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The expanding use of civilian unmanned aerial vehicles (UAVs) has brought forth a crucial need to address the safety risks they pose in the event of failure, especially when flying in populated areas. This paper reviews recent advancements in recovery systems designed for the emergency landing of civilian UAVs. It covers a wide range of recovery methods, categorizing them based on different recovery approaches and UAV types, including multirotor and fixed-wing. The study highlights the diversity of recovery strategies, ranging from parachute and airbag systems to software-based methods and hybrid solutions. It emphasizes the importance of considering UAV-specific characteristics and operational environments when selecting appropriate safety systems. Furthermore, by comparing various emergency landing systems, this study reveals that integrating multiple approaches based on the UAV type and mission requirements can achieve broader cover of emergency situations compared to using a single system for a specific scenario. Examples of UAVs that utilize emergency landing systems are also provided. For each recovery system, three key parameters of operating altitude, flight speed and added weight are presented. Researchers and UAV developers can utilize this information to identify a suitable emergency landing method tailored to their mission requirements and available UAVs. Based on the key trends and challenges found in the literature, this review concludes by proposing specific, actionable recommendations. These recommendations are directed towards researchers, UAV developers, and regulatory bodies, and focus on enhancing the safety of civilian UAV operations through the improvement of emergency landing systems. Full article

To investigate the influence of factors such as tourism, agriculture, and population density on the presence of microplastic (MP) content in aquatic environments and their associated ecological risks, Jingpo Lake, a remote high-mountain lake situated away from urban areas, was selected as the research subject. This study examined the abundance, types, sizes, colors, and polymer compositions of MPs within the water body, fish, and sediments. By considering variables, including fishing practices, agricultural activities, population dynamics, and vegetation cover, an analysis was conducted to unravel the spatial and temporal distribution of MPs concerning human activities, ultimately leading to an assessment of the ecological risks posed by MP pollution. The findings revealed that the average abundance of MPs in the lake’s surface water was recorded as (304.8 ± 170.5) n/m³, while in the sediments, it averaged (162.0 ± 57.45) n/kg. Inside the digestive tracts of fish, the MP abundance was measured at 11.4 ± 5.4 n/ind. The contamination of MPs within the aquatic environment of Jingpo Lake was found to be relatively minimal. Variations in MP loads across time and space were observed, with MPs predominantly falling within the size range of small planktonic organisms (50–1000 μm). Additionally, the prevalent colors of MPs in the water samples were white or transparent, constituting approximately 55.65% of the entire MP composition. Subsequently, they were black, red, and blue. This colors distribution were consistent across MPs extracted from fish and sediment samples. The chemical compositions of the MPs predominantly comprised PE (31.83%) and PS (25.48%), followed by PP (17.56%), PA (11.84%), PET (6.71%), EVA (4.56%), and PC (2.03%). Regarding the seasonal aspect, MP concentrations were highest during summer (46.68%), followed by spring (36.75%) and autumn (16.56%). The spatial distribution of MPs within Jingpo Lake’s water body, fish, and sediments was notably influenced by human activities, as confirmed by Pearson correlation coefficients. A strong association was observed between MP levels and water quality indicators such as ammonium nitrogen (NH₄-N), total phosphorus (TP), and chlorophyll-a (Chla), suggesting that human-related pollution contributed significantly to MP contamination. The diversity assessment of MP pollutants exhibited the highest variability in chemical composition (1.23 to 1.79) using the Shannon–Wiener Index. Subsequently, the diversity of colors ranged from 0.59 to 1.54, shape diversity from 0.78 to 1.30, seasonal diversity from 0.83 to 1.10, and size diversity from 0.44 to 1.01. The assessment results of ecological risk highlighted that the risk categories for MPs within the surface water, fish, and sediments of Jingpo Lake were categorized as I for the PHI and PLI and as “Minor” for the PERI. These relatively low-risk values were attributed to the predominantly low toxicity of the distributed MPs within the Jingpo Lake basin. Moreover, the results of the risk assessment were found to be interconnected with the distribution of the local population and agricultural activities around the sampling sections. Usage patterns of coastal land and population density were recognized as influential factors affecting MP loads within the water body, sediments, fish, and other components of the lake ecosystem. Full article

