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Social media data are transforming sustainability science. However, challenges from restrictions in data accessibility and ethical concerns regarding potential data misuse have threatened this nascent field. Here, we review the literature on the use of social media data in environmental and sustainability research. We find that they can play a novel and irreplaceable role in achieving the UN Sustainable Development Goals by allowing a nuanced understanding of human-nature interactions at scale, observing the dynamics of social-ecological change, and investigating the co-construction of nature values. We reveal threats to data access and highlight scientific responsibility to address trade-offs between research transparency and privacy protection, while promoting inclusivity. This contributes to a wider societal debate of social media data for sustainability science and for the common good.

Dataset used to build up tillage classification model

Population growth and unrestricted development policies are driving low-density urbanization and fragmentation of peri-urban landscapes across North America. While private individuals own most undeveloped land, little is known about how their decision-making processes shape landscape-scale patterns of urbanization over time. We introduce a hybrid agent-based modeling (ABM) – cellular automata (CA) modeling approach, developed for analyzing dynamic feedbacks between landowners’ decisions to sell their land for development, and resulting patterns of landscape fragmentation. Our modeling approach builds on existing conceptual frameworks in land systems modeling by integrating an ABM into an established grid-based land-change model – FUTURES. The decision-making process within the ABM involves landowner agents whose decision to sell their land to developers is a function of heterogeneous preferences and peer-influences (i.e., spatial neighborhood relationships). Simulating landowners’ decision to sell allows an operational link between the ABM and the CA module. To test our hybrid ABM-CA approach, we used empirical data for a rapidly growing region in North Carolina for parameterization. We conducted a sensitivity analysis focusing on the two most relevant parameters—spatial actor distribution and peer-influence intensity—and evaluated the dynamic behavior of the model simulations. The simulation results indicate different peer-influence intensities lead to variable landscape fragmentation patterns, suggesting patterns of spatial interaction among landowners indirectly affect landscape-scale patterns of urbanization and the fragmentation of undeveloped forest and farmland.

The ubiquitous use of the internet and social media has provided social and spatial scientists with a wealth of data from which inferences about landscape preferences can be gained. These data are increasingly being used as an alternative to data collected from surveys of recreationists. While the rapidly growing body of research using social media is impressive, little work has been done to compare the image content of social media to preferences elucidated via more traditional methods. We compare the landscape features derived through a computer vision algorithm used to analyze social media photographs with preferences derived through a traditional on-site intercept survey. We found that landscape features identified through the computer vision algorithm were, by and large, significantly different compared to landscape features that park users said improved their recreational experiences. Additionally, we did not find substantial differences in landscape preferences between visitors who share photographs of their park visit on social media and those who do not. We suggest a diversity of data sources and analytical methods should be used in a complementary and comparative way. Our analysis here suggests both surveys and social media images can provide important insights about landscape preferences, but neither in isolation is perfect.

There is a growing literature on tropical forests that demonstrates ways in which rural-to-urban migration establishes dynamic connections between forest landscapes and urban areas. In the United States, context, however, studies of the geography of absentee ownership of non-industrial private forest (NIPF) lands focus on urban-to-rural migration for retirement or amenity purposes. Using parcel data sourced from local governments in an 11-county study area in central and southeastern Ohio, along with a range of openly available data, we analyze patterns of absentee ownership of NIPF parcels to determine the characteristics of areas where absentee owners reside. We hypothesize the rural-to-urban migration patterns, particularly of youth, will help explain where absentee NIPF owners of parcels in our study reside. We estimate models for all census tracts in the United States, finding that indicators of migration, creative class employment opportunities, and affluence are strongly associated with finding at least one absentee owner of an NIPF parcel in our study area. Considering these complex connections affecting NIPF parcels in a North American context could support improved forest management education, outreach, and planning efforts.

Landscapes are increasingly recognized for providing valuable cultural ecosystem services with numerous non-material benefits by serving as places of rest, relaxation, and inspiration that ultimately improve overall mental health and physical well-being. Maintaining and enhancing these valuable benefits through targeted management and conservation measures requires understanding the spatial and temporal determinants of perceived landscape values. Content contributed through mobile technologies and the web are emerging globally, providing a promising data source for localizing and assessing these landscape benefits. These georeferenced data offer rich in situ qualitative information through photos and comments that capture valued and special locations across large geographic areas. We present a novel method for mapping and modeling landscape values and perceptions that leverages viewshed analysis of georeferenced social media data. Using a high resolution LiDAR (Light Detection and Ranging) derived digital surface model, we are able to evaluate landscape characteristics associated with the visual-sensory qualities of outdoor recreationalists. Our results show the importance of historical monuments and attractions in addition to specific environmental features which are appreciated by the public. Evaluation of photo-image content highlights the opportunity of including temporally and spatially variable visual-sensory qualities in cultural ecosystem services (CES) evaluation like the sights, sounds and smells of wildlife and weather phenomena.

