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Implementing a scheduled and reliable estimation of forest characteristics is important for the sustainable management of forests. This study aimed at evaluating the capability of Sentinel-2 satellite data to estimate above-ground biomass (AGB) in coppice forests of Persian oak (Quercus brantii var. persica) located in Western Iran. To estimate the AGB, field data collection was implemented in 80 square plots (40×40 m, area of 1600 m2). Two diameters of the crown were measured and used to calculate the AGB of each tree based on allometric equations. Then, the performance of satellite data in estimating the AGB was evaluated for the area of study using the field-based AGB (dependent variable) as well as the spectral band values, spectrally-derived vegetation indices (independent variables) and four machine learning (ML) algorithms: Multi-Layer Perceptron Artificial Neural Network (MLPNN), k-Nearest Neighbor (kNN), Random Forest (RF), and Support Vector Regression (SVR). A five-fold cross-validation was used to verify the effectiveness of models. Examination of the Pearson’s correlation coefficient between AGB and the extracted ‎values showed that IPVI and NDVI vegetation indices had the highest correlation with AGB (r = 0.897). The results indicated that the MLPNN algorithm was the best ML option (RMSE = 1.71 t ha-1; MAE = 1.37 t ha-1; relative RMSE = 24.75%; R2 = 0.87) in estimating the AGB, providing new insights on the capability of remotely sensed-based AGB modeling of sparse Mediterranean forest ecosystems in an area with limited number of field sample plots.

One of the main challenges of using unmanned aerial vehicles (UAVs) in forest data acquisition is the implementation of Ground Control Points (GCPs) as a mandatory step, which is sometimes impossible for inaccessible areas or within canopy closures. This study aimed to test the accuracy of a UAV-mounted GNSS RTK (real-time kinematic) system for calculating tree height and crown height without any GCPs. The study was conducted on a Cupressus arizonica (Greene., Arizona cypress) plantation on the Razi University Campus in Kermanshah, Iran. Arizona cypress is commonly planted as an ornamental tree. As it can tolerate harsh conditions, this species is highly appropriate for afforestation and reforestation projects. A total of 107 trees were subjected to field-measured dendrometric measurements (height and crown diameter). UAV data acquisition was performed at three altitudes of 25, 50, and 100 m using a local network RTK system (NRTK). The crown height model (CHM), derived from a digital surface model (DSM), was used to estimate tree height, and an inverse watershed segmentation (IWS) algorithm was used to estimate crown diameter. The results indicated that the means of tree height obtained from field measurements and UAV estimation were not significantly different, except for the mean values calculated at 100 m flight altitude. Additionally, the means of crown diameter reported from field measurements and UAV estimation at all flight altitudes were not statistically different. Root mean square error (RMSE < 11%) indicated a reliable estimation at all the flight altitudes for trees height and crown diameter. According to the findings of this study, it was concluded that UAV-RTK imagery can be considered a promising solution, but more work is needed before concluding its effectiveness in inaccessible areas.

Exploring spatial and temporal changes in protected areas (PAs) is essential for protecting natural capital and creating a harmonious relationship between humans and nature. This study has assessed land use/land cover (LULC) changes in the Jajrud, a Protected Area with a semi-arid climate zone in Iran (covers an area of 18,814 km2), to assess the sustainability of the use of natural resources using Landsat imagery from 1989 to 2018. Likewise, Ecological Footprint accounts (including the sum of biological, freshwater, energy, and pollution) and changes in the per-capita Ecological Carrying Capacity were investigated to uncover Ecological Deficits. The Ecological Pressure Index was used to explore driving factors of natural capital utilization in each of the various identified zones. Between 1989 and 2018, high-density pastures decreased the most in Jajrud, while built-up land increased the most. Likewise, the Ecological Footprint increased while the Ecological Carrying Capacity decreased, increasing Ecological Deficit quantities. Driving factors for the use of natural capital differs among the various zones due to differing management goals, type of uses, and human activity development. As supply and demand for natural resources were clearly out of an imbalance between the supply and demand of natural resources and exceeded the maximum tolerable limits in Jajrud, a change in production and consumption patterns is necessary. This case study has practical importance for establishing mathematical models to reveal the patterns of LULC, ecological footprint, ecological deficit, and ecological pressure indices in a typical PA in a semi-arid region of Iran. Our approach is advisable for semi-arid PAs in Iran and regions with similar attributes in other countries.

