Geography of Talent in China During 2000-2015:An Eigenvector Spatial Filtering Negative Binomial Approach

The increase in China’s skilled labor force has drawn much attention from policymakers,national and international firms and media.Understanding how educated talent locates and re-locates across the country can guide future policy discussions of equality,firm localization and service allocation.Prior studies have tended to adopt a static cross-national approach providing valuable insights into the relative importance of economic and amenity differentials driving the distribution of talent in China.Yet,few adopt longitudinal analysis to examine the temporal dynamics in the stregnth of existing associations.Recently released official statistical data now enables space-time analysis of the geographic distribution of talent and its determinants in China.Using four-year city-level data from national population censuses and 1%population sample surveys conducted every five years between 2000 and 2015,we examine the spatial patterns of talent across Chinese cities and their underpinning drivers evolve over time.Results reveal that the spatial distribution of talent in China is persistently unequal and spatially concentrated between 2000 and 2015.It also shows gradually strengthened and significantly positive spatial autocorrelation in the distribution of talent.An eigenvector spatial filtering negative binomial panel is employed to model the spatial determinants of talent distribution.Results indicate the influences of both economic opportunities and urban amenities,particularly urban public services and greening rate,on the distribution of talent.These results highlight that urban economic-and amenity-related factors have simultaneously driven China’s talent’s settlement patterns over the first fifteen years of the 21st century.

Assessment of soil erosion in the Irga watershed on the eastern edge of the Chota Nagpur Plateau,India

Human activities to improve the quality of life have accelerated the natural rate of soil erosion.In turn,these natural disasters have taken a great impact on humans.Human activities,particularly the conversion of vegetated land into agricultural land and built-up area,stand out as primary contributors to soil erosion.The present study investigated the risk of soil erosion in the Irga watershed located on the eastern fringe of the Chota Nagpur Plateau in Jharkhand,India,which is dominated by sandy loam and sandy clay loam soil with low soil organic carbon(SOC)content.The study used the Revised Universal Soil Loss Equation(RUSLE)and Geographical Information System(GIS)technique to determine the rate of soil erosion.The five parameters(rainfall-runoff erosivity(R)factor,soil erodibility(K)factor,slope length and steepness(LS)factor,cover-management(C)factor,and support practice(P)factor)of the RUSLE were applied to present a more accurate distribution characteristic of soil erosion in the Irga watershed.The result shows that the R factor is positively correlated with rainfall and follows the same distribution pattern as the rainfall.The K factor values in the northern part of the study area are relatively low,while they are relatively high in the southern part.The mean value of the LS factor is 2.74,which is low due to the flat terrain of the Irga watershed.There is a negative linear correlation between Normalized Difference Vegetation Index(NDVI)and the C factor,and the high values of the C factor are observed in places with low NDVI.The mean value of the P factor is 0.210,with a range from 0.000 to 1.000.After calculating all parameters,we obtained the average soil erosion rate of 1.43 t/(hm^(2)•a),with the highest rate reaching as high as 32.71 t/(hm^(2)•a).Therefore,the study area faces a low risk of soil erosion.However,preventative measures are essential to avoid future damage to productive and constructive activities caused by soil erosion.This study also identifies the spatial distribution of soil erosion rate,which will help policy-makers to implement targeted soil erosion control measures.

Climate-growth relationships of Pinus tabuliformis along an altitudinal gradient on Baiyunshan Mountain,Central China

