Landscape-scale predictions of future grassland conversion to cropland or development.

Grassland conservation planning often focuses on high-risk landscapes, but many grassland conversion models are not designed to optimize conservation planning because they lack multidimensional risk assessments and are misaligned with ecological and conservation delivery scales. To aid grassland conservation planning, we developed landscape-scale models at relevant scales that predict future (2021-2031) total and proportional loss of unprotected grassland to cropland or development. We developed models for 20 ecoregions across the contiguous United States by relating past conversion (2011-2021) to a suite of covariates in random forest regression models and applying the models to contemporary covariates to predict future loss. Overall, grassland loss models performed well, and explanatory power varied spatially across ecoregions (total loss model: weighted group mean R2 = 0.89 [range: 0.83-0.96], root mean squared error [RMSE] = 9.29 ha [range: 2.83-22.77 ha]; proportional loss model: weighted group mean R2 = 0.74 [range: 0.64-0.87], RMSE = 0.03 [range: 0.02-0.06]). Amount of crop in the landscape and distance to cities, ethanol plants, and concentrated animal feeding operations had high variable importance in both models. Total grass loss was greater when there were moderate amounts of grass, crop, or development (∼50%) in the landscape. Proportional grass loss was greater when there was less grass (∼<30%) and more crop or development (∼>50%). Some variables had a large effect on only a subset of ecoregions, for example, grass loss was greater when ∼>70% of the landscape was enrolled in the Conservation Reserve Program. Our methods provide a simple and flexible approach for developing risk layers well suited for conservation that can be extended globally. Our conversion models can support conservation planning by enabling prioritization as a function of risk that can be further optimized by incorporating biological value and cost.

Predicciones a escala de paisaje de la conversión futura de los pastizales a tierras de cultivo o desarrollo Resumen La planificación de la conservación de los pastizales a menudo se centra en paisajes de alto riesgo, pero muchos modelos de conversión de pastizales no están diseñados para optimizar la planificación de la conservación porque carecen de evaluaciones de riesgo multidimensionales y están mal alineados con las escalas ecológicas y de conservación. Para ayudar a la planificación de la conservación de los pastizales, desarrollamos modelos a escala de paisaje en escalas relevantes que predicen la pérdida futura (2021­2031) total y proporcional de pastizales no protegidos a tierras de cultivo o desarrollo. Desarrollamos modelos para 20 ecorregiones a lo largo de los Estados Unidos en relación con la conversión pasada (2011­2021) con un conjunto de covariables en modelos de regresión de bosque aleatorio y aplicando los modelos a covariables contemporáneas para predecir la pérdida futura. En general, los modelos de pérdida de pastizales funcionaron bien y el poder explicativo varió espacialmente entre las ecorregiones (modelo de pérdida total: media ponderada del grupoR2 = 0.89 [rango 0.83­0.96], error cuadrático medio [RMSE] = 9,29 ha [rango 2,83­22,77 ha]; modelo de pérdidas proporcionales: R2 medio ponderado del grupo = 0,74 [rango 0,64­0,87], RMSE = 0,03 [rango 0,02­0,06]). La cantidad de cultivos en el paisaje y la distancia a ciudades, plantas de etanol y operaciones concentradas de alimentación animal tuvieron una importancia variable alta en ambos modelos. La pérdida total de pastos fue mayor cuando había cantidades moderadas de pastos, cultivos o desarrollo (∼50%) en el paisaje. La pérdida proporcional de pastos fue mayor cuando había menos pastos (∼<30%) y más cultivos o desarrollo (∼>50%). Algunas variables tuvieron un gran efecto sólo en un subconjunto de ecorregiones, por ejemplo, la pérdida de pastos fue mayor cuando ∼>70% del paisaje estaba inscrito en el Programa de Reservas de Conservación. Nuestros métodos proporcionan un enfoque sencillo y flexible para desarrollar capas de riesgo adecuadas para la conservación que pueden extenderse globalmente. Nuestros modelos de conversión pueden apoyar la planificación de la conservación al permitir la priorización en función del riesgo, que puede optimizarse aún más si se incorporan el valor biológico y el costo.

Green infrastructure design for the containment of biological invasions. Insights from a peri-urban case study in Rome, Italy.

