Land Use Data Research Articles

Driving Factors of Land Change in China’s Loess Plateau: Quantification Using Geographically Weighted Regression and Management Implications

Land change is a key topic in research on global environmental change, and the restoration of degraded land is the core component of the global Land Degradation Neutrality target under the UN 2030 Agenda for Sustainable Development. In this study, remote-sensing-derived land-use data were used to characterize the land-change processes in China’s Loess Plateau, which is experiencing large-scale ecological restoration. Geographically Weighted Regression was applied to capture the spatiotemporal variations in land change and driving-force relationships. First, we explored land-use change in the Loess Plateau for the period 1990–2015. Grassland, cropland and forestland were dominant land cover in the region, with a total percentage area of 88%. The region experienced dramatic land-use transitions during the study period: degraded grassland and wetland, expansion of cropland and built-up land and weak restoration of forestland during 1990–2000; and increases in grassland, built-up land, forestland and wetland, concurrent with shrinking cropland during 2000–2015. A Geographically Weighted Regression (GWR) analysis revealed altitude to be the common dominant factor associated with the four major land-use types (forestland, grassland, cropland and built-up land). Altitude and slope were found to be positively associated with forestland, while being negatively associated with cropland in the high, steep central region. For both forestland and grassland, temperature and precipitation behaved in a similar manner, with a positive hotspot in the northwest. Altitude, slope and distance to road were all negatively associated with built-up land across the region. The GWR captured the spatial non-stationarity on different socioeconomic driving forces. Spatial heterogeneity and temporal variation of the impact of socioeconomic drivers indicate that the ecological restoration projects positively affected the region’s greening trend with hotspots in the center and west, and also improved farmer well-being. Notably, urban population showed undesired effects, expressed in accelerating grassland degradation in central and western regions for 1990–2000, hindering forestland and grassland restoration in the south during 2000–2015, and highlighting the long-term sustainability of the vegetation restoration progress. Such local results have the potential to provide a methodological contribution (e.g., nesting local-level approaches, i.e., GWR, within land system research) and spatially explicit evidence for context-related and proactive land management (e.g., balancing urbanization and ecological restoration processes and advancing agricultural development and rural welfare improvement).

Biogenic Isoprene Emissions and Temporal and Spatial Distribution Characteristics in Tianjin

Based on the localized improved GLOBEIS model, the total amount of biogenic isoprene emissions in Tianjin in 2018 was estimated and the temporal and spatial distribution characteristics were analysed by using the land-use type data interpreted from remote sensing images and the observed hourly meteorological data. The results show that the total amount of biogenic isoprene emission in Tianjin reached 694 t (calculated by C, the same below) in 2018, and the emission intensity was 0.06 t/km2/a. The diurnal, monthly and seasonal variations of biogenic isoprene emissions are obvious: High at noon and low at night; Highest in August and lowest in January; Emissions in summer are the largest while the smallest in winter. The spatial characteristics are closely related to land-use types, and the emissions of biogenic isoprene are mainly concentrated in the forest areas, and the emissions are small in the Urban districts of the city and Binhai New District. Finally, the uncertainty sources of biogenic isoprene emission estimation were analysed.

A Generalized Automated Framework for Urban Runoff Modeling and Its Application at a Citywide Landscape

This research presents a fully automated framework for runoff estimation, applied to Philadelphia, Pennsylvania, a major urban area. Trends in global urbanization are exacerbating stormwater runoff, making it an increasingly critical challenge in urban areas. Understanding the fine-scale spatial distribution of local flooding is difficult due to the complexity of the urban landscape and lack of measured data, but it is critical for urban management and development. A one-meter resolution Digital Elevation Model (DEM) was used in conjunction with a model developed by using ArcGIS Pro software to create urban micro-subbasins. The DEM was manipulated to account for roof drainage and stormwater infrastructure, such as inlets. The generated micro-subbasins paired with 24-h storm data with a 10-year return period taken from the National Resources Conservation Service (NRCS) for the Philadelphia area was used to estimate runoff. One-meter land-cover and land-use data were used to estimate pervious and impervious areas and the runoff coefficients for each subbasin. Peak runoff discharge and runoff depth for each subbasin were then estimated by the rational and modified rational methods and the NRCS method. The inundation depths from the NRCS method and the modified rational method models were compared and used to generate percent agreement, maximum, and average of inundation maps of Philadelphia. The outcome of this research provides a clear picture of the spatial likelihood of experiencing negative effects of excessive precipitation, useful for stormwater management agencies, city managers, and citizen.

