Landscape Ecology

, Volume 25, Issue 2, pp 249–266 | Cite as

Exploring subtle land use and land cover changes: a framework for future landscape studies

  • Thomas HouetEmail author
  • Thomas R. Loveland
  • Laurence Hubert-Moy
  • Cédric Gaucherel
  • Darrell Napton
  • Christopher A. Barnes
  • Kristi Sayler
Research article


Land cover and land use changes can have a wide variety of ecological effects, including significant impacts on soils and water quality. In rural areas, even subtle changes in farming practices can affect landscape features and functions, and consequently the environment. Fine-scale analyses have to be performed to better understand the land cover change processes. At the same time, models of land cover change have to be developed in order to anticipate where changes are more likely to occur next. Such predictive information is essential to propose and implement sustainable and efficient environmental policies. Future landscape studies can provide a framework to forecast how land use and land cover changes is likely to react differently to subtle changes. This paper proposes a four step framework to forecast landscape futures at fine scales by coupling scenarios and landscape modelling approaches. This methodology has been tested on two contrasting agricultural landscapes located in the United States and France, to identify possible landscape changes based on forecasting and backcasting agriculture intensification scenarios. Both examples demonstrate that relatively subtle land cover and land use changes can have a large impact on future landscapes. Results highlight how such subtle changes have to be considered in term of quantity, location, and frequency of land use and land cover to appropriately assess environmental impacts on water pollution (France) and soil erosion (US). The results highlight opportunities for improvements in landscape modelling.


Scenarios Modelling Forecasting Backcasting LULCC Agriculture Brittany Corn-Belt Prospective 



This study was partly founded by the French Ministry of Research through the “Aires Culturelles” grant and by the CAREN (Centre Armoricain de Recherches en ENvironnement). Authors would like to thank all US and French farmers and actors for this co-investigation, J. Douvinet and D. Delahaye for the use of the Ruicells model. We would like to thank reviewers for their very helpful comments and suggestions on earlier draft.

Supplementary material

10980_2009_9362_MOESM1_ESM.doc (36 kb)
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(WMV 1,419 kb)

(WMV 1,388 kb)