A set of standard chronologies for tree-ring width(TRW),earlywood width(EWW)and latewood width(LWW)in Pinus tabuliformis Carr.along an altitudi-nal gradient(1450,1400,and 1350 m a.s.l.)on Baiyunshan Mountain,Central China to analyze the effect of varying temperature and precipitation on growth along the gradi-ent.Correlation analyses showed that at all three altitudes and the TRW and EWW chronologies generally had signifi-cant negative correlations with mean and maximum tem-peratures in the current April and May and with minimum temperatures in the prior July and August,but significant positive correlations with precipitation in the current May.Correlations were generally significantly negative between LWW chronologies and all temperatures in the prior July and August,indicating that the prior summer temperature had a strong lag effect on the growth of P.tabuliformis that increased with altitude.The correlation with the standard-ized precipitation evapotranspiration index(SPEI)confirmed that wet conditions in the current May promoted growth of TR and EW at all altitudes.Significant altitudinal differences were also found;at 1400 m,there were significant positive correlations between EWW chronologies and SPEI in the current April and significant negative correlations between LWW chronologies and SPEI in the current September,but these correlations were not significant at 1450 m.At 1350 m,there were also significant negative correlations between the TRW and the EWW chronologies and SPEI in the prior October and the current July and between LWW chronology and SPEI in the current August,but these cor-relations were not significant at 1400 m.Moving correlation results showed a stable response of EWW in relation to the SPEI in the current May at all three altitudes and of LWW to maximum temperature in the prior July-August at 1400 m from 2002 to 2018.The EWW chronology at 1400 m and the LWW chronology at 1450 m were identified as more suitable for climate reconstruction.These results provide a strong scientific basis for forest management decisions and climate reconstructions in Central China.

Dendroclimatological study of Sabina saltuaria and Abies faxoniana in the mixed forests of the Qionglai Mountains,eastern Tibetan Plateau

Tree-ring chronologies were developed for Sabina saltuaria and Abies faxoniana in mixed forests in the Qionglai Mountains of the eastern Tibetan Plateau.Climate-growth relationship analysis indicated that the two co-exist-ing species reponded similarly to climate factors,although S.saltuaria was more sensitive than A.faxoniana.The strong-est correlation was between S.saltuaria chronology and regional mean temperatures from June to November.Based on this relationship,a regional mean temperature from June to November for the period 1605-2016 was constructed.Reconstruction explained 37.3%of the temperature variance during th period 1961-2016.Six major warm periods and five major cold periods were identified.Spectral analysis detected significant interannual and multi-decadal cycles.Reconstruction also revealed the influence of the Atlantic Multi-decadal Oscillation,confirming its importance on climate change on the eastern Tibetan Plateau.

Business of deep transformations:How can geography contribute to understanding degrowth business?

There is currently considerable interest in what degrowth compatible business practices may be and what they may look like.However,while the embeddedness of a degrowth business in the wider environment has been recognised,and this affects theorising of practices and principles,there remains a need to seriously consider the inter-connection between degrowth business and its surrounding environment as a physical and cultural space.To avoid merely hinting at geographical concepts such as space,place,and location,a better approach is establishing a dialogue between degrowth business and geography.To do this,I use the degrowth business framework and connect its elements with the concepts of space,place,and location.This analysis shows that each of the elements is intimately inter-related with geographical concepts and needs to be thought of,theorised,and implemented as such.I conclude that geographical concepts should not be merely implied when theorising degrowth business.Rather,looking at degrowth business through various lenses provided by geographies is indispensable for making degrowth reality in diverse locations.

Circulation Pattern Controls of Summer Temperature Anomalies in Southern Africa

This study investigates the relationship between circulation patterns and austral summer temperature anomalies in southern Africa. The results show that the formation of continental lows tends to increase the thickness of the lower atmosphere. Further, the distinct variabilities of high and low pressure under the circulation types, influence air mass advection from the adjacent oceans, as well as atmospheric stability over land. Stronger anticyclonic circulation at the western branch of the Mascarene high-pressure system enhances the low-level cold air advection by southeast winds,decreases the thickness, and lowers the temperature over a majority of the land in southern Africa. Conversely, a weaker Mascarene High, coupled with enhanced cyclonic activity in the southwest Indian Ocean increases low-level warm air advection and increases temperature anomalies over vast regions in southern Africa. The ridging of a closed South Atlantic anticyclone at the southern coast of southern Africa results in colder temperatures near the tip of southern Africa due to enhanced low-level cold air advection by southeast winds. However, when the ridge is weak and westerly winds dominate the southern coast of southern Africa, these areas experience temperature increases. The northward track of the Southern Hemisphere mid-latitude cyclone, which can be linked to the negative Southern Annular Mode, reduces the temperature in the southwestern part of southern Africa. Also, during the analysis period, El Ni?o was associated with temperature increases over the central parts of southern Africa;while the positive Indian Ocean dipole was linked to a temperature increase over the northeastern, northwestern, and southwestern parts of southern Africa.