Secondary shrublands and transitional woodland/shrub formations are recognised to be particularly susceptible to plant invasions, one of the main global threats to biodiversity, especially in dynamic peri-urban landscapes. Urban fringes are in fact often the place for the sprawl of artificial surfaces, fragmentation of habitats, and complex land transitions (including both agriculture intensification and abandonment), which in turn increase propagule pressure of exotic species over residual semi-natural ecosystems. Within this framework, the present study was aimed at analysing i) how landscape composition and configuration affect the richness of woody exotic species in shrubland and transitional woodland/shrub patches, and ii) how this threat can be addressed by means of green infrastructure design in a peri-urban case study (Metropolitan City of Rome, Italy). Accordingly, the occurrence of exotic plants was recorded with field surveys and then integrated with landscape analyses, both at patch level and over a 250 m buffer area around each patch. Thus, the effect of landscape features on exotic plant richness was investigated with Generalised Linear Models, and the best model identified (pseudo R-square = 0.62) for inferring invasibility of shrublands throughout the study area. Finally, a Green Infrastructure (GI) to contain biological invasion was planned, based on inferred priority sites for intervention and respective, site-tailored, actions. The latter included not only the removal of invasive woody alien plants, but also reforestation and planting of native trees for containment of dispersal and subsequent establishment. Even though specifically developed for the study site, and consistent with local government needs, the proposed approach represents a pilot planning process that might be applied to other peri-urban regions for the combined containment of biological invasions and sustainable development of peripheral complex landscapes.

Using multi-sourced big data to correlate sleep deprivation and road traffic noise: A US county-level ecological study.

BACKGROUND: Road traffic noise is a serious public health problem globally as it has adverse psychological and physiologic effects (i.e., sleep). Since previous studies mainly focused on individual levels, we aim to examine associations between road traffic noise and sleep deprivation on a large scale; namely, the US at county level. METHODS: Information from a large-scale sleep survey and national traffic noise map, both obtained from government's open data, were utilized and processed with Geographic Information System (GIS) techniques. To examine the associations between traffic noise and sleep deprivation, we used a hierarchical Bayesian spatial modelling framework to simultaneously adjust for multiple socioeconomic factors while accounting for spatial correlation. FINDINGS: With 62.90% of people not getting enough sleep, a 10 dBA increase in average sound-pressure level (SPL) or Ls10 (SPL of the relatively noisy area) in a county, was associated with a 49% (OR: 1.49; 95% CrIs:1.19-1.86) or 8% (1.08; 1.00-1.16) increase in the odds of a person in a particular county not getting enough sleep. No significant association was observed for Ls90 (SPL of the relatively quiet area). A 10% increase in noise exposure area or population ratio was associated with a 3% (1.03; 1.01-1.06) or 4% (1.04; 1.02-1.06) increase in the odds of a person within a county not getting enough sleep. INTERPRETATION: Traffic noise can contribute to variations in sleep deprivation among counties. This study suggests that policymakers could set up different noise-management strategies for relatively quiet and noisy areas and incorporate geospatial noise indicators, such as exposure population or area ratio. Furthermore, urban planners should consider urban sprawl patterns differently in terms of noise-induced sleep problems.

Proximity to built structures on the seabed promotes biofilm development and diversity.

The rapidly expanding built environment in the northern Gulf of Mexico includes thousands of human built structures (e.g. platforms, shipwrecks) on the seabed. Primary-colonizing microbial biofilms transform structures into artificial reefs capable of supporting biodiversity, yet little is known about formation and recruitment of biofilms. Short-term seafloor experiments containing steel surfaces were placed near six structures, including historic shipwrecks and modern decommissioned energy platforms. Biofilms were analyzed for changes in phylogenetic composition, richness, and diversity relative to proximity to the structures. The biofilm core microbiome was primarily composed of iron-oxidizing Mariprofundus, sulfur-oxidizing Sulfurimonas, and biofilm-forming Rhodobacteraceae. Alpha diversity and richness significantly declined as a function of distance from structures. This study explores how built structures influence marine biofilms and contributes knowledge on how anthropogenic activity impacts microbiomes on the seabed.

Global trends toward urban street-network sprawl.