Human activities and climate change have accelerated land use and land cover change (LUCC) globally, diminishing the ecosystem service value (ESV) in ecologically fragile areas such as highly mountainous canyons and disrupting the human–nature balance. However, existing research lacks analysis on the impact of land use changes on ecosystem service value in typical counties with highly mountainous canyon regions. Therefore, we aim to address this gap by analyzing land use changes and their driving factors in Chayu County using multi-year land use data, calculating the ecosystem service value (ESV) for different periods, and estimating its spatial correlation and stability. The results showed the following: (1) Forestland and grassland were the predominant land-use types, with notable conversions between grassland and water bodies, grassland and unused land, and water bodies and unused land. (2) The total ESV increased steadily from 2003 to 2023, with higher values in the north and west and lower values in the central east. Forestland and water areas were the primary contributors to ESV changes, and ESV sensitivity to LUCC steadily increased from 0.46% to 2.49%. (3) Moran’s I ESV shows an overall increase, with a heightened correlation and enhanced stability. Spatially, the ESV exhibited a general high–high and low–low clustering pattern, with localized high–low and low–high clusters. These changes, driven by natural resource endowments and climate change, provide essential support for ecological protection and sustainable development in highly mountainous canyons and similar regions. Full article

The Qinghai Plateau has a complex geographical environment and vast amounts of land with a sparse population, dispersed settlements, and a low traffic density. In the face of major disasters, the rational layout of emergency material reserve warehouses is crucial for reducing disaster losses, ensuring regional stability, and quickly restoring production and life. This paper starts by considering the rationality and timeliness of the location selection of provincial emergency material reserve warehouses, considering the distance costs of emergency material transportation on the Qinghai Plateau. By using a traffic accessibility analysis model combined with a location–allocation model and an L-A maximum coverage model, this study optimizes the location selection of emergency material reserve warehouses on the Qinghai Plateau. The research results show the following: (1) On the basis of the existing Golmud Depot and Chengxi Depot in Qinghai Province, it is necessary to add four more depots, i.e., the Yushu Depot, Gande Depot, Ping’an Depot, and Tongde Depot, to achieve the timely and efficient supply of emergency materials. (2) After the optimization, the layout of the six provincial emergency material reserve warehouses can achieve full coverage of Qinghai Province within 8 h in the event of major disasters, increasing the coverage by 20% compared to the original layout; the new plan allows for emergency material transportation to cover 87% of Qinghai Province within 4 h, an increase of 28% compared to before. (3) The optimized location selection plan for emergency material reserve warehouses saves 139 min of time costs, and the transportation efficiency is increased by 46% compared to the previous plan. The optimized location selection plan for emergency material reserve warehouses is instructive for the construction of emergency material reserve warehouses on the Qinghai–Tibet Plateau. Full article

Land desertification management in the Mu Us Desert has received widespread attention. Assessing land desertification sensitivity is crucial for desertification monitoring and management. This study constructed a comprehensive evaluation index system using four factors: dryness index, the number of windy and sandy days in the winter and spring, soil texture, and vegetation cover. Land sand sensitivity was divided into five grades, and multi-source data from the Ecological Functional Reserve of the Mu Us Desert from 2002 to 2022 were used to study spatial distribution and dynamic changes. The results show the following: (1) the overall land desertification sensitivity in the Mu Us Desert Ecological Functional Reserve decreased from 2002 to 2022, with the proportion of highly sensitive land decreasing from 92.39% to 82.75%, and the proportion of medium-, medium–low-, and low-sensitivity areas increasing from 0.63% to 1.70%. (2) Low-sensitivity areas were concentrated in Jingbian County, Hengshan District, and southern Uxin Banner. Southeast Otog Banner and northern Jingbian County saw the most significant decreases in land desertification sensitivity since 2002. (3) The four selected factors interacted, with increased vegetation cover being the most crucial factor. This study provides a reference for future ecological restoration in the Mu Us Desert area. Full article

Change detection, as a popular research direction for dynamic monitoring of land cover change, usually uses hyperspectral remote-sensing images as data sources. Hyperspectral images have rich spatial–spectral information, but traditional change detection methods have limited ability to express the features of hyperspectral images, and it is difficult to identify the complex detailed features, semantic features, and spatial–temporal correlation features in two-phase hyperspectral images. Effectively using the abundant spatial and spectral information in hyperspectral images to complete change detection is a challenging task. This paper proposes a hyperspectral image change detection method based on the balanced metric, which uses the spatiotemporal attention module to translate bi-temporal hyperspectral images to the same eigenspace, uses the deep Siamese network structure to extract deep semantic features and shallow spatial features, and measures sample features according to the Euclidean distance. In the training phase, the model is optimized by minimizing the loss of distance maps and label maps. In the testing phase, the prediction map is generated by simple thresholding of distance maps. Experiments show that on the four datasets, the proposed method can achieve a good change detection effect. Full article

