A land-use systems approach to represent land-use dynamics at continental and global scales

Most of the current global land cover datasets and global scale land-use models use a classification of land cover based on the dominant land cover type within a distinct region or pixel. Such a classification disregards the diversity and intensity of human influence on land systems. In this paper we propose a novel way of classification and modeling land-use using a classification based on land-use systems (LUSs) that represent specific combinations of human-environment interactions. A cluster analysis was used to identify and map these LUSs. The analysis accounted for population density, accessibility to market places, land-use/cover types and livestock densities. A conceptual framework was developed to model dynamics in LUSs accounting for both land cover and land management changes. LUSs changes were simulated based on changes in both local socio-economic and biophysical conditions and regional-scale changes in demand for agricultural products. The new land-use systems change model was used in the context of the integrated assessment model IMAGE.

[1]  N. Ramankutty,et al.  Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000 , 2008 .

[2]  Millenium Ecosystem Assessment Ecosystems and human well-being: synthesis , 2005 .

[3]  Henricus Bernardus Maria Hilderink,et al.  World Population in Transition: An Integrated Regional Modelling Framework , 2000 .

[4]  Michael Obersteiner,et al.  Agriculture and resource availability in a changing world: The role of irrigation , 2010 .

[5]  J. Alcamo,et al.  Simulating changes in global land cover as affected by economic and climatic factors , 1994 .

[6]  Erle C. Ellis,et al.  A global assessment of market accessibility and market influence for global environmental change studies , 2011, Environmental Research Letters.

[7]  J. Townshend,et al.  Global Percent Tree Cover at a Spatial Resolution of 500 Meters: First Results of the MODIS Vegetation Continuous Fields Algorithm , 2003 .

[8]  J. Settle,et al.  Linear mixing and the estimation of ground cover proportions , 1993 .

[9]  C. Müller,et al.  Global food demand, productivity growth, and the scarcity of land and water resources: a spatially explicit mathematical programming approach. , 2008 .

[10]  E. Lambin,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:Global land use change, economic globalization, and the looming land scarcity , 2011 .

[11]  C. Müller,et al.  The yield gap of global grain production: A spatial analysis , 2010 .

[12]  E. Schmid,et al.  Impacts of population growth, economic development, and technical change on global food production and consumption , 2011 .

[13]  Erle C. Ellis,et al.  Putting people in the map: anthropogenic biomes of the world , 2008 .

[14]  Jennifer Koch,et al.  Evaluation of an integrated land use change model including a scenario analysis of land use change for continental Africa , 2011, Environ. Model. Softw..

[15]  T. Sohl,et al.  Using the FORE-SCE model to project land-cover change in the southeastern United States , 2008 .

[16]  Vernon W. Ruttan,et al.  Population and Technological Change: A Study of Long-Term Trends by Ester Boserup (review) , 1982 .

[17]  K. K. Goldewijk Estimating global land use change over the past 300 years: The HYDE Database , 2001 .

[18]  Kerstin Ronneberger,et al.  Land in sight?: Achievements, deficits and potentials of continental to global scale land-use modeling , 2006 .

[19]  J. Townshend,et al.  A new global 1‐km dataset of percentage tree cover derived from remote sensing , 2000 .

[20]  Petra Döll,et al.  Development and validation of the global map of irrigation areas , 2005 .

[21]  G. Foody,et al.  Sub-pixel land cover composition estimation using a linear mixture model and fuzzy membership functions , 1994 .

[22]  Serhan Cevik,et al.  A Barrel of Oil or a Bottle of Wine; How Do Global Growth Dynamics Affect Commodity Prices? , 2011 .

[23]  T. Robinson,et al.  The Food and Agriculture Organization's Gridded Livestock of the World. , 2007, Veterinaria italiana.

[24]  N. Ramankutty,et al.  Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000 , 2008 .

[25]  Robert Gilmore Pontius,et al.  Assessing a predictive model of land change using uncertain data , 2010, Environ. Model. Softw..

[26]  Peter H. Verburg,et al.  Characterization of the spatial distribution of farming systems in the Kenyan Highlands , 2010 .

[27]  A. Dewan,et al.  Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization , 2009 .

[28]  Peter H. Verburg,et al.  Exploring global irrigation patterns : a multilevel modelling approach , 2011 .

[29]  F. Achard,et al.  Tropical forests were the primary sources of new agricultural land in the 1980s and 1990s , 2010, Proceedings of the National Academy of Sciences.

[30]  Bas Eickhout,et al.  Exploring changes in world ruminant production systems , 2005 .

[31]  Eric Koomen,et al.  Comparing the input, output, and validation maps for several models of land change , 2008 .

[32]  Sergios Theodoridis,et al.  Pattern Recognition , 1998, IEEE Trans. Neural Networks.

[33]  P. Verburg,et al.  Trajectories of land use change in Europe: a model-based exploration of rural futures , 2010, Landscape Ecology.