Effectiveness of hybrid ensemble machine learning models for landslide susceptibility analysis:Evidence from Shimla district of North-west Indian Himalayan region

The Indian Himalayan region is frequently experiencing climate change-induced landslides.Thus,landslide susceptibility assessment assumes greater significance for lessening the impact of a landslide hazard.This paper makes an attempt to assess landslide susceptibility in Shimla district of the northwest Indian Himalayan region.It examined the effectiveness of random forest(RF),multilayer perceptron(MLP),sequential minimal optimization regression(SMOreg)and bagging ensemble(B-RF,BSMOreg,B-MLP)models.A landslide inventory map comprising 1052 locations of past landslide occurrences was classified into training(70%)and testing(30%)datasets.The site-specific influencing factors were selected by employing a multicollinearity test.The relationship between past landslide occurrences and influencing factors was established using the frequency ratio method.The effectiveness of machine learning models was verified through performance assessors.The landslide susceptibility maps were validated by the area under the receiver operating characteristic curves(ROC-AUC),accuracy,precision,recall and F1-score.The key performance metrics and map validation demonstrated that the BRF model(correlation coefficient:0.988,mean absolute error:0.010,root mean square error:0.058,relative absolute error:2.964,ROC-AUC:0.947,accuracy:0.778,precision:0.819,recall:0.917 and F-1 score:0.865)outperformed the single classifiers and other bagging ensemble models for landslide susceptibility.The results show that the largest area was found under the very high susceptibility zone(33.87%),followed by the low(27.30%),high(20.68%)and moderate(18.16%)susceptibility zones.The factors,namely average annual rainfall,slope,lithology,soil texture and earthquake magnitude have been identified as the influencing factors for very high landslide susceptibility.Soil texture,lineament density and elevation have been attributed to high and moderate susceptibility.Thus,the study calls for devising suitable landslide mitigation measures in the study area.Structural measures,an immediate response system,community participation and coordination among stakeholders may help lessen the detrimental impact of landslides.The findings from this study could aid decision-makers in mitigating future catastrophes and devising suitable strategies in other geographical regions with similar geological characteristics.

Elevational patterns of warming effects on plant community and topsoil properties: focus on subalpine meadows ecosystem

