Influence Of Land Use Research Articles

EHT and environmental justice at EPA Victoria: Aspirations and regulatory realities

Abstract EPA Victoria (Australia) is a statutory authority that regulates polluting activities and advises other Victorian government departments on relevant policy settings. In 2016, a public health function was installed at EPA Vic to provide emergency health messaging during pollution events, review research evidence of environmental-health relationships and assess industry-contracted health risk assessments of polluting entities. An Environmental Health Tracking Network (EHTN) is under development to support these activities. The EHTN is an agile data and analytical infrastructure for translating expertise across an expanding multidisciplinary network of public health researchers, EPA operational staff and public sector policy makers. Its current interactive dashboards calculate health impacts and associated costs of air pollution scenarios, model land-use influences on land and water contamination and identify coincidences of sociodemographic-, urban environment- and pollution exposure-disadvantage in a high spatial resolution environmental justice (EJ) framework. Regulatory leverage of EHTN intelligence, however, requires legislated EJ thresholds and/or legally tractable costing of industry-externalised human health impacts. Thus, to establish triggers for more stringent conditions on polluting activities and promote equity of interventions and regulations, novel regionally and EJ specific health risk functions are required. Considering these ambitions and challenges, the EHTN at EPA Vic is focussed on 1) identifying and characterising vulnerable populations at high spatial resolution, 2) estimating associated exposure-health effect size modifications using primary epidemiological methods and 3) applying these to health impact and cost assessments of pollution and waste. We seek defensible grounds on which to impose more stringent standards for polluters and redress entrenched social, health and economic disadvantage. Speakers/Panelists Hanna Tolonen THL, Helsinki, Finland

Field-scale variability and dynamics of soil moisture in Southwestern Nigeria

This research leverages field-based sensors and Geographic Information Systems (GIS) to elucidate soil moisture dynamics across diverse land uses in Southwestern Nigeria, including Cocoa, Cassava, Oil Palm, and Riparian ecosystems. The study synthesizes soil moisture data and geospatial coordinates from strategically selected land covers with satellite-derived soil moisture records from NASA's Prediction of Worldwide Energy Resources (POWER) and the US Geological Survey. Through a robust analytical framework combining cross-correlation functions, wavelet analysis, and inverse distance weighting interpolation, we revealed distinct soil moisture patterns ranging from 0 to 47.9% in arable farms, 0 to 46.8% in built-up areas, 0 to 49.9% in cocoa farms, 0.2 to 49.7% in oil palm farms, and 5.6 to 94.1% in riparian vegetation. The coefficient of determination values between 0.7 and 0.97 (p ≤ 0.05) underscore the significant influence of periodic land use on soil moisture during the study period. A comparative analysis of ground-based and satellite data revealed a potential overestimation of minimum soil moisture values by 66% and an underestimation of maximum values by 4%. This investigation provides critical insights into the interplay between hydrological variables and agro-meteorological factors, informing the management and assessment of agricultural resources.

Influence of Typical Regional Land Use/Landscape Pattern on Water TN of the Upper Yellow River

This study aimed to explore the relationship between land use landscape pattern and water quality in the upstream of the Gansu water conservation, water and soil erosion, and ecological fragile areas. Based on the land use data and water quality monitoring section in 2020 in the 200 m, 500 m, 1 km, 2 km, 50 km, and 10 km riparian buffer area, the single-factor index evaluation method, random forest regression model, and BP neural network were used to quantify the response relationship between land use and landscape pattern of the upper Yellow River in Gansu province and water quality index and to carry out the basin water quality prediction based on land use landscape index data. The results showed that： ① through the single-factor index method, the major indicators of the total nitrogen （TN） in July and September, dissolved oxygen （DO）, permanganate index, ammonia nitrogen （NH4+ -N）, total phosphorus （TP）, and other surface indexes met the surface water environment class Ⅲ water quality standard. ② The random forest regression model was used to analyze the influence of land use and landscape index on TN, and the difference in TN in different typical areas was obtained. The land use types with the highest influence on the TN index in water conservation areas, soil and soil erosion areas, and ecological fragile areas were cultivated land, grassland, and construction land, respectively. ③ The BP neural network was used to predict the water quality index based on different typical areas of land use landscape index. The result of water conservation areas was good, the error rate between the predicted value and the actual value was below 10%, and the prediction accuracy was high. The study showed that water quality prediction based on land use and landscape index/water quality quantitative relationship model had a good water quality prediction effect.

