Entire Area Research Articles

Soil Fertility Status of Major Coconut Growing Soils of Tumkur District, Karnataka, India

A study was conducted to assess the soil fertility status of major coconut growing soils of Tumkur district of Karnataka with soil pedon locations being Turuvekere and Gubbi. The results revealed that soils of the study area were slightly to strongly alkaline in reaction and non-saline in nature. The organic carbon content was varying from low to high and it followed decreasing trend with soil depth in both soil profiles (Turuvekere and Gubbi). The clay distribution, cation exchange capacity and base saturation of the soils varied from 17.83 to 60.37 per cent, 8.71 to 28.86 cmol (p+) kg-1 and 75.53 to 93.42 per cent, respectively. The macronutrient status of the soil samples indicated that the available nitrogen and phosphorus varied from low to medium, and available potassium content was varying from low to high. Analysis of secondary nutrients showed that exchangeable calcium and magnesium were found to be sufficient but available sulphur was varying from deficient to sufficient level in these soils. The DTPA extractable micronutrients viz., iron, manganese, zinc and boron were found to be deficient in entire study area where as copper was varying from deficient to adequate level with surface soil having relatively high copper content than subsurface soil.

Disassembly of in-plastic embedded printed electronics

We explored a novel design-for-recycling method for encapsulated printed electronics in an injection-molded package that improves disassembly at End-of-Life (EoL). To this end, a non-adhering disassembly layer (NADL) was applied onto the printed circuitry and light-emitting diodes prior to injection molding. Surprisingly, the devices with a disassembly layer remained fully functional after injection molding, despite exposure to high shear forces and elevated temperatures. Facilitating the disassembly of an encapsulated electronic device using a weak link in the adhesion strength of the overmolded encapsulant invokes a contradiction: the possibility to remove the injected plastic from any underlying coating goes against the requirement of high adhesion over the entire surface area for structural strength and integrity during the harsh conditions expected by industry. To achieve balance between disassemblability and reliability, the adhesion strength of the overmolded encapsulant was tuned using vias in the coating design. To the author's best knowledge, this is the first time design-for-recycling principles were successfully applied to such in-mold structural electronics devices. Accelerated lifetime tests at 85 °C/85% relative humidity for 1000 consecutive hours were conducted to study the reliability of devices realized with this design-for-recycling method. Mechanical disassembly of molded devices proceeded uniformly along the intended interface of NADL with molded polycarbonate resin and exposed the printed Ag and surface-mounted components, thereby demonstrating the possibility to perform subsequent and dedicated recycling on plastics and metals separately.

The green window view index: automated multi-source visibility analysis for a multi-scale assessment of green window views

ContextProviding accessible urban green spaces is crucial for planning and ensuring healthy, resilient, and sustainable cities. The importance of visually accessible urban green spaces increases due to inner urban development processes.ObjectivesThis article proposes a new index, the Green Window View Index (GWVI) for analyzing and assessing visible vegetation, that promotes an integrated planning of urban green spaces and buildings at different scales and levels. It is defined as the proportion of visible vegetation area in a field of view when looking out of a specific window with a defined distance to the window.MethodsThe method for estimating GWVI consists of three steps: (a) the modeling of the three-dimensional environment, (b) the simulation of the two-dimensional window views using modern rendering engines for three-dimensional graphics, (c) the computation of the GWVI. The method is proposed and tested through a case study of the urban area of Bonn, Germany, using a Digital Terrain Model (DTM), CityGML-based semantic 3D City Model at level of detail (LoD) 2, airborne Light Detection and Ranging (LiDAR) data, and 2D land use data from the official German property cadaster information system (ALKIS).ResultsWith an average processing time of 0.05 s per window view, an average GWVI of 26.00% could be calculated for the entire study area and visualized in both 2D and 3D.ConclusionThe proposed engine generates multi-scale visibility values for various vegetation shapes. These values are intended for use in participatory citizenship and decision-making processes for analysis by architects, real-estate appraisers, investors, and urban as well as landscape planners.