Land Use Change in the Major Bays Along the Coast of the South China Sea in Southeast Asia from 1988 to 2018

Bays are some of the core areas for marine economic development. The South China Sea coast is one of the most developed and dynamic places in the Asia-Pacific. In this study, we focused on the large bays surrounding the South China Sea. The techniques of image segmentation and supervised classification as well as image interpretation were used to acquire land-use data of 41 bays from 1988 to 2018. Then, we quantified the intensity and pattern of land-use and land-cover change during the two periods. Plantation land was the dominant agriculture land type as well as the second land use type after natural forest. Agriculture land cover increased from 29.8% to 40.9% and the growth was driven by plantation expansion. Deforestation was serious, including both natural forests and mangroves. Natural forest cover decreased by 31.6% and mangrove cover decreased by 16.2%. The vast majority of forest loss occurred in Sumatra and western Kalimantan. Commodity-driven deforestation for plantations was the major reason for forest loss.

Impact of Energy Landscapes on the Abundance of Eurasian Skylark (Alauda arvensis), an Example from North Germany

The increasing use of biomass for energy production is reshaping landscapes into energy landscapes. Our study aims to analyze the impact of the biogas energy landscape on the abundance of Eurasian skylark. The biogas power plants have a high impact on the landscape, because of the energy crops like silage maize and rape. We analyze land-use and land-cover heterogeneity in connection with this bird species in the Federal State of Schleswig-Holstein. Three databases are used: abundance data of a typical farmland bird (Eurasian skylark), Corine land cover, and statistical land-use data from the German Agricultural Structure Survey. Several spatial analyses and statistical analyses were conducted. Generalized linear models are used with model averaging and predicted marginal effects were calculated. We estimate the changes in individuals per km2 by considering six crop types and the Shannon Diversity Index (SDI). The Eurasian skylark abundance has a significant negative correlation with the area of the inland wetlands, the Shannon Diversity Index (SDI), permanent crops, silage maize, and rape. We found significant positive correlation with the pasture, potato, and wheat. The replacement of pastures, Eurasian skylarks’ preferred habitat, with energy crops, mostly silage maize, and the ongoing homogenization of the landscape, negatively affected this species’ distribution in the study area.

Home and school environmental correlates of childhood BMI

BackgrouandActive commuting to school can be a substantial opportunity to provide the necessary daily physical activity for children and to counteract childhood obesity. This paper examines the associations of urban form, in general, and street network design, in particular, with body mass index (BMI) in children aged between 12 and 16, controlling for socio-economic features (gender, educational attainment, income, and auto ownership) and daily physical activity (access mode to/from school and walking behaviour). MethodsData were drawn from questionnaires conducted in 20 elementary schools located in the Anatolian part of İstanbul, Turkey. Randomly selected 6th, 7th, and 8th grade students (N = 1784) completed questionnaires regarding their commuting modes to/from school while their parents (N = 1118) completed questionnaires about their socio-economic characteristics and their children's daily physical activity. Each student's BMI was calculated by measured height and weight data. Home- and school-environments (800-and 1600-m buffers around the respondent and school) were evaluated through GIS-based land-use data and segment-based street connectivity measures. Selected street segments within school-environments were also audited with regard to pedestrian environment characteristics. ResultsFindings indicate that children who actively commuted to/from school had lower BMIs than non-active commuters. More importantly, it is shown that increased street network connectivity measured at the segment-level is significantly associated with reduced BMI in school children. In fact, connectivity measures appear to be the strongest correlates of BMI. ConclusionsThis study provides important evidence for planners, urban designers, and policy makers on the significance of built environment, in general, and street network configuration, in particular, within home- and school-environments. One rule of thumb would be to design a well-connected street network with relatively denser connections and reduced direction changes within the neighbourhood – not only within a couple of blocks of homes and schools but also within their larger fabric (800–1600 mt buffers).