Deciphering the point source carbon footprint puzzle: Land use dynamics and socio-economic drivers

Point source carbon emissions account for approximately 80 % of total emissions. Investigating the influence of land use and socio-economic indicators on these emissions is crucial for achieving sustainable development goals. Existing research faces challenges such as focusing on specific regions, mixing variables that may exhibit multicollinearity, and lacking sufficient land use information. This study takes China, the largest emitting country, as a case study, utilizing geospatial big data to subdivide land use into 11 categories based on emission sectors. The impacts of land use and socio-economic indicators on different emission sectors are discussed from the perspectives of bivariate and spatial statistical analysis, with spatial hotspots identified. Hierarchical regression is used to evaluate the explanatory power of the indicators and to establish models, and potential carbon reduction strategies are further explored. Key findings reveal: (1) Significant multicollinearity between land use and socio-economic indicators was demonstrated, with land use explaining 57.1 % of emissions compared to 37.4 % explained by socio-economic indicators. The spatial consistency between land use and emissions exceeds 80 %, and the spatiotemporal variability is relatively low, making land use a more advantageous factor in explaining point source carbon emissions. (2) Agricultural mechanization increases emission intensity, but this efficient farming method helps convert surplus plowland, the largest influencing factor (Coefficient = 0.717), into carbon sinks, thereby controlling agricultural emissions. (3) Land intensification helps control industrial land, the main factor influencing industrial emissions (Coefficient = 0.392). It also contributes to the efficient use of carbon reduction technologies and industrial supporting land. (4) Mixed commercial and residential land has the greatest impact on commercial, service, and household emissions. However, its relationship with the economy (Correlation = 0.479) is stronger than its relationship with emissions (Correlation = 0.182), making it more applicable to cities that serve as economic growth hubs.

The effects of climate and population on human land use patterns in Europe from 22ka to 9ka ago

Between 22ka and 9ka ago, after the Last Glacial Maximum (LGM) and during the transition to the Holocene, mobile hunter-gatherer populations, differentiated by their stone tool assemblages, periodically dispersed and contracted across Europe. It is well understood that climate played an important role in human distributions and population sizes during the post-LGM Late Pleistocene and Early Holocene, but the question remains as to whether increasing population sizes drove early human dispersal. Here, using a spatiotemporal species distribution model to infer the fundamental and potential human climatic niche space of Late Upper Paleolithic, Final Paleolithic and Early Mesolithic Europe, and hypotheses derived from the Ideal Distribution Model, we test i) how changes in climate affected the size and extent of the projected potential human niche space, ii) for effects of changes in size of projected potential niche on regional human population sizes, iii) whether increasing human population sizes drove human dispersal into less climatically suitable habitats, and iv) whether populations associated with different high-order material culture groupings (macro-level technocomplexes) occupied different climatic spaces. We find that changes in climate correlate strongly with the size and extent of the projected potential human niche space, that increases in the projected human niche space correlate with increases in human population, that human population size is just beginning to become large enough to influence land use and dispersal patterns at the Pleistocene-Holocene transition, and that archaeological technocultural entities overlap in their fundamental climatic niche space. This overlap implies that changing tools forms cannot readily been seen as reflecting adaptations to changing climates.

Driving the Evolution of Land Use Patterns: The Impact of Urban Agglomeration Construction Land in the Yangtze River Delta, China

The rapid increase in population and economic activities has greatly influenced land use and spatial development. In urban agglomerations where socioeconomic activities are densely concentrated, the clash between ecological protection and economic growth is becoming more evident. Therefore, a thorough quantitative assessment of spatial changes driven by land use dynamics, alongside an examination of temporal and spatial driving factors, is crucial in offering scientific backing for the long-term and sustainable growth of urban agglomerations. This paper focuses on the major urban agglomerations in China’s Yangtze River Delta region, examining the spatiotemporal evolution of land use and landscape patterns from 2000 to 2020. By employing the standard deviation ellipse technique, coupled with multiple linear regression and the geographical detector model, we conduct a quantitative assessment of the directional trends in urban construction land expansion as well as the diverse impacts of temporal and spatial factors on this expansion across various periods and regions. The findings indicate that over the past 20 years, construction land in the Yangtze River Delta Urban Agglomeration expanded in concentrated patches, showing significant scale effects with relatively intact farmland and forest land being increasingly encroached upon. Landscape-type transitions predominantly occurred in cities around Taihu Lake and Hangzhou Bay, with the most significant transition being farmland converted to construction land, resulting in a greater number of patches and more pronounced land fragmentation. Throughout the 20 years, the standard deviation ellipse of construction land in the Yangtze River Delta Urban Agglomeration expanded and shifted, with the predominant expansion trending from the northwest toward the southeast, and the EN orientation being the most intense expansion area, covering 1641.24 km2. The influence of temporal and spatial driving factors on the expansion of urban construction land differed across various periods and regions. This study thoroughly examines the driving factors that affect the evolution of urban construction land in the region, offering valuable scientific evidence and references for future planning and development of the Yangtze River Delta Urban Agglomeration, aiding in the formulation of more precise and efficient urban management and land use strategies.