Shallow Hard-Bottom Benthic Assemblages of South Bay (Antarctic Peninsula): An Update 40 Years Later

This work completes and updates the information about the diversity and distribution of benthic assemblages in an Antarctic fjord (South Bay, Antarctic Peninsula) 40 years after the first and only community-level study was conducted there. To determine the community changes, a photographic survey was conducted at four sites with different substrate inclinations along a bathymetric gradient of 5–20 m depth. In total, 160 photoquadrats were analyzed, resulting in a total area of 40 m2. Sixty taxa represented by 12 phyla were identified, of which eight phyla corresponded to animals. The remaining species corresponded to macroalgae and benthic diatoms, both taxa presenting the highest coverages of the entire study area. The highest richness and diversity values were obtained at greater depths and at the sites with the steepest slopes. Here, we discuss the role of substrate inclination and depth in the structure of the benthic assemblages concerning possible variations in the presence and frequency of physical disturbances (e.g., ice disturbance and sedimentation). The abundances, densities, and distributions of all species found are detailed, updating the ecological data of the benthic ecosystem of this Antarctic fjord from the previously published assessment four decades ago. In a continent where rapid environmental changes are being experienced due to climate-induced processes, we discuss the first massive record of benthic diatoms in this fjord and the striking absence of the sea urchin Sterechinus neumayeri, an abundant species from previous records from the early 1980s.

Crustal deformation in the vicinity of the Tan-Lu Fault Zone in East China constrained by receiver function analyses

To investigate the spatial distribution of crustal deformation and related geodynamic processes associated with the Tan-Lu Fault Zone (TLFZ) in East China, we measured crustal anisotropy based on the sinusoidal moveout of the P-to-S conversions from the Moho observed on receiver functions. Totally 142 well-defined crustal anisotropy measurements were obtained from the China National Seismic Network and other broadband dense seismic stations, including three stations exhibiting the pattern of a double layered anisotropy structure. The fast orientations observed at stations in the vicinity of the TLFZ were dominantly fault-parallel except for the southernmost part of the study area, where the fast orientations were approximately normal to the strike of the fault zone and may primarily be attributed to the NW-SE oriented Dabie Orogenic Belt. In the North China Block, NW-SE fast orientations were found to be consistent with the dominant orientation of the secondary faults. The Lower Yangtze Block showed two dominant fast orientations. The fault-parallel measurements in the west of the Jiangshao Fault Zone were controlled by the NE-trending faults in the Lower Yangtze Block, while the fast orientations in the east and south of the Jiangshao Fault Zone were dominantly E-W, which could be mainly influenced by the regional principal compressive stress. The average delay time of the entire study area was 0.27 ± 0.07 s. In the vicinity of the TLFZ where fault-parallel fast orientations were observed, an approximately 44% increase in delay time was observed, suggesting a well-developed fault zone.

Abundance and potential sources of floating polystyrene foam macro- and microplastics around Japan