  1. Agarwal C, Green GM, Grove JM, Evans TP, Schweik CM (2002) A review and assessment of land-use change models: dynamics of space, time and human choice. USDA Forest Service, Gen. Tech. Rep. NE-297. Available from Accessed Feb 2009
  2. Alcamo J (2001) Scenarios as tools for international environmental assessments. Experts’ corner report Prospects and Scenarios No 5. Copenhagen, European Environment Agency: 31Google Scholar
  3. Bain D, Roubelat F (1994) Profutures—the birth of the strategic prospective and futures studies international network for applied methodology. Futures 26:345–349. doi: 10.1016/0016-3287(94)90020-5 CrossRefGoogle Scholar
  4. Baudry J, Thenail C (2004) Interaction between farming systems, riparian zones, and landscape patterns: a case study in western France. Landsc Urban Plan 67:121–129. doi: 10.1016/S0169-2046(03)00033-1 CrossRefGoogle Scholar
  5. Berg R, Stevens R, Jurgensen B, Williamson G, Wiebesiek A (2002) Tillage and crop rotations for southeast South Dakota. SDSU, Coll. of Agric. & Biol. Sc. —Plant Science Dept. Available from Accessed Feb 2009
  6. Borjeson L, Hojer M, Dreborg KH, Ekvall T, Finnveden G (2006) Scenario types and techniques: towards a user’s guide. Futures 38:723–739. doi: 10.1016/j.futures.2005.12.002 CrossRefGoogle Scholar
  7. Bousquet F, Le Page C (2004) Multi-agent simulations and ecosystem management: a review. Ecol Modell 176:313–332. doi: 10.1016/j.ecolmodel.2004.01.011 CrossRefGoogle Scholar
  8. Burgi M, Hersperger AM, Schneeberger N (2004) Driving forces of landscape change—current and new directions. Landscape Ecol 19:857–868. doi: 10.1007/s10980-004-0245-8 CrossRefGoogle Scholar
  9. Butler SJ, Vickery JA, Norris K (2007) Farmland biodiversity and the footprint of agriculture. Science 315:381–384. doi: 10.1126/science.1136607 CrossRefPubMedGoogle Scholar
  10. Castella J, Verburg P (2007) Combination of process-oriented and pattern-oriented models of land-use change in a mountain area of Vietnam. Ecol Modell 202:410–420. doi: 10.1016/j.ecolmodel.2006.11.011 CrossRefGoogle Scholar
  11. Castella JC, Kam SP, Quang DD, Verburg P, Hoanh CT (2007) Combining top-down and bottom-up modelling approaches of land use/cover change to support public policies: application to sustainable management of natural resources in northern Vietnam. Land use policy 24:531–545. doi: 10.1016/j.landusepol.2005.09.009 CrossRefGoogle Scholar
  12. de Nijs TCM, de Niet R, Crommentuijn L (2004) Constructing land-use maps of the Netherlands in 2030. J Environ Manage 72:35–42. doi: 10.1016/j.jenvman.2004.03.015 CrossRefPubMedGoogle Scholar
  13. Encyclopedia of Earth (2007) Land-use and land-cover change. Washington DC. Available from Accessed Feb 2009
  14. Franklin JF (1993) Preserving biodiversity—species, ecosystems, or landscapes. Ecol Appl 3:202–205. doi: 10.2307/1941820 CrossRefGoogle Scholar
  15. Gaucherel C, Giboire N, Viaud V, Houet T, Baudry J, Burel F (2006) A domain-specific language for patchy landscape modelling: the Brittany agricultural mosaic as a case study. Ecol Modell 194:233–243. doi: 10.1016/j.ecolmodel.2005.10.026 CrossRefGoogle Scholar
  16. Geoghegan J, Pritchard L, Ogneva-Himmelberger Y, Roy Chowdhury R, Sanderson S, Turner BLII (1998) Socializing the pixel and pixelizing the social in land-use/cover change. In: Committee on Human Dimension of Global Environmental Change (ed) Linking remote sensing and social science. National Research Council, Washington DC, pp 51–69Google Scholar
  17. GLP (2005) Global land project science plan and implementation strategy. IGBP Report No. 53/IHDP Report No. 19. IGBP Secretariat, Stockholm. Available from Accessed Feb 2009
  18. Godet M (1986) Introduction to la prospective: seven key ideas and one scenario method. Futures 18:134–157. doi: 10.1016/0016-3287(86)90094-7 CrossRefGoogle Scholar