The Influence of Land Use and Land Cover Transitions on Hydrology in a Tropical River Basin of Southwest India

The Influence of Land Use and Land Cover Transitions on Hydrology in a Tropical River Basin of Southwest India

Occurrence, risk assessment and source apportionment of perfluoroalkyl acids in the river of a hill-plain intersection region: The impacts of land use and river network structure

Studying the impacts of land use and river network structure on perfluoroalkyl acids (PFAAs) footprint in rivers is crucial for predicting the fate of PFAAs in aquatic environments. This study investigated the distribution, ecological risks, sources and influence factors of 17 PFAAs in water and sediments of rivers from hills to plain areas. The results showed that the detection frequencies were higher for short-chain PFAAs than long-chain PFAAs in water, whereas an opposite pattern was found in sediments. The concentration of ∑PFAAs ranged from 59.2 to 414 ng/L in water and from 1.4 to 60.1 ng/g in sediments. Perfluorohexanoic acid and perfluorooctanoic acid were identified as the main pollutants in the river. The average concentrations of PFAAs were higher in the aquaculture areas (water: 309.8 ng/L; sediments: 43.27 ng/g) than in residential areas (water: 206.03 ng/L; sediments: 11.7 ng/g) and farmland areas (water: 123.12 ng/L; sediments: 9.4 ng/g). Environmental risk assessment showed that PFAAs were mainly low risk or no risk in water, but were moderate risk and even high risk in sediments, especially for perfluorooctane sulfonate. Source apportionment found that PFAA sources were mostly from industry, wastewater discharge, and surface runoff. Dissolved oxygen, chemical oxygen demand, water system circularity, network connectivity and organic matter were significantly correlated to PFAA concentration, indicating that the physicochemical properties and river network might directly influence the environmental behavior of PFAAs. The built-up area was positively correlated with PFAAs. These findings indicated that a comprehensive understanding of the influences of land use and river network structure on PFAAs in rivers is essential for managers to formulate effective PFAA control strategies.

Hidden conflicts? Revealing power mechanisms in collaborative governance for redeveloping heritage districts: The case of Dashilar, Beijing, China

ABSTRACT The redevelopment of Chinese heritage districts increasingly adopts collaborative approaches, raising concerns about power dynamics in these processes and their potential impact on resolving conflicts of interest through collaboration. This study establishes a multi-dimensional framework, examining arenas and sources of power to uncover power mechanisms and their impact on collaborative governance in the redevelopment of Dashilar, Beijing, China. Through ethnographic research, we found that institutionalized collaborative decision-making empowers participants to have the final say on relocation and renovation decisions. However, biased mobilization and discursive practices, with different sources of power utilized, affect collaborative processes and outcomes. Over time, collaborative decision-making results in elite control of Dashilar’s historic fabric and its subsequent gentrification. The government consolidates its power by controlling economic resources and influencing land use decisions. Crucial conflicts remain obscured, weakening the interests of residents and market actors. To understand power in collaborative governance, analysis must encompass both sources and arenas of power, transcending observable interactions within formal institutions to include informal practices.