Polystyrene foam is widely used due to its lightweight, impact resistance, and excellent thermal insulation properties. Meanwhile, weak adhesion between beads in polystyrene foam leads to fragmentation, generating a substantial amount of microplastics (<5 mm). Such polystyrene foam debris littered on beaches diminishes the aesthetic value of coastal areas, negatively impacting tourism. Due to its density lower than other plastics, polystyrene foam macroplastics float on the sea surface and, thus, they are significantly influenced by wind drag during oceanic transport. In contrast, polystyrene foam microplastics drifting beneath the sea surface are carried mostly by ocean currents. These properties of polystyrene foam macroplastics and microplastics hinder the elucidation of their transport, distribution, and fate in nature, despite their potential to adversely impact marine ecosystems. To elucidate the generation, transport, and fragmentation processes of polystyrene foam ocean plastics, we conducted concurrent visual observations and surface net towing from seven training vessels around Japan during 2014–2020. Overall, the abundances of polystyrene foam ocean plastics were higher in the Sea of Japan than in the North Pacific south of Japan. The average abundances of polystyrene foam microplastics and macroplastics were 0.33 pieces/m3 and 0.45 pieces/km, respectively, over the entire sea area around Japan. In the Sea of Japan, the peak abundances of polystyrene foam macroplastics occurred in upstream of the Tsushima Current, while the peak for microplastics occurred downstream, suggesting that continuous fragmentation occurred during transport between the two peaks. Backward-in-time particle tracking model experiments suggested that the sources of polystyrene foam macroplastics observed in the Sea of Japan included aquaculture buoys and styrene debris beached around the Tsushima Strait. The present study demonstrated that reducing the release of polystyrene foam aquaculture floats will likely diminish the abundance of ocean plastics in the Sea of Japan.

Enhancing river floodplain management with nature‐based solutions: Overcoming barriers and harnessing enablers

AbstractFloodplains are regularly inundated areas of land that provide ecosystem benefits for the entire catchment area, along with numerous benefits for communities making them ideal for human settlement. The management of floodplains involves an ongoing dilemma; how best to balance the need to protect urban settlements from significant flood events with the benefits that inundation brings to the environmental and cultural values of the floodplain. These flood events have been traditionally addressed using technical flood protection measures. However, nature‐based solutions (NbS), provide a potential alternative approach. In this research, we analyze 29 global case studies centered on river floodplain management to investigate the barriers and enablers that affect the implementation of NbS, including floodplain restoration, mangroves, riparian forest restoration, wetland green infrastructure, among other strategies. The aim of this paper is to gain insights into improving floodplain management through the assessment of barriers and enablers evident in these case studies. The barriers and enablers were divided into six categories: social, technical, financial, political, institutional and economic and further into several sub‐divided categories. Social and technical categories were the most commonly described barriers and enablers closely followed by the institutional category. The discussion is centered around four topics: understanding community and decision‐maker risk perceptions, increased focus on stakeholders, managing multiple conflicting objectives, and consideration of multiple spatial scales. Further research on the uptake of NbS needs to focus on addressing risk communication and modeling, managing trade‐offs, and demonstration of delayed benefits.This article is categorized under: Water and Life &gt; Conservation, Management, and Awareness Science of Water &gt; Water and Environmental Change

Assessing habitat connectivity of rare species to inform urban conservation planning.

Urbanization is commonly associated with biodiversity loss and habitat fragmentation. However, urban environments often have greenspaces that can support wildlife populations, including rare species. The challenge for conservation planners working in these systems is identifying priority habitats and corridors for protection before they are lost. In a rapidly changing urban environment, this requires prompt decisions informed by accurate spatial information. Here, we combine several approaches to map habitat and assess connectivity for a diverse set of rare species in seven urban study areas across southern Michigan, USA. We incorporated multiple connectivity tools for a comprehensive appraisal of species-habitat patterns across these urban landscapes. We observed distinct differences in connectivity by taxonomic group and site. The three turtle species (Blanding's, Eastern Box, and Spotted) consistently had more habitat predicted to be suitable per site than other evaluated species. This is promising for this at-risk taxonomic group and allows conservation efforts to focus on mitigating threats such as road mortality. Grassland and prairie-associated species (American Bumble Bee, Black and Gold Bumble Bee, and Henslow's Sparrow) had the least amount of habitat on a site-by-site basis. Kalamazoo and the northern Detroit sites had the highest levels of multi-species connectivity across the entire study area based on the least cost paths. These connectivity results have direct applications in urban planning. Kalamazoo, one of the focal urban regions, has implemented a Natural Features Protection (NFP) plan to bolster natural area protections within the city. We compared our connectivity results to the NFP area and show where this plan will have an immediate positive impact and additional areas for potential consideration in future expansions of the protection network. Our results show that conservation opportunities exist within each of the assessed urban areas for maintaining rare species, a key benefit of this multi-species and multi-site approach.

