Modeling tropical deforestation in the southern Yucatán peninsular region: comparing survey and satellite data

Geoghegan, Jacqueline; Villar, Sergio Cortina; Klepeis, Peter; Mendoza, Pedro Mac Ario; Ogneva‐Himmelberger, Yelena; Chowdhury, Rinku Roy; Turner, B. L.; Vance, Colin

doi:10.1016/s0167-8809(01)00201-8

Cited by 225 publications

(122 citation statements)

References 9 publications

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“…For instance, certain models of LCLUC allow for identifying both the processes of change related to forest management and the biophysical and economic forces driving such processes [30]. Other models include decision-making by local communities and the influence of such decisions in land administration [31]. Modeling environmental conditions that determine processes of change is difficult because of the numerous biophysical, socioeconomic and cultural variables involved [7,15,17].…”

Section: Introductionmentioning

confidence: 99%

Modeling Historical Land Cover and Land Use: A Review fromContemporary Modeling

Chang-Martínez

Mas

Valle

et al. 2015

IJGI

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Spatially-explicit land cover land use change (LCLUC) models are becoming increasingly useful tools for historians and archaeologists. Such kinds of models have been developed and used by geographers, ecologists and land managers over the last few decades to carry out prospective scenarios. In this paper, we review historical models to compare them with prospective models, with the assumption that the ample experience gained in the development of models of prospective simulation can benefit the development of models having as their objective the simulation of changes that happened in the past. The review is divided into three sections: in the first section, we explain the functioning of contemporary LCLUC models; in the second section, we analyze historical LCLUC models; in the third section, we compare the former two types of models, and finally, we discuss the contributions to historical LCLUC models of contemporary LCLUC models.

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Section: Introductionmentioning

confidence: 99%

Modeling Historical Land Cover and Land Use: A Review fromContemporary Modeling

Chang-Martínez

Mas

Valle

et al. 2015

IJGI

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“…A maximum of 1000 iterations were used for classification and produced an output of 100 spectral classes. We then applied a postclassification sorting method and merged the 100 spectral classes into four information classes: forest, nonforest, clouds, and cloud shadows through a combination of visual interpretation of these images and information on land cover obtained from high spatial resolution multispectral imagery, i.e., four IKONOS multispectral scenes (4 x 4 m / pixel), acquired on August 31, October 3, and In the logistic regression models, we used biophysical variables that were used in previous studies of forest dynamics (Geoghegan et al 2001, Nagendra et al 2003, Viña et al 2011). These variables included elevation, slope, aspect, which was converted into soil moisture classes (Parker 1982), and distance to the forest edge (Tables 3, 4).…”

Section: Landscape Submodelmentioning

confidence: 99%

Assessing the Effectiveness of Payments for Ecosystem Services: an Agent-Based Modeling Approach

Chen¹,

Viña²,

Shortridge³

et al. 2014

E&S

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ABSTRACT. Payments for ecosystem services (PES) have increasingly been implemented to protect and restore ecosystems worldwide. The effectiveness of conservation investments in PES may differ under alternative policy scenarios and may not be sustainable because of uncertainties in human responses to policies and dynamic human-nature interactions. To assess the impacts of these interactions on the effectiveness of PES programs, we developed a spatially explicit agent-based model: human and natural interactions under policies (HANIP). We used HANIP to study the effectiveness of China's Natural Forest Conservation Program (NFCP) and alternative policy scenarios in a coupled human-nature system, China's Wolong Nature Reserve, where indigenous people's use of fuelwood affects forests. We estimated the effects of the current NFCP, which provides a cash payment, and an alternative payment scenario that provides an electricity payment by comparing forest dynamics under these policies to forest dynamics under a scenario in which no payment is provided. In 2007, there were 337 km² of forests in the study area of 515 km². Under the baseline projection in which no payment is provided, the forest area is expected to be 234 km² in 2030. Under the current NFCP, there are likely to be 379 km² of forests in 2030, or an increase of 145 km² of forests to the baseline projection. If the cash payment is replaced with an electricity payment, there are likely to be 435 km² of forests in 2030, or an increase of 201 km² of forests to the baseline projection. However, the effectiveness of the NFCP may be threatened by the behavior of newly formed households if they are not included in the payment scheme. In addition, the effects of socio-demographic factors on forests will also differ under different policy scenarios. Human and natural interactions under policies (HANIP) and its modeling framework may also be used to assess the effectiveness of many other PES programs around the world.

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“…The relationship between the probability of urban expansion and its driving factors has been evaluated by the use of logistic regression models (Geoghegan et al 2001, Gobin et al 2001, Serneels and Lambin 2001, Verburg et al 2002, Tian et al 2011. Our model took a number of proximity variables into account (Wu 2002, Li andLiu 2007).…”

Section: Linear Regression and Markov Matrixmentioning

confidence: 99%

Modeling urban expansion policy scenarios using an agent-based approach for Guangzhou Metropolitan Region of China

Tian¹,

Qiao²

2014

E&S

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ABSTRACT. Policy makers and the human decision processes of urban planning have an impact on urban expansion. The behaviors and decision modes of regional authority, real estate developer, resident, and farmer agents and their interactions can be simulated by the analytical hierarchy process (AHP) method. The driving factors are regressed with urban dynamics instead of static land-use types. Agents' behaviors and decision modes have an impact on the urban dynamic pattern by adjusting parameter weights. We integrate an agent-based model) (ABM) with AHP to investigate a complex decision-making process and future urban dynamic processes. Three policy scenarios for baseline development, rapid development, and green land protection have been applied to predict the future development patterns of the Guangzhou metropolitan region. A future policy scenario analysis can help policy makers to understand the possible results. These individuals can adjust their policies and decisions according to their different objectives.

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Modeling tropical deforestation in the southern Yucatán peninsular region: comparing survey and satellite data

Cited by 225 publications

References 9 publications

Modeling Historical Land Cover and Land Use: A Review fromContemporary Modeling

Modeling Historical Land Cover and Land Use: A Review fromContemporary Modeling

Assessing the Effectiveness of Payments for Ecosystem Services: an Agent-Based Modeling Approach

Modeling urban expansion policy scenarios using an agent-based approach for Guangzhou Metropolitan Region of China

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