Auswahl der wissenschaftlichen Literatur zum Thema „Bark beetle calamity“

Currently, the decline in spruce wood prices is a serious problem for the forestry sector in the Czech Republic. We estimate that the fall in wood prices in European markets causes losses not only to the forestry companies producing, harvesting, and processing the wood, but also to the workers in the sector. These losses are mainly caused by a combination of several natural factors: drought, climate change, and the effects of bark beetles. In particular, spruce bark beetles cause the greatest damage. Due to this bark beetle calamity, unplanned logging has increased. In 2019, these damages have culminated. Almost 100 million m3 of wood has been harvested over the last decade due to the bark beetle and more than half of this volume has been mined in the last four years. Therefore, the losses in the forestry sector are around EUR 1.12 billion. The aim of this study is an analysis of the relationship between the volume of incidental logging and the decline in the price of spruce wood. These results show the strong correlation between the measure of unplanned wood harvesting and the decrease in wood prices, as well as an estimate of price development if the upward trend of incidental mining continues. The average price of wood in the Czech Republic could thus reach a historical minimum of EUR 79.39 per m3 of spruce and category SM/JE II (spruce/fir). In addition, the decline in wood prices will be reflected in the management of forestry and timber businesses, including stagnant wages for forestry workers. The socio-economic impact of the bark beetle calamity is high and is most affected by the decline in spruce timber prices.

In this article, we investigated the detection of forest vegetation changes during the period of 2017 to 2019 in the Low Tatras National Park (Slovakia) and the Sumava National Park (Czechia) using Sentinel-2 data. The evaluation was based on a time-series analysis using selected vegetation indices. The case studies represented five different areas according to the type of the forest vegetation degradation (one with bark beetle calamity, two areas with forest recovery mode after a bark beetle calamity, and two areas without significant disturbances). The values of the trajectories of the vegetation indices (normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI)) and the orthogonal indices (tasseled cap greenness (TCG) and tasseled cap wetness (TCW)) were analyzed and validated by in situ data and aerial photographs. The results confirm the abilities of the NDVI, the NDMI and the TCW to distinguish disturbed and undisturbed areas. The NDMI vegetation index was particularly useful for the detection of the disturbed forest and forest recovery after bark beetle outbreaks and provided relevant information regarding the health of the forest (the individual stages of the disturbances and recovery mode). On the contrary, the TCG index demonstrated only limited abilities. The TCG could distinguish healthy forest and the gray-attack disturbance phase; however, it was difficult to use this index for detecting different recovery phases and to distinguish recovery phases from healthy forest. The areas affected by the disturbances had lower values of NDVI and NDMI indices (NDVI quartile range Q2–Q3: 0.63–0.71; NDMI Q2–Q3: 0.10–0.19) and the TCW index had negative values (Q2–Q3: −0.06–−0.05)). The analysis was performed with a cloud-based tool—Sentinel Hub. Cloud-based technologies have brought a new dimension in the processing and analysis of satellite data and allowed satellite data to be brought to end-users in the forestry sector. The Copernicus program and its data from Sentinel missions have evoked new opportunities in the application of satellite data. The usage of Sentinel-2 data in the research of long-term forest vegetation changes has a high relevance and perspective due to the free availability, distribution, and well-designed spectral, temporal, and spatial resolution of the Sentinel-2 data for monitoring forest ecosystems.

This study focused on the evaluation of forest vegetation changes from 1992 to 2015 in the Low Tatras National Park (NAPANT) in Slovakia and the Sumava National Park in Czechia using a time series (TS) of Landsat images. The study area was damaged by wind and bark beetle calamities, which strongly influenced the health state of the forest vegetation at the end of the 20th and beginning of the 21st century. The analysis of the time series was based on the ten selected vegetation indices in different types of localities selected according to the type of forest disturbances. The Landsat data CDR (Climate Data Record/Level 2) was normalized using the PIF (Pseudo-Invariant Features) method and the results of the Time Series were validated by in-situ data. The results confirmed the high relevance of the vegetation indices based on the SWIR bands (e.g., NDMI) for the purpose of evaluating the individual stages of the disturbance (especially the bark beetle calamity). Usage of the normalized Landsat data Climate Data Record (CDR/Level 2) in the research of long-term forest vegetation changes has a high relevance and perspective due to the free availability of the corrected data.