The influence of the geographic positioning system error on the quality of ship magnetic signature reproduction based on measurements in sea conditions

In previous studies, the authors performed the magnetic signature reconstruction of the marine ship Zodiak as part of the measurement campaign focused on recording magnetic data and the relative position of a ship during its passage over a magnetometer immersed on the testing ground. A high degree of representation of the magnetic signature was obtained. However, the recorded measurement data revealed new patterns of the multi-dipole model behavior that were not observed in the synthetic data based analyzes. It was assumed that the main factor influencing the abovementioned behavior of the model is the error in determining the geographical position of the ship in relation to the magnetometer. Therefore, another research was carried out to determine the relative position of the ship and the measurement device in sea conditions, in the area of the test site used in the previous study. For this purpose, two different classes of GPS receivers were used. The first receiver was the same as that used to determine the position of Zodiak in the previous measurement campaign, while the second receiver, treated as a reference, was a top-class geodetic receiver. The difference in indications between these two receivers gave a picture of the scale of errors in the data recorded during the previous measurement campaign. These errors are used in the article to analyze the effect of inaccuracies in determining the ship position on the quality of magnetic signature reproduction. Two types of signature reproduction error were introduced – the error based only on the data collected from the ship’s paths, and the error in the entire area of magnetic anomaly. The model of Zodiak was used to determine the value of the magnetic flux outside the paths. Profiles of differences in indications of GPS receivers at sea which were obtained from actual measurements were used to analyze the errors in determining the ship position. A measurable result of the work reported in the article is the map of the loss of quality of magnetic signature reproduction as a function of the ship position determination error, which can indicate the range of applicability of the model and the described method.

Experimental analysis of the electric field distribution in semi-insulating GaAs detectors via alpha particles

Semi-insulating gallium arsenide (SI GaAs) detectors offer a promising alternative to commercially available silicon detectors. They demonstrate superior radiation hardness and provide improved efficiency for gamma and X-ray detection, primarily attributed to their higher density. In this study, we examined 350 μm thick SI GaAs detectors featuring front-side Ti/Pt/Au Schottky contacts with varying contact areas, complemented by back-side Ni/AuGe/Au ohmic contacts spanning the entire area. First, the reverse current-voltage characteristics of the prepared detectors were measured. The dependence of the reverse current and the breakdown voltage on the Schottky contact area was revealed. As the contact area decreases, the reverse current decreases and the breakdown voltage increases. The detection performance of the detectors was evaluated by alpha spectrometry using an 241Am source. After irradiation of the detectors from the Schottky electrode, the measured alpha spectra show an increasing CCE with decreasing Schottky contact area. Finally, the correlation between the applied bias voltage and the extent of the active detector area from the edge of the detector contact was investigated.

CBR Mapping Prediction from 2D Resistivity Imaging Using Regression Following Archie’s Formula

Indirect geophysical methods are increasingly associated with direct underground methods in investigating the subsurface to address environmental and geotechnical problems and reduce the cost of underground studies. These methods make it possible to explore large areas with acceptable precision, time, and cost. The present study combines the electrical resistivity method with the California Bearing Ratio for exploring an area located west of the Nouakchott port in Mauritania. The study aims firstly to verify that the thickness of the backfill layer must be less than 2 m throughout the entire study area and secondly to map areas with low California Bearing Ratio values (&lt;80%) indicating substandard backfill compaction using 2D Electrical Resistivity Tomography imaging survey and regression. The measured Electrical Resistivity values exhibit a good nonlinear regression with California Bearing Ratio, following Archie's equation. A map of California Bearing Ratio variation was derived from the Electrical Resistivity values, indicating the distribution and variation of soil strength in the study area. The results revealed that the backfill layer did not meet the standards, with approximately 35% of the total area having a California Bearing Ratio value below 80%. The areas with poor compaction requiring treatment were primarily located in the southern sector, followed by the middle and eastern sectors.

