Land | Special Issue : Land Change Modeling: Connecting to the Bigger Picture

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10331 KiB

Open AccessArticle

Integrating Forest Cover Change with Census Data: Drivers and Contexts from Bolivia and the Lao PDR

by Sébastien Boillat, Hy Dao, Patrick Bottazzi, Yuri Sandoval, Abraham Luna, Sithong Thongmanivong, Louca Lerch, Joan Bastide, Andreas Heinimann and Frédéric Giraut

Land 2015, 4(1), 45-82; https://doi.org/10.3390/land4010045 - 20 Jan 2015

Cited by 12 | Viewed by 10349

Abstract

The aim of this paper is to explore possible links between forest cover change and characteristics of social-ecological systems at sub-national scale based mainly on census data. We assessed relationships between population density, poverty, ethnicity, accessibility and forest cover change during the last [...] Read more.

The aim of this paper is to explore possible links between forest cover change and characteristics of social-ecological systems at sub-national scale based mainly on census data. We assessed relationships between population density, poverty, ethnicity, accessibility and forest cover change during the last decade for four regions of Bolivia and the Lao PDR, combining a parcel-based with a cell-based approach. We found that accessibility is a key driver of forest cover change, yet it has the effect of intensifying other economic and policy-related underlying drivers, like colonization policies, cash crop demand, but also policies that lead to forest gain in one case. Poverty does not appear as a driver of deforestation, but the co-occurrence of poverty and forest loss driven by external investments appears critical in terms of social-ecological development. Ethnicity was found to be a moderate explanatory of forest cover change, but appears as a cluster of converging socio-economic characteristics related with settlement history and land resource access. The identification of such clusters can help ordering communities into a typology of social-ecological systems, and discussing their possible outcomes in light of a critical view on forest transition theory, as well as the relevance and predictive power of the variables assessed. Résumé: L’objectif de cet article est d’explorer les liens entre le changement de la couverture forestière et les caractéristiques des systèmes socio-écologiques à l’échelle nationale, principalement à l’aide de données de recensement. Nous avons évalué les relations entre la densité de population, la pauvreté, l’ethnicité, l’accessibilité et le changement de la couverture forestière pendant la dernière décennie pour quatre régions de Bolivie et du Laos, en combinant des approches par parcelles et par cellules. Nous avons constaté que l’accessibilité est un facteur clé du changement de la couverture forestière, tandis qu’elle a pour effet d'intensifier d'autres facteurs économiques et politiques sous-jacents, comme les politiques de colonisation, la demande de cultures de rente, mais aussi, dans un cas, des politiques conduisant à un accroissement de la forêt. La pauvreté n’apparait pas comme un facteur de déforestation, mais la co-occurrence de la pauvreté et de la perte de forêt entrainée par les investissements extérieurs semble critique en termes de développement socio-écologique. L'ethnicité se révèle être modérément explicative du changement de la couverture forestière, mais elle apparait comme un ensemble de caractéristiques socio-économiques convergentes liées à l'histoire de l’implantation humaine et à l'accès aux ressources foncières. L'identification de tels ensembles peut aider à classer les communautés selon une typologie des systèmes socio-écologiques, et à discuter leurs possibles impacts sur la forêt avec un point de vue critique sur la théorie de la transition forestière, ainsi que la pertinence et la puissance prédictive des variables évaluées. Full article

(This article belongs to the Special Issue Land Change Modeling: Connecting to the Bigger Picture)

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9465 KiB

Open AccessArticle

Regional Development Scenario Evaluation through Land Use Modelling and Opportunity Mapping

by Harutyun Shahumyan, Brendan Williams, Laura Petrov and Walter Foley

Land 2014, 3(3), 1180-1213; https://doi.org/10.3390/land3031180 - 19 Sep 2014

Cited by 10 | Viewed by 11365

Abstract

In the context of sustainable urban development, the application of selected indicators integrated with scenario simulation and analysis can contribute to evidence-based decision making. This paper discusses the application of land use modelling and opportunity mapping approaches to evaluate regional development scenarios for [...] Read more.