Revealing the role of land-use features on macrolitter distribution in Swiss freshwaters

Macrolitter, especially macroplastics, (> 0.5 cm) negatively impact freshwater ecosystems, where they can be retained along lake shores, riverbanks, floodplains or bed sediments. Long-term and large-scale assessments of macrolitter on riverbanks and lake shores provide an understanding of litter abundance, composition, and origin in freshwater systems. Combining macrolitter quantification with hydrometeorological variables allows further study of leakage, transport, and accumulation characteristics. Several studies have explored the role of hydrometeorological factors in influencing macrolitter distribution and found that river discharge, runoff, and wind only partially explains its distribution. Other factors, such as land-use features, have not yet been thoroughly investigated. In this study, we provide a country-scale assessment of land-use influence on macrolitter abundance in freshwater systems. We analyzed the composition of the most commonly found macrolitter items (referred to as ‘top items’, n = 42,565) sampled across lake shores and riverbanks in Switzerland between April 2020 and May 2021. We explored the relationship between eleven land-use features and macrolitter abundance at survey locations (n = 143). The land-use features included buildings, city centers, public infrastructure, recreational areas, forests, marshlands, vineyards, orchards, other land, and rivers and canals. The majority of top items are significantly and positively correlated with land-use features related to urban coverage, notably roads and buildings. Over 60% of top items were found to be correlated with either roads or buildings. Notably, tobacco, food and beverage-related products, as well as packaging and sanitary products, showed strong associations with these urban land-use features. Other types of items, however, did not exhibit a relationship with land-use features, such as industry and construction-related items. Ultimately, this highlights the need to combine measures at the local and regional/national scales for effective litter reduction.

Monitoring the effects of climate, land cover and land use changes on multi-hazards in the Gianh River watershed, Vietnam

Abstract In recent decades, global rapid urbanization has exacerbated the impacts of natural hazards due to changes in Southeast Asia’s environmental, hydrological, and socio-economic conditions. Confounding non-stationary processes of climate change and global warming and their negative impacts can make hazards more complex and severe, particularly in Vietnam. Such complexity necessitates a study that can synthesize multi-dimensional natural-human factors in disaster risk assessments. This synthesis study aims to assess and monitor climate change and land-cover/land-use change impacts on flood and landslide hazards in Vietnam’s Gianh River basin. Three Deep Neural Network (DNN) and optimization algorithms, including the Adam, Tunicate Swarm Algorithm (TSA), and Dwarf Mongoose Optimization (DMOA) were used to determine the regions with the probability of the occurrence of flood and landslide and their combination. All efficiently evaluated hazard susceptibility based on a synthesis analysis encompassing 14 natural and anthropogenic conditioning factors. Of the three, the Deep Neural Network (DNN)-DMOA model performed the best for both flood and landslide susceptibility, with area-under-curve values of 0.99 and 0.97, respectively, followed by DNN-TSA (0.97 for flood, 0.92 for landslide), and DNN-Adam (0.96 for flood, 0.89 for landslide). Although the area affected by flooding is predicted to decrease, the overall trend for total hazard-prone areas increases over 2005–2050 due to the more extensive area affected by landslides. This study develop and demonstrate a robust framework to monitor multi-hazard susceptibility, taking into account the changes in climate and land-use influence the occurrence of multiple hazards. Based on the quantitative assessment, these findings can help policymakers understand and identify confounding hazard issues to develop proactive land-management approaches in effective mitigation or adaptation strategies that are spatially and temporally appropriate.

Urban Transformation: Opportunities for Land Use Change in Urban Fabric Redevelopment

With the arrival of modernity in Iran, the concept of the "city" as we understand it today was born, undergoing significant transformations that have continued to evolve over time. These transformations in the physical structure of the city have created multifaceted challenges in three primary dimensions: housing, urban facilities, and transportation. This research, adopting a thematic approach to these challenges and aiming to provide valuable insights for social policymakers and urban planners, employs a descriptive-analytical method. It leverages existing data from documentary resources to explore opportunities for land use change in the process of redeveloping urban fabrics. The study delves deeply into the role of urban transformation in enhancing the quality of life and improving the efficiency of urban spaces. By investigating urban fabrics as crucial components in the redevelopment process, the research analyzes the various factors influencing land use change. Through detailed case studies, the article identifies existing opportunities for the improvement and modification of land uses within urban fabrics, offering practical solutions for optimizing these processes. The ultimate goal of this study is to propose comprehensive strategies for the optimal utilization of urban resources, thereby significantly enhancing the quality of life in urban environments. This study aims to provide a thorough understanding of the dynamics at play in urban redevelopment and to offer actionable recommendations for policymakers and urban planners to create more livable, efficient, and sustainable urban spaces.

