Modeling sensitivity to accuracy in classified imagery: A study of areal interpolation by dasymetric mapping

Professional Geographer

Volumn 48, Issue 3, 1996, Pages 299-309

  Fisher, Peter F ^a   Langford, Mitchel ^a  

^a UNIVERSITY OF LEICESTER   (United Kingdom)

Author keywords

Accuracy; Areal interpolation; Dasymetric mapping; Error; Sensitivity analysis

Indexed keywords

AREAL INTERPOLATION; DASYMETRIC MAPPING; METHODOLOGICAL EVALUATION; SENSITIVITY ANALYSIS;

EID: 0030440326     PISSN: 00330124     EISSN: 14679272     Source Type: Journal    
DOI: 10.1111/j.0033-0124.1996.00299.x     Document Type: Article

References (19)

1. Anderson, J. R., E. E. Hardy, J. T. Roach, and R. E. Witmer. 1976. A Land Use and Land Cover Classification System for Use with Remote Sensor Data. USGS Professional Paper No. 964. Washington, DC: U.S. Geological Survey.
2. Artzen, Pym. 1992. Personal communication. Campbell, James B. 1987. Introduction to Remote Sensing. New York: Guilford.
3. Congalton, Russell G. 1992. A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment 37:35-46.
4. Eastman, Ronald. 1992. Idrisi User’s Guide, Version 4. Worcester, MA: Idrisi Project, Clark University.
5. Fisher, Peter F. 1991. Modelling soil map-unit inclusions by Monte Carlo simulation. International Journal of Geographical Information Systems 5:193-208.
6. Fisher, Peter F. 1994. Visualizing the accuracy in classified remotely sensed images. Photogrammetric Engineering and Remote Sensing 60:905-10.
7. Fisher, Peter F., and Mitchel Langford. 1995. Modelling the errors in areal interpolation between zonal systems by Monte Carlo Simulation. Environment and Planning A 27:211-24.
8. Flowerdew, Robin, and Michael Green. 1989. Statistical methods for inference between incompatible zonal systems. In The Accuracy of Spatial Databases, ed. Michael F. Goodchild and Sucharita Gopal, 239-47. London: Taylor & Francis.
9. Franklin, J., T. L. Logan, C. E. Woodcock, and A. H. Strahler. 1986. Coniferous forest classification and inventory using Landsat and digital terrain data. IEEE Transactions on Geoscience and Remote Sensing GE-24:139-49.
10. Gershmel, Philip J., and D. E. Napton. 1982. Interpretation of resource data: Problems of scale and spatial transferability. In Proceedings of the Annual Meeting of the Urban and Regional Information Systems Association, 471-82. Washington, DC: URISA.
11. Goodchild, Michael F. 1991. Issues of quality and uncertainty. In Advances in Cartography, ed. Jean- Claude Muller, 113-39. London: Elsevier.
12. Goodchild, Michael F., and Sucharita Gopal. 1989. Accuracy of Spatial Databases. London: Taylor & Francis.
13. Goodchild, Michael F., and Nina S.-N. Lam. 1980. Areal interpolation: A variant of the traditional spatial problem. Geoprocessing 1:297-331.
14. Goodchild, Michael F., Luc Anselin, and U. Deichmann. 1993. A framework for the areal interpolation of socioeconomic data. Environment and Planning A 25:383-97.
15. Langford, Mitchel, David J. Maguire, and David J. Unwin. 1991. The areal interpolation problem: Estimating population using remote sensing in a GIS framework. In Handling Geographical Information: Methodology and Potential Applications, ed. Ian Masser and Michael Blakemore, 55-77. London: Longman.
16. Monmonier, Mark, and G. Schnell. 1984. Land use and land cover data and the mapping of population density. International Yearbook of Cartography 115-21.
17. Openshaw, Stan. 1977. Algorithm 3: A procedure to generate pseudo-random aggregations of N zones into M zones, where M is less than N. Environment and Planning A 9:169-84.
18. Strahler, Alan H. 1981. Stratification of natural vegetation for forest and rangeland inventory using Landsat digital imagery and collateral data. International Journal of Remote Sensing 2:15-41.
19. Wright, J. K. 1936. A method of mapping densities of population with Cape Cod as an example. Geographical Review 26:103-10.