We present a global time series of street-network sprawl-that is, sprawl as measured through the local connectivity of the street network. Using high-resolution data from OpenStreetMap and a satellite-derived time series of urbanization, we compute and validate changes over time in multidimensional street connectivity measures based on graph-theoretic and geographic concepts. We report on global, national, and city-level trends since 1975 in the street-network disconnectedness index (SNDi), based on every mapped node and edge in the world. Streets in new developments in 90% of the 134 most populous countries have become less connected since 1975, while just 29% show an improving trend since 2000. The same period saw a near doubling in the relative frequency of a street-network type characterized by high circuity, typical of gated communities. We identify persistence in street-network sprawl, indicative of path-dependent processes. Specifically, cities and countries with low connectivity in recent years also had relatively low preexisting connectivity in our earliest time period. We discuss implications for policy intervention in road building in new and expanding cities as a top priority for sustainable urban development.

Air pollution outcomes, land misallocation, and the transmission through urban sprawl.

Air pollution is an inevitable negative environmental externality in the process of industrialization and urbanization in countries around the world. Land misallocation in the process of urbanization and industrialization and the resulting urban sprawl exacerbates the above problems. As a major country in the stage of rapid urbanization and industrialization, China also faces severe air pollution problems. Therefore, this paper will systematically study the impact of land misallocation and urban sprawl on air pollution. We first set up the utility maximization problem of each economic entity in the process of land misallocation in the mathematical model, and form a general equilibrium theory model to analyze the relationship between land misallocation, urban sprawl and air pollution, and then put forward the research hypotheses. We further use the big data of land market transactions of China Land Market Network and LandScan global population data to build the land misallocation index and urban sprawl index respectively, and use an extended mediating effect model to empirically test the hypotheses. The results suggest that the effect of land misallocation on air pollution is significantly positive, and the impact of land misallocation on urban sprawl largely depends on the return rate of land relative to labor (RRIRL). When the RRIRL is relatively low, the impact is weak, or even has a negative effect to some extent. At this time, low transportation costs are conducive to reducing air pollution. On the contrary, when the RRIRL is relatively high, land misallocation has a significant role in promoting urban sprawl. At this time, high traffic costs are conducive to reducing air pollution. In addition, we also find that there is an inverted U-shaped relationship between urban sprawl and air pollution. When the urban sprawl level is low, its impact on air pollution increases with the increase of its level, but once it exceeds a specific node, the impact will decrease. Based on the characteristics of the relationship among land misallocation, urban sprawl and air pollution under different RRIRL, we summarize four environmentally friendly urban development paths. We bring the land bid rent theory and environmental pollution research into a same theoretical model framework, which provides a modeling idea and research perspective with a micro-foundation for subsequent research on land misallocation. We integrate the research conclusions of existing literature and unify them under the research frameworks concerning different RRIRL in the empirical results, which greatly improving their applicability. The four urban development paths summarized in this paper will also provide inspiration for future researchers and policy makers.

Past and future impacts of land-use changes on ecosystem services in Austria.

Environmental and socio-economic developments induce land-use changes with potentially negative impacts on human well-being. To counteract undesired developments, a profound understanding of the complex relationships between drivers, land use, and ecosystem services is needed. Yet, national studies examining extended time periods are still rare. Based on the Special Report on land use, land management and climate change by the Austrian Panel on Climate Change (APCC), we use the Driver-Pressure-State-Impact-Response (DPSIR) framework to (1) identify the main drivers of land-use change, (2) describe past and future land-use changes in Austria between 1950 and 2100, (3) report related impacts on ecosystem services, and (4) discuss management responses. Our findings indicate that socio-economic drivers (e.g., economic growth, political systems, and technological developments) have influenced past land-use changes the most. The intensification of agricultural land use and urban sprawl have primarily led to declining ecosystem services in the lowlands. In mountain regions, the abandonment of mountain grassland has prompted a shift from provisioning to regulating services. However, simulations indicate that accelerating climate change will surpass socio-economic drivers in significance towards the end of this century, particularly in intensively used agricultural areas. Although climate change-induced impacts on ecosystem services remain uncertain, it can be expected that the range of land-use management options will be restricted in the future. Consequently, policymaking should prioritize the development of integrated land-use planning to safeguard ecosystem services, accounting for future environmental and socio-economic uncertainties.

Influence assessment of urban expansion on groundwater level fluctuations in Gandhinagar, Gujarat, India.

