Land Use Composition Research Articles

Exploring the role of smallholder perceptions in shaping land-use decisions in a tropical agro-forest frontier in southern Mexico

Conversion of tropical forests into agricultural lands is increasing at a rapid pace. Smallholders are responsible for most of the world’s agricultural production, and thus are important land-use decision-makers and land-use change actors. In agro-forest frontiers, land-use changes are dynamic and short-term, and highly influenced by different social-ecological factors. We employed the Photovoice methodology to assess how the perceptions of 20 smallholder families about what they most value in their daily lives, influence farm land-use decisions in two villages in southern Mexico. Results indicate that what farmers perceive as the most valued in their daily lives are the household (including family and food) and the farm. Similar perceptions sometimes result in similar farm land-use composition (land-use type and proportion) decisions (agriculture, reforestation), but sometimes not (pasture, forest). Positive and negative perceptions about oil palm highly influence whether this land-use is adopted or not. In contrast, positive perceptions about rubber do not always translate in this crop being planted. We conclude that perceptions play an important role in smallholder land-use decisions. However, perceptions are influenced and operate along other factors at multiple levels, including survival motivations, culture, economic considerations, markets, farm size, institutional programs, local ecological knowledge, ecosystem services, and risk assessment. We suggest that smallholder perceptions should be taken into account as part of the set of social-ecological factors driving land-use decisions. Involving farmers in the co-design of land-use policies, planning, and rural development initiatives that address their perceptions, values, and livelihood needs will improve the effectiveness of such policies.

Land-Use Composition, Distribution Patterns, and Influencing Factors of Villages in the Hehuang Valley, Qinghai, China, Based on UAV Photogrammetry

Rapid changes in land use have rendered existing data for land-use classification insufficient to meet the current data requirements for rural revitalization and improvements in the living environment. Therefore, we used unmanned aerial vehicle (UAV) remote sensing imagery and an object-based human-assisted approach to obtain ultra-high-resolution land-use data for 55 villages and accurately analyzed village land-use composition and distribution patterns. The highest proportion of land use in the villages is built-up land (33.01% ± 8.89%), and the proportion of road land is 17.76% ± 6.92%. The proportions for forest land and grassland are 16.41% ± 7.80% and 6.51% ± 4.93%, respectively. The average size of the villages is 25.85 ± 17.93 hm2, which is below the national average. The villages have a relatively scattered distribution, mostly concentrated on both sides of the main roads. The correlation analysis indicates that mean annual temperature (MAT) and annual precipitation (AP) are the primary factors influencing the land-use composition of villages, with contribution rates of 50.56% and 12.51%, respectively. The use of UAV remote sensing imagery to acquire ultra-high-resolution land-use data will provide a scientific basis for the planning of the living environment in the villages of the Hehuang Valley.

Land Use Impact on Water Quality and Phytoplankton Community Structure in Danjiangkou Reservoir

The composition and intensity of land use significantly influence the aquatic ecological environment, further affecting the physicochemical attributes of the water body, and indirectly modulating the phytoplankton community structure. This study centers around the Danjiangkou Reservoir, investigating the correlation between land use, water environment, and phytoplankton alongside varying intensities of anthropogenic activities, based on the review of land use, phytoplankton, and water quality data of 2021. Firstly, an analysis was conducted over five circular buffer zones generated around sampling points with radii set at 500 m, 1000 m, 1500 m, 2000 m, and 2500 m, wherein the intensity of human activity was categorized into low, medium, and high, in accordance with the human activity intensity level score (HAILS). This study proceeded to explore the correlation between land use and the water environment across different scales, compared phytoplankton density and community structure differences across varied levels of human activity, and analyzed the association between phytoplankton communities in the Danjiangkou Reservoir and environmental variables under various intensities. The findings showed: The land use within the 500 m circular buffer zone has the greatest impact on the water quality of the Danjiangkou Reservoir, especially with the increase in human activities leading to elevated nutrient levels in the water, thereby promoting the growth and reproduction of algae, and increasing the risk of algal blooms. This research scrutinizes the relationship between land use, water environment, and plankton under varying human activity intensities, serving as a foundation for environmental management sectors to make informed decisions and promote the sustainable development of the catchment water environment.