Sparsely settled forests (SSF) are poorly studied, coupled natural and human systems involving rural communities in forest ecosystems that are neither largely uninhabited wildland nor forests on the edges of urban areas. We developed and applied a multidisciplinary approach to define, map, and examine changes in the spatial extent and structure of both the landscapes and human populations of SSF in the United States. We estimated that the SSF in the contiguous United States, which are home to only 6–7% of the population, account for over 60% of all forested land and over 30% of all land. From 1990 to 2010 SSF declined in area by 16%, changing little overall but declining markedly in proximity to urban perimeters. A PCA ordination and cluster analysis of the human and landscape characteristics of SSF areas revealed complex and regionally variable patterns. Very broadly, SSF in the far northern and western states are less densely settled and more amenity driven, while the southeastern states north through Pennsylvania and Ohio are more densely settled and more agricultural. The socioeconomic characteristics of SSF are often quite variable at fine scales, especially in proximity to urban areas. Our improved multidisciplinary understanding of SSF raises important questions about regional differences in the dynamics, structure and future socioeconomic trajectories of these forests. To best manage these landscapes for the sake of both human and natural systems, SSF need to be considered a distinct land classification in their own right, not merely perceived as fuzzy boundaries around wild lands or urban areas.

Human perceptions of the landscape can influence land-use and land-management decisions. Recognizing the diversity of landscape perceptions across space and time is essential to understanding land change processes and emergent landscape patterns. We summarize the role of landscape perceptions in the land change process, demonstrate advances in quantifying and mapping landscape perceptions, and describe how these spatially explicit techniques have and may benefit land change research. Mapping landscape perceptions is becoming increasingly common, particularly in research focused on quantifying ecosystem services provision. Spatial representations of landscape perceptions, often measured in terms of landscape values and functions, provide an avenue for matching social and environmental data in land change studies. Integrating these data can provide new insights into land change processes, contribute to landscape planning strategies, and guide the design and implementation of land change models. Challenges remain in creating spatial representations of human perceptions. Maps must be accompanied by descriptions of whose perceptions are being represented and the validity and uncertainty of those representations across space. With these considerations, rapid advancements in mapping landscape perceptions hold great promise for improving representation of human dimensions in landscape ecology and land change research.

We examine interesting variations in tourist rental rates and revenues in Hocking County, Ohio. The “hot tub cabin” industry began in the 1970s and grew sharply in number beginning in the 1990s. We employ hedonic regression analysis on a dataset of 503 hot tub cabins in 143 cabin businesses to explain the variation in cabin rental rates and revenues, supplemented by exploratory spatial data analysis. We estimate the relative contribution of the proximity to amenities, infrastructure, environment and local business. Cabin rental rates were strongly associated with variation in individual cabin attributes. Cabin average daily revenue was higher with better access. The draw of natural amenities on hot tub cabin tourism appears to be indirect. There was a significant disamenity to being located closer to mines, but this was more than offset by increasing forest cover.JEL Codes: Q21, Q26, R11, R14.

We used nine years of geotagged social media posts uploaded to Flickr and Panoramio to investigate the ability of social media to measure and map spatial patterns in visitation to national parks, national forests, and state parks in Utah, USA. Our analysis shows support for the use of geotagged social media to supplement data collected through traditional means (e.g., on-site counts of visitors) as part of visitor use monitoring protocols. However, we did observe notable differences in the amount of variance in reported visitation explained by geotagged social media. Social media posts made within national parks and national forests captured substantially more of the variation in reported visitation relative to posts made within state parks. We attribute this to a variety of factors including the unique types of sites managed within the state park system, lower levels of visitation relative to national parks and forests within the state, and the method by which the state estimates visitation. We use exploratory spatial analyses to investigate spatial patterns of visitation across public lands. The analysis, performed at three different spatial scales (statewide, region, and county) illustrate the diversity of ways in which geotagged social media can inform outdoor recreation and tourism planning efforts and supplement traditional methods of measuring visitation. Our investigation demonstrates how social media can serve as a useful tool to inform proactive planning and management efforts.