Climate warming profoundly affects plant biodiversity, community productivity, and soil properties in alpine and subalpine grassland ecosystems. However, these effects are poorly understood across elevational gradients in subalpine meadow ecosystems. To reveal the elevational patterns of warming effects on plant biodiversity, community structure, productivity, and soil properties, we conducted a warming experiment using open-top chambers from August 2019 to August 2022 at high(2764 m a. s. l.), medium(2631 m a. s. l.), and low(2544 m a. s. l.) elevational gradients on a subalpine meadow slope of Mount Wutai, Northern China. Our results showed that three years of warming significantly increased topsoil temperature but significantly decreased topsoil moisture at all elevations(P<0.05), and the percentage of increasing temperature and decreasing moisture both gradually raised with elevation lifting. Warming-induced decreasing proportions of soil organic carbon(SOC, by 19.24%), and total nitrogen(TN, by 24.56%) were the greatest at high elevational gradients. Experimental warming did not affect topsoil C: N, p H, NO_(3)^(-)-N, or NH_(4)^(+)-N at the three elevational gradients. Warming significantly increased species richness(P<0.01) and Shannon-Weiner index(P<0.05) at low elevational gradients but significantly decreased belowground biomass(P<0.05) at a depth of 0–10 cm at three elevational gradients. Warming caused significant increases in the aboveground biomass in the three elevational plots. Warming significantly increased the aboveground biomass of graminoids in medium(by 92.47%) and low(by 98.25%) elevational gradients, that of sedges in high(by 72.44%) and medium(by 57.16%) elevational plots, and that of forbs in high(by 75.88%), medium(by 34.38%), and low(by 74.95%) elevational plots. Species richness had significant linear correlations with SOC, TN, and C: N(P<0.05), but significant nonlinear responses to soil temperature and soil moisture in the warmed treatment(P<0.05). The warmed aboveground biomass had a significant nonlinear response to soil temperature and significant linear responses to soil moisture(P<0.05). This study provided evidence that altitude is a factor in sensitivity to climate warming, and these different parameters(e.g., plant species richness, Shannon-Weiner index, soil temperature, soil moisture, SOC, and TN) can be used to measure this sensitivity.

How far have we come?Review of main public policies to reduce landslide impacts in Brazil

During the rainy season in Brazil,landslides can have catastrophic consequences,including loss of life,damage to urban infrastructure and significant economic impacts.Now,more than eight million people in Brazil live in disaster-prone areas.The objective of this article is to present a chronological review of the principal policies and programmes at the national,state,and municipal levels,with an emphasis on their key actions aimed at mitigating the impact of disasters related to natural hazards,particularly landslides.Our analysis was based on official records of public policies from the national,state,and municipal governments.The results show that several initiatives were initially developed at the local and regional level.However,it was not until the late 1980s that a comprehensive organisation of civil protection at the national level emerged as a response measure.It is possible to highlight three phases(understanding,coexistence,and prevention)of institutional action focused on risk management in the face of disasters.Despite the growing knowledge of risk scenarios,disasters continue to occur in Brazil on an annual basis,revealing several obstacles to reducing their impact,particularly given the social and economic disparities between Brazilian regions and the applicability of public policies that must overcome the limitations of each municipality.

Quantification of the concrete freeze–thaw environment across the Qinghai–Tibet Plateau based on machine learning algorithms

The reasonable quantification of the concrete freezing environment on the Qinghai–Tibet Plateau(QTP) is the primary issue in frost resistant concrete design, which is one of the challenges that the QTP engineering managers should take into account. In this paper, we propose a more realistic method to calculate the number of concrete freeze–thaw cycles(NFTCs) on the QTP. The calculated results show that the NFTCs increase as the altitude of the meteorological station increases with the average NFTCs being 208.7. Four machine learning methods, i.e., the random forest(RF) model, generalized boosting method(GBM), generalized linear model(GLM), and generalized additive model(GAM), are used to fit the NFTCs. The root mean square error(RMSE) values of the RF, GBM, GLM, and GAM are 32.3, 4.3, 247.9, and 161.3, respectively. The R^(2) values of the RF, GBM, GLM, and GAM are 0.93, 0.99, 0.48, and 0.66, respectively. The GBM method performs the best compared to the other three methods, which was shown by the results of RMSE and R^(2) values. The quantitative results from the GBM method indicate that the lowest, medium, and highest NFTC values are distributed in the northern, central, and southern parts of the QTP, respectively. The annual NFTCs in the QTP region are mainly concentrated at 160 and above, and the average NFTCs is 200 across the QTP. Our results can provide scientific guidance and a theoretical basis for the freezing resistance design of concrete in various projects on the QTP.