  19. Godet M, Roubelat F (1996) Creating the future: the use and misuse of scenarios. Long Range Plann 29:164–171. doi: 10.1016/0024-6301(96)00004-0 CrossRefGoogle Scholar
  20. Gordon LJ, Peterson GD, Bennett EM (2008) Agricultural modifications of hydrological flows create ecological surprises. Trends Ecol Evol 23:211–219. doi: 10.1016/j.tree.2007.11.011 CrossRefPubMedGoogle Scholar
  21. Greeuw S, van Asselt M, Grosskurth J, Storms C, Rijkens-Klomp N, Rothmans D, Rotmas J (2000) Cloudy crystal balls, an assessment of recent European and global scenario studies and models. Environmental issues series, 17, European Environment Agency, LuxembourgGoogle Scholar
  22. Hobbs R (1997) Future landscapes and the future of landscape ecology. Landsc Urban Plan 37:1–9. doi: 10.1016/S0169-2046(96)00364-7 CrossRefGoogle Scholar
  23. Houet T, Gaucherel C (2007) Simulation dynamique et spatialement explicite d’un paysage agricole bocager: validation sur un petit bassin versant breton sur la période 1981–1998. Rev Int Geomatique 17:489–516Google Scholar
  24. Houet T, Hubert-Moy L (2006) Modelling and projecting land-use and land-cover changes with a cellular automaton in considering landscape trajectories: an improvement for simulation of plausible future states. EARSeL eProceedings 5:63–76Google Scholar
  25. Houet T, Hubert-Moy L, Tissot C (2008) Modélisation prospective spatialisée à l’échelle locale: approche méthodologique. Rev Int Geomatique 18:345–373Google Scholar
  26. Houghton RA, Hackler JL, Lawrence KT (1999) The US carbon budget: contributions from land-use change. Science 285:574–578. doi: 10.1126/science.285.5427.574 CrossRefPubMedGoogle Scholar
  27. IPCC (2000) Special report on emissions scenarios. Cambridge University press, Cambridge, p 27Google Scholar
  28. Kahn H, Wiener A (1967) The year 2000. Macmillan, New YorkGoogle Scholar
  29. Kok K, Verburg P, Veldkamp T (2007) Integrated assessment of the land system: the future of land use. Land use policy 24:517–520. doi: 10.1016/j.landusepol.2006.04.007 CrossRefGoogle Scholar
  30. Kristensen SP, Thenail C, Kristensen L (2001) Farmers’ involvement in landscape activities: an analysis of the relationship between farm location, farm characteristics and landscape changes in two study areas in Jutland, Denmark. J Environ Manage 61:301–318. doi: 10.1006/jema.2000.0409 CrossRefPubMedGoogle Scholar
  31. Lambin E, Geist H (eds) (2006) Land-use and land-cover change: local processes and global impacts. The IGBP series. Springer-Verlag, BerlinGoogle Scholar
  32. Lambin EF, Baulies X, Bockstael N, Fischer G, Krug T, Leemans R, Moran EF, Rindfuss RR, Sato Y, Skole D, Turner BL, Vogel C (1999) Land-use and land-cover change (LUCC): implementation strategy. IGBP, Stockholm/BonnGoogle Scholar
  33. Lambin EF, Turner BL, Geist HJ, Agbola SB, Angelsen A, Bruce JW, Coomes OT, Dirzo R, Fischer G, Folke C, George PS, Homewood K, Imbernon J, Leemans R, Li XB, Moran EF, Mortimore M, Ramakrishnan PS, Richards JF, Skanes H, Steffen W, Stone GD, Svedin U, Veldkamp T, Vogel C, Xu JC (2001) The causes of land-use and land-cover change: moving beyond the myths. Glob Environ Change 11:261–269. doi: 10.1016/S0959-3780(01)00007-3 CrossRefGoogle Scholar
  34. Langlois P, Delahaye D (2002) RuiCells, automate cellulaire pour la simulation du ruissellement de surface. Rev Int Geomatique 12:461–487Google Scholar
  35. Loveland TR, Sohl TL, Stehman SV, Gallant AL, Sayler KL, Napton DE (2002) A strategy for estimating the rates of recent United States land-cover changes. Photogramm Eng Remote Sens 68:1091–1099Google Scholar
  36. Marien M (2002) Futures studies in the 21st Century: a reality-based view. Futures 34:261–281. doi: 10.1016/S0016-3287(01)00043-X CrossRefGoogle Scholar