ANALISIS PERUBAHAN PENUTUPAN ;AHAN DAN FAKTOR PENDORONG PENGGUNAAN LAHAN KAWASAN HUTAN DESA LAIYA, MAROS

Land cover change is strongly influenced by land use. Increasing population growth results in the need for food and other needs. The causes of land use change are influenced by human activities or activities that directly affect land use. Physical, social and economic factors are factors that trigger land use change in Laiya Village, Cenrana District. The purpose of this study was to describe land cover change in Laiya Village, Cenrana Subdistrict for the period 2011, 2015 and 2019 and to determine the driving factors that influence land use change around the forest area of Laiya Village. This research uses GIS analysis to analyze and see land cover changes that occur and qualitative descriptive methods to determine land use changes. The period 2011-2015 mixed dryland agriculture decreased in area by 2,893.19 ha while shrubs increased in area by 2,744.51 ha. The period 2015-2019 mixed dryland agriculture experienced an increase in land area of 3,030.64 ha and shrubs experienced a decrease in land area of 2,744.51 ha. Factors that influence land use change are physical, social and economic factors. Socio-economic factors are the main driving factor of land use change, the need for land for settlements is increasing due to the high population density that occurs around the forest area of Laiya Village, Cenrana District, Maros Regency which causes people to utilize land as an economic source.

Decision-making factors influencing land use transformation and its implication on forest landscape restoration in Ethiopia

ABSTRACT Macro-level landscape patterns are often a result of a strong influence on human decisions at the micro level. The abilities and objectives of decision-makers should be explicitly addressed to improve our understanding of land use transformation. This research explores the factors influencing smallholder farmers to transform their land use while implementing Forest Landscape Restoration (FLR). We employed a systematic sampling technique to select a study catchment in Southern Ethiopia and 228 households were randomly approached for a household survey. Reaping more economic benefits is the most contributing factor for land use transformation in the study region. Land use transformation towards FLR options such as woodlot and agroforestry is substantially influenced by the location of the farm within the catchment. Furthermore, the study reveals that land allocated for different land uses differs across farmers depending upon their change orientation behaviours categorized as survivalist, subsistence-oriented and market-orientated smallholder farmers. When carrying out FLR in the study region and in similar landscapes that aim to engage smallholder farmers, it is important to promote fast-growing economically rewarding tree species.

Land use and urbanization indirectly control riverine CH4 and CO2 emissions by altering nutrient input

Urban rivers are recognized as significant sources of methane (CH4) and carbon dioxide (CO2) emissions. Despite this, the influence of land use and urbanization on carbon emissions across rural-urban rivers at the watershed scale has been insufficiently explored. This study utilized in-situ surveys of the Liao River in northern China to investigate the spatial and temporal variations of CH4 and CO2 emissions and their relationship with urbanization and its potential controlling factors. The findings revealed that CH4 emissions peaked in fall, whereas CO2 emissions were highest in summer. The average fluxes of CH4 and CO2 at the water-gas interface were 1387.22 ± 2474.98 µmol·m−2·d−1 and 52.78 ± 54.44 mmol·m−2·d−1, respectively. Water quality parameters accounted for 80.49 % of the total variation in CH4 and CO2 concentrations and fluxes. Structural equation modeling indicated that TN, TP, DTC, and conductivity had direct effects on riverine CH4 and CO2 emissions, with standardized direct effects of 0.50 and 0.49, respectively. Nutrient input emerged as the primary driver, increasing CH4 and CO2 concentrations and fluxes, particularly in urban-adjacent river sections likely receiving higher nutrient loads. This study underscores that land use and urbanization indirectly influence riverine CH4 and CO2 emissions by modifying nutrient inputs. Effective land use management and nutrient input control are recommended strategies to mitigate riverine CH4 and CO2 emissions.

Influence of hydroclimatic conditions and anthropogenic activities on the water quality of a floodplain lake (Argentina) during a warm season.

Contamination of water bodies, associated with urbanization, agricultural, and industrial activities, is a serious environmental challenge, with particular concern about microbial pollution due to its public health implications. This study is aimed at evaluating the spatial and temporal variations in the microbiological and physicochemical quality of a floodplain lake used for recreational purposes, whose watershed has been disturbed by diverse anthropogenic activities. The results showed that, while the spatial variation of water quality principally depends on the basin characteristics, temporal variation of water quality depends on land uses, hydrological conditions, and climatic conditions. Rainfall and rising water level intensified the influence of land use on the water quality by increasing concentrations of Escherichia coli, thermotolerant coliforms, and organic matter and decreasing dissolved oxygen. Thus, the residents and tourists are potentially exposed to microbiological risks given that it exceeds the international standards suggested for recreational waters on some occasions. It would be advisable to improve routine bathing water monitoring and management to preserve the health of the inhabitants and limit the recreational use of the water body in the days following heavy rainfall as well as during the beginning of the increase in the hydrometric level.