Lakes are critical resources that support the ecological balance and provide essential services for human and environmental well-being. However, their quality is being increasingly threatened by both natural and anthropogenic processes. This study aimed to assess the water quality and the presence of heavy metals in 15 lakes in the Vidarbha and Marathwada regions of Maharashtra, India. To understand the extent of pollution and its sources, the physico-chemical parameters were analyzed which included pH, turbidity, total hardness, orthophosphate, residual free chlorine, chloride, fluoride, and nitrate, as well as heavy metals such as iron, lead, zinc, copper, arsenic, chromium, manganese, cadmium, and nickel. The results revealed significant pollution in several lakes, with the Lonar Lake showing a pH value of 12, exceeding the Bureau of Indian Standards’ (BIS) limit. The Lonar Lake also showed elevated levels of fluoride having a value of 2 mg/L, nitrate showing a value of 45 mg/L, and orthophosphate showing a concentration up to 2 mg/L. The Rishi Lake had higher concentrations of nickel having a value of 0.2 mg/L and manganese having a value of 0.7 mg/L, crossing permissible BIS limits. The Rishi Lake and the Salim Ali Lake exhibited higher copper levels than other lakes. Cadmium was detected in most of the lakes ranging from values of 0.1 mg/L to 0.4 mg/L, exceeding BIS limits. The highest turbidity levels were observed in Rishi Lake and Salim Ali Lake at 25 NTU. The total hardness value observed in the Kharpudi Lake was 400 mg/L, which is highest among all the lakes under study. The spatial analysis, which utilized remote sensing and GIS techniques, including Sentinel-2 multispectral imagery for land use and land cover mapping and Digital Elevation Model (DEM) for watershed delineation, provided insights into the topography and drainage patterns affecting these lakes. The findings emphasize the urgent need for targeted management strategies to mitigate pollution and protect these vital freshwater ecosystems, with broader implications for public health and ecological sustainability in regions reliant on these water resources. Full article

The connectivity of forest ecosystems is increasingly recognized as a key factor in evaluating the sustainability of forest management, with significant implications for biodiversity conservation. This study examines the impact of afforestation programs on forest evolution, fragmentation, and connectivity in León province, Spain, over the past 25 years (1996–2020). Three scenarios were modeled across two periods (1996–2006 and 2006–2020), integrating data from the national forest inventories (IFN2, IFN3, and IFN4) and afforestation program records provided by the Junta de Castilla y León. The evolution of connectivity “with” and “without” afforestation was analyzed using Graphab 2.6 and graph theory, and several connectivity metrics were calculated. The first period analyzed, influenced by the two initial afforestation programs, corresponded to the end of a forest expansion phase, followed by a decrease in tree cover. Despite this reduction, a net positive balance of up to 24% of all connectivity metrics (NC, PC, Flux, and ECA) was observed throughout the study period. Afforestation in mountain areas enhanced tree cover continuity, resulting in a more homogeneous but less diverse landscape. Conversely, afforestation in agricultural lands increased landscape heterogeneity, diversifying and extending the ecological network of connections. These programs have played a crucial role in shaping the landscape, influencing its diversity and the evolution of forest connectivity. Legislation grounded in technical and ecological principles should be prioritized as a strategic tool to address pressing land management challenges and preserve natural values. Full article

This study analyzed the changes in landscape patterns and the ecological health status of karst plateau wetlands, providing valuable insights into their conservation. Using land cover data from 1996 to 2021, DEM, and Landsat series satellite imagery, this study employed landscape ecology methods and the pressure–state–response (PSR) model framework. A regional landscape grid was constructed, and 13 indicators were selected to establish an ecological health evaluation system for karst plateau wetlands. This allowed us to explore the spatiotemporal change characteristics of the landscape pattern and the ecological health of karst plateau wetlands. The results showed that over a 25-year period, farmland, grassland, and construction land areas have increased, whereas forested land areas have decreased. Water bodies remained relatively stable but showed a trend of transitioning into grassland. Unused land showed no significant change. Landscape analysis indicated that grasslands experience the highest rate of fragmentation, complex shapes, and greater heterogeneity, whereas water bodies have the lowest fragmentation, more regular shapes, and lower heterogeneity. Other landscape types exhibited moderate characteristics. Overall, the landscape of the study area exhibited high fragmentation, specific patch aggregation, moderate patch density, and low diversity. A comprehensive ecological health evaluation revealed that the wetland health value remained at an “unhealthy” level from 1996 to 2021. Although there was a brief improvement in 2010, effective long-term recovery was not achieved. Spatially, the proportion of “diseased” areas peaked in 2006, and most grid zones remained in an “unhealthy” state over the years, with none reaching the “healthy” standard. These findings highlight the severe challenges faced by the wetland ecosystem. Full article