The number of severe storm events has increased in recent decades due to climate change. These storms are one of the main causes for timber loss in European forests and damaged areas are prone to further degradation by, for example, bark beetle infestations. Usually, manual mapping of damaged areas based on aerial photographs is conducted by forest departments. This is very time-consuming and therefore automatic detection of windthrows based on active and passive remote sensing data is an ongoing research topic. In this study we evaluated state-of-the-art Convolutional Neural Networks (CNNs) in combination with Geographic Information Systems (GIS) for calamity assessment. The study area is in in the northern part of Hesse (Germany) and was covered by twelve Sentinel-2 scenes from 2018. Labels of damaged areas from the Friedericke storm (18 January 2018) were provided by HessenForst. We conducted several experiments based on a custom U-Net setup to derive the optimal architecture and input data as well as to assess the transferability of the model. Results highlight the possibility to detect damaged forest areas using Sentinel-2 data. Using a binary classification, accuracies of more than 92% were achieved with an Intersection over Union (IoU) score of 46.6%. The proposed workflow was integrated into ArcGIS and is suitable for fast detection of damaged areas directly after a storm and for disaster management but is limited by the deca-meter spatial resolution of the Sentinel-2 data.

Achieving public support and understanding in addressing the challenges of climate change and the bark beetle calamity is a prerequisite for the successful future of Czech forestry. The most important instrument for achieving public support is communication. To be effective, this communication has to be built on a communication strategy reflecting the long-term goals of forest policy and has to be based on both current analyses and other relevant information, which, in turn, is based on the research results of the public perception of the forests and forestry. This article deals with the results of current research studies and formulates conclusions in relation to this communication strategy. Among other things, these results indicate the willingness of a large part of the public to actively participate in voluntary assistance to forestry, markedly differing opinions among individual groups on forest functions, and rather below-average interest in information concerning forests and forestry.

This paper deals with evaluating the ecological impacts of Kaiser S2 harvester utilization in mountain terrains. The harvester was used in bark beetle calamity and secondary felling in mixed forest (spruce, fir, beech) stand with average incline of 70%. Assisting its movement in these extreme conditions were two supporting bases, which were used to stabilize it in the stand. Our aim was to determine the damage to the trees, underwood and stand soil. The resulting damage of remaining stand was 6.19%, which is, considering the demanding terrain conditions and in comparison with the outcomes of other research, a relatively acceptable value. Damage to the underwood was not found, due to its insufficient height and low representation. Measurements of damage to the soil by its compression indicated that the heaviest damage was under the supporting bases, where a heavy surface damage was found by creation of holes up to 15 cm deep. This type of damage is not dangerous, because it does not create a continuous track dangerous in storm rainfall and subsequent soil erosion. Soil compression in the track and on unimpaired soil reached lower levels. All of the measurements of compression by static penetration were carried out only to the depth of 15 cm due to high soil skeleton. This also negatively affected the measurements, which had to be repeated in many cases.

AbstractIn this chapter, we present a multi-source remote sensing approach for country-wise monitoring of bark beetle calamity to support government decision making processes. In the first part, we describe the forest health monitoring system, which is based on the analysis of satellite big data–Sentinel-2 observations collected every five days. We propose an automated processing chain for high-quality cloud-free image synthesis for user-defined acquisition periods. Such a processing chain is applied to yield yearly cloud-free images of the entire Czech Republic from 2015 onwards. Based on this data, we assess forest health trends using Sentinel-2 derived vegetation indices and in situ data of forest status. Finally, we demonstrate the benefits of multi-source remote sensing for timely and objective mapping of bark beetle spread by combining several data sources, including planet high-resolution satellite data, Sentinel-2 forest health maps and other maps of forest conditions. Detected bark beetle sanitary logging and dead standing wood polygons are used by the Ministry of Agriculture of Czech Republic in their decision processes regarding the management of affected forest areas.