This study aimed at delineating the wildfire risk zones in a fire-prone region located in a rarely addressed area of western Iran (Paveh city) by assessing the potential of factors such as NDVI, topographic factors (elevation, slope, and aspect), land cover, and evaporation in explaining the fire occurrence probability. Analytic hierarchy process (AHP) and geographical information system (GIS) methods were used synergistically to integrate the mentioned factors into analysis, following an informed categorization of each factor based on the information on previous fire occurrence. In the AHP process, elevation and evaporation data were considered to be the most critical factors. It was found that the predicted wildfire risk areas were in agreement with past fire events by the use of the methodology proposed by this study. Accordingly, the study's final wildfire risk map indicated that approximately 64.7% of the study area is located in the high- and very high-risk zones. Land-use planners and decision-makers may use the developed map to setup and implement fire prevention strategies and enhance or develop the fire-surveillance logistics and infrastructure, including but not limited to the positions of fire watchtowers, fire lines, and fire sensors, with the aim to minimize potential fire impacts.

Due to the challenges brought by field measurements to estimate the aboveground biomass (AGB), such as the remote locations and difficulties in walking in these areas, more accurate and cost-effective methods are required, by the use of remote sensing. In this study, Sentinel-2 data were used for estimating the AGB in pure stands of Carpinus betulus (L., common hornbeam) located in the Hyrcanian forests, northern Iran. For this purpose, the diameter at breast height (DBH) of all trees thicker than 7.5 cm was measured in 55 square plots (45 × 45 m). In situ AGB was estimated using a local volume table and the specific density of wood. To estimate the AGB from remotely sensed data, parametric and nonparametric methods, including Multiple Regression (MR), Artificial Neural Network (ANN), k-Nearest Neighbor (kNN), and Random Forest (RF), were applied to a single image of the Sentinel-2, having as a reference the estimations produced by in situ measurements and their corresponding spectral values of the original spectral (B2, B3, B4, B5, B6, B7, B8, B8a, B11, and B12) and derived synthetic (IPVI, IRECI, GEMI, GNDVI, NDVI, DVI, PSSRA, and RVI) bands. Band 6 located in the red-edge region (0.740 nm) showed the highest correlation with AGB (r = −0.723). A comparison of the machine learning methods indicated that the ANN algorithm returned the best ABG-estimating performance (%RMSE = 19.9). This study demonstrates that simple vegetation indices extracted from Sentinel-2 multispectral imagery can provide good results in the AGB estimation of C. betulus trees of the Hyrcanian forests. The approach used in this study may be extended to similar areas located in temperate forests.

This study examines the distribution of water resources in Protected Areas in Iran and their priority for conservation. The results show that most of the water resources are located in the north and northwest of Iran due to favorable climatic conditions, topography, ambient temperature, and annual rainfall levels. Conversely, the lowest amount of water resources are located in the center and southeast of the country. Water resources were prioritized based on expert ratings of indicators to determine their value for conservation. The wetland with the highest priority for conservation is the Anzali Wetland (Gilan province), which is an international Ramsar Wetland. Conversely, Namak Lake (Qom province) was deemed the least important due to its geographical location, biological sensitivity, and conservation status. Protected Areas were found to support more surface water resources and provide space for the largest percentage of water resources, demonstrating their great value for protecting water resources in Iran. However, the level of protection of these critical resources, although located in Protected Areas, was shown to be insufficient. Therefore, appropriate planning and integrated management approaches are urgently needed to protect water resources and aquatic habitats in Protected Areas in Iran to address the current water crisis.

Vegetation roots contribute to soil fixation and reinforcement, thus improving soil resistance against erosion. Generally, the amount of soil fixation presented by roots mainly depends on root density and tensile strength. In the present study, we conducted the research in order to further understand the biotechnical properties of Haloxylon persicum and also to quantify its role in increasing soil cohesion in arid lands of Iran. Ten H. persicum shrubs were randomly selected for root distribution and strength investigations, in which five samples were set on flat terrain and other five samples on a moderate slope terrain. The profile trench method was used to assess the root area ratio (RAR) as the index of root density and distribution. Two profiles were dug around each sample, up and downslope for sloped treatment and north and south sides for flat treatment. The results showed that RAR increased with increasing soil depth and significantly decreased in 40–50 cm layers of downhill (0.320%) and 50–60 cm for uphill (0.210%). The minimum values for the northward and southward profiles were 0.003% and 0.003%, respectively, while the maximum values were 0.260% and 0.040%, respectively. The relationship between the diameter of root samples and root tensile strength followed a negative power function, but tensile force increased with increasing root diameter following a positive power function. The pattern of increased cohesion changes in soil profile was relatively similar to RAR curves. The maximum increased cohesion due to the presence of roots in uphill and downhill sides were 0.470 and 1.400 kPa, respectively. In the flat treatment, the maximum increased cohesions were 0.570 and 0.610 kPa in northward and southward profiles, respectively. The analysis of variance showed that wind and slope induced stresses did not have any significant effect on the amount of increased cohesion of H. persicum. The findings served to develop knowledge about biotechnical properties of H. persicum root system that can assist in assessing the efficiency of afforestation and restoration measures for erosion control in arid lands.