Understanding heterogeneous spatial production externalities as a missing link between land-use planning and urban economic futures

ABSTRACT Land-use planning influences economic performance as it can intervene with location-specific and heterogeneous production externalities. This paper examines the impacts of heterogeneous externalities on local employment growth using a panel model framework with block-level land-use data inventory for Chicago. Cross-industry spillovers provide positive impacts on growth, but the mechanisms behind them differ across sectors and spatial scales. Improved understanding of heterogeneity in agglomeration economies can better support plan-making and urban economic performance. The results show significant and positive influence of cross-industry spillovers, a missing consideration in existing planning processes.

Agroforestry as a sustainable land use option to reduce wildfires risk in European Mediterranean areas

Wildfires have always been an integral part of the ecology of many terrestrial ecosystems, but their frequency is increasing in many parts of the world. Wildfires were once a natural phenomenon, but after humans learned to control fire, it has been used as a management tool to increase soil fertility, to regenerate natural vegetation for grazing and to control competing vegetation. However, currently uncontrolled wildfires threaten not only natural vegetation, landscape biodiversity, communities and economies, but they also release large amounts of carbon dioxide, thus contributing to global temperature increase. Higher temperatures and drier summers have increased the risk of wildfires in biodiversity rich areas of European Mediterranean countries and have resulted in human casualties. The aim of this article is to investigate whether agroforestry, the practice of integrating woody vegetation and agricultural crops and/or livestock, could be a management tool to reduce wildfires in European Mediterranean countries. Fire events from 2008 to 2017 and data of land cover and land use were spatially correlated. Results indicated that agroforestry areas had fewer wildfire incidents than forests, shrublands or grasslands, providing evidence of the potential of agroforestry to reduce fire risk and protect ecosystems.

Influence of urban spatial configuration and sea breeze on land surface temperature on summer clear-sky days

Understanding the spatiotemporal characteristics of land surface temperature (LST), a physical quantity that greatly contributes to the formation of urban thermal environment, is essential for constructing a sustainable urban environment. This study explores the relationship between urban space, atmospheric conditions, and diurnal change characteristics of LST on summer clear-sky days in an urban area of Osaka Plain using a 10 min LST dataset retrieved from the Japanese geostationary satellite (Himawari-8) data. The principal temporal change patterns forming the diurnal cycle of LST were extracted through a principal component analysis, and their spatial variabilities were investigated through the exploitation of ground-based meteorological observation and land-use data. The result showed two temporal change patterns, identified as the amplitude and phase of the diurnal change, being extracted in different clear-sky days. A hierarchical cluster analysis confirmed that the spatial variations of such patterns corresponded to the sea breeze and urban land-use. Moreover, LST change at daytime was found to be larger in the high-density areas rather than in the low-density areas of low buildings, thereby suggesting the influence of building density on LST at daytime.

Ecosystem Service Response to Human Disturbance in the Yangtze River Economic Belt: A Case of Western Hunan, China

Ecosystem conservation is one of the core elements of sustainable development. Studying the relationship between human disturbance and the ecosystem service value (ESV) change is an urgent need for the future. The Yangtze River Economic Belt is one of the key economic strategies implemented by the Chinese government and is also a demonstration zone for ecological conservation. Western Hunan is an important ecological barrier in the Yangtze basin where different ethnic groups live together and various cultures coexist. In this study, using land-use data and spatial analysis modeling, the changes in the ecosystem service value at five topographic gradients were evaluated. Human disturbance and its spatial correlation with the ecosystem service value from 1990 to 2015 were also investigated. The results demonstrated the following: (1) the proportional area of forestland and grassland increased as the topographic gradient index increased and other types of land-use gradually decreased; (2) The ecosystem service value at middle gradients increased over the study period; but ESV of the lowest topographic gradient showed a significant decline and a substantial decrease, as well as a terrain index under 0.7970; (3) The spatial analysis of human disturbance showed that more than 90% of intense human disturbance was distributed in the area of the lowest topographic gradient where topographic features were low-altitude and low-slope, and little human disturbance was scattered at other gradients; (4) There was a significant spatial aggregation distribution between the ecosystem service value and human disturbance in western Hunan, the high disturbance and low ESV aggregation was mainly distributed in Loudi City, the area east of Shaoyang City and Zhangjiajie City all belonged to the lowest topographic gradient, and the low–high and high–high aggregations were mainly distributed in Huaihua City and Xiangxi Tujia and Miao Autonomous Prefecture. Population density and gross domestic product were the main driving factors, while topography was the main ecological factor. This study could provide additional spatial information and theoretical guidance for ecosystem service management for sustainable development in western Hunan, China.