Soil Erosion Characteristics in Tropical Island Watersheds Based on CSLE Model: Discussion of Driving Mechanisms

Previous research has primarily focused on soil erosion issues in arid and semi-arid regions, with a limited understanding of soil erosion mechanisms in tropical areas. Additionally, there is a lack of a holistic perspective to determine the spatial attribution of soil erosion. The conversion of tropical rainforests into economically driven plantations, like rubber and pulpwood, has resulted in distinct soil erosion characteristics in specific regions. To enhance our knowledge of soil erosion patterns and mechanisms in tropical regions, it is necessary to examine soil erosion in the three major watersheds of Hainan Island from 1991 to 2021, which encompass significant geographical features such as tropical island water sources and tropical rainforest national parks. The study employed the China Soil Loss Equation (CSLE) model, slope trend analysis, Pearson correlation analysis, land-use transfer matrix, and spatial attribution analysis to examine soil erosion under different scenarios. The research results indicate that scenarios driven by the combination of natural and human factors have the greatest impact on soil erosion changes in the entire study area. Co-driven increases affected 53.56% of the area, while co-driven decreases affected 21.74%. The 31-year soil erosion showed an overall increasing trend. Human factors were identified as the primary drivers of increased soil erosion in the Nandu River basin, while a combination of climate and anthropogenic factors influenced the decrease in soil erosion. In the Changhua River basin, climate and human activities contributed to the soil erosion increase, while human activities primarily caused the decrease in soil erosion. In the Wanquan River basin, climate intensified soil erosion, whereas human activities mitigated it. This study underscores the significant combined impact of human activities and natural factors on soil erosion in tropical regions. It emphasizes the importance of considering human-induced factors when implementing soil erosion control measures in tropical regions.

Half-century trends of radioactivity in fish from Danish areas of the North Sea, Kattegat, and Baltic Sea

This work reports comprehensive time-series datasets over the past 50 years for natural (210Po) and anthropogenic (134Cs and 137Cs) radionuclides in three fish species (cod, herring and plaice) from Danish marine areas covering the North Sea, Kattegat, and Baltic Sea. Impact from the global fallout of atmospheric nuclear weapons testing, radioactive discharges from the European nuclear reprocessing plants and release from Chernobyl accident are clearly detected in the fish samples. While 210Po concentrations in each fish species demonstrated comparable levels across the three regions without notable temporal trends, significantly higher median 210Po concentration was observed in the lower trophic level fish, namely herring and plaice, compared to cod. In contrast, 137Cs concentrations in all three species steadily decrease over time after the Chernobyl-attributed peaks in late 1980s in the entire study area, whereas 137Cs always demonstrated higher concentrations in cod than herring and plaice. Our calculated concentration factors (CFs) for 137Cs in this work indicate that the mean CFs for 137Cs over the past 50 years are significantly different across the three species, following the order of cod < herring < plaice. Based on the time-series data, ecological half-lives (Teco) of 137Cs in fish from Danish marine areas were estimated to evaluate the long-term impact of anthropogenic radioactive contamination in different regions. Our results indicate no significant difference in Teco across different fish species, whereas the weighted mean Teco for fish in the Baltic Sea (29.3 ± 3.9 y) is significantly longer than those of the North Sea (9.8 ± 0.9 y) and Kattegat (11.7 ± 1.2 y), reflecting the strong ‘memory effect’ of the Baltic Sea due to its slow water renewal. However, the dose assessment demonstrates that the contribution of the natural radionuclide 210Po to ingestion dose from fish consumption is 1–2 order of magnitude higher compared to that of 137Cs.