In the context of sustainable urban development, the application of selected indicators integrated with scenario simulation and analysis can contribute to evidence-based decision making. This paper discusses the application of land use modelling and opportunity mapping approaches to evaluate regional development scenarios for the Greater Dublin Region in the period to 2026 evolving from research initially developed with the Dublin Regional Authority. This involved the simulation of four different future regional development scenarios using an adapted version of the MOLAND model with opportunity maps based on combined spatial indicators corresponding to these scenarios. The results produce valuable information for policy makers and planners assisting the evaluation of the consequences of their decisions in both a spatial and temporal context. This paper aims to show how current and future planning and economic policy can make targeted and evidence-based policy interventions and achieve resource efficiencies through the use of scenario analysis. Full article

(This article belongs to the Special Issue Land Change Modeling: Connecting to the Bigger Picture)

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1857 KiB

Open AccessArticle

Calibrating and Validating a Simulation Model to Identify Drivers of Urban Land Cover Change in the Baltimore, MD Metropolitan Region

by Claire Jantz, Scott Drzyzga and Michael Maret

Land 2014, 3(3), 1158-1179; https://doi.org/10.3390/land3031158 - 17 Sep 2014

Cited by 19 | Viewed by 7345

Abstract

We build upon much of the accumulated knowledge of the widely used SLEUTH urban land change model and offer advances. First, we use SLEUTH’s exclusion/attraction layer to identify and test different urban land cover change drivers; second, we leverage SLEUTH’s self-modification capability to [...] Read more.

We build upon much of the accumulated knowledge of the widely used SLEUTH urban land change model and offer advances. First, we use SLEUTH’s exclusion/attraction layer to identify and test different urban land cover change drivers; second, we leverage SLEUTH’s self-modification capability to incorporate a demographic model; and third, we develop a validation procedure to quantify the influence of land cover change drivers and assess uncertainty. We found that, contrary to our a priori expectations, new development is not attracted to areas serviced by existing or planned water and sewer infrastructure. However, information about where population and employment growth is likely to occur did improve model performance. These findings point to the dominant role of centrifugal forces in post-industrial cities like Baltimore, MD. We successfully developed a demographic model that allowed us to constrain the SLEUTH model forecasts and address uncertainty related to the dynamic relationship between changes in population and employment and urban land use. Finally, we emphasize the importance of model validation. In this work the validation procedure played a key role in rigorously assessing the impacts of different exclusion/attraction layers and in assessing uncertainty related to population and employment forecasts. Full article

(This article belongs to the Special Issue Land Change Modeling: Connecting to the Bigger Picture)

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3531 KiB

Open AccessArticle

Adaptation to New Climate by an Old Strategy? Modeling Sedentary and Mobile Pastoralism in Semi-Arid Morocco

by Korbinian P. Freier, Manfred Finckh and Uwe A. Schneider

Land 2014, 3(3), 917-940; https://doi.org/10.3390/land3030917 - 31 Jul 2014

Cited by 14 | Viewed by 6801

Abstract

In a modeling study we examine vulnerability of income from mobile (transhumant) pastoralism and sedentary pastoralism to reduced mean annual precipitation (MAP) and droughts. The study is based on empirical data of a 3410 km² research region in southern, semi-arid Morocco. The [...] Read more.

In a modeling study we examine vulnerability of income from mobile (transhumant) pastoralism and sedentary pastoralism to reduced mean annual precipitation (MAP) and droughts. The study is based on empirical data of a 3410 km² research region in southern, semi-arid Morocco. The land use decision model integrates a meta-model of the Environmental Policy Integrated Climate (EPIC) simulator to depict perennial and annual forage plant development. It also includes livestock dynamics and forward-looking decision making under uncertain weather. Mobile livestock in the model moves seasonally, sedentary livestock is restricted to pastures around settlements. For a reduction of MAP by 20%, our model shows for different experimental frequencies of droughts a significant decrease of total income from pastoralism by 8%–19% (p < 0.05). Looking separately at the two modes of pastoralism, pronounced income losses of 18%–44% (p < 0.05) show that sedentary pastoralism is much more vulnerable to dryer climate than mobile pastoralism, which is merely affected. Dedicating more pasture area and high quality fodder to mobile pastoralism significantly abates impacts from reduced MAP and droughts on total income by 11% (p < 0.05). Our results indicate that promotion of mobile pastoralism in semi-arid areas is a valuable option to increase resilience against climate change. Full article

(This article belongs to the Special Issue Land Change Modeling: Connecting to the Bigger Picture)

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4441 KiB

Open AccessArticle

Integrating Land Cover Modeling and Adaptive Management to Conserve Endangered Species and Reduce Catastrophic Fire Risk

by David Breininger, Brean Duncan, Mitchell Eaton, Fred Johnson and James Nichols

Land 2014, 3(3), 874-897; https://doi.org/10.3390/land3030874 - 24 Jul 2014

Cited by 9 | Viewed by 6730

Abstract

Land cover modeling is used to inform land management, but most often via a two-step process, where science informs how management alternatives can influence resources, and then, decision makers can use this information to make decisions. A more efficient process is to directly [...] Read more.