Environment, Colonization, and the Baltic Crusader States: Terra Sacra I ed. by Aleksander Pluskowski, and: Ecologies of Crusading, Colonization, and Religious Conversion in the Medieval Baltic: Terra Sacra II ed. by Aleksander Pluskowski

Reviewed by: Environment, Colonization, and the Baltic Crusader States: Terra Sacra I ed. by Aleksander Pluskowski, and: Ecologies of Crusading, Colonization, and Religious Conversion in the Medieval Baltic: Terra Sacra II ed. by Aleksander Pluskowski Roderick McDonald Pluskowski, Aleksander, ed., Environment, Colonization, and the Baltic Crusader States: Terra Sacra I (Environmental Histories of the North Atlantic World, 2), Turnhout, Brepols, 2019; paperback; pp. xxviii, 548; 189 b/w, 8 colour illustrations, 41 b/w tables; R.R.P. €115.00; ISBN 9782503551326 Pluskowski, Aleksander, ed., Ecologies of Crusading, Colonization, and Religious Conversion in the Medieval Baltic: Terra Sacra II (Environmental Histories of the North Atlantic World, 3), Turnhout, Brepols, 2019; paperback; pp. xx, 246; 73 b/w, 9 colour illustrations, 22 b/w tables; R.R.P. €100.00; ISBN 9782503551333. Terra Sacra is the term coined to ‘emphasize the clash of sacred associations embedded in the landscapes of the eastern Baltic’ (p. 2), and with this orientation these two volumes squarely place medieval human theocratic expansionism into environmental, ecological, and social contexts. These books comprise the primary published output of a four-year research project, funded by the European Research Council, which set out to examine the broad environmental impact of the fourteenth-and fifteenth-century crusader states in the eastern Baltic region, and the societies created through successive phases of military conquest, colonization, and religious conversion. Much of this expansion was instigated under the military, Christian, Teutonic Order, which rose to authoritarian prominence prosecuting penitential wars (with papal sanction) against pagan Baltic tribes, after Christian eyes turned from the Byzantine east following the fall of Jerusalem. The study traces the impact of the Christian theocratic regime on the regions that were to become known as Livonia and Prussia, and the regime’s establishment of a social system based around centralized defensive castle-convents holding authority over the wider landscape, exploiting synergies of technology with religion for the purpose of maintaining and expanding territorial control, and accruing and monopolizing the wealth of the land. The analyses in these volumes explore growth, establishment, and impact of specialized economies where lordships developed and operated specialist farms—arable cropping, dairy cattle, sheep—that served diversified markets, and in the course of the centuries, imposed [End Page 238] marked and divergent impacts on local environments. The research identifies the importance of conventual castles at the core of the Christian expansion, with the establishment of towns encouraging the immigration of colonists, while environmental transformation is revealed as doubly significant for the colonized pagan Baltic tribes, as they held many aspects of the natural world as sacred: a natural world that was modified permanently as a result of the crusades. This work is strongly interdisciplinary. It synthesizes and contextualizes a wide range of data sources across an array of disciplines: archaeology, history, and environmental and ecological sciences, all heavily supported with detailed and well-visualized data, and extensively illustrated with supporting maps, illustrations and photographs, both technical and descriptive. Environmental analyses of the characteristics of occupation and settlement activities are prominent throughout both volumes, deriving and closely examining geographic data for land use, vegetation, and animal use, integrated with archaeozoological, geoarchaeological, and archaeobotanical evidence. The scope of this project was massive, and the comprehensive nature of these two volumes is due in part to the fact that very many people were involved in both the research and the writing, from a number of European countries. All up, the two volumes are composed of thirty-five chapters and five appendices, with close to fifty contributors. The research itself was overseen by a project team of twelve, of which the editor, Andrew Pluskowski (University of Reading), was the principal investigator, while the many project partners came from a wide range of universities and research institutions across Estonia, Latvia, Lithuania, Poland, and the United Kingdom. Unfortunately, with such a large undertaking it is only possible to provide a broad description of the contents of these two volumes, and this review is certainly unable to do justice to the scope and precision of scholarship that has been brought together here in this landmark work. The first volume offers a series of comparisons of changes in the environment in the...