Evaluation of periglacial landforms and formation of soil properties on the Mount Honaz,SW Türkiye

The main aim of this study is to explain periglacial processes on the summits of Mount Honaz(2571 m a.s.l.),define periglacial landforms,and determine the relationships between morphometric features and topographic factors.Mud circles,stony earth circles,non sorted steps,and non sorted stripes were identified on the summits of Mount Honaz.Pearson's correlation coefficient(r)and linear regression analyses were performed by taking metric measurements from 125 periglacial landforms to describe their morphometric features(length,width,height)of periglacial landforms and explain the relationships between them and topographic factors(elevation,slope).To explain the relationships between periglacial landforms and soil properties,soil samples from 11 periglacial landforms were taken and analysed.Periglacial landforms,which continue to develop on the summits of Mount Honaz today,have been evaluated with present climate data.Analysis of soil samples indicates a notable impact of parent material on the genesis of periglacial landforms.The high ratio of organic matter in mud circle and non sorted step landforms and the high lime ratio in stony earth circle landforms prove a strong relationship between the formation mechanisms of landforms and the soil properties.Furthermore,it is consistent with the findings obtained from the analysis that severe periglacial processes and washing and scavenging events are experienced more on the northern slopes.

Establishing the relationship between land use land cover,normalized difference vegetation index and land surface temperature:A case of Lower Son River Basin,India

The study explores the intricate interplay between land use land cover(LULC),normalized difference vegetation index(NDVI),and land surface temperature(LST)within the Lower Son River Basin in India from 1991 to 2020.The region’s ecological balance has been increasingly strained due to rapid urbanization and changing land use patterns.Through a combination of Landsat TM&OLI/TIRS satellite imageries and geospatial analysis techniques,this study unveils the intricate connection between land use and land cover changes,vegetation,and land surface temperature variations.The study area is classified into three altitudinal zones(Zone Ⅰ:39–300 m,Zone Ⅱ:301–600 m and Zone Ⅲ:601–1,247 m)to examine the changes in depth.The area has seen significant changes in LULC,vegetation and LST in all the three altitudinal zones.The findings hold significant implications for sustainable land management and environmental conservation strategies in the Lower Son River Basin.As per the result,103,438 ha of vegetation was converted into agriculture land and 82,572 ha of agricultural land was transformed into settlements from 1991 to 2020.This trend shows human pressure on the land resource in the study area.Minor increase in water body is seen which is attributed to commissioning of Bansagar dam.Zone Ⅰ has seen highest settlement growth while Zone Ⅲ experienced severe deforestation of around 15%.Zone Ⅱ and Ⅲ needs attention for holistic sustenance.Analysis of LST shows that it has increased by 0.82℃ from 1991 to 2020 which is a red flag.The study underscores the critical importance of balanced land use practices to preserve ecological integrity and mitigate the adverse effects of urbanization and climate change.

Sustainable Intensification and Large-scale Operation of Cultivated Land Use at the Farmers’ Scale:A Case Study of Shandong Province,China

Sustainable intensification of cultivated land use(SICLU) and large-scale operations(LSO) are widely acknowledged strategies for enhancing agricultural performance.However,the existing literature has faced challenges in precisely defining SICLU and constructing comprehensive indicators,which has hindered the exploration of factors influencing LSO within the SICLU framework.To address this gap,we integrated self-efficacy theory into the design of an index framework for evaluating SICLU.We subsequently employed econometric models to analyze the significant factors that impact LSO.Our findings reveal that SICLU can be divided into four key dimensions:intensive management,efficient output,resource conservation,and ecological environment optimization.Furthermore,it is crucial to incorporate belief-based cognitive factors into the index system,as farmers’ understanding of fertilizer and pesticide application significantly influences their willingness to engage in LSO.Moreover,we identify grain market turnover as the most influential factor in promoting LSO,with single-factor contribution rates reaching 70.9% for cultivated land transfer willingness and 62.5% for the total planting areas.Interestingly,unlike irrigation and agricultural machinery inputs,increased labor inputs correspond to larger planting areas for farmers.This trend may be attributed to reduced labor availability because of rural labor migration,whereas the reduction in irrigation and agricultural input is contingent on innovations in production practices and the transfer of cultivated land management rights.Importantly,SICLU dynamically influences LSO,with each index related to SICLU having an optimal range that fosters LSO.These insights offer valuable guidance for policymakers,emphasizing farmers as their central focus,with the adjustment of input and output factors as a means to achieve LSO as the ultimate goal.In conclusion,we propose research avenues for further enriching the SICLU framework to ensure that it aligns with the specific characteristics of regional agricultural development.