Land cover modeling is used to inform land management, but most often via a two-step process, where science informs how management alternatives can influence resources, and then, decision makers can use this information to make decisions. A more efficient process is to directly integrate science and decision-making, where science allows us to learn in order to better accomplish management objectives and is developed to address specific decisions. Co-development of management and science is especially productive when decisions are complicated by multiple objectives and impeded by uncertainty. Multiple objectives can be met by the specification of tradeoffs, and relevant uncertainty can be addressed through targeted science (i.e., models and monitoring). We describe how to integrate habitat and fuel monitoring with decision-making focused on the dual objectives of managing for endangered species and minimizing catastrophic fire risk. Under certain conditions, both objectives might be achieved by a similar management policy; other conditions require tradeoffs between objectives. Knowledge about system responses to actions can be informed by developing hypotheses based on ideas about fire behavior and then applying competing management actions to different land units in the same system state. Monitoring and management integration is important to optimize state-specific management decisions and to increase knowledge about system responses. We believe this approach has broad utility and identifies a clear role for land cover modeling programs intended to inform decision-making. Full article

(This article belongs to the Special Issue Land Change Modeling: Connecting to the Bigger Picture)

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4181 KiB

Open AccessArticle

Spatially-Explicit Simulation of Urban Growth through Self-Adaptive Genetic Algorithm and Cellular Automata Modelling

by Yan Liu, Yongjiu Feng and Robert Gilmore Pontius, Jr.

Land 2014, 3(3), 719-738; https://doi.org/10.3390/land3030719 - 18 Jul 2014

Cited by 60 | Viewed by 10753

Abstract

This paper presents a method to optimise the calibration of parameters and land use transition rules of a cellular automata (CA) urban growth model using a self-adaptive genetic algorithm (SAGA). Optimal calibration is achieved through an algorithm that minimises the difference between the [...] Read more.

This paper presents a method to optimise the calibration of parameters and land use transition rules of a cellular automata (CA) urban growth model using a self-adaptive genetic algorithm (SAGA). Optimal calibration is achieved through an algorithm that minimises the difference between the simulated and observed urban growth. The model was applied to simulate land use change from non-urban to urban in South East Queensland’s Logan City, Australia, from 1991 to 2001. The performance of the calibrated model was evaluated by comparing the empirical land use change maps from the Landsat imagery to the simulated land use change produced by the calibrated model. The simulation accuracies of the model show that the calibrated model generated 86.3% correctness, mostly due to observed persistence being simulated as persistence and some due to observed change being simulated as change. The 13.7% simulation error was due to nearly equal amounts of observed persistence being simulated as change (7.5%) and observed change being simulated as persistence (6.2%). Both the SAGA-CA model and a logistic-based CA model without SAGA optimisation have simulated more change than the amount of observed change over the simulation period; however, the overestimation is slightly more severe for the logistic-CA model. The SAGA-CA model also outperforms the logistic-CA model with fewer quantity and allocation errors and slightly more hits. For Logan City, the most important factors driving urban growth are the spatial proximity to existing urban centres, roads and railway stations. However, the probability of a place being urbanised is lower when people are attracted to work in other regions. Full article

(This article belongs to the Special Issue Land Change Modeling: Connecting to the Bigger Picture)

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Open AccessArticle

New Cropland on Former Rangeland and Lost Cropland from Urban Development: The “Replacement Land” Debate

by Lisa A. Emili and Richard P. Greene

Land 2014, 3(3), 658-674; https://doi.org/10.3390/land3030658 - 9 Jul 2014

Cited by 6 | Viewed by 7437

Abstract

In this study, a land use/land cover change analysis method was developed to examine patterns of land use/land cover conversions of cropland to urban uses and conversions of rangeland to cropland uses in the United States (US) Midwest region. We used the US [...] Read more.