The ‘road-effect zone’ is a concept developed to describe the impact of road construction on the surrounding area. Although many aspects of the road-effect zone have been investigated, the road-effect zone on soil properties (pH, bulk density, soil moisture, electrical conductivity, organic matter (%), C (%), total N (%), available Na, Ca, Mg, P, and K), light regimes (leaf area index and canopy cover), and a Raunkiaer’s life-form classification of plants remains poorly understood, especially in oriental beech (Fagus orientalis Lipsky) forests. Hence, the main aims of this research were to estimate the extent of the road-effect zone and to identify the main environmental changes due to forest roads. Specifically, we aimed to evaluate road-effects on: (1) the composition of herbaceous species and tree regeneration (up to 100 m distance from the forest road); (2) the light regime; and (3) soil properties, potentially related to changes in ecosystem functions and composition. We observed that forest roads can have significant impacts on soil, stand characteristics, and vegetation composition. The estimated road-effect zone extended up to 30 m from the road edge. Landscape planners should be aware that road-effect zones can potentially influence the ecology and environmental conditions of an area up to 30 m from the road edge.

Determining the physical and mechanical properties of soil and its behavior for engineering projects is essential for road construction operations. One of the most important principles in forest road construction, which is usually neglected, is to avoid mixing organic matter with road materials during excavation and embankment construction. The current study aimed to assess the influence of organic matter on the physical properties and mechanical behaviors of forest soil and to analyze the relation between the amount of organic matter and the behavior of forest soil as road material. A typical soil sample from the study area was collected beside a newly constructed roadbed. The soil was mixed with different percentages of organic matter (control treatment, 5, 10, and 15% by mass) and different tests including Atterberg limits, standard compaction, and California bearing ratio (CBR) tests were conducted on these different soil mixtures. The results showed that soil plasticity increased linearly with increasing organic matter. Increasing the organic matter from 0% (control) to 15% resulted in an increase of 11.64% of the plastic limit and 15.22% of the liquid limit after drying at 110 °C. Also, increasing the organic matter content reduced the soil maximum dry density and increased the optimum moisture content. Increasing the organic matter from 0 to 15% resulted in an increase of 11.0% of the optimum moisture content and a decrease of 0.29 g/cm3 of the maximum dry density. Organic matter decreased the CBR, which is used as the index of road strength. Adding 15% organic matter to the soil resulted in a decrease of the CBR from 15.72 to 4.75%. There was a significant difference between the two drying temperatures (60 and 110 °C) for the same organic matter mixtures with lower water content values after drying at 60 °C. The results revealed the adverse influence of organic matter on soil engineering properties and showed the importance of organic matter removal before excavation and fill construction.

The use of global positioning systems (GPS) has increased in recent years, including for urban forestry management, as a result of its wide range of applications, ease of use and direct use of GPS data in geographic information systems. This study was conducted in an urban green space to assess the accuracy and precision of two consumer-grade GPS receivers with regard to ground control point (GCP) coordinates. Eleven fixed GCPs with known positions were selected and their data collected on four days (two seasons) and three different daytime periods (08:00, 11:00 and 14:00) each day. For each treatment (season and daytime) five replications were recorded. The results showed that the best mean position accuracies were provided by the Colorado receiver in leaf-off period (4–5 m), and its corresponding position accuracies for summer ranged from 9 to 12 m. The results of the Rino receiver mean position error in summer (19–36 m) and winter (10–26 m) were higher than reported in literature. Point averaging had a...

Forest roads alter the biotic and abiotic components of ecosystems, modifying temperature, humidity, wind speed, and light availability that, in turn, cause changes in plant community composition and diversity. We aim at investigating and comparing the diversity of herbaceous species along main and secondary forest roads in a temperate-managed hornbeam-beech forest, north of Iran. Sixteen transects along main and secondary forest roads were established (eight transects along main roads and eight along secondary roads). To eliminate the effect of forest type, all transects were located in Carpinetum-Fagetum forests, the dominant forest type in the study area. The total length of each transect was 200 m (100 m toward up slope and 100 m toward down slope), and plots were established along it at different distances from road edge. The diversity of herbaceous plant species was calculated in each plot using Shannon-Wiener index, species richness, and Pielou's index. The results showed that diversity index decreased when distance from road edge increases. This decreasing trend continued up to 60 m from forest road margin, and after this threshold, the index slightly increased. Depending on the type of road (main or secondary) as well as cut or fill slopes, the area showing a statistical different plant composition and diversity measured through Shannon-Wiener, species richness, and Pielou's index is up to 10 m. The length depth of the road edge effect found in main and secondary forest roads was small, but it could have cumulative effects on forest microclimate and forest-associated biota at the island scale. Forest managers should account for the effect of road buildings on plant communities.