Being the state capital of Gujarat, Gandhinagar is snowballing urban population, resulting in overexploitation of groundwater resources and consequent decline in local groundwater level. The key objective of the current research is to understand the impact of urban expansion on the groundwater level of Gandhinagar district for the last 3 decades. Long-term land use/land cover (LULC) alterations using Landsat images (1991-2021) reveal a 234% increase in overall built-up area and it is more prominent in western and southern parts than the eastern part of study area till 2021 due to urban sprawl of adjacent Ahmedabad City. Spatial distribution of groundwater levels exhibits the same pattern of groundwater level drop as that of the urban expansion and the drop of maximum depth of the groundwater level has also observed during study tenure. Rapid population growth indicates inevitable urban densification which may lead to increase in groundwater abstraction and consequent groundwater level depletion of Gandhinagar City in near future. The scenario may be worsened due to the reduction in groundwater recharge area owing to enhancement of impervious surfaces. A negative correlation is established between groundwater level and respective built-up areas from 1991 to 2011. After 2001, groundwater levels in some areas showed a rising trend and the number of those locations have increased from 2001 to 2021, indicating a sufficient supply of surface water, meeting the escalating water demand and subsequent reduction in groundwater abstraction. High fluoride content was found in many groundwater samples collected from Gandhinagar's shallow unconfined aquifer. In lieu of almost unperturbed natural groundwater recharge, built-up expansion, rising population, and over-exploitation result in groundwater level depletion in both shallow and deeper aquifers. To replenish the already depleted groundwater level and for sustainable water supply, an integration of rainwater-surface water-groundwater management plan and sustainable urban management plan is highly required. The future sustainable urban-groundwater management plan of Gandhinagar City must emphasized on the expansion of green and permeable spaces for groundwater recharge, mandatory rainwater harvesting system in every building possible, suitable area demarcation for artificial recharge, and identification of areas which are less prone to groundwater level depletion for city expansion. The outcomes of the present study will help the decision-makers to prepare inclusive and resilient urban management plan to accomplish the 6th and 11th Sustainable Development Goals of United Nations by 2030.

The effects of urban growth on natural areas: the three metropolitan areas in Türkiye.

Today, more than half of the world's population of 7.6 billion lives in cities, and by 2030, it is estimated that the population of urban residents will exceed 5 billion worldwide. Since growth in cities destroys agriculture, forests, and wetlands, an increasing carbon footprint brings many environmental problems, such as global climate change. Among the developing countries, Türkiye's largest cities have been experiencing a rapid urbanization process. The study aims to analyze the adverse effects of urban growth in Türkiye's largest metropolises on natural areas such as agriculture, forests, and wetlands. In this context, the Istanbul, Ankara, and Izmir metropolitan areas have been determined as case areas. The correlation between the changes in the land cover and the urban expansion processes of the three big cities from 1990 to 2018 has been systematically analyzed in the GIS environment using Corine land cover program data. The study indicates the devastating effect of urban growth on agricultural areas in all three case areas. In addition, the urbanization pressure in Istanbul continues to destroy northern forests.

Variations in land surface temperatures in small-scale urban areas in Vietnam during Covid-19 restrictions: Case studies from Da Nang, Hue and Vinh City.

Land surface temperature (LST) is an important variable in urban microclimate research. At the end of 2019, the emergence of Covid-19 pandemic has changed the world in a manner that forced many countries to impose restrictions in human activities. As a measure to prevent the expansion of Covid-19 infections, most of the major cities have entered a prolonged lockdown period and reduction in human activities between the early 2020 and the late 2021. These restrictions were strict in most of the cities in Southeast Asia, particularly in Vietnam. The present study investigated the variations in LST and NDVI observed in three rapidly growing urban areas, namely Da Nang, Hue and Vinh, in Vietnam using Landsat-8 imagery acquired between 2017 and 2022. There has been a slight reduction in LST in the study sites, particularly in Da Nang City, during the lockdown period but not as high as observed in recently conducted studies from big metropolitan cities, including in Vietnam. It is also observed that LST estimated from built-up areas and other impervious surfaces remained relatively stable during the study period which is similar to the results from recent studies.

Measuring the effects of Compactness/Sprawl on COVID 19 spread patterns at the neighborhood level.

This study analyzes the compactness/sprawl index and its effects on the spread of COVID-19 in the neighborhoods of Ahvaz, Iran. Multiple Criteria Decision Making and GIS techniques were used to develop the index. Also, the effects of compactness/sprawl on COVID-19 were investigated using a regression model. It was found that when considering the number of COVID-19 cases per 1000 people, the compactness/sprawl index did not affect the spread of the disease. However, it had a low but significant effect if the raw number of cases was considered. Results also showed that the compactness index significantly affected the raw number of cases, with a coefficient of 0.291, indicating that more compact neighborhoods had more COVID-19 cases. This is unsurprising as more people live in compact areas and, therefore, the raw number of cases is also likely to be higher. In the absence of proper control measures, this could result in further contact between people, thereby, increasing the risk of virus spread. Overall, we found that compactness had a dual effect on the spread of COVID-19 in Ahvaz. We conclude that proper development and implementation of control measures in well-designed compact neighborhoods are essential for enhancing pandemic resilience.

