scholarly journals A review of global-local-global linkages in economic land-use/cover change models

2019 ◽  
Vol 14 (5) ◽  
pp. 053003 ◽  
Author(s):  
Thomas W Hertel ◽  
Thales A P West ◽  
Jan Börner ◽  
Nelson B Villoria
Keyword(s):  
Land Use ◽  
Change Models ◽  
Global Linkages

Theory, Data, and Methods

2019 ◽  
pp. 156-202
Author(s):  
Eda Ustaoglu ◽  
Arif Çagdaş Aydinoglu
Keyword(s):  
Machine Learning ◽  
Land Use ◽  
Information System ◽  
Land Use Change ◽  
Model Development ◽  
Agent Based ◽  
Change Models ◽  
Multi Scale ◽  
Land Use Dynamics ◽  
Scale Characteristics

Land-use change models are tools to support analyses, assessments, and policy decisions concerning the causes and consequences of land-use dynamics, by providing a framework for the analysis of land-use change processes and making projections for the future land-use/cover patterns. There is a variety of modelling approaches that were developed from different disciplinary backgrounds. Following the reviews in the literature, this chapter focuses on various modelling tools and practices that range from pattern-based methods such as machine learning and GIS (Geographic Information System)-based approaches, to process-based methods such as structural economic or agent-based models. For each of these methods, an overview is given for the advances that have been progressed by geographers, natural and economy scientists in developing these models of spatial land-use change. It is noted that further progress is needed in terms of model development, and integration of models operating at various scales that better address the multi-scale characteristics of the land-use system.

A Remote Sensing Based Calibration Framework for the MOLAND Urban Growth Model of Dublin

2012 ◽  
Vol 3 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Tim Van de Voorde ◽  
Johannes van der Kwast ◽  
Frank Canters ◽  
Guy Engelen ◽  
Marc Binard ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Urban Form ◽  
Model Calibration ◽  
Remote Sensing Data ◽  
Model Output ◽  
Spatial Metrics ◽  
Change Models ◽  
Form And Function ◽  
And Function

Land-use change models are useful tools for assessing and comparing the environmental impact of alternative policy scenarios. Their increasing popularity as spatial planning instruments also poses new scientific challenges, such as correctly calibrating the model. The challenge in model calibration is twofold: obtaining a reliable and consistent time series of land-use information and finding suitable measures to compare model output to reality. Both of these issues are addressed in this paper. The authors propose a model calibration framework that is supported by information on urban form and function derived from medium-resolution remote sensing data through newly developed spatial metrics. The remote sensing derived maps are compared to model output of the same date for two model scenarios using well-known spatial metrics. Results demonstrate a good resemblance between the simulation output and the remote sensing derived maps.

An ecosystem-based approach to support water quality assessment and management under climate and land-use condition

2020 ◽  
Author(s):  
Andrea Critto ◽  
Hung Vuong Pham ◽  
Anna Sperotto ◽  
Silvia Torresan ◽  
Elisa Furlan ◽  
...  
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Best Management Practices ◽  
Water Demand ◽  
Management Practices ◽  
Freshwater Ecosystems ◽  
Water Yield ◽  
Management Scenarios ◽  
Nitrogen And Phosphorus ◽  
Change Models

<p>Freshwater ecosystems can be negatively affected by climate change and human interventions through the alteration of water supply and demand. There is an urgent need to protect the ecosystems, and the services they provide, to maintain their essential contribution to human wellbeing and economic prosperity, especially in a rapid and unpredictable global change context. In this work, we developed an integrated approach, coupling the outputs of ecosystem services (InVEST), climate (COSMO-CLM) and land use (LUISA) change models utilizing Bayesian Networks (BNs), to map freshwater-related Ecosystem Services (ESs), namely, water yield, nitrogen and phosphorus retention, and to assess their changes until 2050 under different management scenarios. First, InVEST was calibrated and validated with climate and land-use data to map and quantify ESs. Second, outputs of the ES model were integrated into the BN and the changes induced by different learning techniques and input settings were investigated. Finally, thousands of different scenarios were simulated testing multiple input variables configurations, thus allowing to describe the uncertainty of climate conditions, land-use change and water demand. Two types of inferences were conducted, namely, diagnostic and prognostic inference. The former permitted to find the best combination of the key drivers (i.e.  precipitation, land-use, and water demand) so that ESs are maximized while the latter concentrated on the quantification of ESs under different scenarios. This approach was applied and validated in the Taro River basin in Italy. The results show that the values of all the three types of ESs would decline in the medium-term period under most scenarios. Moreover, there would be a limit of space to improve those values, especially for nutrient retention services. The obtained results provide valuable support to identify and prioritize the best management practices for sustainable water use, balancing the tradeoffs among services. This analysis allows decision-makers to pick up one scenario with a specific configuration of land-use and water demand to optimize relevant ESs within their basin. Finally, these decisions are transformed into a “decision space” where the values of selected services are plotted in the space of ES to represent the gain/loss of each decision.</p>

scholarly journals A Time Monte Carlo method for addressing uncertainty in land-use change models