Spatiotemporal dynamics of land use/land cover(LULC)changes and its impact on land surface temperature:A case study in New Town Kolkata,eastern India

Rapid urbanization creates complexity,results in dynamic changes in land and environment,and influences the land surface temperature(LST)in fast-developing cities.In this study,we examined the impact of land use/land cover(LULC)changes on LST and determined the intensity of urban heat island(UHI)in New Town Kolkata(a smart city),eastern India,from 1991 to 2021 at 10-a intervals using various series of Landsat multi-spectral and thermal bands.This study used the maximum likelihood algorithm for image classification and other methods like the correlation analysis and hotspot analysis(Getis–Ord Gi^(*) method)to examine the impact of LULC changes on urban thermal environment.This study noticed that the area percentage of built-up land increased rapidly from 21.91%to 45.63%during 1991–2021,with a maximum positive change in built-up land and a maximum negative change in sparse vegetation.The mean temperature significantly increased during the study period(1991–2021),from 16.31℃to 22.48℃in winter,29.18℃to 34.61℃in summer,and 19.18℃to 27.11℃in autumn.The result showed that impervious surfaces contribute to higher LST,whereas vegetation helps decrease it.Poor ecological status has been found in built-up land,and excellent ecological status has been found in vegetation and water body.The hot spot and cold spot areas shifted their locations every decade due to random LULC changes.Even after New Town Kolkata became a smart city,high LST has been observed.Overall,this study indicated that urbanization and changes in LULC patterns can influence the urban thermal environment,and appropriate planning is needed to reduce LST.This study can help policy-makers create sustainable smart cities.

Exploring the Spatiotemporal Changes and Driving Forces of Ecosystem Services of Zhejiang Coasts,China,Under Sustainable Development Goals

Ecosystem services(ESs)refer to the continuous provisioning of ecosystem goods and services that benefit human beings.Over recent decades,rapid urbanization has exerted significant pressure on coastal ecosystems,resulting in biodiversity and habitat loss,environmental pollution,and the depletion of natural resources.In response to these environmental challenges,the Sustainable Development Goals(SDGs)were proposed.Given the pressing need to address these issues,understanding the changes in ESs under the SDGs is crucial for formulating specific ecological strategies.In this study,we first analyzed land use and cover change in the Zhejiang coasts of China during 2000–2020.Then,we investigated the spatiotemporal configuration of ESs by integrating carbon storage(CS),soil retention(SR),habitat quality(HQ)and water yield(WY)using the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model.The driving mechanisms of ESs,which varied by space and time,were also explored using the Geo-detector method.The results revealed that,over the past two decades:1)the Zhejiang coasts have experienced a significant increase of 2783.72 km^(2) in built-up land areas and a continuous decrease in farmland areas due to rapid urbanization;2)owing to higher precipitation,extensive vegetation cover,and reduced anthropogenic disturbances,forests emerge as a crucial land use type for maintaining ecosystem services such as HQ,CS,WY,and SR;3)ESs have generally declined across the entire Zhejiang coasts,with a significant decrease observed in the northern areas and an increase in the southern areas spatially;4)the expansion of built-up land areas emerged as the primary factor affecting ecosystem services,while the vegetation factor has been increasingly significant and is expected to become predominant in the near future.Our study provides insights of understanding of ecosystem service theory and emphasizing the importance of preserving biodiversity for long-term sustainable development,and valuable scientific references to support the ecological management decision-making for local governments.