Transformation scenarios towards multifunctional landscapes: A multi-criteria land-use allocation model applied to Jambi Province, Indonesia

In tropical regions, shifting from forests and traditional agroforestry to intensive plantations generates conflicts between human welfare (farmers’ demands and societal needs) and environmental protection. Achieving sustainability in this transformation will inevitably involve trade-offs between multiple ecological and socioeconomic functions. To address these trade-offs, our study used a new methodological approach allowing the identification of transformation scenarios, including theoretical landscape compositions that satisfy multiple ecological functions (i.e., structural complexity, microclimatic conditions, organic carbon in plant biomass, soil organic carbon and nutrient leaching losses), and farmers needs (i.e., labor and input requirements, total income to land, and return to land and labor) while accounting for the uncertain provision of these functions and having an actual potential for adoption by farmers. We combined a robust, multi-objective optimization approach with an iterative search algorithm allowing the identification of ecological and socioeconomic functions that best explain current land-use decisions. The model then optimized the theoretical land-use composition that satisfied multiple ecological and socioeconomic functions. Between these ends, we simulated transformation scenarios reflecting the transition from current land-use composition towards a normative multifunctional optimum. These transformation scenarios involve increasing the number of optimized socioeconomic or ecological functions, leading to higher functional richness (i.e., number of functions). We applied this method to smallholder farms in the Jambi Province, Indonesia, where traditional rubber agroforestry, rubber plantations, and oil palm plantations are the main land-use systems. Given the currently practiced land-use systems, our study revealed short-term returns to land as the principal factor in explaining current land-use decisions. Fostering an alternative composition that satisfies additional socioeconomic functions would require minor changes (“low-hanging fruits”). However, satisfying even a single ecological indicator (e.g., reduction of nutrient leaching losses) would demand substantial changes in the current land-use composition (“moonshot”). This would inevitably lead to a profit decline, underscoring the need for incentives if the societal goal is to establish multifunctional agricultural landscapes. With many oil palm plantations nearing the end of their production cycles in the Jambi province, there is a unique window of opportunity to transform agricultural landscapes.

Characteristics Analysis and Prediction of Land Use Evolution in the Source Region of the Yangtze River and Yellow River Based on Improved FLUS Model

Climate change profoundly alters land use in alpine regions, and delving into the evolutionary characteristics of these changes is crucial for the sustainable development of regional land resources and the gradual enhancement of the ecological environment. Taking the source region of the Yangtze and Yellow River (SRYAYE) as a case study, we integrate permafrost and snowfall data into the Future Land Use Simulation model (FLUS). Analyzing historical land use, we predict and simulate the land use scenarios for 2030, 2035, and 2060 under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 climates, and conduct a detailed analysis of the scale, composition, and pattern of land use in this area. Scale. The results showed that ① the Kappa coefficient of the improved FLUS model was higher than 0.927, and that the overall accuracy of the simulation was increased by 2.64%; ② the area of forest land and the high-coverage grassland will increase in the future and the center of gravity will migrate to the west, and that the area of moderate and low-coverage grassland will slightly decrease but tend to become green to the west; and ③ the fragmentation degree of the SRYAYE is decreasing, and the influence of human activities on the landscape pattern is weaker than in the past.

Spatio-Temporal Changes and Habitats of Rare and Endangered Species in Yunnan Province Based on MaxEnt Model