  37. Maron M, Fitzsimons JA (2007) Agricultural intensification and loss of matrix habitat over 23 years in the West Wimmera, south-eastern Australia. Biol Conserv 135:587–593. doi: 10.1016/j.biocon.2006.10.051 CrossRefGoogle Scholar
  38. Matson PA, Parton WJ, Power AG, Swift MJ (1997) Agricultural intensification and ecosystem properties. Science 277:504–509. doi: 10.1126/science.277.5325.504 CrossRefGoogle Scholar
  39. Maxwell T, Costanza R (1997) An open geographic modelling environment. Simulation 68:175–185. doi: 10.1177/003754979706800304 CrossRefGoogle Scholar
  40. Medley KE, Okey BW, Barrett GW, Lucas MF, Renwick WH (1995) Landscape change with agricultural intensification in a rural watershed, South-western Ohio, USA. Landscape Ecol 10:161–176. doi: 10.1007/BF00133029 CrossRefGoogle Scholar
  41. Mérot P (1999) The influence of hedgerow systems on the hydrology of agricultural catchments in a temperate climate. Agronomie 19:655–669. doi: 10.1051/agro:19990801 CrossRefGoogle Scholar
  42. Mérot P, Hubert-Moy L, Gascuel-Odoux C, Clément B, Durand P, Baudry J, Thenail C (2006) A method for improving the management of controversial wetland. Environ Manag (NY) 37(2):258–270. doi: 10.1007/s00267-004-0391-4 CrossRefGoogle Scholar
  43. Millenium Ecosystems Assessment (2003) Ecosystems and human. Island Press, WashingtonGoogle Scholar
  44. Munier B, Birr-Pedersen K, Schou JS (2004) Combined ecological and economic modelling in agricultural land use scenarios. Ecol Modell 174:5–18. doi: 10.1016/j.ecolmodel.2003.12.040 CrossRefGoogle Scholar
  45. Nassauer JI, Corry RC (2004) Using normative scenarios in landscape ecology. Landscape Ecol 19:343–356. doi: 10.1023/ CrossRefGoogle Scholar
  46. Omernik J (1987) Ecoregions of the conterminous United-States. Ann Assoc Am Geogr 77:118–125. doi: 10.1111/j.1467-8306.1987.tb00149.x CrossRefGoogle Scholar
  47. Overmars K, Verburg P, Veldkamp T (2007) Comparison of a deductive and an inductive approach to specify land suitability in a spatially explicit land use model. Land use policy 24:584–599. doi: 10.1016/j.landusepol.2005.09.008 CrossRefGoogle Scholar
  48. Paegelow M, Olmedo MTC (2005) Possibilities and limits of prospective GIS land cover modelling—a compared case study: Garrotxes (France) and Alta Alpujarra Granadina (Spain). Int J Geogr Inf Sci 19:697–722. doi: 10.1080/13658810500076443 CrossRefGoogle Scholar
  49. Parker DC, Manson SM, Janssen MA, Hoffmann MJ, Deadman P (2003) Multi-agent systems for the simulation of land-use and land-cover change: a review. Ann Assoc Am Geogr 93:314–337. doi: 10.1111/1467-8306.9302004 CrossRefGoogle Scholar
  50. Sala OE, Chapin FS, Armesto JJ, Berlow E, Bloomfield J, Dirzo R, Huber-Sanwald E, Huenneke LF, Jackson RB, Kinzig A, Leemans R, Lodge DM, Mooney HA, Oesterheld M, Poff NL, Sykes MT, Walker BH, Walker M, Wall DH (2000) Biodiversity—global biodiversity scenarios for the year 2100. Science 287:1770–1774. doi: 10.1126/science.287.5459.1770 CrossRefPubMedGoogle Scholar
  51. Santelmann MV, White D, Freemark K, Nassauer JI, Eilers JM, Vache KB, Danielson BJ, Corry RC, Clark ME, Polasky S, Cruse RM, Sifneos J, Rustigian H, Coiner C, Wu J, Debinski D (2004) Assessing alternative futures for agriculture in Iowa, USA. Landscape Ecol 19:357–374. doi: 10.1023/B:LAND.0000030459.43445.19 CrossRefGoogle Scholar
  52. Schulp CJE, Nabuurs GJ, Verburg P (2008) Future carbon sequestration in Europe—effects of land use change. Agric Ecosyst Environ 127:251–264. doi: 10.1016/j.agee.2008.04.010 CrossRefGoogle Scholar
  53. Seppelt R, Voinov A (2002) Optimization methodology for land use patterns using spatially explicit landscape models. Ecol Modell 151:125–142. doi: 10.1016/S0304-3800(01)00455-0 CrossRefGoogle Scholar
  54. Sheppard SRJ (2005) Landscape visualisation and climate change: the potential for influencing perceptions and behaviour. Environ Sci Policy 8:637–654. doi: 10.1016/j.envsci.2005.08.002 CrossRefGoogle Scholar