Assessment of geoecological conditions and the depletion risk of the river Belaya catchment area

At the present time water resources in the Republic of Bashkortostan (Russia) are exposed by negative anthropogenic influence. Natural processes also contribute to the depletion of water resources. The implementation of the water management system raises a number of methodological problems: the uncertainty of the criteria for assessing the ecological status of water bodies; the complexity of the relationship between the quantitative and qualitative characteristics of the water body due to the regional natural, anthropogenic, climatic features of the territory. The aim of this study is to development of a method for calculating the risk of water resources depletion. The method was tested on the river Belaya (Republic of Bashkortostan, Russia) catchment area. In calculating of water resources depletion risk several parameters were taken into account in particular: the area of watershed, catchment data of surface water and groundwater, data of land use, the average annual runoff, karst phenomena, vegetation. In this paper we use the method of import of geo data containing the soil composition, vegetation, geological structure and forest to assess the ecological condition of the river Belaya. There are defined the catchment areas of the river Belaya, which required immediate management solutions. Mapping of the Belaya River catchment areas requiring immediate management decisions was carried out.

Power Outage Estimation: The Study of Revenue-Led Top Affected States of U.S

The electric power systems are becoming smart as well as complex with every passing year, especially in response to the changing environmental conditions. Resilience of power generation and transmission infrastructure is important to avoid power outages, ensure robust service, and to achieve sustained economic benefits. In this study, we employ a two-stage model to estimate the power outage in terms of its intensity as well as the duration. We identify the top three potentially critical states of United States of America, not merely based on duration of the power outage, but by also incorporating outage related revenue loss. In the proposed model, the first stage classifies the intensity of the outage event while the second stage predicts the duration of the outage itself. Moreover, the key predictors are characterized and their association with outage duration is illustrated. We use a comprehensive and publicly available dataset, which provides the information related to historical power outage events, such as electricity usage patterns, climatological annotations, socio-economic indicators, and land-use data. Our rigorous analysis and results suggest that the power outage interval is the function of several parameters, such as climatological condition, economic indicators as well as the time of the year. The proposed study can help the regulatory authorities taking appropriate decisions for long term economic paybacks. It can also help disaster management authorities to take risk-informed resilient decisions for system safety.

Space-Time Ground-Level PM2.5 Distribution at the Yangtze River Delta: A Comparison of Kriging, LUR, and Combined BME-LUR Techniques

Ambient air PM2.5 is one of the major pollutants linked to respiratory and lung diseases in the Yangtze River Delta (YRD), which is China’s leading economic region and one of the top economic regions worldwide. The main objectives of this work is to compare the accuracy of some widely-used techniques to characterize and predict the space-time distribution of ground-level PM2.5 in the YRD, and to propose a synthesis of techniques that can yield better results than previous techniques. First, a land-use regression (LUR) model is implemented using the relevant data bases (such as air quality, aerosol optical depth, AOD, Modern -Era Retrospective analysis for Research and Applications, MERRA, meteorological monitoring, road networks information, longitude, latitude, elevation and land-use data). Then, the synthesis of the LUR and the Bayesian maximum entropy (BME) techniques is proposed and implemented, for the first time, in the study of PM2.5 concentrations over the YRD region. It was found that the combined (integrated) BME-LUR technique generated PM2.5 concentration estimates showing a 28.34% improvement in accuracy (R2 indicator) compared to the standard LUR technique, and a 12.53% improvement compared to the mainstream geostatistical Kriging technique.

Coastal Ecosystem as Salt Production Centre in Indonesia

This study analyzes several factors in which salt production can be produced and also identify the existing knowledge to manage the process as well as equipment of salt making. This study is qualitative research, therefore primary and secondary data of climatology, land typology and land use have been used. The results of this study show there are some factors that affected salt production, including rainfall, soil texture, land contour; and access to seawater. The rainfall is a major factor affecting the success of salt making in Indonesia. Meanwhile, heavy rain has influenced the success of salt production. Soil texture plays an important role in salt production. It is not only due to the effect on the productivity and quality of the water above it but also because of its suitability for the construction of salt ponds and embankment. Seawater access to is also greatly crucial in salt production. Ideal access to seawater is by utilizing tides so that it does not need a machine to pump seawater to the salt production plots.