Using a socioecological systems perspective, we advance a conceptual approach for characterizing trajectories of change in rural forest-based communities. We call attention to “communities in the middle,” communities positioned within forested regions representing neither unpopulated wilderness nor heavily urbanized or densely populated places on the edge of urban areas. In 2010, these middle places accounted for 27.3% of the continental United States landscape yet less than 5% of the human population. Common shocks, such as the decline of traditional production industries, demographic shifts, new information technologies, climate change, invasive species, and demand for new energy resources, unite these areas. Yet, we observe variation in existing patterns of change across communities, which grows out of interactions between local contexts and larger drivers of change. Focusing on community dynamics, structure, and well-being in transitioning rural forested landscapes, we synthesize insights on three commonly identified development trajectories. We identify interactions among the resource base, connectivity to other places, and social adaptability as critical to these trajectories. Further, we describe vulnerabilities, opportunities, contingencies, diversity, novel recombinations, and mitigation as useful concepts for understanding community pathways within these trajectories. This framework provides a starting point to guide further synthesis, formal meta-analyses, and future interdisciplinary research on change in these important ‘middle’ places.

After decades of falling real commodity prices in agriculture, forestry and mining, natural amenities have become central components of regional growth strategies. While the prospects for amenity-led growth are perceptible, there are still many open questions regarding how natural resources become valuable amenity assets. In this manuscript, we investigate spatial patterns of natural amenity-based tourism; i.e., tourist lodging in so-called hot tub cabins (HTCs) in Hocking County, Ohio. A rare events logistic regression (RELR) is used to examine which spatial factors are most strongly associated with the observed patterns of HTCs. We evaluate how apparent spatial conflicts (water availability and exurbanization), tourist and natural amenities (forest cover, topography, state parks and federal forestland) and legacy effects (past mining areas and an urban density instrumental variable) influence the suitability for HTCs. Prior literature on natural amenity tourism has largely focused on regional or continental scales in order to have a large sample size for analysis. In so doing, finer-scale variation in land suitability is difficult to represent. We use RELR to control for the rarity of tourism lodging at the county scale. Our findings suggest that accessibility combined with tree cover and topography explains much of the variation in HTC locations. While protected areas are likewise important, past activities like mining impact current recreation possibilities, appearing to be incompatible with the natural experiences sought by HTC visitors. HTCs are also more likely to be located in remaining “remote areas”, or inversely related to the patterns of urban density. Policymakers wishing to enhance regional competitiveness in amenity-led growth should consider fine scale characteristics and environmental legacies in their development planning.

Increasing population and rural to urban migration are accelerating urbanization globally, permanently transforming natural systems over large extents. Modelling landscape change over large regions, however, presents particular challenges due to local-scale variations in social and environmental factors that drive land change. We simulated urban development across the South Atlantic States (SAS), a region experiencing rapid population growth and urbanization, using FUTURES&mdash, an open source land change model that uses demand for development, local development suitability factors, and a stochastic patch growing algorithm for projecting alternative futures of urban form and landscape change. New advances to the FUTURES modelling framework allow for high resolution projections over large spatial extents by leveraging parallel computing. We simulated the adoption of different urban growth strategies that encourage settlement densification in the SAS as alternatives to the region&rsquo, s increasing sprawl. Evaluation of projected patterns indicate a 15% increase in urban lands by 2050 given a status quo development scenario compared to a 14.8% increase for the Infill strategy. Status quo development resulted in a 3.72% loss of total forests, 2.97% loss of highly suitable agricultural land, and 3.69% loss of ecologically significant lands. An alternative Infill scenario resulted in similar losses of total forest (3.62%) and ecologically significant lands (3.63%) yet consumed less agricultural lands (1.23% loss). Moreover, infill development patterns differed qualitatively from the status quo and resulted in less fragmentation of the landscape.

Land abandonment is not a static end state but a transitional stage leading to different trajectories of varying intensity and long-term outcomes. Environmental benefits include carbon sequestration, regulation of terrestrial albedo and increases in certain habitat. Tradeoffs include the spatial concentration of ecologically harmful agricultural activities when agricultural intensification facilitates abandonment. Abandoned lands may be vulnerable to invasive species and fire. Societal tradeoffs include loss of traditional landscapes and displacement of rural livelihoods. Abandonment in high-income areas may be enabled by trade in agricultural and forest products, resulting in the destruction of ecosystems in low-income areas. Further research should pay greater conceptual attention to multiple pathways of abandonment and ecological regeneration, and what corresponding livelihood opportunities could be encouraged. © 2013 Elsevier B.V.

