Search Results (1,986)

With the wide application of airdrop technology in rescue activities in civil and aerospace fields, the importance of accurate airdrop is increasing. This work comprehensively analyzes the interactive mechanisms among multiple models affecting airdrops, including wind field distribution, drag force effect, and the parachute opening process. By integrating key parameters across various dimensions of these models, a multidimensional parameter dynamic evolution (MPDE) target prediction method for aerial delivery parachutes in radar-detected wind fields is proposed, and the Runge–Kutta method is applied to dynamically solve for the final landing point of the target. In order to verify the performance of the method, this work carries out field airdrop experiments based on the radar-measured meteorological data. To evaluate the impact of model input errors on prediction methods, this work analyzes the influence mechanism of the wind field detection error on the airdrop prediction method via the Relative Gain Array (RGA) and verifies the analytical results using the numerical simulation method. The experimental results indicate that the optimized MPDE method exhibits higher accuracy than the widely used linear airdrop target prediction method, with the accuracy improved by 52.03%. Additionally, under wind field detection errors, the linear prediction method demonstrates stronger robustness. The airdrop error shows a trigonometric relationship with the angle between the synthetic wind direction and the heading, and the phase of the function will shift according to the difference in errors. The sensitivity of the MPDE method to wind field errors is positively correlated with the size of its object parachute area. Full article

This study examines the complex interactions among soil moisture, evaporation, extreme weather events, and lightning, and their influence on fire activity across the extratropical and Pan-Arctic regions. Leveraging reanalysis and remote-sensing datasets from 2000 to 2020, we applied cross-correlation analysis, a modified Mann–Kendall trend test, and assessments of interannual variability to key variables including soil moisture, fire frequency and risk, evaporation, and lightning. Results indicate a significant increase in dry days (up to 40%) and heatwave events across Central Eurasia and Siberia (up to 50%) and Alaska (25%), when compared to the 1980–2000 baseline. Upward trends have been detected in evaporation across most of North America, consistent with soil moisture trends, while much of Eurasia exhibits declining soil moisture. Fire danger shows a strong positive correlation with evaporation north of 60° N (r ≈ 0.7, p ≤ 0.005), but a negative correlation in regions south of this latitude. These findings suggest that in mid-latitude ecosystems, fire activity is not solely driven by water stress or atmospheric dryness, highlighting the importance of region-specific surface–atmosphere interactions in shaping fire regimes. In North America, most fires occur in temperate grasslands, savannas, and shrublands (47%), whereas in Eurasia, approximately 55% of fires are concentrated in forests/taiga and temperate open biomes. The analysis also highlights that lightning-related fires are more prevalent in Eastern Europe and Southeastern Asia. In contrast, Western North America exhibits high fire incidence in temperate conifer forests despite relatively low lightning activity, indicating a dominant role of anthropogenic ignition. These findings underscore the importance of understanding land–atmosphere interactions in assessing fire risk. Integrating surface conditions, climate extremes, and ignition sources into fire prediction models is crucial for developing more effective wildfire prevention and management strategies. Full article

Many contemporaries considered the crusader conquest of Jerusalem in 1099 as a significant moment in Salvation History. This article investigates how the reception of the Roman conquest of the city (70 CE) contributed to such an understanding. The important Benedictine exegete Rupert of Deutz (c. 1070–1129) refers to the Roman conquest in 79 passages within his opus, notably in his various biblical commentaries. This case study shows how the past event provided a rationale, exegetical and providential in nature, to understand three dimensions: (a) the role of the Jews, especially that it had been necessary to deprive them of the Holy Land; (b) the current situation of and purpose of Christians in the Holy Land; and (c) the End of Time, which was expected in Jerusalem, and which Rupert anchored already significantly in his own present. His commentary on John’s Revelation even asserted that the Roman conquest had opened the sixth of seven seals (Rev. 6:12). Therefore, the Apocalypse had been ongoing since 70 CE—but only in the Holy Land, a fact that made it necessary for Christians to travel there. The article thus demonstrates that biblical commentaries are potent sources for both crusade studies and historical research in general. Full article