Future scenarios in the former oil capital: coastal flooding and social vulnerability in Macaé, RJ.

The accelerated urban growth in Macaé had important consequences on socio-spatial organization, especially about housing spaces that became increasingly difficult to be accessed by the low-income population. The most devalued lands, such as mangroves and floodplains, were occupied by the low-income population. The proposal highlighted in this project focuses directly on the problem of rising sea levels and flooding in the urban space of Macaé, which is of social interest. A simulation of future scenarios with sea level rise above the current one, allowing the identification of areas flooded by marine transgression on a time scale of 100 years (for the year 2100). For this, the rate was chosen for the simulation: the greenhouse gas scenario RCP8.5, as given in IPCC's Fifth Assessment Report (AR5) of 2014. A radiative forcing that corresponds to more than 700 ppm CO2-eq, but less than 1500 ppm, the projected increase is 1 m to more than 3 m (medium confidence) and more than 3 m (medium confidence). This assessment is based on the average confidence in the contribution from thermal expansion and low confidence in the modeled contribution modeled contribution of the ice sheets. Therefore, the climate change-induced global mean sea level rise is caused by thermal expansion of ocean water and ocean mass gain, the latter being mainly due to a decrease in land ice mass. The estimated sea-level rise used for the projection of this study is 2.15, as proposed by Grinsted et al. in 2009.

The end of urban sprawl? Internal migration across the rural-urban continuum in Switzerland, 1966-2018.

In high-income countries, migration redistributed populations from congested city centres into the sparsely populated outskirts, raising challenges to environmental and population health and the conservation of biodiversity. We evaluate whether this periurbanisation process came to a halt in Switzerland by expecting a decline in internal migration and a renewed residential attractiveness of urban agglomeration centres (i.e., re-urbanisation)-two recent trend changes observed in Europe. Relying on data from censuses, registers and surveys, we describe trends in the intensity, geography and sociodemographic differentials of migration across consistently defined urban agglomeration density zones between 1966 and 2018. Although the overall intensity of migration declined, the rate increased among the working age population in part because of the societal diffusion of tertiary education. The dominant urban-bound migration flows are increasingly confined within agglomerations over time. After the diffusion of periurbanisation down the city hierarchy between 1966 and 1990, we observe the emergence of re-urbanisation in some agglomerations and sociodemographic groups around 2000. However, this phenomenon has been temporarily inflated by period-specific transformations in Swiss society. More recently, the process of periurbanisation intensified again and expanded more and more beyond official agglomeration borders.

Using combined Global Position System and accelerometer data points to examine how built environments and gentrification are associated with physical activity in four Canadian cities.

BACKGROUND: Built and social environments are associated with physical activity. Global Positioning Systems (GPS) and accelerometer data can capture how people move through their environments and provide promising tools to better understand associations between environmental characteristics and physical activity. The purpose of this study is to examine the associations between GPS-derived exposure to built environment and gentrification characteristics and accelerometer-measured physical activity in a sample of adults across four cities. METHODS: We used wave 1 data from the Interventions, Research, and Action in Cities Team, a cohort of adults living in the Canadian cities of Victoria, Vancouver, Saskatoon, and Montreal. A subsample of participants wore a SenseDoc device for 10 days during May 2017-January 2019 to record GPS and accelerometry data. Two physical activity outcomes were derived from SenseDoc data: time spent in light, moderate, and vigorous physical activity; and time spent in moderate or vigorous physical activity. Using corresponding GPS coordinates, we summarized physical activity outcomes by dissemination area-a Canadian census geography that represents areas where 400 to 700 people live- and joined to built (active living space, proximity to amenities, and urban compactness) and gentrification measures. We examined the associations between environmental measures and physical activity outcomes using multi-level negative binomial regression models that were stratified by city and adjusted for covariates (weekday/weekend), home dissemination area, precipitation, temperature) and participant-level characteristics obtained from a survey (age, gender, income, race). RESULTS: We found that adults spent more time being physically active near their homes, and in environments that were more walkable and near parks and less time in urban compact areas, regardless of where participants lived. Our analysis also highlighted how proximity to different amenities was linked to physical activity across different cities. CONCLUSIONS: Our study provides insights into how built environment and gentrification characteristics are associated with the amount of time adults spend being physically active in four Canadian cities. These findings enhance our understanding of the influence that environments have on physical activity over time and space, and can support policies to increase physical activity.