High-performance imbalanced learning ensembles of decision trees for detecting mineralization anomalies from geochemical exploration data

How to effectively detect geochemical anomalies associated with mineralization is a challenging task due to the extreme class-imbalance of geochemical exploration data. To address this challenge, various machine learning techniques have been employed to detect geochemical anomalies associated with mineralization. However, almost all of these machine learning techniques have their limitations when it comes to modeling class-imbalanced geochemical exploration data. To establish efficient robust high-performance models for detecting geochemical anomalies associated mineralization, a case study was carried out in the Helong area, Jilin Province, China. Decision tree (C4.5) classifiers were used as the base or weak classifiers, four imbalanced learning ensemble models, including self-paced ensemble model, under-bagging ensemble model, synthetic minority oversampling technique (SMOTE)-boost ensemble model and random under sampling (RUS)-boost ensemble model were established and compared in the detection of polymetallic mineralization anomalies from the 1:50,000 stream sediment survey data. The output of the base classifier is a vector consisting of the probability that the sample belongs to a mineralization anomaly and the probability that the sample belongs to the background. The performance of each ensemble model was evaluated using the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC). The ROC curves of the four models are close to the upper left corner of the ROC space. The AUC values of the four models are not lower than 0.9589. The polymetallic mineralization anomalies detected by the four models account for less than 7 % of the entire study area, but contain not less than 93 % of the polymetallic deposits found in the study area. In addition, the polymetallic mineralization anomalies detected by the four models spatially coincide with the regional controlling factors of polymetallic mineralization in the study area. To summarize, the four models have very high performance in detecting polymetallic mineralization anomalies, and the polymetallic mineralization anomaly detection results are consistent with the regional geological and metallogenic characteristics in the study area. Therefore, the imbalanced learning ensemble techniques are powerful tools for the establishment of high-performance ensemble classification models for detecting mineralization anomalies from geochemical exploration data.

Position Optimization of Passive Patch Based on Mode Contribution Factor for Vibration Attenuation of Asymmetric 1D Structure

When the thickness of a structure is reduced to decrease weight, it may experience structural vibration and disturbance. The use of passive patches is effective in addressing this issue when the loss factor is small or when space and weight are restricted. The greatest attenuation occurs when passive patches are used across the entire coverage area. However, passive patches of reasonable size must be affixed to ensure that they are effective in terms of cost and design. In this paper, the sum of squares’ value for the bending mode shape is used to determine the location of a small passive patch to achieve vibration damping for multiple modes. Under the condition of forced vibration, the modal contribution of each mode is obtained. Using this contribution as a weight, the optimal position of the passive patch is determined as the maximum value obtained in the form of a linear combination multiplied by the curvature of the beam. Simulation and experiment were used to test the efficacy of the location determined for passive patches. It was determined that, depending on the location of the passive patch, the peak amplitude at the natural frequency of each mode decreased significantly, validating the effectiveness of the design method.

Spatial Dynamics of Land Use Land Cover of Minna City and Environs, Niger State, Nigeria

Aims: Spatial dynamics of land use land cover of Minna city and environs, Niger State, Nigeria.&#x0D; Study Design: Survey and longitudinal research were carried out.&#x0D; Place and Duration of Study: Minna town, Niger State, Nigeria between 1990 and 2022.&#x0D; Methodology: This study investigated the dynamics of land use land cover of Minna city and environs, Niger State, Nigeria using satellite remote sensing and Geographic Information System (GIS) technique. &#x0D; Results: Findings of the study showed that in 1990, land use type was dominated by agricultural land (50%), followed by vegetation land (30%). However, built-up area was less than 10% indicating that urban heat stress was limited. It was observed that the built-up area concentrated on the center and north-western segments of the city. In 2010, bare ground dominated the land use type of Minna city and environs at the rate of 45%. This was followed by agricultural land at the rate of 35%. The built-up area occupied 15% of the entire land surface area of the city, indicating a tremendous rise from the previous decades. In 2022, the land use type showed a tremendous rise in agricultural land at the rate of 37%. This was followed by bare ground at an alarming increase of 36%. The built-up area ranked third at the rate of 20%, showing that the city had a severe urban heat effect due to heat generated by urban pavement materials.&#x0D; Conclusion: Thus, the practice of sustainable land use, good implementation of forest practice, appropriate water resources conservation and the promotion of alternative livelihood to agriculture should be implemented for the Minna inhabitants to reverse the situation of LULC changes without further delay.

