Forestry as well as the efforts to delay climate change, both need that tree stand in forest would be healthy and high growing potential. Even if tree damaging and killing pests are a natural part of forest ecosystem, the extensive pest outbreaks hamper the support of ecosystem services expected to be provided by forest. Therefore, instant and highly detailed awareness about the health status of trees in mature and old-age stands is vital to maintain ecosystem services, to apply timely salvage cuttings rescuing the timber of dead trees supporting local rural economy and to heal gaps in the damaged forest.
We tested several automated and semi-automated image analysis methods to pin-point dead trees from high-resolution summer orthophotos combined with ALS (Aerial Laser Scanning) derived nDSM. Both are open data provided by Estonian Land Board. Starting with object-based machine learning we reached the situation where simple map algebra was even more efficient in dead trees detection and computational resources. The methodological testing revealed multiple sources of false-positive observations. We had to apply various cleaning algorithms to reduce the proportion of biased objects. The removal occurred to be the major task. Finally, the large-scale test object layer was produced for one quarter of the country (16600km2), and these results were shared with experts for review. When feedback was collected, additional algorithms and parameters were tested to improve the results. Only then the final version was published.
The resulting object-layer is published in open-access GIS platform XGIS provided by Estonian Land Board, which has many stakeholder-oriented thematic maps (CountrysideGIS https://xgis.maaamet.ee/xgis2/page/app/maaeluGIS). The specific thematic map also provides many other open access data. For example, we will show, how the indicated dead tree locations can be assessed for the current state and assess the outbreak using the latest Sentinel-2 images and their derivates. All combined, the pile of open data will improve the forest management, maintenance of ecological quality as well as public awareness on the forest processes as a natural ecosystem in Estonia. The experience, surely, can be transferred to other countries.