The simulation of urban growth is an important part of urban planning and development. Due to large data and computational challenges, urban growth simulation models demand efficient data analytic frameworks for scaling them to large geographic regions. Agent-based models are widely used to observe and analyze the urban growth simulation at various scales. The incorporation of the agent-based model makes the scaling task even harder due to communication and coordination among agents. Many existing agent-based model frameworks were implemented using traditional shared and distributed memory programming models. On the other hand, Apache Spark is becoming a popular platform for distributed big data in-memory analytics. This paper presents an implementation of agent-based sub-model in Apache Spark framework. With the in-memory computation, Spark implementation outperforms the traditional distributed memory implementation using MPI. This paper provides (i) an overview of our framework capable of running urban growth simulations at a fine resolution of 30 meter grid cells, (ii) a scalable approach using Apache Spark to implement an agent-based model for simulating human decisions, and (iii) the comparative analysis of performance of Apache Spark and MPI based implementations.

Reservation databases utilized by parks and protected lands (PPLs) are a source of empirical data that holds a wealth of spatiotemporal information about both destination usage (from the supply side) and visitor characteristics (the demand population). Unfortunately, PPL reservation databases are rarely explored with these goals in mind. Geovisualizations of reservation data can be used to identify longitudinal patterns, trends and relationships that can help PPL managers generate knowledge useful in decision support. To demonstrate the knowledge that can be gained through geospatial analytics of PPL reservation data, 12.5 million reservation records from the recreation.gov database between January 1, 2007 and December 30, 2015 are examined. The database includes 3272 distinct destinations that provided camping, permitting or ticketing on U.S. Federal PPLs. This chapter discusses both the value of, and the methodology for, inductively exploring spatiotemporal PPL reservation data through geovisualization. Efforts such as those described in this chapter can provide decision support to managers of Federal, State and County agencies tasked with tourism and resource management.

Individuals, communities, and societies ascribe a diverse array of values to landscapes. These values are shaped by the aesthetic, cultural, and recreational benefits and services provided by those landscapes. However, across the globe, processes such as urbanization, agricultural intensification, and abandonment are threatening landscape integrity, altering the personally meaningful connections people have toward specific places. Existing methods used to study landscape values, such as social surveys, are poorly suited to capture dynamic landscape-scale processes across large geographic extents. Social media data, by comparison, can be used to indirectly measure and identify valuable features of landscapes at a regional, continental, and perhaps even worldwide scale. We evaluate the usefulness of different social media platforms-Panoramio, Flickr, and Instagram-and quantify landscape values at a continental scale. We find Panoramio, Flickr, and Instagram data can be used to quantify landscape values, with features of Instagram being especially suitable due to its relatively large population of users and its functional ability of allowing users to attach personally meaningful comments and hashtags to their uploaded images. Although Panoramio, Flickr, and Instagram have different user profiles, our analysis revealed similar patterns of landscape values across Europe across the three platforms. We also found variables describing accessibility, population density, income, mountainous terrain, or proximity to water explained a significant portion of observed variation across data from the different platforms. Social media data can be used to extend our understanding of how and where individuals ascribe value to landscapes across diverse social, political, and ecological boundaries.

Simulating structural changes in landscape is a routine task in computational geography. Owing to advances in sensing and data collection technologies, geospatial data is becoming available at finer spatial and temporal resolutions. However, in practice, these large datasets impede land simulation based studies over large geographic regions due to computational and I/O challenges. The memory overhead of sequential implementations and long execution times further limit the possibilities of simulating future urban scenarios. In this paper, we present a generic framework for co-ordinating I/O and computation for geospatial simulations in a distributed computing environment. We present three parallel approaches and demonstrate the performance and scalability benefits of our parallel implementation pFUTURES, an extension of the FUTURES open-source multi-level urban growth model. Our analysis shows that although a time synchronous parallel approach obtains the same results as a sequential model, an asynchronous parallel approach provides better scaling due to reduced disk I/O and communication overheads.