Role of land use, green energy, and water resources for food accessibility: Evidence from emerging economies in the lens of COP28

AbstractIn the era of COP28, where most of the developed and developing economies concentrate more on the development of environmentally friendly energy resources to tackle the issue of climate change. Nevertheless, the literature lacks appropriate evidence regarding the influences of green energy and other resources on food security. This study analyses the influences of land use, green energy, and water resources on food accessibility in emerging economies, while also considering the important roles of natural resources, research and development (R&D) expenditure, and economic growth during 1980–2020. Due to non‐linear data dispersion, the novel moments quantile regression is employed. Results assert that land use has a positive significant influence on food accessibility in the presence of water resources and a weaker negative impact in the presence of natural resources. Natural and water resources are detrimental to food accessibility in the Emerging Seven (E7) countries. Furthermore, R&D expenditure and green energy positively (negatively), while economic growth negatively (positively) impacted food accessibility in the presence of natural resources (water resources). The results are robust and validate causal inferences that help develop appropriate policies for emerging economies concerning food accessibility or security. In this rapidly evolving era, most empirical studies consider environmental quality. Conversely, this study contributes to the literature by examining the factors influencing food accessibility, as this issue is of considerable importance because of the rapidly growing global population.

Metro Stations as Catalysts for Land Use Patterns: Evidence from Wuhan Line 11

Urban rail transit systems significantly influence land use patterns in newly developed areas, yet their impact on spatial organization and functional characteristics remains understudied. This research examines Wuhan Metro Line 11, analyzing land use within an 800 m radius of stations using Point of Interest data, ArcGIS spatial analysis, and locational entropy methods. The study reveals three station types, i.e., single-function, mixed-function, and underdeveloped, each exhibiting distinct spatial differentiation patterns. On this basis, a novel “core-diffusion” model emerges, with the highest density of functional elements observed at approximately 600 m from station centers, challenging conventional proximity assumptions. Three spatial organization modes are identified: single-core independent in two-level axis, single-core continuous in single-level axis, and double-core continuous in two-level axis. These findings contribute to the Transit-Oriented Development literature, offering sustainable insights into optimizing land use around metro stations in rapidly urbanizing contexts. This study also provides a methodological framework applicable to similar urban environments, enhancing the understanding of the complex relationships between metro development and surrounding land use patterns. These results have significant implications for urban planning and policy-making, particularly in emerging economies seeking to balance transit efficiency with sustainable urban growth.

The Influence of Urban Land-Use on Criminalities and Safety in Nigerian Public Places: The Case of Abuja Municipal Area Council (AMAC), Abuja, Nigeria

The Influence of Urban Land-Use on Criminalities and Safety in Nigerian Public Places: The Case of Abuja Municipal Area Council (AMAC), Abuja, Nigeria

Construction of ecological security pattern of arid area based on landscape ecological risk assessment: a case study of the Wu-Chang-Shi urban agglomeration.

The construction of ecological security pattern (ESP) holds paramount importance in ensuring regional environment sustainability. This study introduces an innovative approach to ESP construction grounded in landscape ecological risk (LER) assessment, with Wu-Chang-Shi urban agglomeration in Xinjiang, China, serving as a case study. Initially, LER within the area was evaluated using the LER Index (LERI) method. Subsequently, the Geodetector model was employed to discern the relationship between multi-source data and LER. Furthermore, ecological resistance and corridors were delineated utilizing the minimum cumulative resistance (MCR) model. Lastly, the corridors were optimized using the gravity model, finalizing the ESP construction. Study results reveal that LER was always fluctuating from 1990 to 2010, and tended to stabilize from 2010 to 2020. Factor detection underscores the predominant influence of land use on LER, followed by elevation and vegetation distribution. The ESP shows the imperative for improving connectivity of the natural areas that are fragmented by urban land, highlighting the great significance of the woodland-originating corridors. Finally, strategies are proposed to enhance woodland and water coverage, boost landscape diversity in nature reserves, and prioritize ecological conservation in corridor regions. In summation, the study furnishes a framework for analyzing arid regions in Eurasia. Furthermore, the research idea of evaluation-analysis-remodeling also offers insights into environmental management in developing areas with more diverse climate types.