Using satellite-derived land surface temperatures to clarify the spatiotemporal warming trends of the Alborz Mountains in northern Iran

The Alborz Mountains are some of the highest in Iran,and they play an important role in controlling the climate of the country’s northern regions.The land surface temperature(LST)is an important variable that affects the ecosystem of this area.This study investigated the spatiotemporal changes and trends of the nighttime LST in the western region of the Central Alborz Mountains at elevations of 1500-4000 m above sea level.MODIS data were extracted for the period of 2000-2021,and the Mann-Kendall nonparametric test was applied to evaluating the changes in the LST.The results indicated a significant increasing trend for the monthly average LST in May-August along the southern aspect.Both the northern and southern aspects showed decreasing trends for the monthly average LST in October,November,and March and an increasing trend in other months.At all elevations,the average decadal change in the monthly average LST was more severe along the southern aspect(0.60°C)than along the northern aspect(0.37°C).The LST difference between the northern and southern aspects decreased in the cold months but increased in the hot months.At the same elevation,the difference in the lapse rate between the northern and southern aspects was greater in the hot months than in the cold months.With increasing elevation,the lapse rate between the northern and southern aspects disappeared.Climate change was concluded to greatly decrease the difference in LST at different elevations for April-July.

Performance validation of High Mountain Asia 8-meter Digital Elevation Model using ICESat-2 geolocated photons

High Mountain Asia(HMA),recognized as a third pole,needs regular and intense studies as it is susceptible to climate change.An accurate and high-resolution Digital Elevation Model(DEM)for this region enables us to analyze it in a 3D environment and understand its intricate role as the Water Tower of Asia.The science teams of NASA realized an 8-m DEM using satellite stereo imagery for HMA,termed HMA 8-m DEM.In this research,we assessed the vertical accuracy of HMA 8-m DEM using reference elevations from ICESat-2 geolocated photons at three test sites of varied topography and land covers.Inferences were made from statistical quantifiers and elevation profiles.For the world’s highest mountain,Mount Everest,and its surroundings,Root Mean Squared Error(RMSE)and Mean Absolute Error(MAE)resulted in 1.94 m and 1.66 m,respectively;however,a uniform positive bias observed in the elevation profiles indicates the seasonal snow cover change will dent the accurate estimation of the elevation in this sort of test sites.The second test site containing gentle slopes with forest patches has exhibited the Digital Surface Model(DSM)features with RMSE and MAE of 0.58 m and 0.52 m,respectively.The third test site,situated in the Zanda County of the Qinghai-Tibet,is a relatively flat terrain bed,mostly bare earth with sudden river cuts,and has minimal errors with RMSE and MAE of 0.32 m and 0.29 m,respectively,and with a negligible bias.Additionally,in one more test site,the feasibility of detecting the glacial lakes was tested,which resulted in exhibiting a flat surface over the surface of the lakes,indicating the potential of HMA 8-m DEM for deriving the hydrological parameters.The results accrued in this investigation confirm that the HMA 8-m DEM has the best vertical accuracy and should be of high use for analyzing natural hazards and monitoring glacier surfaces.

Role of self-help groups on socioeconomic development and the achievement of Sustainable Development Goals(SDGs)among rural women in Cooch Behar District,India