  55. Sohl TL, Sayler KL, Drummond MA, Loveland TR (2007) The FORE-SCE model: a practical approach for projecting land cover change using scenario-based modelling. J Land Use Sci 2:103–126. doi: 10.1080/17474230701218202 CrossRefGoogle Scholar
  56. Sullivan P, Hellerstein D, Hansen L, Johansson R, Koenig S, Luboswki R, Mcbride W, Mcgranahan D, Roberts M, Vogel S, Bucholtz S (2004) The conservation reserve program: economic implications for rural America. Agricultural Economic Report No AER-834. Available from Accessed Feb 2009
  57. Tress B, Tress G (2003) Scenario visualisation for participatory landscape planning: a study from Denmark. Landsc Urban Plan 64:161–178. doi: 10.1016/S0169-2046(02)00219-0 CrossRefGoogle Scholar
  58. USDA (1978) Soil survey of Hanson and Hutchison counties (SD), Soil service conservation, Washington DCGoogle Scholar
  59. USDA (1979) Soil survey of Yankton county (SD), Soil service conservation, Washington DCGoogle Scholar
  60. USDA (2002) Census of agriculture, Table 8: Farms, Land in farms, Value of land and building and Land Use: 2002 and 1997, pp 262–279Google Scholar
  61. van Notten PWF, Rotmans J, van Asselt MBA, Rothman DS (2003) An updated scenario typology. Futures 35:423–443. doi: 10.1016/S0016-3287(02)00090-3 CrossRefGoogle Scholar
  62. Veldkamp A, Fresco LO (1997) Exploring land use scenarios, an alternative approach based on actual land use. Agric Syst 55:1–17. doi: 10.1016/S0308-521X(95)00079-K CrossRefGoogle Scholar
  63. Veldkamp A, Lambin EF (2001) Predicting land-use change. Agric Ecosyst Environ 85:1–6. doi: 10.1016/S0167-8809(01)00199-2 CrossRefGoogle Scholar
  64. Veldkamp A, Kok K, De Koning GHJ, Schoorl JM, Sonneveld MPW, Verburg P (2001) Multi-scale system approaches in agronomic research at the landscape level. Soil Tillage Res 58:129–140. doi: 10.1016/S0167-1987(00)00163-X CrossRefGoogle Scholar
  65. Verburg PH, Schot P, Dijst MJ, Veldkamp A (2004) Land use change modelling: current practice and research priorities. GeoJournal 61(4):309–324. doi: 10.1007/s10708-004-4946-y CrossRefGoogle Scholar
  66. Verburg P, Schulp CJE, Witte N, Veldkamp A (2006a) Downscaling of land use change scenarios to assess the dynamics of European landscapes. Agric Ecosyst Environ 114:39–56. doi: 10.1016/j.agee.2005.11.024 CrossRefGoogle Scholar
  67. Verburg P, Veldkamp A, Rounsevell MDA (2006b) Scenario-based studies of future land use in Europe. Agric Ecosyst Environ 114:1–6. doi: 10.1016/j.agee.2005.11.023 CrossRefGoogle Scholar
  68. Verburg P, Eickhout B, van Meijl H (2008) A multi-scale, multi-model approach for analyzing the future dynamics of European land use. Ann Reg Sci 42(1):57–77. doi: 10.1007/s00168-007-0136-4 CrossRefGoogle Scholar
  69. Vitousek PM, Mooney HA, Lubchenco J, Melillo JM (1997) Human domination of Earth’s ecosystems. Science 277:494–499. doi: 10.1126/science.277.5325.494 CrossRefGoogle Scholar
  70. Wilson GV, McGregor KC, Boykin D (2008) Residue impacts on runoff and soil erosion for different corn plant populations. Soil Tillage Res 99:300–307. doi: 10.1016/j.still.2008.04.001 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Thomas Houet
    • 1
    Email author
  • Thomas R. Loveland
    • 2
  • Laurence Hubert-Moy
    • 3
  • Cédric Gaucherel
    • 4
  • Darrell Napton
    • 5
  • Christopher A. Barnes
    • 6
  • Kristi Sayler
    • 2
  1. 1.GEODE—UMR CNRS 5602Université Toulouse 2Toulouse Cedex 9France
  2. 2.U.S. Geological Survey Earth Resources Observation and Science (EROS) CenterSioux FallsUSA
  3. 3.COSTEL—UMR CNRS 6554 LETG/IFR 190 CARENUniversité Rennes 2Rennes cedexFrance
  4. 4.INRA—EFPA, UMR AMAPMontpellier Cedex 5France
  5. 5.Department of GeographySouth Dakota State UniversityBrookingsUSA
  6. 6.SGT, Inc. USGS EROS CenterSioux FallsUSA

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