Search Results (135)

Fire suppression in the upper U.S. Midwest has led to the expansion of flammable coniferous ladder fuels, necessitating precise tracking of conifer species basal area (BA) for fire risk management. This study benchmarks four subset-selection pipelines—xPLS, GA-xPLS, RF-xPLS, and SVR-xPLS—to optimize the fusion of high-dimensional, collinear data from Sentinel-2, Landsat-9, and LiDAR sensors. Using 141 field plots in Minnesota’s Kawishiwi Ranger District of the Superior National Forest, we evaluated 175 predictors against eight BA response variables. Results show that RF-xPLS provided the superior accuracy–parsimony trade-off, achieving the highest pooled R² (≈0.86) and lowest error with a compact 27-predictor block. GA-xPLS ranked second, excelling for specific species such as Pinus resinosa. The most effective predictors combined SWIR-based moisture indices, red-edge/NIR structure, and a single LiDAR-derived surface of vertical-structure (quadratic mean height). Our findings demonstrate that integrating machine learning selection engines with multi-sensor fusion substantially enhances the scalability and precision of forest inventory and fuels monitoring. This comparative framework offers practical insights for sustainable management and fire risk mitigation in northern temperate–boreal forests. Full article

Mountain forests play a key role in buffering local climate, yet their climate sensitivity is seldom mapped in a way that is directly usable for spatial planning. This study investigates how phenological thermal and vegetation variability are organized within the forested landscape of Namyangju, a mountainous region in central Korea, and derives spatial indicators of forest climate sensitivity. Using monthly, cloud-screened Landsat-8/9 land surface temperature (LST) and normalized difference vegetation index (NDVI) images over a recent multi-year period, we calculated phenological coefficients of variation for 34,123 forest grid cells and applied local clustering analysis to identify belts of high and low variability. Forest areas where LST and NDVI variability simultaneously occupied the upper tail of their distributions (top 5%/10%/20%) were interpreted as climate-sensitivity hotspots, whereas co-located coldspots were treated as microclimatic refugia. Across the mountainous terrain, sensitivity hotspots formed continuous belts along high-elevation ridges and steep, dissected slopes, while coldspots were concentrated in sheltered valley floors. Notably, the most sensitive belts were dominated by high-elevation conifer stands, despite the limited seasonal fluctuation typically expected in evergreen canopies. This pattern suggests that elevation strongly amplifies the coupling between thermal responsiveness and vegetation health, whereas valley-bottom forests act as stabilizers that maintain comparatively constant microclimatic and phenological conditions. We refer to these patterns as “forest climate-sensitivity belts,” which translate satellite observations into spatially explicit information on where climate-buffering functions are most vulnerable or resilient. Incorporating climate-sensitivity belts into forest plans and adaptation strategies can guide elevation-aware species selection in new afforestation, targeted restoration and fuel-load management in upland sensitivity zones, and the protection of valley refugia that support biodiversity, thermal buffering, and hydrological regulation. Because the framework relies on standard satellite products and transparent calculations, it can be updated as new imagery becomes available and transferred to other seasonal, mountainous regions, providing a practical basis for climate-resilient forest planning. Full article

Air-assisted sprayers are widely used in orchards to ensure deep canopy penetration and effective pesticide coverage, yet excessive or misdirected airflow often causes spray drift and ground losses. This study evaluated spray deposition efficiency, drift, and environmental performance of a novel double-tower orchard sprayer (DIVENT) equipped with two independently driven axial fans allowing separate airflow adjustment on each side. Field experiments were conducted in apple orchards under crosswind conditions using the following three airflow emission scenarios (air volume to the LEFT/RIGHT side of sprayer): symmetrical (100%/100%), compensating crosswind (30%/100%), and one-sided (0%/100%). Measurements of spray deposition within the canopy, ground losses, and off-target deposition drift were performed using fluorescent tracer, and power consumption was recorded to estimate fuel use and CO₂ emissions. The compensating airflow setting significantly improved spray targeting, reducing both in-orchard ground losses and off-target drift by up to 60%, while maintaining uniform canopy coverage comparable to the conventional symmetrical mode. The one-sided emission scenario achieved the highest drift reduction (67.8%) and the lowest power and CO₂ emissions, though at the cost of reduced canopy deposition. Overall, the study demonstrates that independent fan control allows effective adaptation of spraying to weather and canopy conditions, providing substantial environmental and energy benefits without compromising spray efficiency. Full article

