more than 83%.
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