Comparison of land use classifications obtained by visual interpretation and digital processing

ITC Journal

Volumn , Issue 3-4, 1996, Pages 278-283

  Mas, Jean François ^a   Ramírez, Isabel ^b  

^a UNIVERSIDAD AUTÓNOMA DE CAMPECHE   (Mexico)

^b UNIVERSIDAD COMPLUTENSE DE MADRID   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

GIS; LAND USE CLASSIFICATION; LANDSAT TM; SUPERVISED CLASSIFICATION;

MEXICO, MICHOACON STATE, MESETA TARASCA;

EID: 0030357920     PISSN: 03032434     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Review

References (28)

1. Batista, G T and C J Tucker. 1991. Accuracy of digital classification versus visual interpretation of deforestation in the Amazon. Memoria del VI simposio SELPER, pp 407-423.
2. Bouchardy, J Y and B Zand-Rodriguez. 1992. Amélioration du classement des pixels d'une image satellite: présentation d'une méthodologie simple utilisant la technique des masques. Photointerprétation 1991-2-5/6, pp 199-212.
3. Cochrane, G R. 1986. Land use forest resource of Kauai and New Caledonia: the role of Landsat. In: M J Eden and J T Parry (eds), Remote Sensing and Land Management. New Zealand, pp 157-174.
4. Conese, C and F Maselli. 1991. Use of multitemporal information to improve classification performance of TM scenes in complex terrain. ISPRS JP&RS 46, 4, pp 187-197.
5. De Jong, S M. 1993. An application of spatial filtering techniques for land cover mapping using TM images. Geocarto Internatl 8, 1, pp 43-49.
6. Ducrot-Gambart, D. 1992. Traitement d'Image. Centre d'Etude Spatiale des Rayonnements, Univ Paul Sabatier, Toulouse, 150 pp.
7. Fuller, R M, R J Parsell, M Oliver and G Wyatt. 1989. Visual and computer classifications of remotely sensed images, a case study of grasslands in Cambridgeshire. IJRS 10, 1, pp 193-210.
8. Gong, P and P J Howarth. 1990. The use of structural information for improving land cover classification accuracies at the rural-urban fringe. PE&RS 56, 1, pp 67-73.
9. Hutchinson, C F. 1982. Techniques for combining Landsat and ancillary data for digital classification improvement. PE&RS 48, 1, pp 123-130.
10. Janssen, L L F and J M Vanderwel. 1994. Accuracy assessment of satellite-derived land cover data: a review. PE&RS 60, 4, pp 419-426.
11. Kenk, E, M Sondheim and B Yee. 1988. Methods for improving accuracy of Thematic Mapper ground cover classifications. Canadian J of Rem Sens 14, 1, pp 17-31.
12. Kontoes, C, G Wilkinson, A Burril, S Goffredo and J Mégier. 1993. An experimental system for the integration of GIS data in knowledge-based analysis for remote sensing of agriculture. Internatl J of GIS 7, 3, pp 247-262.
13. Landgrebe, D A. 1978. Useful information from multispectral image data: another look. In: P H Swain and S M Davis (eds), Remote Sensing, the Quantitative Approach. McGraw-Hill, Purdue Univ, Indiana, pp 336-363.
14. Lopez, J and J F Mas. 1995. Comparación de dos fuentes cartográficas utilizando un SIG. Memorias del VII simposio Latinoamericano de percepción remota, November 1995, Puerto Vallarta, Mexico, pp 837-842.
15. Maselli, F, C Conese, T De Filippis and R Romani. 1995. Integration of ancillary data into a maximum likelihood classifier with nonparametric priors. ISPRS JP&RS 50, 2, pp 2-11.
16. Mausel, P W, W J Kramber and J K Lee. 1990. Optimum band selection for supervised classification of multispectral data. PE&RS 56, 1, pp 55-60.
17. Palacio-Prieto J L and L Luna-González. 1994. Clasificacion espectral automática vs clasificación visual: un ejemplo al sur de la ciudad de Mexico. Investigaciones Geográficas 29, pp 25-40.
18. Palacio-Prieto, J L and L Luna-González. 1996. Improving spectral results in a GIS context. IJRS 17, 11, pp 2201-2209.
19. PCI. 1994. Using PCl Software. Vol 1, PCI, Richmond Hill, Ontario, 232 pp.
20. Peddle, D R. 1993. An empirical comparison of evidencial reasoning, linear discriminant analysis and maximum likelihood algorithms for alpine land cover classification. Canadian J of Rem Sens 19, 1, pp 31-44.
21. Plumb, G A. 1993. Knowledge-based digital mapping of vegetation type in Big Bend National Park, Texas. Geocarto Internatl 8, 2, pp 29-38.
22. Rzedowski, J. 1981. Vegetación de México. Editorial Limusa, Mexico, 341 pp.
23. Sader, S A, G V N Powell and J H Rappole. 1991. Migratory bird habitat monitoring through remote sensing. IJRS 12, 3, pp 363-372.
24. Sader, S A, T A Stone and A T Joyce. 1990. Remote sensing of tropical forests: an overview of research and applications using non-photographic sensors. PE&RS 55, 10, pp 1343-1351.
25. SARH. 1994. Inventario Forestal National Periódico, Memoria National. Publicaciones de la Ed Secretaría de Agricultura y Recursos Hidráulicos, Subsecretaría Forestal y de Fauna Silvestre, Mexico DF, 81 pp.
26. Sorani, V, R Alvarez, J C Baca and S Varela. 1993. The forest inventory of Mexico, phase 1: classification with TM imagery. 25th internatl symp on rem sens and global change, April 1993, Graz, Austria.
27. Srinivasan, A and J A Richards. 1990. Knowledge-based techniques for multi-source classification. IJRS 3, 3, pp 505-525.
28. Toll, D L. 1984. An evaluation of simulated Thematic Mapper data and Landsat MSS data for discriminating suburban and regional land use and land cover. PE&RS 50, 12, pp 1713-1724.