[34]  Steven J. Staal,et al.  Location and uptake: integrated household and GIS analysis of technology adoption and land use, with application to smallholder dairy farms in Kenya , 2002 .

[35]  J. E. Dobson,et al.  LandScan: A Global Population Database for Estimating Populations at Risk , 2000 .

[36]  Eric F. Lambin,et al.  Impact of Macroeconomic Change on Deforestation in South Cameroon: Integration of Household Survey and Remotely-Sensed Data , 2000 .

[37]  Peter H. Verburg,et al.  Accessibility and land-use patterns at the forest fringe in the northeastern part of the Philippines , 2004 .

[38]  Pushpam Kumar,et al.  The economics of ecosystems and biodiversity : mainstreaming the economics of nature : a synthesis of the approach, conclusions and recommendations of TEEB , 2010 .

[39]  Serhan Cevik,et al.  A Barrel of Oil or a Bottle of Wine: How Do Global Growth Dynamics Affect Commodity Prices?* , 2011, Journal of Wine Economics.

[40]  E. Lambin,et al.  The emergence of land change science for global environmental change and sustainability , 2007, Proceedings of the National Academy of Sciences.

[41]  Will Steffen,et al.  No . 0105 The causes of land-use and landcover change : Moving beyond the myths , 2007 .

[42]  R. Nemani,et al.  Global Distribution and Density of Constructed Impervious Surfaces , 2007, Sensors.

[43]  H. L. Miller,et al.  Climate Change 2007: The Physical Science Basis , 2007 .

[44]  Wolfgang Lucht,et al.  Scenarios of global bioenergy production: The trade-offs between agricultural expansion, intensification and trade , 2010 .

[45]  S. Carpenter,et al.  Global Consequences of Land Use , 2005, Science.

[46]  J. Gareth Polhill,et al.  Agent-based land-use models: a review of applications , 2007, Landscape Ecology.

[47]  B. Eickhout,et al.  A multi-scale, multi-model approach for analyzing the future dynamics of European land use , 2008 .

[48]  F. Chapin,et al.  A safe operating space for humanity , 2009, Nature.

[49]  J A Swets,et al.  Measuring the accuracy of diagnostic systems. , 1988, Science.

[50]  Bas Eickhout,et al.  The Impact of Environmental and Climate Constraints on Global Food Supply , 2008, GTAP Working Paper.

[51]  E. Lambin,et al.  Land use transitions: Socio-ecological feedback versus socio-economic change , 2010 .

[52]  Rob Alkemade,et al.  GLOBIO3: A Framework to Investigate Options for Reducing Global Terrestrial Biodiversity Loss , 2009, Ecosystems.

[53]  Peter H. Verburg,et al.  Projecting land use changes in the Neotropics: the geography of pasture expansion into forest , 2007 .

[54]  R. Gil Pontius,et al.  Modeling the spatial pattern of land-use change with GEOMOD2: application and validation for Costa Rica , 2001 .

[55]  E. Ostrom,et al.  Earth System Science for Global Sustainability: Grand Challenges , 2010, Science.

[56]  E. Lambin,et al.  Dynamics of Land-Use and Land-Cover Change in Tropical Regions , 2003 .

[57]  R. Netting,et al.  Smallholders, Householders: Farm Families and the Ecology of Intensive, Sustainable Agriculture. , 1994 .

[58]  A. Veldkamp,et al.  A model analysis of the terrestrial vegetation model of image 2.0 for Costa Rica , 1996 .

[59]  Eric F. Lambin,et al.  Are agricultural land-use models able to predict changes in land-use intensity? , 2000 .

[60]  V. Smil Population Growth and Nitrogen: An Exploration of a Critical Existential Link , 1991 .

[61]  I. Duvernoy Use of a land cover model to identify farm types in the Misiones agrarian frontier (Argentina) , 2000 .

[62]  B. Eickhout,et al.  The impact of different policy environments on agricultural land use in Europe , 2006 .

[63]  J. Townshend,et al.  Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data , 2008, Proceedings of the National Academy of Sciences.

[64]  R. Zomer,et al.  Trees on farm: analysis of global extent and geographical patterns of agroforestry. , 2009 .

[65]  Kathleen Neumann,et al.  Challenges in using land use and land cover data for global change studies , 2011 .

[66]  Jennifer Koch,et al.  An integrated approach to modelling land-use change on continental and global scales , 2011, Environ. Model. Softw..

[67]  J. Priess,et al.  Integrated Models of the Land System: A Review of Modelling Approaches on the Regional to Global Scale , 2008 .

[68]  Anne Larigauderie,et al.  The Biodiversity and Ecosystem Services Science-Policy Interface , 2011, Science.

[69]  Christian Schweitzer,et al.  A generic framework for land-use modelling , 2011, Environ. Model. Softw..

[70]  F. Chapin,et al.  Planetary boundaries: Exploring the safe operating space for humanity , 2009 .

[71]  Inge Uljee,et al.  Inferring urban land use using the optimised spatial reclassification kernel , 2011, Environ. Model. Softw..