Crown fires are a major disturbance in boreal and cold–temperate forests worldwide, threatening both ecosystems and human activities. The Da Xing’anling Mountains of Northeast China exemplify these dangers due to their complex vegetation and high crown fire potential. Crown fire occurrence depends on vertical fuel continuity, fuel load, heating value, surface fire spread rate, and critical fireline intensity. However, many assessments rely on single-factor metrics or low-adaptability simulations. This study developed a Potential Canopy Fire Danger Index (PCDI) that integrates five parameters—fuel vertical distribution continuity index, fuel loading, heating value, surface fire rate of spread, and critical fireline intensity—based on field surveys and combustion tests. Pinus pumila (Regel, 1861), with its dense shrub layer, showed the highest PCDI values (0.502, 0.583 and 0.527), whereas other forest types generally fell in the low to low–moderate range (0.350–0.450), with ≈75% of plots within these classes. Surface fire spread rate correlated most strongly with PCDI, followed by vertical fuel continuity, heating value, and fuel load; critical fireline intensity had minimal influence. The elevated hazard in P. pumila reflects its structural and fuel characteristics, while other forest types present comparatively lower dangers. Model checks indicated high stability and agreement with BehavePlus 6.0 scenarios, with the PCDI showing the lowest sample SD. The PCDI provides a quantitative framework for assessing crown fire danger in cold–temperate forests and supports targeted mitigation—prioritizing P. pumila while employing cost-effective maintenance in low-danger forest types. Full article

Crown fire hazard assessment and behavior prediction in dwarf pine (Pinus pumila) forests are dictated by the amount of canopy fuel available, topography, and weather. In this study, we collected data on CFL (available canopy fuel load), CBD (canopy bulk density), and CBH (canopy base height) through the destructive sampling of dwarf pine trees in the Greater Khingan Mountains of Northeast China. Allometric equations were developed for estimating the canopy’s available biomass, CFL, and CBD to support the assessment of canopy fuel. Three burning scenarios were designed to investigate the impact of various environmental parameters on fire behavior. Our findings indicated that the average CFL of a dwarf pine was 0.36 kg·m⁻², while the average CBD was measured at 0.17 kg·m⁻³. The vertical variation trends of both CFL and CBD exhibited consistency, with values increasing progressively from the bottom to the top of the tree crown. Fire behavior simulations indicated that the low CBH of dwarf pine trees increased the likelihood of crown fires. Various factors, including wind speed, slope, and CBH, exerted considerable influence on fire behavior, with wind speed emerging as the most critical determinant. Silvicultural treatments, such as thinning and pruning, may effectively reduce fuel loads and elevate the canopy base height, thereby decreasing both the probability and intensity of crown fires. Full article