Biodiversity is crucial for ecosystem functioning, but it is rapidly declining due to human activities and climate change. Protecting biodiversity has become a key priority for global environmental conservation actions. Rare and endangered species have a great impact on the ecosystem, yet due to their limited survival capacity, they are more prone to extinction, thus exerting a significant impact on biodiversity. However, current research reveals a lack of information concerning the potential distribution and changes of these species. This study used the maximum entropy model to predict the present and future potential habitats of rare and endangered species in Yunnan Province. After superimposing model results, four richness regions are divided by the natural breakpoint method and analyzed. Existing protected areas are compared with hotspots, and the land-use composition of hotspots is also analyzed. The results revealed that, in both current and future scenarios, rare and endangered species in Yunnan Province are primarily found in the western mountainous region, the Xishuangbanna–Wenshan high temperature area, and the Kunming–Qujing dense vegetation cover area. These species are also expanding their distribution towards the western mountainous area. However, under the low carbon emission scenario (RCP2.6), these species will spread from the high abundance regions to the low altitude hotspots by 2070. In the high carbon emissions scenario (RCP8.5), there will be fewer high abundance areas in 2070 than in 2050. The transfer matrix analysis reveals regional richness variations over time. Furthermore, the analysis revealed significant conservation gaps and found that existing hotspot areas were heavily affected by human activities. To improve conservation efficiency, it is necessary to enhance the protection of existing hotspots in Yunnan Province. Climate change plays a significant role in species migration, with precipitation levels being a key factor. The necessary actions should be taken to address the insufficient protection, resolve conflicts between human activities and land use in critical areas, and formulate effective strategies for adapting to future climate changes. Yunnan Province, with its rich species resources, has the potential to become a global innovator in biodiversity conservation by implementing improved conservation strategies.

Adapting moving‐window metrics to vector datasets for the characterization and comparison of simulated urban scenarios

AbstractDescriptive scenarios about the possible evolution of land use in our cities are essential instruments in urban planning. Although the simulation of these scenarios has enormous potential, further characterization is needed in order to be able to evaluate and compare them so as to provide more effective support for public policy. One of the most commonly used tools for assessing these scenarios is spatial moving‐window metrics, a useful mechanism for extracting accurate information from simulated land‐use maps on urban diversity and urban growth patterns. This article seeks to explore this question further and has two main aims. First, to develop and implement vSHEI and vLEI, two multiscale composition and configuration vector moving‐window metrics for calculating urban diversity and urban growth patterns. Second, to test these metrics using the spatially explicit simulation of three prospective scenarios in the Henares Corridor (Spain), comparing the results and analyzing how well the scenario narratives match their spatial configuration, as measured using vSHEI and vLEI. Via the implementation of vSHEI and vLEI, we obtained urban diversity and urban expansion values at a local level, offering more precise and more realistic, mappable information on the composition and configuration of urban land use than that provided by raster metrics or by vector Patch‐Matrix model metrics. We also used these metrics to test whether the simulated scenarios matched their description in the narrative storylines. Our results demonstrate the potential of vector moving‐window metrics for characterizing the urban patterns that might develop under different scenarios at the parcel level.

Modeling the Impact of Land Use Optimization on Non-Point Source Pollution: Evidence from Chinese Reservoir Watershed

We assessed the effectiveness of land optimization for controlling non-point source (NPS) pollution by combining a multi-objective dynamic planning approach with the application of the Land Use and its Effects at Small regional extents model and the Soil and Water Assessment Tool. The combined modeling approach showed substantial ability to reduce NPS pollution in Shitoukoumen Reservoir, Changchun City, China, reducing the annual total loads of nitrogen and phosphorus in the study area by 8.7 and 10.12%, respectively. The total nitrogen load decreased significantly and stabilized at less than 8 kg/hm2 from a peak level of over 15 kg/hm2. Higher total phosphorus loads before land use optimization were concentrated in the central parts of the study area, with the highest values exceeding 2.3 kg/hm2, and tended to spread outward but resolved at 1.5 kg/hm2 after optimization. The results showed that from a macro-perspective, optimization of the spatial distribution and quantitative composition of land use can effectively control NPS pollution. The study also demonstrates the potential effectiveness of the coupled multi-model methodology for mitigating NPS in the future.

Oil palm plantations in an aging agricultural landscape in the eastern Amazon: Pushing Amazon forests farther from biodiversity-friendly landscapes