Land-use diversity can better predict urban spontaneous plant richness than impervious surface coverage at finer spatial scales.

Urban spontaneous plants, that are not intentionally propagated by humans and do not belong to the remnants of the natural habitats, not only occur in green spaces but are also distributed in diverse microhabitats in impervious surface areas. Impervious surface coverage is commonly used in studies on spontaneous plant diversity patterns in human-dominated landscapes; however, the role of habitat diversity (i.e., land-use diversity) has been overlooked. Here, we surveyed spontaneous plant composition and land uses (12 types) in 321 0.25 ha sampling sites on the Chongming District islands, Shanghai, to determine the role of land-use diversity in explaining species richness. We examined the linear relationships between species richness and land-use diversity, and quantified the importance of impervious surface coverage and land-use diversity using the random forest (RF) method. All these analyses were conducted for spatial scales from 0.25 to 5 ha in 0.25 ha increments. We found an overall positive relationship between species richness and land-use diversity, and the RF model predicted approximately 50% of the species richness variation at the smallest spatial scale. However, the positive relationship weakened with spatial scale increase, and a rapid decline in explanatory power occurred for all predictor variables in the RF model. Besides impervious surface coverage, both the vegetated and non-vegetated land-use diversity contributed substantially to the prediction of species richness at finer spatial scales. The findings clarify how land-use diversity, both in green spaces and impervious surface areas, affect urban spontaneous plant richness and should be considered in urban biodiversity conservation strategies at the neighborhood scale.

Geospatial measurement of urban sprawl using multi-temporal datasets from 1991 to 2021: case studies of four Indian medium-sized cities.

In recent decades, medium-sized Indian cities have experienced accelerated urban growth due to the saturation of large cities. Such rapid urban growth combined with inadequate urban planning has triggered urban sprawl in medium-sized Indian cities. In this context, the present study focuses on the geospatial measurement of urban sprawl in four rapidly expanding Indian medium-sized cities located in diverse physiographic regions, such as Lucknow urban agglomeration (UA), Bhubaneswar UA, Raipur UA, and Dehradun UA. Multi-temporal Landsat imageries from 1991 to 2021 were downloaded for land cover classification through the maximum likelihood classification tool in ArcGIS 10.3. Thereafter, spatiotemporal land cover change detection was performed based on the classified land cover maps. The presence of urban sprawl was detected using the relative entropy index while the urban expansion index quantified the urban sprawl typologies such as edge expansion, leapfrog development, and ribbon development. The results exhibited a rapid rise in built-up land cover from 1991 to 2021. The prevalence of urban sprawl was detected in all four cities as per the relative entropy index. Edge expansion typology of urban sprawl was dominant compared to leapfrog development and ribbon development. Such urban growth phenomenon creates a hindrance in promoting sustainable urban development in medium-sized Indian cities. The results obtained from this paper would assist urban planners and policymakers in developing strategies to encourage planned urban growth. This paper exhibits the potential of geoinformatics to monitor and analyze urban sprawl.

Rapid growth of the US wildland-urban interface raises wildfire risk.

The wildland-urban interface (WUI) is the area where houses and wildland vegetation meet or intermingle, and where wildfire problems are most pronounced. Here we report that the WUI in the United States grew rapidly from 1990 to 2010 in terms of both number of new houses (from 30.8 to 43.4 million; 41% growth) and land area (from 581,000 to 770,000 km2; 33% growth), making it the fastest-growing land use type in the conterminous United States. The vast majority of new WUI areas were the result of new housing (97%), not related to an increase in wildland vegetation. Within the perimeter of recent wildfires (1990-2015), there were 286,000 houses in 2010, compared with 177,000 in 1990. Furthermore, WUI growth often results in more wildfire ignitions, putting more lives and houses at risk. Wildfire problems will not abate if recent housing growth trends continue.