This study examines the transformative role of self-help groups(SHGs)in the socioeconomic development of rural women in Cooch Behar District,India,and their contribution toward achieving Sustainable Development Goals(SDGs)of the United Nations.In this study,we explored the effect of SHGs on rural women by specifically addressing SDGs,such as no poverty(SDG 1),zero hunger(SDG 2),good health and well-being(SDG 3),quality education(SDG 4),and gender equality(SDG 5).Given this issue,a cross-sectional survey and comparison analyses are needed to assess the socioeconomic development of rural women and their awareness level before and after the participation of rural women in SHGs.The survey conducted as part of this study was divided into three sections,namely,demographic characteristics,socioeconomic development,and awareness level,with each focusing on different aspects.A group of 400 individuals who were part of SHGs completed the questionnaire survey form.The results showed that the participation of rural women in SHGs significantly improved their socioeconomic development and awareness level,as supported by both mean values and t test results.Memberships in SHGs and microcredit programs were the major elements that boosted the socioeconomic development of rural women,which also achieves SDGs 1,2,3,4,and 5.This study revealed that participation in SHGs and related financial services significantly aided rural women in economically disadvantaged communities in accumulating savings and initiating entrepreneurial ventures.Moreover,participation in SHGs was instrumental in enhancing the self-confidence,self-efficacy,and overall self-esteem of rural women.Finally,doing so enabled them to move more freely for work and other activities and to make family and common decisions.

Sedimentary Characteristics,Ages,and Environmental Significance of Gravel Deposits and Loess in Shandong,Eastern China:Regional Response to Global Change Since the Last Glacial Period

Investigation of rarely studied gravel layers found in the loess in Shandong Province,eastern China,reveals the fabric characteristics of two gravel layers(G1,G2)and the sedimentary characteristics of loess at the typical and well-preserved Heiyu section(HY),where,to determine the paleoclimatic changes during Marine Isotope Stage 3a.Optically stimulated luminescence dates of the HY formation range from 0.26±0.02 ka to 39.00±2.00 ka.In addition,the ages of G1 and G2 were estimated using the Bayesian model to be 39.60-40.50 and 29.00-29.50 ka.G1 and G2 are mainly composed of fine and medium gravel,both of which were subangular to subrounded limestone,with gravel directions to NE and E.The average flow velocity,average depth,and flood peak flow of G1 are 1.10 m/s,0.49 m,and 37.04 m^(3)/s,respectively,calculated using the flow energy method,whereas those of G2 are 0.98 m/s,0.38 m,and 18.38 m^(3)/s,respectively.Analysis of climate proxy indices show that the sedimentary environment of the gravel and loess in HY might be a regional response to global change.

Spatiotemporal characteristics and driving mechanisms of land use/land cover(LULC)changes in the Jinghe River Basin,China

Understanding the trajectories and driving mechanisms behind land use/land cover(LULC)changes is essential for effective watershed planning and management.This study quantified the net change,exchange,total change,and transfer rate of LULC in the Jinghe River Basin(JRB),China using LULC data from 2000 to 2020.Through trajectory analysis,knowledge maps,chord diagrams,and standard deviation ellipse method,we examined the spatiotemporal characteristics of LULC changes.We further established an index system encompassing natural factors(digital elevation model(DEM),slope,aspect,and curvature),socio-economic factors(gross domestic product(GDP)and population),and accessibility factors(distance from railways,distance from highways,distance from water,and distance from residents)to investigate the driving mechanisms of LULC changes using factor detector and interaction detector in the geographical detector(Geodetector).The key findings indicate that from 2000 to 2020,the JRB experienced significant LULC changes,particularly for farmland,forest,and grassland.During the study period,LULC change trajectories were categorized into stable,early-stage,late-stage,repeated,and continuous change types.Besides the stable change type,the late-stage change type predominated the LULC change trajectories,comprising 83.31% of the total change area.The period 2010-2020 witnessed more active LULC changes compared to the period 2000-2010.The LULC changes exhibited a discrete spatial expansion trend during 2000-2020,predominantly extending from southeast to northwest of the JRB.Influential driving factors on LULC changes included slope,GDP,and distance from highways.The interaction detection results imply either bilinear or nonlinear enhancement for any two driving factors impacting the LULC changes from 2000 to 2020.This comprehensive understanding of the spatiotemporal characteristics and driving mechanisms of LULC changes offers valuable insights for the planning and sustainable management of LULC in the JRB.