Oil palm plantations across the tropics are intended to promote sustainable production by incorporating degraded lands while sparing old-growth forests. Here, we examine the trajectory of an Amazonian-forest focal landscape as it experiences the expansion of oil palm and its interactions with multiple land-uses. Land-use composition, landscape spatial configuration and structure in a 765.65-km2 watershed were examined over a 16-yr period (2002–2018) via Landsat imagery. Briefly, (1) old-growth forest coverage dropped from 37.3 % to 18.3 % across the whole landscape, (2) secondary forest and arable fields expanded until 2014, and (3) oil palm plantations emerged in 2010 with a positive trend thereafter, resulting in an 11.9 % expansion until 2018. In 2018, only 140.7 km2 of old-growth forest persisted, while oil palm plantations covered 91.8 km2. Oil palm expansion resulted from 14 land-use trajectories, with changes involving old-growth forests accounting for half the area (48.1 %) covered by plantations in 2018. However, only 0.4 % of the plantation area resulted from a direct conversion of old-growth forests. Landscape structure became increasingly degraded, which included the elimination of gallery forests, the proliferation of edge-affected habitats and the collapse of forest structural connectivity. Our results suggest that the eastern Amazon is still experiencing forest loss and exhibit highly dynamic land-use changes. Furthermore, landscapes continue to suffer degradation of key attributes related to biodiversity persistence and the provision of ecosystem services. Oil palm plantations have a catalytic effect on land-use dynamics, speeding up forest shrinking and landscape degradation. The oil palm sector requires a better governance based on guidelines able to guarantee either the persistence or the emergence of biodiversity-friendly landscapes.

Factors influencing short-term parasitoid establishment and efficacy for the biological control of Halyomorpha halys with the samurai wasp Trissolcus japonicus.

Classical biological control has been identified as the most promising approach to limit the impact of the invasive pest species Halyomorpha halys (Heteroptera: Pentatomidae). This study investigated the parasitism rate at sites where the biocontrol agent Trissolcus japonicus (Hymenoptera: Scelionidae) was released and where its unintentional introduction took place, in the Trentino-South Tyrol region. The effect of land-use composition was studied to understand which factors favor the establishment of hosts and parasitoids, including native and exotic species. The released T.japonicus were detected a year after the start of the program, with a significant parasitoid impact and discovery, compared to control sites. Trissolcus japonicus was the most abundant H.halys parasitoid, and Trissolcus mitsukurii and Anastatus bifasciatus were recorded also. The efficacy of T.mitsukurii was lower in sites where T.japonicus was successfully established, suggesting a possible competitive interaction. Parasitism level by T. japonicus at the release sites was 12.5% in 2020 and 16.4% in 2021. The combined effect of predation and parasitization increased H.halys mortality up to 50% at the release sites. Landscape composition analysis showed that both H.halys and T.japonicus were more likely to be found at sites with lower altitude and with permanent crops, whereas other hosts and parasitoids preferred different conditions. Trissolcus japonicus showed a promising impact on H.halys, at release and adventive sites, with minor nontarget effects, mediated by landscape heterogeneity. The prevalence of T.japonicus in landscapes with permanent crops could support IPM in the future. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Measuring the relationship between morphological spatial pattern of green space and urban heat island using machine learning methods

Land use pattern can substantially shape urban thermal environment. Although previous studies have shown that urban heat island (UHI) intensity will be easily affected by the landscape pattern of green space, the relationship between the morphological spatial pattern of green space and UHI intensity remains to be discovered. Compared with landscape pattern, morphological spatial pattern analysis (MSPA) can reveal more specific details on the configuration and composition of land use. Therefore, this study aims to explore whether the morphological spatial pattern of land use matters to UHI using machine learning methods. Firstly, the morphological characteristics of green space were analyzed based on MSPA. Secondly, the linear associations between UHI intensity and a set of potential influencing factors (including morphological characteristics) were measured according to correlation coefficient. Lastly, the non-linear contribution of the morphological factors to UHI intensity was quantified based on random forest. An empirical case study in a rapidly-urbanized city has revealed the huge influence of morphological characteristics on UHI intensity with benchmark factors considered. The UHI intensity was negatively correlated with the cores, perforations, and loops of green space, but positively correlated with islets. Therefore, a few large core areas would be better than a large number of small islets when the total amount of green space is fixed. In addition, the fragmented patches of green space should be integrated or connected to enhance the cooling capacity. Our findings could offer some insights for UHI mitigation and land use planning, especially when the size of green space cannot be unlimitedly increased.