Effective estimation of fuel load is critical for mitigating wildfire risks. Here, we evaluate the performance of mobile laser scanning (MLS) and terrestrial laser scanning (TLS) to estimate fuel loads across multiple vegetation layers. Data were collected in two forest regions: the North Kaibab (NK) Plateau in Arizona and Monroe Mountain (MM) in Utah. We used random forest models to predict vegetation attributes, evaluating the performance of full models and transferred models using R², RMSE, and bias. The MLS consistently outperformed the TLS system, particularly for canopy-related attributes and woody biomass components. However, the TLS system showed potential for capturing canopy structure attributes, while offering advantages like operational simplicity, low equipment demands, and ease of deployment in the field, making it a cost-effective alternative for managers without access to more complex and expensive mobile or airborne systems. Our results show that model transferability between NK and MM is highly variable depending on the fuel attributes. Attributes related to canopy biomass showed better transferability, with small losses in predictive accuracy when models were transferred between the two sites. Conversely, surface fuel attributes showed more significant challenges for model transferability, given the difficulty of laser penetration in the lower vegetation layers. In general, models trained in NK and validated in MM consistently outperformed those trained in MM and transferred to NK. This may suggest that the NK plots captured a broader complexity of vegetation structure and environmental conditions from which models learned better and were able to generalize to MM. This study highlights the potential of ground-based LiDAR technologies in providing detailed information and important insights into fire risk and forest structure. Full article

The integration of a real-time image processing system using multiple webcams with a variable rate spraying system mounted on the back of an unmanned tractor presents an effective solution to the labor shortage in agriculture. This research aims to design and fabricate a low-cost, variable-rate, remote-controlled sprayer specifically for use in sugarcane fields. The primary method involves the modification of a 15-horsepower tractor, which will be equipped with a remote-control system to manage both the driving and steering functions. A foldable remote-controlled spraying arm is installed at the rear of the unmanned tractor. The system operates by using a webcam mounted on the spraying arm to capture high-angle images above the sugarcane canopy. These images are recorded and processed, and the data is relayed to the spraying control system. As a result, chemicals can be sprayed on the sugarcane accurately and efficiently based on the insights gained from image processing. Tests were conducted at various nozzle heights of 0.25 m, 0.5 m, and 0.75 m. The average system efficiency was found to be 85.30% at a pressure of 1 bar, with a chemical spraying rate of 36 L per hour and a working capacity of 0.975 hectares per hour. The energy consumption recorded was 0.161 kWh, while fuel consumption was measured at 6.807 L per hour. In conclusion, the development of the remote-controlled variable rate sprayer mounted on an unmanned tractor enables immediate and precise chemical application through remote control. This results in high-precision spraying and uniform distribution, ultimately leading to cost savings, particularly by allowing for adjustments in nozzle height from a minimum of 0.25 m to a maximum of 0.75 m from the target. Full article

Residual dry matter (RDM) is a term used in rangeland management to describe the non-photosynthetic plant material left on the soil surface at the end of the growing season. RDM measurements are used by agencies and conservation entities for managing grazing and fire fuels. Measuring the RDM using traditional methods is labor-intensive, costly, and subjective, making consistent sampling challenging. Previous studies have assessed the use of multispectral remote sensing to estimate the RDM, but with limited success across space and time. The existing approaches may be improved through the use of spectroscopic (hyperspectral) sensors, capable of capturing the cellulose and lignin present in dry grass, as well as Unmanned Aerial Vehicle (UAV)-mounted Light Detection and Ranging (LiDAR) sensors, capable of capturing centimeter-scale 3D vegetation structures. Here, we evaluate the relationships between the RDM and spectral and LiDAR data across the Jack and Laura Dangermond Preserve (Santa Barbara County, CA, USA), which uses grazing and prescribed fire for rangeland management. The spectral indices did not correlate with the RDM (R² < 0.1), likely due to complete areal coverage with dense grass. The LiDAR canopy height models performed better for all the samples (R² = 0.37), with much stronger performance (R² = 0.81) when using a stratified model to predict the RDM in plots with predominantly standing (as opposed to laying) vegetation. This study demonstrates the potential of UAV LiDAR for direct RDM quantification where vegetation is standing upright, which could help improve RDM mapping and management for rangelands in California and beyond. Full article