Agriculture accounts for 29% of the Gross Domestic Product of the Nusa Tenggara Islands (NTIs). However, recurring agricultural droughts pose a major threat to the sustainability of agriculture in this region. The interplay between precipitation, solar radiation, and surface temperature as meteorological factors plays a key role in affecting vegetation (Soil-Adjusted Vegetation Index) and agricultural drought (Temperature Vegetation Dryness Index) in the NTIs. Based on the analyses of interplay with temporal lag, this study investigates the effect of each factor on agricultural drought and attempts to provide early warnings regarding drought in the NTIs. We collected surface information data from Moderate-Resolution Imaging Spectroradiometer (MODIS). Meanwhile, rainfall was estimated from Himawari-8 based on the INSAT Multi-Spectral Rainfall Algorithm (IMSRA). The results showed reliable performance for 8-day and monthly scales against gauges. The drought analysis results reveal that the NTIs suffer from mild-to-moderate droughts, where cropland is the most vulnerable, causing shifts in the rice cropping season. The driving factors could also explain >60% of the vegetation and surface-dryness conditions. Furthermore, our monthly and 8-day TVDI estimation models could capture spatial drought patterns consistent with MODIS, with coefficient of determination (R²) values of more than 0.64. The low error rates and the ability to capture the spatial distribution of droughts, especially in open-land vegetation, highlight the potential of these models to provide an estimation of agricultural drought. Full article

Soil available nitrogen (AN) is a critical nutrient for plant absorption and utilization. Accurately mapping its spatial distribution is essential for improving crop yields and advancing precision agriculture. In this study, 188 AN soil samples (0–20 cm) were collected at Heshan Farm, Nenjiang County, Heihe City, Heilongjiang Province, in 2023. The soil available nitrogen content ranged from 65.81 to 387.10 mg kg⁻¹, with a mean value of 213.85 ± 61.16 mg kg⁻¹. Sentinel-2 images and normalized vegetation index (NDVI) and enhanced vegetation index (EVI) time series data were acquired on the Google Earth Engine (GEE) platform in the study area during the bare soil period (April, May, and October) and the growth period (June–September). These remote sensing variables were combined with soil sample data, crop type information, and crop growth period data as predictive factors and input into a Random Forest (RF) model optimized using the Optuna hyperparameter tuning algorithm. The accuracy of different strategies was evaluated using 5-fold cross-validation. The research results indicate that (1) the introduction of growth information at different growth periods of soybean and maize has different effects on the accuracy of soil AN mapping. In soybean plantations, the introduction of EVI data during the pod setting period increased the mapping accuracy R² by 0.024–0.088 compared to other growth periods. In maize plantations, the introduction of EVI data during the grouting period increased R² by 0.004–0.033 compared to other growth periods, which is closely related to the nitrogen absorption intensity and spectral response characteristics during the reproductive growth period of crops. (2) Combining the crop types and their optimal period growth information could improve the mapping accuracy, compared with only using the bare soil period image (R² = 0.597)—the R² increased by 0.035, the root mean square error (RMSE) decreased by 0.504%, and the mapping accuracy of R² could be up to 0.632. (3) The mapping accuracy of the bare soil period image differed significantly among different months, with a higher mapping accuracy for the spring data than the fall, the R² value improved by 0.106 and 0.100 compared with that of the fall, and the month of April was the optimal window period of the bare soil period in the present study area. The study shows that when mapping the soil AN content in arable land, different crop types, data collection time, and crop growth differences should be considered comprehensively, and the combination of specific crop types and their optimal period growth information has a greater potential to improve the accuracy of mapping soil AN content. This method not only opens up a new technological path to improve the accuracy of remote sensing mapping of soil attributes but also lays a solid foundation for the research and development of precision agriculture and sustainability. Full article

In water-scarce regions such as Jordan, accurate tracking of water flows is critical for informed water management. This study applied the Water Accounting Plus (WA+) framework using open-source remote sensing data from the FAO WaPOR portal to develop agricultural water accounting (AWA) for the Amman–Zarqa Basin (AZB) during 2014–2022. Inflows, outflows, and water consumption were quantified using WaPOR and other open datasets. The results showed a strong correlation between WaPOR precipitation (P) and rainfall station data, while comparisons with other remote sensing sources were weaker. WaPOR evapotranspiration (ET) values were generally lower than those from alternative datasets. To improve classification accuracy, a correction of the WaPOR-derived land cover map was performed. The revised map achieved a producer’s accuracy of 15.9% and a user’s accuracy of 86.6% for irrigated areas. Additionally, ET values over irrigated zones were adjusted, resulting in a fivefold improvement in estimates. These corrections significantly enhanced the reliability of key AWA indicators such as basin closure, ET fraction, and managed fraction. The findings demonstrate that the accuracy of P and ET data strongly affects AWA outputs, particularly the estimation of percolation and beneficial water use. Therefore, calibrating remote sensing data is essential to ensure reliable water accounting, especially in agricultural settings where data uncertainty can lead to misleading conclusions. This study recommends the use of open-source datasets such as WaPOR—combined with field validation and calibration—to improve agricultural water resource assessments and support decision making at basin and national levels. Full article