Air Pollution PM10 Forecasting Maps in the Maritime Area of the Bay of Algeciras (Spain)

Predicting the levels of a pollutant in a given area is an open problem, mainly because historical data are typically available at certain locations, where monitoring stations are located, but not at all locations in the area. This work presents an approach based on developing predictions at each of the points where an immission station is available; in this case, based on shallow Artificial Neural Networks, ANNs, and then using a simple geostatistical interpolation algorithm (Inverse Distance Weighted, IDW), a pollutant map is constructed over the entire study area, thus providing predictions at each point in the plane. The ANN models are designed to make 1 h ahead and 4 h ahead predictions, using an autoregressive scheme as inputs (in the case of 4 h ahead as a jumping strategy). The results are then compared using the Friedman and Bonferroni tests to select the best model at each location, and predictions are made with all the best models. In general, to the 1 h ahead prediction models, the optimal models typically have fewer neurons and require minimal historical data. For instance, the best model in Algeciras has an R of almost 0.89 and consists of 1 hidden neuron and 3 to 5 lags, similar to Colegio Los Barrios. In the case of 4h ahead prediction, Colegio Carteya station shows the best model, with an R of almost 0.89 and a MSE of less than 240, including 5 hidden neurons and different lags from the past. The results are sufficiently adequate, especially in the case of predictions 4 h into the future. The aim is to integrate the models into a tool for citizens and administrations to make decisions.

Geographical Types and Driving Mechanisms of Rural Hollowing-Out in the Yellow River Basin

Understanding the regional variations and mechanisms of rural hollowing-out in the Yellow River Basin (YRB) is crucial to guiding regional rural revitalization. However, further quantitative evaluation and analysis are essential to address the issue of rural hollowing-out caused by the decrease in rural population and expansion of residential land in the YRB at different spatio-temporal scales. Based on China’s census data and residential areas extracted from remote sensing images, the rural hollowing-out in the YRB is classified into five types: smart development type (SDT), human–-land recession type (HRT), population loss type (PLT), land expansion type (LET), and human–land–vacant waste type (HLW). Then, the influential features shaping the spatial diversity of rural hollowing-out types are examined, and the feature importance values at different spatio-temporal scales are assessed using the XGBoost model. The results of rural hollowing-out in the YBR indicate that (1) the geographical types of rural hollowing-out in the YRB are dominated by the HRT type and show significant heterogeneity and distribution at different spatio-temporal scales. At different time stages, the number of counties dominated by HRT in lower reaches accounts for 57% of the total counties, whereas the number of counties in the middle reaches is only 37%. Compared to the rural hollowing-out results from 2000 to 2010, the number of counties dominated by PLT and HLW from 2010 to 2020 in the middle reaches increased by 19% and 16%, respectively. (2) Precipitation had a positive effect on the variability of the rural hollowing-out distribution results based on the feature importance values, whereas agricultural productivity had a negative effect and exhibited a decreasing trend. In the entire study area, economic non-agriculturalization had a negative impact, but the topographic relief was positively correlated with the rural hollowing-out results of regional areas, and the intensity of its effect showed an increased trend from 2000 to 2020. (3) The evaluation results in the entire study area show that the main functional type and the distance from provincial capitals are the most important factors affecting rural hollowing out. Compared to other factors, the level of non-agricultural economic development has a greater impact on the spatio-temporal differentiation of rural hollowing types in different Yellow River basins. Given the significant effect of non-agricultural economic development in the evaluation of regional rural hollowing-out, it can provide methodological and indicator references for the evaluation of rural hollowing-out in different regions.