Linking experienced barriers during daily travel and transport poverty in peripheral rural areas: the case of Zeeland, the Netherlands

People living in peripheral rural areas are often considered to be prone to transport poverty and inaccessibility to activities. Previous identifications of transport poverty have mainly relied on accessibility measures based on land-use and transport data. However, such measures may be very different from how people themselves perceive accessibility. Therefore, explicitly considering perceptions of accessibility may be valuable in evaluating the nature of accessibility issues such as transport poverty. By conducting semi-structured focus group discussions in Zeeland, a rural area of the Netherlands, this paper shows that the mechanisms behind transport poverty are mediated by individual perceptions of accessibility. Local social norms related to accessibility appear to be important in shaping these perceptions. In peripheral rural areas, norms reflecting the dominance of the private car add to the negative appropriation of other transport options and shape expectations with respect to accessibility. Therefore, taking account of perceptions of accessibility, and the ways these are shaped, adds to the understanding of the nature of accessibility issues and is considered vital in designing responsive policies.

Granica państwa a spójność danych dla potrzeb analiz hydrologicznych. Studium przypadku dla zlewni Wiaru na pograniczu polsko-ukraińskim = A state border and the integrity of data for hydrological analysis. A case study of the River Wiar catchment on the Poland-Ukraine borderland

Hydrological investigations require the development of a geodatabase allowing for the calculation of physiographic catchment parameters, as well as the analysis of amounts of water resources and changes therein. Such a geodatabase usually consists of meteorological, hydrological and cartographic data. The present study offers a review of datasets that may be used for geodatabase development in the interests of hydrological research, in catchments located in the Polish-Ukrainian borderland. The catchment of the Wiar River – selected to serve as a case study – is in fact divided by the state border into two equal sub-catchments (395.5 km2 in Poland and 398.9 km2 in Ukraine).The results reveal disparities in the spatial distribution of stream and meteorological gauges. For the Polish part of the catchment datasets include many parameters (in accordance with EU Directive and Regulations) and the results from monitoring are available online as yearly reports. For the Ukrainian part, only chemical components are monitored, and these data are not made available publicly. Consistent data sets such as DEM can be obtained from globally available ASTER and SRTM models. Datasets, such as LiDAR, which are important for medium and large-scale analyses allowing for the development of high-resolution DEMs, do not exist. Use of TanDEM-X data is restricted for the Ukrainian territory. However, comparison between the SRTM and LiDAR models (for the Polish part) revealed that the SRTM model may be optimised to serve the whole area. Land-use and land-cover data (LULC) are important in many hydrological analyses. the authors propose using satellite images in the development of a comparable layer describing land cover of the whole catchment.

Land use/cover and landscape pattern changes in Manas River Basin based on remote sensing

Large-scale water and soil development in inland river basins in arid areas has made changes in landscape composition and structure, threatening the ecological balance. In order to study the trend of land use/cover and landscape pattern change and its relationship with water resources utilization in Manas River Basin, the land-use data of five periods in 1976, 1990, 2000, 2010 and 2015 were analyzed. The results showed that: (1) During 1976-2015, farmland and construction land continuously increased, forest land and grassland continuously decreased, the water area initially reduced and then increased, the area of saline-alkali land initially increased and then reduced, the overall trend of unused land and the sandy area was decreasing and the area of different time periods is floating. The areas of land-use types either increased or decreased. This indicates that the landscape pattern of the basin changes dramatically, and human activities are the main reasons for this phenomenon; (2) The oasis area increased from 3480.2 km2 in 1976 to 7982.0 km2 in 2015, with an obvious increasing trend. The oasis area clearly increased during 1976-1990, the growth rate was 40.6%, the growth rate of the oasis area was 129.4%. In the last 40 years, the degree of desertification fluctuated and decreased. The increase of the oasis area directly leads to the increase of water resources utilization and aggravates the degree of water resources shortage; (3) The pattern of land-use types showed a non-equilibrium trend. In the region with increasing landscape heterogeneity, the overall landscape pattern was increasingly controlled by the majority of patches. The intensive land management model and drip irrigation under mulch have improved the utilization efficiency of water resources and saved water resources from engineering renovation and irrigation management. Keywords: arid area, Manas River Basin, land use/cover change, landscape pattern, remote sensing, driving force DOI: 10.25165/j.ijabe.20201305.4783 Citation: Li X L, He X L, Yang G, Liu H G, Long A H, Chen F L, et al. Land use/cover and landscape pattern changes in Manas River Basin based on remote sensing. Int J Agric & Biol Eng, 2020; 13(5): 141–152.