Rapid urbanization in China has driven substantial rural population out-migration, raising concerns about its implications for the governance of land commons in villages. While existing studies have acknowledged the effects of migration on rural resource management, little attention has been paid to its influence on the self-governance of rural public open spaces (POSs). This study adopts the social–ecological systems (SES) framework to examine how rural out-migration shapes POS self-governance mechanisms. Based on survey data from 594 villagers across 198 villages in Taigu District, partial least squares structural equation modeling (PLS-SEM) and a mediation model grounded in the SES framework were employed for analysis. The results indicate that rural out-migration does not exert a direct impact on POS self-governance. Instead, it negatively influences governance outcomes through full mediation by villager organizations, the left-behind population, collective investment in POSs, and self-organizing activities. Notably, the mediating roles of the left-behind population and self-organizing activities account for 67.38% of the total effect, underscoring their critical importance. Drawing on these insights, the study proposes four policy recommendations to strengthen rural POS self-governance under conditions of demographic transition. This research contributes to the literature by being the first to incorporate an external social factor—rural out-migration—within the SES framework in the context of POS governance, thereby advancing both theoretical and practical understandings of rural commons management. Full article

In the case of forest inventory, heterogeneous areas are particularly challenging due to variability in vegetation structure. This is especially true in Galicia (northwest Spain), where land is highly fragmented, complicating the planning and management of single-species plantations such as Pinus radiata. This study proposes a cost-effective strategy using open-access tools and data to characterize and estimate wood volume in these plantations. Two stratification approaches—classical and cluster-based—were compared to a modeling method based on Principal Component Analysis (PCA). Data came from open-access national LiDAR point clouds, acquired using manned aerial vehicles under the Spanish National Aerial Orthophoto Plan (PNOA). Moreover, two volume estimation methods were applied: one from the Xunta de Galicia (XdG) and another from Spain’s central administration (4IFN). A Generalized Linear Model (GLM) was also fitted using PCA-derived variables with logarithmic transformation. The results show that although overall volume estimates are similar across methods, cluster-based stratification yielded significantly lower absolute errors per hectare (XdG: 28.04 m³/ha vs. 44.07 m³/ha; 4IFN: 25.64 m³/ha vs. 38.22 m³/ha), improving accuracy by 7% over classical stratification. Moreover, it does not require precise field parcel locations, unlike PCA modeling. Both official volume estimation methods tended to overestimate stock by about 10% compared to PCA. These results confirm that clustering offers a practical, low-cost alternative that improves estimation accuracy by up to 18 m³/ha in fragmented forest landscapes. Full article

We investigated the combined effects of climate and land-use change on plant diversity in northwestern Greece, a region representative of broader European trends in land abandonment. We based our study on comprehensive field data on plants’ distribution and modelling of land-use changes based on socio-economic trends. We build distribution models for 358 taxa based on current (2015) and future (2055) conditions according to the combinations of three climate and three land-use change scenarios. We compared species distribution changes between current and future conditions for each scenario, and we investigated species trends concerning their ecological indicator values and strategies. Additionally, by analyzing the distribution changes in aggregated differential taxa representing the various plant communities in the study area, we identified patterns of distribution shifts at the community level. Our results indicated more pronounced differences between land-use scenarios than between climate ones, which was attributed to the local scale of the study area, its climatic and physiographic characteristics, and its complex land-use legacy. Both climate and land-use changes drastically reduced the distribution of some species, with species distribution loss exceeding 80% under certain combinations of socioeconomic and climate change scenarios. Species ecological indicator values and strategies showed a buffering effect of forest microclimate against climate change, which, however, may favor only species of forest communities. At the community level, land-use change had again a stronger impact than climate change, with consistent patterns within major vegetation types (forests and open habitats) but contrasting trends between them. Our results highlight the need for appropriate conservation plans to counteract the negative impacts of land abandonment and to take advantage of its positive impacts. Full article

