The European spruce bark beetle (Ips typographus [L.]) is one of the most damaging pest insects forests. A crucial measure in control removal infested trees before beetles leave bark, which generally happens end June. However, stressed tree crowns do not show any significant color changes visible spectrum at this early-stage infestation, making early detection difficult. In order to detect related forest stress an stage, we investigated differences radar and spectral signals healthy trees....

Detecting disease- or insect-infested forests as early possible is a classic application of remote sensing. Under conditions climate change and global warming, outbreaks the European spruce bark beetle (Ips typographus, L.) are threatening related timber industry across Europe, detection infestations important for damage control. Infested trees without visible discoloration (green attack) have been identified using multispectral images, but how green attacks can be detected still unknown....

Obtaining low vegetation data is important in order to quantify the structural characteristics of a forest. Dense three-dimensional (3D) laser scanning can provide information on vertical profile However, most studies have focused dominant and subdominant layers forest, while few tried delineate vegetation. To address this issue, we propose framework for individual tree crown (ITC) segmentation from that focuses both overstory understory trees. The includes 1) new algorithm (SSD) 3D ITC...

In the recent decades, Norway spruce forests (Picea abies Karst.) in Europe have been subject to large-scale tree mortality caused by bark beetle (Ips typographus L.). The outbreaks were induced storm-felling events and periods of drought, which are becoming increasingly frequent due climate change. Because storms droughts spatially affect differently, infestation patterns configuration beetles might differ between drought. this study, we examined local landscape factors associated with...

Pine wilt disease (PWD), caused by pine wood nematode (PWN), poses a tremendous threat to global forests because it can result in rapid and widespread infestations within months, leading large-scale tree mortality. Therefore, the implementation of preventive measures relies on early detection PWD. Unmanned aerial vehicle (UAV)-based hyperspectral images (HSI) detect tree-level changes are thus an effective tool for forest change detection. However, previous studies mainly used single-date...

Forest stress monitoring and in-time identification of forest disturbances are important to improve resilience climate change. Fast-developing drone techniques hyperspectral imagery provide tools for understanding the decline process under contribute focused monitoring. This study explored developed early detection caused by European spruce bark beetle Ips typographus (L.), before offspring emergence, which is crucial in controlling spread but has been shown be challenging. challenges...

Multispectral imagery from unmanned aerial vehicles (UAVs) can provide high-resolution data to map tree mortality caused by pests or diseases. Although many studies have investigated UAV-imagery-based methods detect trees under acute stress followed mortality, few tested the feasibility and accuracy of detecting chronic stress. This study aims develop test how well UAV-based multispectral pine needle disease long before mortality. images were acquired four times through growing season in an...

Introduction European forests face increasing threats from climate change-induced stressors, which create favorable conditions for bark beetle outbreaks. The most critical spruce forest pest in Europe is the Spruce Bark Beetle ( Ips typographus L.). Effective management of this beetles’ outbreaks necessitates timely detection recently attacked trees, challenging given difficulty identifying symptoms on infested tree crowns, especially over large areas. This study assessed detectability trees...

Abstract The frequent outbreaks of European spruce bark beetle Ips typographus (L.) have destroyed huge amounts Norway Picea abies forests in central and Northern Europe. Identifying the risk factors estimating damage level is important for strategic control. forest by beetles mostly been analyzed on landscape scale, while in-stand less investigated. This study aims at exploring local-scale a flat area with spruce-dominated southern Sweden. investigated include four abiotic factors, i.e.,...

In sustainable forest resource management, establishing conservation areas is important to maintain biodiversity. However, assessing the value of forests challenging because target are often both large and remote. We explored using dense airborne laser scanning (ALS) data estimate values. Field were collected at sites in Sweden for standing deadwood (S trees), laying (L trees considered particularly conserving biodiversity (N values determined a commonly employed method field. A template...

Satellite-based inventories of bark beetle attacks are increasingly used for detecting and monitoring infested forest at the landscape scale. The Normalized Distance Red & SWIR index is one few indices that have shown higher accuracies than commonly vegetation indices. In this study, temporal changes distance red swir (ΔDRS) were analyzed, validated applied to multi-temporal Sentinel-2 images covering tile 110 x km2. main purpose was assess applicability a new ΔDRS detect spruce after (Ips...

Multispectral airborne laser scanning (MS-ALS) provides information about 3D structure as well the intensity of reflected light and is a promising technique for acquiring forest information. Data from MS-ALS have been used tree species classification health evaluation. This paper investigates its potential individual detection (ITD) when using an additional metric. To this end, rasters height, point density, vegetation ratio, at three wavelengths were template matching to detect trees....

Detecting forest insect damage before the visible discoloration (green attacks) using remote sensing data is challenging, but important for control. In recent years, European spruce bark beetle (Ips typographus, L.) has damaged large amounts of in Europe, and some studies have been conducted on early detection infestations vulnerabilities attacks. This study assessed detectability green attacks multispectral drone images examined possibility detecting vulnerable trees The used covering 24...

Detecting forest insect damage before the visible discoloration (green attacks) using remote sensing data is challenging, but important for control. In recent years, European spruce bark beetle (Ips typographus, L.) has damaged large amounts of in Europe. However, it still debatable how early infestations can be detected with data. Some studies showed a spectral difference between healthy and green-attacked trees at plot level, while others that differences existed attacks. Therefore,...

In this study, we compared the classification accuracy at plot-level of three tree species in a boreal forest using deep learning (DL) network applied to very high resolution (VHR) ALS data acquired with ~593 points/m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , or linear discriminant analysis (LDA) method dual-wavelength (DW) data, ~80 .The methods were single trees, which aggregated (10 m radius) where majority class was used for...

Pine wilt disease (PWD) is a devastating forest and has been listed as quarantine pest in 52 countries around the world. Early identification of affected trees timely removal them from crucial to control spread. This study aims explore potential hyperspectral data on early PWD exhibit common spectral features, early-infected tree crowns needles, different species located regions. Two types were used compared. One was using drone-based images with range 400 – 1 000 nm resolution 0.11 m. The...

Due to the ongoing global warming, European spruce bark beetles has become a serious threat forests in Europe and caused environmental economic issues. This study proposes new vegetation index, Normalized Projected Red & SWIR (NPRS), for detection of beetle attacks. 29 healthy 24 attacked plots southern Sweden were used evaluating classification accuracy using NPRS at early-, intermediate- late-stage The obtained kappa coefficients 0.73, 0.80 0.88, respectively. It was concluded that is...