Study on Land-use Changes and Their Impacts on Air Pollution in Chengdu

The expansion of urban areas and the increase in the number of buildings and urbanization characteristics, such as roads, affect the meteorological environment in urban areas, resulting in weakened pollutant dispersion. First, this paper uses GIS (geographic information system) spatial analysis technology and landscape ecology analysis methods to analyze the dynamic changes in land cover and landscape patterns in Chengdu as a result of urban development. Second, the most appropriate WRF (Weather Research and Forecasting) model parameterization scheme is selected and screened. Land-use data from different development stages in the city are included in the model, and the wind speed and temperature results simulated using new and old land-use data (1980 and 2015) are evaluated and compared. Finally, the results of the numerical simulations by the WRF-Chem air quality model using new and old land-use data are coupled with 0.25° × 0.25°-resolution MEIC (Multi-resolution Emission Inventory for China) emission source data from Tsinghua University. The results of the sensitivity experiments using the WRF-Chem model for the city under different development conditions and during different periods are discussed. The meteorological conditions and pollution sources remained unchanged as the land-use data changed, which revealed the impact of urban land-use changes on the simulation results of PM2.5 atmospheric pollutants. The results show the following. (1) From 1980 to 2015, the land-use changes in Chengdu were obvious, and cultivated land exhibited the greatest changes, followed by forestland. Under the influence of urban land-use dynamics and human activities, both the richness and evenness of the landscape in Chengdu increased. (2) The microphysical scheme WSM3 (WRF Single–Moment 3 class) and land-surface scheme SLAB (5-layer diffusion scheme) were the most suitable for simulating temperatures and wind speeds in the WRF model. The wind speed and temperature simulation results using the 2015 land-use data were better than those using the 1980 land-use data when assessed according to the coincidence index and correlation coefficient. (3) The WRF-Chem simulation results obtained for PM2.5 using the 2015 land-use data were better than those obtained using the 1980 land-use data in terms of the correlation coefficient and standard deviation. The concentration of PM2.5 in urban areas was higher than that in the suburbs, and the concentration of PM2.5 was lower on Longquan Mountain in Chengdu than in the surrounding areas.

Integrating dynamic environmental predictors and species occurrences: Toward true dynamic species distribution models.

While biological distributions are not static and change/evolve through space and time, nonstationarity of climatic and land‐use conditions is frequently neglected in species distribution models. Even recent techniques accounting for spatiotemporal variation of species occurrence basically consider the environmental predictors as static; specifically, in most studies using species distribution models, predictor values are averaged over a 50‐ or 30‐year time period. This could lead to a strong bias due to monthly/annual variation between the climatic conditions in which species' locations were recorded and those used to develop species distribution models or even a complete mismatch if locations have been recorded more recently. Moreover, the impact of land‐use change has only recently begun to be fully explored in species distribution models, but again without considering year‐specific values. Excluding dynamic climate and land‐use predictors could provide misleading estimation of species distribution. In recent years, however, open‐access spatially explicit databases that provide high‐resolution monthly and annual variation in climate (for the period 1901–2016) and land‐use (for the period 1992–2015) conditions at a global scale have become available. Combining species locations collected in a given month of a given year with the relative climatic and land‐use predictors derived from these datasets would thus lead to the development of true dynamic species distribution models (D‐SDMs), improving predictive accuracy and avoiding mismatch between species locations and predictor variables. Thus, we strongly encourage modelers to develop D‐SDMs using month‐ and year‐specific climatic data as well as year‐specific land‐use data that match the period in which species data were collected.