Rural landscapes play a key role in preserving ecological processes, cultural identity, and socio-economic well-being, yet these areas often face challenges such as land degradation, water scarcity, and an inadequate road network. A sustainable approach to rural landscape and tourism planning is essential for enhancing both environmental resilience and socio-economic vitality in areas facing degradation and global change. This study aims to develop and validate an integrated methodological workflow that combines Landscape Character Assessment (LCA), ECOVAST guidelines, SWOT analysis, and open-source GIS techniques, complemented by a bottom-up approach of spontaneous fruition mapped through Wikiloc heatmaps. The framework was applied to a case study in Paternò, Eastern Sicily, Italy—a territory distinguished by its key local values such as Calanchi formations, proximity to Mount Etna, and cultural heritage. Through this application, eight distinct Landscape Units (LUs) were delineated, and key strengths, weaknesses, opportunities, and threats for sustainable development were identified. Using open-access data and a survey-free protocol, this approach facilitates detailed landscape assessment without extensive fieldwork. The methodology is readily transferable to other rural Italian and Mediterranean contexts, providing practical guidance for researchers, planners, and stakeholders engaged in sustainable tourism development and landscape management. Full article

This study, conducted within the SteamBioAfrica project, assessed the potential of Digital Soil Mapping (DSM) to estimate Soil Organic Carbon (SOC) across key regions of southern Africa: Otjozondjupa and Omusati (Namibia), Chobe (Botswana), and KwaZulu-Natal (South Africa). Random Forest (RF) models were implemented in the Google Earth Engine (GEE) environment, integrating multi-source datasets including real-time Sentinel-2 imagery, topographic variables, climatic data, and regional soil samples. Three model configurations were evaluated: (A) climatic, topographic, and spectral data; (B) topographic and spectral data; and (C) spectral data only. Model A achieved the highest overall accuracy (R² up to 0.78), particularly in Otjozondjupa, whereas Model B resulted in the lowest RMSE and MAE. Model C exhibited poorer performance, underscoring the importance of multi-source data integration. SOC variability was primarily influenced by elevation, precipitation, temperature, and Sentinel-2 bands B11 and B8. However, data scarcity and inconsistent sampling, especially in Chobe, reduced model reliability (R²: 0.62). The originality of this study lay in the scalable integration of real-time Sentinel-2 data with regional datasets in an open-access framework. The resulting SOC maps provided actionable insights for land-use planning and climate adaptation in savanna ecosystems. Full article

For the first time, the numerous scattered data on birds (wild and domestic) have been collected based on their medieval bone remains discovered on the modern territory of the Republic of Bulgaria. The collected information is about a total of 37 medieval settlements from the time of the First and Second Bulgarian Empires. Among the settlements studied are both the two medieval Bulgarian capitals (Pliska and Veliki Preslav), as well as other cities, smaller settlements, military fortresses, monasteries, and inhabited caves. The data refer to a total of 48 species of wild birds and 6 forms of domestic birds of 11 avian orders: Accipitriformes, Anseriformes, Ciconiiformes, Columbiformes, Falconiformes, Galliformes, Gruiformes, Otidiformes, Passeriformes, Pelecaniformes, and Strigiformes. The established composition of wild birds amounts to over one tenth (to 11.5%) of the modern avifauna in the country. Five of the established species (10.4%) have disappeared from the modern nesting avifauna of the country—the bearded vulture, the great bustard, the little bustard, the gray crane, and the saker falcon (the latter two species have reappeared as nesters in the past few years). First Bulgarian Empire (681–1018): Investigated settlements—22. Period covered—five centuries (7th to 11th c.). Found in total: at least 44 species/forms of birds, of which 39 species of wild birds and 5 forms of poultry. Second Bulgarian Empire (1185–1396): Investigated settlements—15. Period covered—3 centuries (12th to 14th c.). Found in total: at least 39 species/forms of birds, of which 33 species of wild birds and 6 forms of poultry. The groups of raptors, water, woodland, openland, synanthropic and domestic birds were analyzed separately. The conclusion was made that during the two periods of the Middle Ages, birds had an important role in the material and spiritual life of the population of the Bulgarian lands. Birds were mainly used for food (domestic birds), although some were objects of hunting. No traces of processing were found on the bones. Birds were subjects of works of applied and monumental art. Their images decorated jewelry, tableware, walls of buildings and other structures. Full article