In this study, a land use/land cover change analysis method was developed to examine patterns of land use/land cover conversions of cropland to urban uses and conversions of rangeland to cropland uses in the United States (US) Midwest region. We used the US 2001 and 2006 National Land Cover Datasets (NLCD) for our spatial analyses of these conversion trends. Our analysis showed that the eastern part of the Midwest, like prior periods, continued to experience losses of cropland to urban expansion but at a much more rapid rate, as this was during an expansion phase of the US real estate construction cycle. The period showed a very small net loss of cropland as the loss was being balanced by gains in cropland at the expense of rangeland lost in the western part of the Midwest. We refer to this rangeland to cropland conversion as “replacement land”. We do not suggest by replacement that there is a signal in the system that interconnects the loss of a hectare of cropland to urban land by converting a hectare of rangeland to cropland, rather we highlight this spatial trend as it raises concerns about the environmental sustainability of agriculture in the western part of the region, as production is dependent on the use of irrigation and the already stressed High Plains aquifer. Full article

(This article belongs to the Special Issue Land Change Modeling: Connecting to the Bigger Picture)

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1965 KiB

Open AccessArticle

Development of Future Land Cover Change Scenarios in the Metropolitan Fringe, Oregon, U.S., with Stakeholder Involvement

by Robert W. Hoyer and Heejun Chang

Land 2014, 3(1), 322-341; https://doi.org/10.3390/land3010322 - 14 Mar 2014

Cited by 12 | Viewed by 8812

Abstract

We describe a future land cover scenario construction process developed under consultation with a group of stakeholders from our study area. We developed a simple geographic information system (GIS) method to modify a land cover dataset and then used qualitative data extracted from [...] Read more.

We describe a future land cover scenario construction process developed under consultation with a group of stakeholders from our study area. We developed a simple geographic information system (GIS) method to modify a land cover dataset and then used qualitative data extracted from the stakeholder storyline to modify it. These identified variables related to our study area’s land use regulation system as the major driver in the placement of new urban growth on the landscape; and the accommodation of new population as the determinant of its growth rate. The outcome was a series of three scenario maps depicting a gradient of increased urbanization. The effort attempted to create a simple and transparent modeling framework that is easy to communicate. The incorporation of the regulatory context and rules and place-specific modeling for denser urban and sparse rural areas provide new insights of future land conversions. This relatively rapid mapping process provides useful information for spatial planning and projects for where and how much urban land will be present by the year 2050. Full article

(This article belongs to the Special Issue Land Change Modeling: Connecting to the Bigger Picture)

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Review

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Open AccessReview

Monitoring Forest Change in Landscapes Under-Going Rapid Energy Development: Challenges and New Perspectives

by Paul D. Pickell, Sarah E. Gergel, Nicholas C. Coops and David W. Andison

Land 2014, 3(3), 617-638; https://doi.org/10.3390/land3030617 - 2 Jul 2014

Cited by 15 | Viewed by 8248

Abstract

The accelerated development of energy resources around the world has substantially increased forest change related to oil and gas activities. In some cases, oil and gas activities are the primary catalyst of land-use change in forested landscapes. We discuss the challenges associated with [...] Read more.

The accelerated development of energy resources around the world has substantially increased forest change related to oil and gas activities. In some cases, oil and gas activities are the primary catalyst of land-use change in forested landscapes. We discuss the challenges associated with characterizing ecological change related to energy resource development using North America as an exemplar. We synthesize the major impacts of energy development to forested ecosystems and offer new perspectives on how to detect and monitor anthropogenic disturbance during the Anthropocene. The disturbance of North American forests for energy development has resulted in persistent linear corridors, suppression of historical disturbance regimes, novel ecosystems, and the eradication of ecological memory. Characterizing anthropogenic disturbances using conventional patch-based disturbance measures will tend to underestimate the ecological impacts of energy development. Suitable indicators of anthropogenic impacts in forests should be derived from the integration of multi-scalar Earth observations. Relating these indicators to ecosystem condition will be a capstone in the progress toward monitoring forest change in landscapes undergoing rapid energy development. Full article

(This article belongs to the Special Issue Land Change Modeling: Connecting to the Bigger Picture)

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