Impact of the Beijing-Tianjin sandstorm source control project on ecosystem services and an evaluation of economic benefits

<p indent="0mm">The Beijing-Tianjin sandstorm source control project (BTSSCP) is a large and famous ecological construction project with enormous investment that aims to improve and optimize the ecological condition of Beijing-Tianjin and the surrounding areas. Since the implementation of the BTSSCP in 2000, profound changes have occurred in the region regarding land use, vegetation cover, soil, wind and water erosion, and the supply of regional ecosystem services (ESs). Changes in regional ESs are influenced not only by human activities but also by natural factors such as climate change. Distinguishing and quantifying the roles of climate change and land-use change on regional ES changes can better serve sustainable land-use management decisions at the regional and national levels. Additionally, information is needed on the economic benefits caused by sandstorm control and ecological restoration, such as the value change of the regulating ESs since the BTSSCP began, the variation in the spatial patterns of ESs and their integration, and the contribution of sand control and vegetation restoration to regional ES changes. Moreover, a landscape-level ES multifunctionality concept and measurement framework provided deep insight into the spatial supply-benefit relationship of ESs, and this information is crucial for sustainable ecosystem management and land-use planning. In this study, a set of ES indicators that represent ecological provisioning (<italic>n</italic>=2), regulating (<italic>n</italic>=4), and supporting (<italic>n</italic>=2) services at the county scale in the BTSSCP were calculated based on a field survey, Normalized difference vegetation index (NDVI) data, land-use data, meteorological data (i.e., temperature, precipitation, wind speed, and direction) and socioeconomic census data. Then, the ES multifunctionality of each county was assessed using the multiple ES landscape index (MESLI) and the ES Shannon diversity index (ESHDI). Variation partitioning was used to distinguish the contributions of land-use area composition and major climatic conditions (annual average temperature, annual precipitation, and average wind speed) to various ESs, and the MESLI and ESHDI in different periods were measured and compared. Partial least squares path modeling (PLS-PM) was applied to determine the direct and indirect effects of the BTSSCP on the regional ecological supply, ecological regulation, habitat support services and multifunctional indicators of ESs and their changes. The results showed that (1) the implementation of the BTSSCP effectively improved the regulating ESs in Beijing, Tianjin and surrounding areas and promoted the overall improvement of the comprehensive benefits of regional ESs while effectively improving the integration and diversity of ESs in the core areas of wind and sand management. The MESLI increased in 94.8% of all counties in 2015 compared to 2000. (2) Both land-use composition and climatic factors had impacts on the regional ES provisions, but the influence of land use on the regulating and provisioning ESs was significantly higher than that of climatic factors. The direct effect of land use on ES provision, regulation, and support was enhanced, the multifunctionality of regional ESs was dramatically improved, and the role of climatic factors markedly declined as the project proceeded. (3) The economic benefits of the BTSSCP were positive, with a 415300 yuan/km² increase in the content of regulating ESs, and 82.7% of counties had reduced wind erosion after BTSSCP implementation, which indicated that the comprehensive economic benefits of BTSSCP implementation were significant. These results provide a scientific basis for evaluating the benefits of the BTSSCP and serve as a reference for developing new national management strategies.

Carbonate bedrock control of soil Cd background in Southwestern China: Its extent and influencing factors based on spatial analysis

Previous studies have found that Cadmium (Cd) may be condensed during the processes of the weathering and soil formation over carbonate bedrock, which is a typical phenomenon in the southwest region of China. However, the extent of the high value background and the geographical factors influencing its spatial distribution are still unknown. This study collected data from the Multi-Purpose Regional Geochemical Survey (MPRGS) and the Regional Geochemistry-National Reconnaissance Program (RGNR) to investigate the extent and its controlling factors based on spatial analysis. It was found that the RGNR is an ideal data source for regional Cd background studies. Spatially, the high Cd area (Cd > 1.5 m/kg with reference of the GB15618-2018 soil environmental quality in China, 68.9 × 103 km2) coincide well with the carbonate distribution. In the total area (68.9 × 103 km2) with high Cd concentration, 89.8% is related to carbonates. The composition of parent rock, climate conditions, and landuse are controlling factors of the enrichment. The high Cd background effect of limestone is higher than that of dolomite and their effects decease with increasing detritus component they contain. Warm and humid climate in forest land helps to enrich Cd during weathering. Soil Cd concentration related to carbonate background can be predicted by major element concentrations, which is useful for differentiating Cd background from human pollution in the future soil pollution monitoring. Modelling by artificial neural network (ANN) is recommended rather than tradition multiple linear methods (LM) as the latter may have the effect of collinearity.