Identifying geomorphic domains using hierarchically clustered drainage area‐slope scaling

AbstractArea‐slope scaling is an important tool for analysing geomorphic processes. In this study, we used hierarchical clustering to sort the area‐slope scaling data for both the numerical landscape created using the LandLab model and real landscapes. Random forest analysis was used to explore the effect of hierarchical clustering. We aimed to illustrate the heterogeneous features of area‐slope clustering and their influencing factors and to test whether they can be used to distinguish geomorphic domains. Our results showed that hierarchical clustering can easily detect the heterogeneous features of area‐slope scaling constrained by tectonic uplift and fluvial erodibility but not those constrained by the diffusion coefficient. The slope gradients over the inflection/transition zone of the colluvial and fluvial domains play a key role in identifying area‐slope scaling from different geomorphic domains. Case studies show that area‐slope scaling of clusters would be affected by different lithology and distance away from the trunk channel. In the high erosion circumstance, the fluvial process caused by tectonics leads to increasing slope gradients over whole geomorphic domains, as well as to retreating inflection between the colluvial and fluvial process domains. In low erosion circumstances or steady state, the fluvial process caused by nearby rivers cannot effectively change the slope gradients but can retreat the inflection. The real landscapes suggest that basins should be carefully selected for area‐slope scaling analysis to ensure that they are representative of the entire study area. Before geomorphological research, more basins of a specific research region need to be selected to conduct hierarchical clustering to select representative basins. Our study could be helpful in the identification of area‐slope domains, the extraction of geomorphic metrics and geomorphic process research.

Exploring spatiotemporal dynamics of NDVI and climate-driven responses in ecosystems: Insights for sustainable management and climate resilience

Understanding the intricate relationship between climate variables and the Normalized Difference Vegetation Index (NDVI) is essential for effective ecosystem management. This study focuses on the spatiotemporal dynamics of NDVI and its interaction with climate variables in the ecologically diverse Khyber Pakhtunkhwa (KPK) Province, Pakistan, from 2000 to 2022. The research methodology involves analyzing satellite images and meteorological datasets to examine NDVI and surface latent heat flux (SHF), total precipitation (TPP), temperature (T), soil temperature (ST), and total pressure (TP). KPK Province's ecological significance and complex climate-vegetation interactions drive the selection of this study area. The study uses multiple linear regression analysis to investigate how T, TPP, SHF, and TP influence NDVI. The Mann-Kendall test detects trends, with Sen's slope estimator quantifying trend magnitudes. Additionally, correlation coefficients provide insights into long-term changes and association strengths. The findings highlight a consistent upward trend in mean NDVI over the 23 years, revealing an overall increase in NDVI, particularly in vegetation-dense areas where it rose from 0.27 to 0.32. The research showed an annual growth rate of 0.84% in the entire area, with specific vegetated zones exhibiting a slightly lower rate of 0.80%. However, the average yearly increase in NDVI is higher in vegetation-specific zones (0.00237) compared to the whole area (0.00151). This increase in NDVI occurs alongside a statistically significant decrease in SHF and PPT, suggesting a complex adaptation of vegetation to changing climate conditions in the KPK Province. In contrast, SHF exhibits a statistically significant negative slope of −5.952e-06 (p < 0.05), indicating a pronounced downward trend. Similarly, Sen's slope estimate for precipitation demonstrates a significant negative trend of −0.0001 (p < 0.05), showing diminishing precipitation. The study uncovers intricate linkages between climate variables and vegetation dynamics within KPK Province. These insights have far-reaching implications, guiding decision-making in land management, conservation efforts, and global climate resilience strategies. Ultimately, the research underscores the critical role of data-driven approaches in shaping a greener and more sustainable future.