GeoJournal

, Volume 61, Issue 4, pp 325–334

Calibration and validation of a model of forest disturbance in the Western Ghats, India 1920–1990

Article

Abstract

This paper introduces a new statistical method that we recommend should become standard procedure to quantify the goodness-of-fit of calibration and validation for land-use change models. We present a multiple-resolution Relative Operating Characteristic (ROC) that measures the goodness-of-fit between a reference map, which is considered reality, and a simulated map, which is a model’s output. This proposed ROC is based on: (1) multiple-resolutions, (2) soft classification, (3) sampling without replacement, and 4) explicit separation of factors of quantity versus location of land-use change. We illustrate the method with a case study in India’s Western Ghats, a biodiversity hotspot, where we have maps of cumulative forest disturbance for 1920 and 1990. We use a predictive modeling approach similar to GEOMOD in which we calibrate the model with the map of 1920, then predict the map of 1990, at which point we subject the model to validation. We show that the fit of calibration tends to be much larger than the fit of validation. Thus if a modeler assess a model by goodness-of-fit of calibration only, then the modeler will likely be over confident in the model’s predictive ability.

Keywords

accuracy assessment land-use change model resolution validation ROC 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Army Map Service, Corps of Engineers1944Quarter Inch SheetSurvey of IndiaDehra DunGoogle Scholar
  2. Bawa, K.S., Dayanandan, S. 1997Socioeconomic factors and tropical deforestationNature386562563April 10Google Scholar
  3. Bawa, K.S., Menon, S. 1997Biological monitoring: the missing ingredientsTrends in Ecology and Evolution1242Google Scholar
  4. Jha, C.S., Dutt, C.B.S., Bawa, K.S. 2000Deforestation and land use changes in Western Ghats, IndiCurrent Science79231238Google Scholar
  5. Menon, S., Bawa, K.S. 1997Applications of geographic information systems, remote-sensing, and a landscape ecology approach to biodiversity conservation in the Western GhatsCurrent Science73134145Google Scholar
  6. Menon, S., Bawa, K.S. 1998Deforestation in the tropics reconciling disparities in estimates for India.Ambio27576577Google Scholar
  7. Myers, N., Mittermeier, R.A., Mittermeier, C.G., Fonseca, G.A., Kent, J. 2000Biodiversity hotspots for conservation prioritiesNature403853Google Scholar
  8. Pontius, R.G.,Jr. 2000Quantification error versus location error in comparison of categorical mapsPhotogrammetric Engineering and Remote Sensing6610111016Google Scholar
  9. Pontius, R.G.,Jr. 2002Statistical methods to partition effects of quantity and location during comparison of categorical maps at multiple resolutionsPhotogrammetric Engineering and Remote Sensing6810411049Google Scholar
  10. Pontius Jr., R.G., Cornell J.D. and Hall C.A.S., 2001: Modeling the spatial pattern of land-use change with GEOMOD2: application and validation for Costa Rica. Agriculture, Ecosystems and Environment 191–203.Google Scholar
  11. Pontius, R.G.,Jr., Schneider, L. 2001Land-cover change model validation by an ROC method for the Ipswich watershed, Massachusetts, USAAgriculture, Ecosystems & Environment85239248Google Scholar
  12. Ramesh, B.R., Menon, S., Bawa, K.S. 1997A vegetation based approach to biodiversity gap analysis in the Agastyamalai Region, Western Ghats, IndiaAmbio26529537Google Scholar
  13. Swets, J.A. 1988Measuring the accuracy of diagnostic systemsScienceJune 1st12851293Google Scholar

Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  1. 1.Graduate School of Geography and Department of International Development, Community, and EnvironmentClark UniversityWorcesterUSA

Personalised recommendations