A theoretical foundation for investigating the spatial economic attributes of airport-centric developments

Abstract Among the various areas of interest on the topic of airports and the geographical distribution of land use, one pertinent theme is the spatial economic analysis of airports and their environs. However, the existing literature predominantly focuses on describing the land-use composition of airport-centric developments, without unpacking the spatial economic forces at play. This gap brings to the fore the need to employ an appropriate theoretical lens to guide the spatial economic analysis of airports and their environs. The aim of this theoretical review paper is thus to identify concepts that are relevant to the analysis of airports and their environs; and to use those concepts to systematically identify the existing theory that is most suitable for investigating the spatial economic forces that drive airport-centric developments. Against the background of globalisation, we scrutinise classical location theories, regional science, growth pole theory and new economic geography against their relational interpretations of the concepts of space, proximity, firm, scale and pattern. Given that it portrays a relational perspective of the aforesaid concepts, the paper concludes that growth pole theory is suitable as the main framework for analysing airport-centric developments. It is therefore recommended that growth pole theory be empirically used to guide the analysis of airports and their environs, and subsequently be used as the basis for developing a theoretical framework tailored for airport-centric developments.

Rural–Urban Transformation and Landuse Dynamics in Gunungpati on the Northern Flank of Mt. Ungaran, Semarang, Indonesia

Most of the northern flank of Mt. Ungaran is subject to intensive land occupation that makes landuse change inevitable. The research objectives of this study were to examine the spatial patterns of land-use dynamics from 1997 to 2018 and to analyze their impact on the rural–urban structure of Gunungpati sub-district using on-screen digitation. Rural–urban structure was analyzed based on landuse composition by area in each village. This research revealed that forest areas and paddy fields were decreasing year by year. Over the study period of 21 years, Gunungpati experienced deforestation of 1,777 ha and increase in built-up area of 1,295 ha, forcing shifting in rural structure. Most villages that were categorized as rural frame zones in 1997 had changed into urban–rural frame zones by 2018. This situation must be controlled, since much of Gunungpati territory plays a significant role as a groundwater recharge zone for the Semarang lowland area.

Evaluating Spatiotemporal Distribution of Residential Sprawl and Influencing Factors Based on Multi-Dimensional Measurement and GeoDetector Modelling

Residential sprawl constitutes a main part of urban sprawl which poses a threat to the inhabitant environment and public health. The purpose of this article is to measure the residential sprawl at a micro-scale using a case study of Hangzhou city. An integrated sprawl index on each 1 km × 1 km residential land cell was calculated based on multi-dimensional indices of morphology, population density, land-use composition, and accessibility, followed by a dynamic assessment of residential sprawl. Furthermore, the method of GeoDetector modeling was applied to investigate the potential effects of location, urbanization, land market, and planning policy on the spatial variation of residential sprawl. The results revealed a positive correlation between CO2 emissions and residential sprawl in Hangzhou. There has been a remarkable increase of sprawl index on residential land cells across the inner suburb and outer suburb, and more than three-fifths of the residential growth during 2000–2010 were evaluated as dynamic sprawl. The rapid development of the land market and urbanization were noted to impact the spatiotemporal distribution of residential sprawl, as q-statistic values of population growth and land price ranked highest. Most notably, the increasing q-statistic values of urban planning and its significant interactions with other factors highlighted the effects of incremental planning policies. The study derived the policy implication that it is necessary to transform the traditional theory and methods of incremental planning.

Catchment versus Riparian Buffers: Which Land Use Spatial Scales Have the Greatest Ability to Explain Water Quality Changes in a Typical Temperate Watershed?

Identifying the multi-scale spatial relationship between land use and water quality is critical for determining the priorities and key areas of river management. To more accurately identify the scale effect of land-use patterns on water quality and quantitatively distinguish the difference in the impacts of land-use composition and configuration on water quality, we used 94 sites to extract the upstream catchment and riparian buffer zone with different widths. The results showed that the ability of land use variables with different buffer widths to explain water quality differed slightly from the ability of these variables at the catchment scale, and the joint explanatory ability of land use composition and configuration was greater than that of each individually. The patch density and landscape shape index of cultivated land, shrubland, and built-up land in the buffer area close to the water bodies were the main factors for the increase in the concentration of total nitrogen, nitrate nitrogen, total phosphorus, and suspended solids. As the width of the buffer increased, the role of the percent of land use increased. Our research indicates that water quality management needs to adopt a multi-scale perspective and focus on key local areas while coordinating at a broader scale.