Large-scale land restoration projects require on-the-ground monitoring and evidence-based evaluation. This study, part of the World Bank Burundi Landscape Restoration and Resilience Project (in French: Projet de Restauration et de Résilience du Paysage du Burundi-PRRPB), examines the impact of slow-forming terraces on surface conditions and erosion in Isare (Mumirwa) and Buhinyuza (Eastern Depressions), Burundi. Slow-forming, or progressive, terraces were installed on 16 December 2022 (Isare) and 30 December 2022 (Buhinyuza), featuring ditches and soil bunds to enhance soil and water conservation. Twelve plots were established, with 132 measurement pins, of which 72 were in non-terraced plots (n_PT) and 60 were in terraced plots (PT). Monthly measurements, conducted until May 2023, assessed erosion reduction, surface conditions, roughness, and soil thickness. Terracing reduced soil loss by 54% in Isare and 9% in Buhinyuza, though sediment accumulation in ditches was excessive, especially in n_PT. Anti-erosion ditches improved surface stability by reducing slope length, lowering erosion and runoff. Covered Surface (CoS%) exceeded 95%, while Opened Surface (OS%) and Bare Surface (BS%) declined significantly. At Isare, OS% dropped from 97% to 80%, and BS% from 96% to 3% in PT. Similar trends appeared in Buhinyuza. Findings highlight PRRPB effectiveness in this short-term timeframe, and provide insights for soil conservation in steep-slope regions of Central Africa. Full article

This study investigates the anthropogenic transformation of small- and medium-sized river basins within the Caspian Sea catchment. The basins of seven rivers—Sunzha, Sulak, Ulluchay, Karachay, Atachay, Haraz, and Gorgan—were selected as key study areas. For both the broader Caspian region, particularly its southwestern sector, and the selected study sites, trends in land cover types were analyzed, natural resource use practices were assessed, and population density dynamics were examined. Furthermore, a range of indices were calculated to quantify the degree of anthropogenic transformation, including the coefficient of anthropogenic transformation, the land degradation index, the urbanity index, the degree of anthropogenic transformation, coefficients of absolute and relative tension of the ecological and economic balance, and the natural protection coefficient. The study was conducted using geoinformation research methods and sets of geodata databases—the global LandScan population density database, the GHS Population Grid database, the ESRI land cover type dynamics database, and OpenStreetMap (OSM) data. The analysis was performed using the geoinformation programs QGIS and ArcGIS, and a large amount of literary and statistical data was additionally analyzed. It is shown that within the studied region, there has been a decrease in the number and density of the population, as a result of which the territories of river basins are experiencing an increasing anthropogenic impact, the woody type of land cover is decreasing, and the agricultural type is increasing. The most anthropogenically transformed river basins are Karachay, Haraz, and Gorgan. Full article

Land surface models (LSMs) play a crucial role in climate prediction and carbon cycle assessment. To ensure their reliability, it is crucial to evaluate their performance in simulating key processes, such as evapotranspiration (ET) and gross primary productivity (GPP), across various temporal scales and vegetation types. This study systematically evaluates the performance of the newly modernized Noah-MP LSM version 5.0 in simulating water and carbon fluxes, specifically ET and GPP, across temporal scales ranging from half-hourly (capturing diurnal cycles) to annual using observational data from 105 sites within the globally FLUXNET2015 dataset. The results reveal that Noah-MP effectively captured the overall variability of both ET and GPP, particularly at short temporal scales. The model successfully simulated the diurnal and seasonal cycles of both fluxes, though cumulative errors increased at the annual scale. Diurnally, the largest simulation biases typically occurred around noon; while, seasonally, biases were smallest in winter. Performance varied significantly across vegetation types. For ET, the simulations were most accurate for open shrublands and deciduous broadleaf forests, while showing the largest deviation for woody savannas. Conversely, GPP simulations were most accurate for wetlands and closed shrublands, showing the largest deviation for evergreen broadleaf forests. Furthermore, an in-depth analysis stratified by the climate background revealed that ET simulations failed to capture inter-annual variability in the temperate and continental zones, while GPP was severely overestimated in arid and temperate climates. This study identifies the strengths and weaknesses of Noah-MP in simulating water and carbon fluxes, providing valuable insights for future model improvements. Full article