While the merits of local participatory policy design are widely recognised, limited use is made of model-based scenario results to inform such stakeholder involvement. In this paper we present the findings of a study using an agent based model to help stakeholders consider, discuss and incorporate spatial and temporal processes in a backcasting exercise for rural development. The study is carried out in the Dutch region called the Achterhoek. Region-specific scenarios were constructed based on interviews with local experts. The scenarios are simulated in an agent based model incorporating rural residents and farmer characteristics, the environment and different policy interventions for realistic projection of landscape evolution. Results of the model simulations were presented to stakeholders representing different rural sectors at a workshop. The results indicate that illustration of the spatial configuration of landscape changes is appreciated by stakeholders. Testing stakeholders’ solutions by way of model simulations revealed that the effectiveness of local interventions is strongly related to exogenous processes such as market competition and endogenous processes like local willingness to engage in multifunctional activities. The integration of multi-agent modelling and participatory backcasting is effective as it offers a possibility to initiate discussion between experts and stakeholders bringing together different expertise. Electronic supplementary material The online version of this article (doi:10.1007/s10980-012-9730-7) contains supplementary material, which is available to authorized users.

While the spatial and economic quantification and valuation of ecosystem services is becoming increasingly recognised as a way to communicate the importance of ecosystem conservation, little attention has been given to cultural services of the landscape. Cultural services form an important part of tourism amenities in agricultural landscapes. In this study we present a methodology for quantifying cultural services. To gain understanding of the services valued by cultural service users, a survey was conducted with tourists in the municipality of Winterswijk. The survey collected data on landscape preferences for individual landscape features, and the structure and composition of the landscape as a whole. This was linked to respondent appreciation of the landscape functions of recreation, aesthetic beauty, cultural heritage, spirituality and inspiration. To give a monetary estimate of the value of these services a willingness to pay (WTP) exercise was conducted using photo manipulations depicting likely landscape changes. Increased residential infill, the removal of landscape elements for improved agricultural production and rewilding due to agricultural abandonment were simulated. Complementary to this estimate, a travel cost estimate of the value of landscape service was done based on respondents' travel time to reach the region. The monetary value of the cultural services is placed between €86 (WTP) and €23 (travel cost) per tourist/year. The achieved understanding of the spatial heterogeneity of service provision in the region, as well as, the monetary valuation of the assets delivered by the landscape can help in prioritizing areas, and landscape features and structure for maintenance/restoration, while demonstrating the importance of conserving cultural service delivery. © 2012 Elsevier Ltd.

Emphasis on rural development by the European Commission has renewed the need for tools that can help in determining local development options. Incentives that encourage multifunctionality would be aided by ascertaining the strengths and weaknesses of a region. This article provides a methodological framework for identifying local development capital using scenario storylines, maps and visualisations of possible development outcomes to prompt discussion with local stakeholders about regional potentials. Result from a case study in Northern Portugal show that these tools are particularly suited to gaining a richer understanding of development assets and constraints and for providing insight in the role of spatial variation within regions, which is rarely addressed in scenario studies. The spatial heterogeneity of human, policy and environmental factors are shown to determine where different types of rural development are possible. We conclude that these tools can be used by local government agencies and land managers to develop policy interventions that consider local human capacities, willingness and environmental considerations. © 2011 Elsevier B.V.

Expansion of urban settlements has caused observed declines in ecosystem services (ES) globally, further stressing the need for informed urban development and policies. Incorporating ES concepts into the decision making process has been shown to support resilient and functional ecosystems. Coupling land change and ES models allows for insights into the impacts and anticipated trade-offs of specific policy decisions. The spatial configuration of urbanization likely influences the delivery and production of ES. When considering multiple ES simultaneously, improving the production of one ecosystem service often results in the decrease in the provision of other ES, giving rise to trade-offs. We examine the impact of three urban growth scenarios on several ES to determine the degree to which spatial configuration of urbanization and the development of natural land cover impacts these services over 25 years. We couple land change and ES models to examine impacts to carbon sequestration, surface water-run off, nitrogen and phosphorus export, organic farming and camping site suitability, to determine trade-offs among the six ES associated with each spatial configuration for western North Carolina. Consequences of urban configurations are dramatic, with degraded ES across all scenarios and substantial variation depending on urban pattern, revealing trade-offs. Counter-intuitive trade-offs between carbon sequestration and lands available for organic farming and camping were observed, suggesting that no configurations result in mutual benefits for all ES. By understanding trade-offs associated with urban configurations, decision makers can identify ES critical to an area and promote configurations that enhance those.