Identifying the spatial disparities and determinants of ecosystem service balance and their implications on land use optimization

Ecosystem services (ESs) are increasingly affected by human interventions, and the ES balance between supply and demand plays a vital role in guaranteeing the expected efficacy of ecosystem restoration projects. However, the spatial disparities of ES balance, along with its determinants and spillover effects, remain unclear, constraining effective ES management and landscape planning. The aim of this study was to fill these gaps by quantifying the ES balance in the restoring Loess Plateau using an expert-based ES matrix approach and by examining the spatial associations between ES balance and driving factors via an integrated regression approach. The results showed that the county-scale ES balance was closely related to the land-use composition and population density. Geographic locations of counties with ES surplus were mainly concentrated in mountainous areas with high proportions of woodland and grassland, while urbanized land and a high population density resulted in an ES deficit. Forest and grass regeneration, due to revegetation practices, alleviated ES deficits, while rapid urbanization and population growth aggravated ES imbalance. The integrated regression approach demonstrated that the ES balance and its dependencies (i.e., landscape metrics and population density) had remarkable spatial heterogeneity and spillover effects, which should be practically considered in localized ES management and landscape optimization. Excessive agricultural reclamation and urban expansion improved grain productivity and economic profits but deteriorated landscape fragmentation, further aggravating the ES deficit. In contrast, excessive revegetation practices promoted ecosystem restoration and improved ES surplus but threatened food security. Therefore, an appropriate balanced state should be maintained for sustainable ecosystem restoration through timely and efficient policy interventions and landscape optimization.

Analysis on bike-share ridership for origin-destination pairs: Effects of public transit route characteristics and land-use patterns

Studies on bike-share programs have dramatically increased during the past decades. While numerous studies have examined various factors affecting bike-share demand at the station-level, few attempts have been made to understand bike-share ridership at the origin-destination (OD) level due to technical difficulties. The objective of this study is to examine whether existing public transit characteristics affect bike-share ridership at OD-level. We combined three datasets: (1) bike-share ridership data, (2) land-use and bike-transit infrastructure, and (3) bike-transit route characteristics between OD pairs of bike stations. Zero-inflated negative binomial (ZINB) regression models were used for the analysis. Our results showed that the travel distance between OD bike stations, land-use compositions, and the existence of bike-friendly infrastructures were significant factors determining bike-share ridership at the OD-level. In particular, a longer duration of public transit trips than bike-share, and more transit transfers, were associated with bike-share ridership. Further, this study showed that bike-share and public transit might compete with or promote each other, even within the city. The study's findings suggest that the relative efficiency of bike-share compared to public transit is highly associated with bike-share demand and help to increase the utility of bike-share system in response to several limitations of existing public transit networks.

Investigation the Robustness of Standard Classification Methods for Defining Urban Heat Islands

In the process of studying the spatiotemporal cause mechanism of urban heat island (UHI) effects, the classification method used will directly affect the robustness of urban surface heat classification. Applying five commonly used standard classification methods, we divided Beijing's urban surface temperatures in the summer of 2020 into five levels. We then compared the reliability of the five classification methods in resolving 12-period data and the seasonal average temperature in UHI patches, based on two indicators: UHI area and UHI intensity. The actual land-use composition of the UHI patches obtained with traditional methods was applied to confirm our results. The mean-standard deviation method and natural breaks (Jenks) method were more robust with regard to UHI classification and 12-period data reliability. For the UHI area index, the mean-standard deviation method produced the smallest total area of UHI patches for summer days and nights. For the UHI intensity index, the quantile method, mean-standard deviation method, and natural breaks (Jenks) method were associated with smaller errors. Considering the composition of land-use types in UHI patches, the mean-standard deviation method, and natural breaks (Jenks) method were more rigorous. Thus, our research results provide guidance for method selection when classifying UHI.