Garvin Heights Park in southeastern Minnesota, USA, is a 12 ha mosaic of bluff prairie, oak savanna, and oak–hickory woodland co-owned by the City of Winona and Winona State University, with a 40+ year history of encroachment by non-native woody invasives, especially buckthorn (Rhamnus cathartica) and honeysuckles (Lonicera spp.). Habitat restoration was initiated in the early 1990s, but management gaps and a seedbank of invasives compromised initial efforts. More consistent and sustainable restoration activities since 2016 have included cutting and chemical treatment of invasives, managed goat browsing, targeted reseeding and plug planting with native species, and more regular prescribed fires. Throughout the restoration process, we assessed changes in buckthorn densities in response to various management practices, assessed the restored savanna tree community, and documented the presence of blooming plants across all park habitats. Manual clearing of woody invasives and repeated goat browsing significantly reduced buckthorn and honeysuckle abundance in prairies and savannas. Park plant communities responded to the combination of management strategies with reduced densities of woody invasives and expanding diversity (currently >220 species present) of forbs and grasses, including a large and growing population of state-threatened Great Indian Plantain (Arnoglossum reniforme). Prescribed fires have benefitted prairies but have done little to improve savanna plant communities, due largely to excessive tree canopy coverage causing a lack of burnable fuels (i.e., dry forbs and grasses). Improved partnerships between landowners and dedicated volunteers are working to expand restoration efforts to include other portions of the park and adjacent woodlands. Full article

Selection forestry sustains timber production and stand structural complexity via partial harvesting. However, regeneration initiated by harvesting may function as fuel ladders, providing pathways for fire to reach the forest canopy. We sought potential mitigation approaches by simulating stand growth and potential wildfire behavior over a century in stands dominated by coast redwood (Sequoia sempervirens (Lamb. ex. D. Don) Endl.) on California’s north coast. We used the fire and fuels extension to the forest vegetation simulator (FFE-FVS) to compare group selection (GS) to single-tree selection silviculture with either low-density (LD) or high-density (HD) retention on a 20-year harvest return interval. These three approaches were paired with six options involving vegetation management (i.e., hardwood control or pre-commercial thinning (PCT)) with and without fuels treatments (i.e., prescribed fire or pile burning), or no subsequent vegetation or fuel treatment applied after GS, HD, or LD silviculture. Fuel treatment involving prescribed fire reduced hazardous fuel loading but lowered stand density and hence productivity. Hardwood control followed by prescribed fire mitigated potential wildfire behavior and promoted dominance of merchantable conifers. PCT of small young trees regenerating after selection harvests, followed by piling and burning of these cut trees, sustained timber production while reducing potential wildfire behavior by approximately 40% relative to selection silviculture without vegetation/fuel management, which exhibited the worst potential wildfire behavior. Full article

Soil pollution at airports is a critical environmental issue that affects not only the local ecology but also the health of people living near these infrastructures. The main causes of pollution include the use of chemical products such as de-icing agents, fuels, and lubricants, as well as waste from aircraft and ground vehicles. These substances often seep into the soil, leading to the accumulation of toxic elements. However, due to security reasons, there is a great scarcity of real data on the impact of airport operations on ecosystems and the role trees could play in pollutant limitation. Thus, the aim of this study was to determine whether airport operations have toxic effects on soils within and around Macedonia Airport, Thessaloniki, Northern Greece, by determining the concentrations of potentially toxic elements (Cu, Ni, Pb, Mn, Fe, Co, Cr, Cd, and Zn) in soil samples taken within the airport and near the airport. Furthermore, this study aimed to investigate the effect of the canopies of forest species on the accumulation of toxic metals in the soil inside the airport and in the peripheral zone. The results show that, overall, no important pollution was detected in the soil of the Thessaloniki Airport, Northern Greece, both inside and outside the airport area. Some differences were observed in the content of toxic metals studied between the samples taken inside and outside the airport, and some effects of tree canopy were noted. However, all values were lower than the defined permissible limits according to international standards (except for iron). It is important, however, to perform regular re-checking of soil quality with new samples in order to prevent soil contamination and mitigate any contamination found. Full article