Wet rainfall pulses control vegetation growth through evapotranspiration in most dryland areas. This topic has not been extensively analyzed with respect to the vast semi-arid ecosystems of Central Australia. In this study, we investigated vegetation water responses to in situ root zone soil moisture (SM) variations in savanna woodlands (Mulga) in Central Australia using satellite-based optical and thermal data. Specifically, we used the Land Surface Water Index (LSWI) derived from the Advanced Himawari Imager on board the Himawari 8 (AHI) satellite, alongside Land Surface Temperature (LST) from MODIS Terra and Aqua (MOD/MYD11A1), as indicators of vegetation water status and surface energy balance, respectively. The analysis covered the period from 2016 to 2021. The LSWI increased with the magnitude of wet pulses and showed significant lags in the temporal response to SM, with behavior similar to that of the Enhanced Vegetation Index (EVI). By contrast, LST temporal responses were quicker and correlated with daily in situ SM at different depths. These results were consistent with in situ relationships between LST and SM, with the decreases in LST being coherent with wet pulse magnitude. Daily LSWI and EVI scores were best related to subsurface SM through quadratic relationships that accounted for the lag in vegetation response. Tower flux measures of gross primary production (GPP) were also related to the magnitude of wet pulses, being more correlated with the LSWI and EVI than LST. The results indicated that the vegetation response varied with SM depths. We propose a conceptual model for the relationship between LST and SM in the soil profile, which is useful for the monitoring/forecasting of wet pulse impacts on vegetation. Understanding the temporal changes in rainfall-driven vegetation in the thermal/optical spectra associated with increases in SM can allow us to predict the spatial impact of wet pulses on vegetation dynamics in extensive drylands. Full article

Land Use and Land Cover (LULC) assessment is vital for achieving sustainable ecosystems. This study quantified and mapped the spatiotemporal LULC changes in Ado-Odo Ota Local Government Area of Ogun State, Nigeria, between 2015 and 2023. The LULC was classified into water, forest or thick bush, sparse vegetation, built-up, and bare land using Landsat images. Processing, classification, and image analysis were done using the ESRI ArcGIS Pro 3.3. LULC changed from 2015 to 2023, with built-up areas and sparse vegetation increasing by 138.2 km² and 28.7 km², respectively. In contrast, forest or thick bush, which had the greatest change among the LULC classes, decreased by 153.7 km² over this period while bare land and water bodies decreased by 9.5 km² and 3.8 km², respectively. Forest or thick bush (201.0 km²) was converted to sparse vegetation, which reflects an increase in agricultural activities in the region. The conversion of about 109.8 km² of vegetation and 3.7 km² of water bodies to built-up areas highlights considerable urbanization. Overall, the increase in the built-up area highlights the need for sustainable land use practices to balance urban growth with ecological preservation, achievable through effective management and policy frameworks. Full article

The Amazon biome is frequently targeted by illegal activities, with clandestine mining being one of the most prominent. Due to the dense forest cover, criminals often rely on covert aviation as a logistical tool to supply remote locations and sustain these activities. This work presents an enhancement to a previously developed landing strip detection algorithm tailored for the Amazon biome. The initial algorithm utilized satellite images combined with the use of Convolutional Neural Networks (CNNs) to find the targets’ spatial locations (latitude and longitude). By addressing the limitations identified in the initial approach, this refined algorithm aims to improve detection accuracy and operational efficiency in complex rainforest environments. Tests in a selected area of the Amazon showed that the modified algorithm resulted in a recall drop of approximately 1% while reducing false positives by 26.6%. The recall drop means there was a decrease in the detection of true positives, which is balanced by the reduction in false positives. When applied across the entire biome, the recall decreased by 1.7%, but the total predictions dropped by 17.88%. These results suggest that, despite a slight reduction in recall, the modifications significantly improved the original algorithm by minimizing its limitations. Additionally, the improved solution demonstrates a 25.55% faster inference time, contributing to more rapid target identification. This advancement represents a meaningful step toward more effective detection of clandestine airstrips, supporting ongoing efforts to combat illegal activities in the region. Full article