2018 ◽  
Vol 32 (11) ◽  
pp. 2317-2333 ◽  
Author(s):  
Ahmed Mustafa ◽  
Ismaïl Saadi ◽  
Mario Cools ◽  
Jacques Teller
Keyword(s):  
Land Use ◽  
Monte Carlo ◽  
Monte Carlo Method ◽  
Land Use Change ◽  
Change Models

scholarly journals Incorporating Spatial Dynamics and Temporal Dependency in Land Use Change Models

2012 ◽  
Vol 44 (4) ◽  
pp. 321-349 ◽  
Author(s):  
Raghuprasad Sidharthan ◽  
Chandra R. Bhat
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Spatial Dynamics ◽  
Change Models

scholarly journals An open and extensible framework for spatially explicit land use change modelling in R: the lulccR package (0.1.0)

2015 ◽  
Vol 8 (4) ◽  
pp. 3359-3402 ◽  
Author(s):  
S. Moulds ◽  
W. Buytaert ◽  
A. Mijic
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Global Environmental Change ◽  
Model Development ◽  
Spatially Explicit ◽  
Change Models ◽  
R Programming Language ◽  
Global Environmental ◽  
R Programming ◽  
Scientific Results

Abstract. Land use change has important consequences for biodiversity and the sustainability of ecosystem services, as well as for global environmental change. Spatially explicit land use change models improve our understanding of the processes driving change and make predictions about the quantity and location of future and past change. Here we present the lulccR package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of different models; (3) different aspects of the modelling procedure must be performed in different environments because existing applications usually only perform the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the widely used CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a dataset included with the package. It is envisaged that lulccR will enable future model development and comparison within an open environment.

scholarly journals A Review of Methodological Integration in Land-Use Change Models

2019 ◽  
pp. 1779-1807
Author(s):  
Anh Nguyet Dang ◽  
Akiyuki Kawasaki
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Use Planning ◽  
Essential Feature ◽  
Limited Attention ◽  
Future Trends ◽  
Change Models ◽  
Environmental Impact Assessments ◽  
Land Use Modelling ◽  
Modelling Methods

Global change research communities are paying increasing attention to answering critical questions related to land-use change, questions which are at the root of many pressing socio-economic and environmental issues. In this regard, a huge number of models have been developed to support future land-use planning and environmental impact assessments of land-use change activities. Within land-use change models, methodological integration is recognized as an essential feature for a complete model, which can help to combine the strength of single modelling methods/techniques without inherent weaknesses. Despite the potential and remarkable growth of methodological integration in land-use change models, limited attention has been paid to this aspect of integration. In response to this, the authors' paper summarizes the current major land-use modelling methods/techniques, and explains the co-integration of these methods/techniques. In addition, they summarize the achievements, limitations and future trends in the use of the methodological integration approach in land-use change models.

Cellular automata for simulating land-use change with a constrained irregular space representation: A case study in Nanjing city, China

2020 ◽  
pp. 239980832094988
Author(s):  
Jie Zhu ◽  
Yizhong Sun ◽  
Shuyin Song ◽  
Jing Yang ◽  
Hu Ding
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Use Change ◽  
Urban Space ◽  
Spatial Reasoning ◽  
Land Use Changes ◽  
Space Representation ◽  
Change Models ◽  
Geographic Space ◽  
Ca Model

Traditional cell-based cellular automata (CA) models use a regular cellular grid to represent geographic space, and new approaches to CA models have explored the use of a vector representation of space instead of a regular grid to characterize urban space more realistically. However, less attention has been paid to modeling the interaction between the geospatial information and the irregular cells. To date, the majority of spatial boundaries have been created by individual agencies in an uncoordinated manner. As a consequence, the potential uses of the data collected for land-use change models are limited. In this paper, we propose a new vector-based CA model based on a new constrained irregular space representation using the theory of hierarchical spatial reasoning. For dividing the geographic space considering different items, first land patches are considered as the minimum division unit; then aggregation rules, including attribute, geometric and boundary barrier constraints, are defined; and finally different levels of spatial units are formed through land patches based on aggregation rules. The proposed model is used to simulate the land-use changes in Nanjing, Jiangsu Province, China. The performance validation and comparison illustrate the feasibility of the proposed space representation in a CA model. By using this model, it is expected that the use of the real spatial boundaries that are employed in urban planning could help provide a flexible paradigm to consider various drivers or constraints for realistically simulating land-use changes.

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