Multi-Temporal Change Detection Analysis of Vertical Sprawl over Limassol City Centre and Amathus Archaeological Site in Cyprus during 2015-2020 Using the Sentinel-1 Sensor and the Google Earth Engine Platform.

Urban sprawl can negatively impact the archaeological record of an area. In order to study the urbanisation process and its patterns, satellite images were used in the past to identify land-use changes and detect individual buildings and constructions. However, this approach involves the acquisition of high-resolution satellite images, the cost of which is increases according to the size of the area under study, as well as the time interval of the analysis. In this paper, we implemented a quick, automatic and low-cost exploration of large areas, for addressing this purpose, aiming to provide at a medium resolution of an overview of the landscape changes. This study focuses on using radar Sentinel-1 images to monitor and detect multi-temporal changes during the period 2015-2020 in Limassol, Cyprus. In addition, the big data cloud platform, Google Earth Engine, was used to process the data. Three different change detection methods were implemented in this platform as follow: (a) vertical transmit, vertical receive (VV) and vertical transmit, horizontal receive (VH) polarisations pseudo-colour composites; (b) the Rapid and Easy Change Detection in Radar Time-Series by Variation Coefficient (REACTIV) Google Earth Engine algorithm; and (c) a multi-temporal Wishart-based change detection algorithm. The overall findings are presented for the wider area of the Limassol city, with special focus on the archaeological site of "Amathus" and the city centre of Limassol. For validation purposes, satellite images from the multi-temporal archive from the Google Earth platform were used. The methods mentioned above were able to capture the urbanization process of the city that has been initiated during this period due to recent large construction projects.

Compact development and adherence to stay-at-home order during the COVID-19 pandemic: A longitudinal investigation in the United States.

In the absence of a vaccine and medical treatments, social distancing remains the only option available to governments in order to slow the spread of global pandemics such as COVID-19 and save millions of lives. Despite the scientific evidence on the effectiveness of social distancing measures, they are not being practiced uniformly across the U.S. Accordingly, the role of compact development on the level of adherence to social distancing measures has not been empirically studied. This longitudinal study employs a natural experimental research design to investigative the impacts of compact development on reduction in travel to three types of destinations representing a range of essential and non-essential trips in 771 metropolitan counties in the U.S during the shelter-in-place order amid the COVID-19 pandemic. We employed Multilevel Linear Modeling (MLM) for the three longitudinal analyses in this study to model determinants of reduction in daily trips to grocery stores, parks, and transit stations; using travel data from Google and accounting for the hierarchical (two-level) structure of the data. We found that the challenges of practicing social distancing in compact areas are not related to minimizing essential trips. Quite the opposite, residents of compact areas have significantly higher reduction in trips to essential destinations such as grocery stores/pharmacies, and transit stations. However, residents of compact counties have significantly lower reduction in their trips to parks possibly due to the smaller homes, lack of private yards, and the higher level of anxiety amid the pandemic. This study offers a number of practical implications and directions for future research.

Land-use changes and ecosystem services under different scenarios in Nansi Lake Basin, China.

Ecosystem services (ESs) have been affected drastically by rapid urban sprawl and significant land-use changes (LUC) in Nansi Lake Basin (NLB) in China. Based on land-use data with a 30-m resolution from 1990 to 2015, we analyzed the process of LUC by atlas analysis and explored the impacts of LUC on ecological service value (ESV) under urban sprawl. The results showed that water area and buildup land increased significantly from 1990 to 2015. The area of cultivated land, forests, grassland, and unutilized land decreased. Land transfer mainly occurred between cultivated land, water area, and grassland. The total amount of land transfer was 4830.64 km2, and the average transfer rate is 185.79 km2/year in 26 years. The most obvious transfer occurred in period IV. The increased buildup land was mainly transferred from cultivated land. The total urban sprawl in the NLB was 1623.37 km2 in the past 26 years, with an average expansion rate of 62.44 km2/year, with the fastest sprawl in period IV. Tengzhou city was the most prominent area of expansion. Its ESV increased by 5.73 × 107 US$ with an increased rate of 2.21 × 106 US$/year. The annual total value of regulating and supporting services in the first-level ESs in the NLB accounted for 54.8 and 25.2% of the total ESV in all years, which were the primary types of ESs. Water area, forests, and cultivated land were the principal contributors to ESV changes. In conclusion, urban sprawl had a significant negative effect on ESV changes. Urban sprawl, water area, forests, and cultivated land were all sensitive factors for ESV changes.