In the global context, transportation contributes 26% of the total CO₂ emissions, with land transport responsible for 92% of the emissions within the sector. Given this significant contribution to climate change, it is crucial to quantify vehicular impacts to implement effective mitigation strategies. This study introduces an innovative method for predicting fuel consumption and emissions of carbon monoxide, hydrocarbons, and nitrogen oxides in vehicles, based on instantaneous vehicle-specific power (VSP) and mean accumulated power. VSP is a parameter that measures a vehicle’s power in relation to its mass, providing an indicator of the efficiency with which the vehicle converts fuel into motion. This indicator is particularly useful for assessing how vehicles utilize their energy under different driving conditions and how this affects their fuel consumption and emissions. Using data collected from 10 vehicles over 2000 h and covering altitudes from 0 to 4000 m above sea level in Ecuador, the method not only improved the accuracy of consumption predictions, reducing the margin of error by up to 10% at high altitudes, but also provided a detailed understanding of how altitude affects both consumption and emissions. The precision of the new method was notable, with a standard deviation of only 0.25 L per 100 km, allowing for reliable estimates under various operational conditions. Interestingly, the study revealed an average increase in fuel consumption of 0.43 L per 1000 m of altitude gain, while CO₂ emissions showed a significant reduction from 260.93 g/km to 215.90 g/km when ascending from 500 m to 4000 m. These findings underscore the relevance of considering altitude in route planning, especially in mountainous terrains, to optimize performance and environmental sustainability. However, the study also indicated an increase in CO and NOx emissions with altitude, a challenge that highlights the need for integrated strategies addressing both fuel consumption and air quality. Collectively, the results emphasized the complex interplay between altitude, energy efficiency, and vehicular emissions, underscoring the importance of a holistic approach to transportation management, to minimize adverse environmental impacts and promote sustainability. Full article

Globally, ecosystem services face significant degradation due to land use and land cover change (LULC) driven by human development. Despite numerous habitat quality assessments, comprehensive studies in high-mountain equatorial region basins remain scarce. This research addresses assessing habitat quality in Ecuador’s sub-basins of the Aguilán and Tabacay Rivers, with projections extending to 2050. This study considered anthropogenic threats and examined two land use change scenarios. The “Integrated Valuation of Ecosystem Services and Tradeoffs” (InVEST) model was used for the evaluation. A habitat quality index (HQI) was developed and categorized into five classes. The results showed that in 2018, over 50% of the study area had medium, high, and very high habitat quality levels, partly due to implementing policies, such as Reciprocal Water Agreements, developed by local initiatives. However, future projections suggest a declining trend, particularly in urban and cropland areas, highlighting the need to reinforce proactive policies. The findings of this study contribute to addressing existing gaps in habitat quality research in high-mountain regions, providing key scientific evidence to support conservation strategies, land use planning, and watershed management. Full article

Land use and cover change (LUCC) profoundly impacts the carbon cycle and carbon storage. Under the goal of “carbon neutrality”, studying the mechanisms linking LUCC with terrestrial ecosystem carbon storage is of significant importance for ecological protection and regional development. Using the central Shanxi urban agglomeration as a case study, this research employs various quantitative models based on land cover data to analyze changes in LUCC and carbon storage from 2000 to 2035. The study scientifically explores the impact of the spatial and temporal distribution characteristics of LUCC on carbon storage. The study indicates the following: (1) Over the past 20 years, the land types in the central Shanxi urban agglomeration are primarily grassland, cropland, and forest land. The two primary land transformations are the conversion of cropland to grassland and the conversion of grassland to cropland and forest land; (2) The carbon storage in the study area has shown a declining trend over the past two decades. Spatially, this decline exhibits a “two mountains and one valley” distribution pattern influenced by land use types. The reduction of grassland and cropland is the primary reason for the decline in carbon storage; (3) By 2035, under three different scenarios, carbon storage is projected to decrease compared to 2020. Among these, the scenario focused on cropland protection (CP) shows the least decline, while the naturally developing scenario (ND) shows the most significant decline. The research demonstrates that under scenarios of cropland protection and ecological conservation, strategies such as environmental restoration, development of unused land, and reclamation of built-up land for greening significantly enhance regional carbon storage and improve carbon sequestration capacity. Full article