Safety zones protect firefighters from bodily injury and death caused by exposure to dangerous heat levels. These zones are defined by maintaining a safe distance from combustible fuels, a safe separation distance (SSD) derived from flame height. This study aimed to determine safety zones, integrating an existing automated identification-of-safety-zone model with vegetation height derived from a freely available high-resolution global canopy height dataset for Manavgat Forest Management Directorate (FMD) in Türkiye. Flame height, terrain slope, size of a safety zone, and distance to the closest road were also used as input in this model. The results indicated that vegetation height from high-resolution global canopy height offered promising results for determining potential safety zones (SZs) associated with SSD. Integrating the global canopy height dataset into the existing model could assist in determining the safety zone in the absence of lidar. Thus, this spatial model would provide a framework for decision-makers to develop fire prevention and suppression strategies for higher fire risk areas, especially before and during a fire. Full article

Accurate wildfire spread modeling critically depends on the representation of wind dynamics, which vary with terrain, land cover characteristics, and height above ground. Many fire spread models are often coupled with coarse atmospheric grids that cannot explicitly resolve the vertical variation of wind near flame heights. Rothermel’s fire spread model, a widely used parameterization, relies on midflame wind speed to calculate the fire rate of spread. In coupled fire atmosphere models such as the Community Fire Behavior Model (CFBM), users are required to specify the midflame height before running a fire spread simulation. This study evaluates the use of logarithmic interpolation wind adjustment factors (WAF) for improving midflame wind speed estimates, which are critical for the Rothermel model. We compare the fixed wind height approach that is currently used in CFBM with WAF-derived winds for unsheltered and sheltered surface fire spread. For the first time in this context, these simulations are validated against satellite and ground-based observations of fire perimeters. The results show that WAF implementation improves fire perimeter predictions for both grass and canopy fires while reducing the overestimation of fire spread. Moreover, this approach solely depends on the fuel bed depth and estimation of canopy density, enhancing operational efficiency by eliminating the need for users to specify a wind height for simulations. Full article

As the transition to sustainable transportation has accelerated with the rise of electric vehicles (EVs), ensuring drivers have access to charging to maximize the electric miles driven is critical to lowering carbon emissions in the transportation sector. Limited charging station capacity and poor reliability, especially during peak travel times, long-distance travels, holidays, and events, have hindered the adoption of EVs and threaten the progress toward reducing greenhouse gas emissions. Adaptive, flexible deployment strategies combined with innovative approaches integrating mobility and renewable energy are essential to address these systemic challenges and bridge the current infrastructure gap. To address these challenges, this study proposes a self-contained, mobile charging station (MCS). Designed for rapid deployment, the proposed MCS increases charging capacity during demand surges while minimizing reliance on fossil fuels. The feasibility of integrating a solar canopy with this MCS to further reduce carbon emissions is also studied. This study weighed the pros and cons of differing cell chemistries, sized the battery using data provided by the United States’ largest public CPO, and discussed the feasibility of a solar canopy for off-grid energy. Full article

Anthropogenic disturbances, such as forest conversion, have a profound impact on species distributions and biodiversity in tropical forests. This study aimed to determine the diversity and distribution of bark and ambrosia beetles (Curculionidae: Scolytinae and Platypodinae) across three forest types: Primary Forest (PF), Disturbed Forest (DF), and Rubber Plantation (RP) in southern Sabah, Malaysia. We analyzed biweekly data obtained from ethanol-baited traps over three years, from April 2017 to May 2020, which included 7257 individuals from 154 species. The dominant species remained the same across all forest types. However, species composition was highly stochastic and unpredictable between forest types. The abundance and number of species were highest in RP but lowest in DF. Indigenous forest use in DF mostly for fuel likely reduced the resources for the beetles. Open canopy structure in RP probably increased the number of flying beetles. Although adjacent to PF, RP displayed a distinct species composition predominantly associated with rubber trees. These findings underscore the anthropogenic impact on beetle assemblages due to forest use and emphasize the need for sustainable forest management practices to prevent biodiversity loss and maintain ecosystem stability. Full article