Fractal approaches in texture analysis and classification of remotely sensed data: Comparisons with spatial autocorrelation techniques and simple descriptive statistics

References

• BURROUGH , P. A. 1989 . “ Fractals and geochemistry ” . In The Fractal Approaches to Heterogeneous Chemistry , Edited by: Avnir , D. 383 – 405 . New York : Wiley & Sons Ltd .
   Google Scholar
• BURROUGH , P. A. 1993 . Soil variability: a late 20th century view . Soils and Fertilizers , 56 : 529 – 562 .
   Google Scholar
• CLARKE , K. C. 1986 . Computation of the fractal dimension of topographic surfaces using the triangular prism surface area method . Computers and Geosciences , 12 : 713 – 722 .
   Web of Science ®Google Scholar
• CLARKE , K. C. and SCHWEIZER , D. M. 1991 . Measuring the fractal dimension of natural surfaces using a robust fractal estimator . Cartography and Geographic Information Systems , 18 : 37 – 47 .
   Web of Science ®Google Scholar
• DE COLA , L. 1989 . Fractal analysis of a classified Landsat scene . Photogrammetric Engineering and Remote Sensing , 55 : 601 – 610 .
   Web of Science ®Google Scholar
• DE JONG , S. M. and BURROUGH , P. A. 1995 . A fractal approach to the classification of Mediterranean vegetation types in remotely sensed images . Photogrammetric Engineering and Remote Sensing , 61 : 1041 – 1053 .
   Web of Science ®Google Scholar
• DONG , P. 2000a . Lacunarity for Spatial Heterogeneity Measurement in GIS . Geographic Information Sciences , 6 : 20 – 26 .
   Google Scholar
• DONG , P. 2000b . Test of a new lacunarity estimation method for image texture analysis . International Journal of Remote Sensing , 17 : 3369 – 3373 .
   Web of Science ®Google Scholar
• EMERSON , C. W. , LAM , N. S. N. and QUATTROCHI , D. A. 1999 . Multi-scale fractal analysis of image texture and pattern . Photogrammetric Engineering and Remote Sensing , 65 : 51 – 61 .
   Web of Science ®Google Scholar
• FRANKLIN , S. E. and PEDDLE , D. 1987 . Texture analysis of digital image data using spatial cooccurrence . Computer and Geosciences , 13 : 293 – 311 .
   Web of Science ®Google Scholar
• GONG , P. and HOWARTH , P. J. 1992 . Frequency based contextual classification and gray level vector reduction for land use identification . Photogrammetric Engineering and Remote Sensing , 58 : 423 – 437 .
   Web of Science ®Google Scholar
• GONG , P. 1994 . Reducing boundary effects in a kernel-based classifier . International Journal of Remote Sensing , 15 : 1131 – 1139 .
   Web of Science ®Google Scholar
• GONG , P. , MARCEAU , D. J. and HOWARTH , P. J. 1992 . A comparison of spatial feature extraction algorithms for land-use classification with SPOT HRV data . Remote Sensing of Environment , 40 : 137 – 151 .
   Web of Science ®Google Scholar
• HODGSON , M. E. 1998 . What size window for image classification? A cognitive perspective . Photogrammetric Engineering and Remote Sensing , 64 : 797 – 807 .
   Web of Science ®Google Scholar
• JAGGI , S. , QUATTROCHI , D. A. and LAM , N. S. N. 1993 . Implementation and operation of three fractal measurement algorithms for analysis of remote-sensing data . Computer and Geosciences , 19 : 745 – 767 .
   Web of Science ®Google Scholar
• KERSHAW , C. D. and FULLER , R. M. 1992 . Statistical problems in the discrimination of land cover from satellite images: a case in lowland Britain . International Journal of Remote Sensing , 13 : 3085 – 3104 .
   Web of Science ®Google Scholar
• KLINGKENBERG , B. and GOODCHILD , M. F. 1992 . The fractal properties of topography: a comparison of methods . Earth Surface Processes and Landforms , 17 : 217 – 234 .
   Web of Science ®Google Scholar
• LAM , N. S. N. 1990 . Description and measurement of Landsat TM images using fractals . Photogrammetric Engineering and Remote Sensing , 56 : 187 – 195 .
   Web of Science ®Google Scholar
• LAM , N. S. N. and DE COLA , L. 1993 . “ Fractal simulation and interpolation ” . In Fractals in Geography , Edited by: Lam , N. S. N. and De Cola , L. 56 – 74 . Englewood Cuffs , NJ : Prentice Hall .
   Google Scholar
• LAM , N. S. N. , QUATTROCHI , D. , QUI , H. and ZHAO , W. 1998 . Environmental assessment and monitoring with image characterization and modeling system using multiscale remote sensing data . Applied Geographic Studies , 2 : 77 – 93 .
   Google Scholar
• LOVEJOY , S. and SCHERTZER , D. 1990 . Multifractals, universality classes and satellite and radar measurements of cloud and rain fields . Journal of Geophysical Research , 95 : 2021 – 2034 .
   Web of Science ®Google Scholar
• MANDELBROT , B. 1982 . The Fractal Geometry of Nature , New York , NY : Freeman and Co .
   Google Scholar
• MANDELBROT , B. B. 1987 . “ Fractals ” . In Encyclopedia of Physical Science and Technology , Edited by: Meyers , Robert A. Vol. 5 , 579 – 593 . San Diego , CA : Academic Press .
   Google Scholar
• MANDELBROT , B. 1995 . Measures of fractal lacunarity: Minkowski content and alternatives . Progress in Probability , 37 : 15 – 42 .
   Google Scholar
• MARK , D. M. and ARONSON , P. B. 1984 . Scale dependent fractal dimensions of topographic surfaces: an empirical investigation with applications in geomorphology and computer mapping . Mathematical Geology , 16 : 671 – 683 .
   Google Scholar
• MYINT , S. W. 2001a . “ Wavelet Analysis and Classification of Urban Environment Using Highresolution Multispectral Image Data ” . 329 Louisiana State University . Ph.D. dissertation,
   Google Scholar
• NOVKOV , V. M. and Yu RAIZER , V. 1992 . Fractal dimension of ocean wave-breaking from optical data . European Geophysical Society, Annales Geophysicae, Part II; Oceans, Atmospheres, Hydrology and Nonlinear Geophysics , 10 ( supplement II ) : C343
   Google Scholar
• PELEG , S. , NOAR , J. , HARTLEY , R. and AVNIR , D. D. 1984 . Multiple resolution texture analysis and classification . IEEE Transactions on Pattern Analysis and Machine Intelligence , 6 : 518 – 528 .
   PubMed Web of Science ®Google Scholar
• PENTLAND , A. 1984 . Fractal-based description of natural scenes . IEEE Transactions on Pattern Analysis and Machine Intelligence , 6 : 661 – 674 .
   PubMed Web of Science ®Google Scholar
• PESARESI , M. 2000 . Texture analysis for urban pattern recognition using fine-resolution panchromatic satellite imagery . Geographical and Environmental Modelling , 4 : 43 – 63 .
   Google Scholar
• QUATTROCHI , D.A. , LAM , N. S. N. , QIU , H. and ZHAO , W. 1997 . “ Image Characterization and Modeling System (ICAMS): a geographic information system for the characterization and modeling of multiscale remote sensing data ” . In Scale in Remote Sensing and GIS , Edited by: Quattrochi , D. A. and Goodchild , M. F. 295 – 308 . Boca Raton , FL : CRC Press .
   Google Scholar
• ROACH , D. and FUNG , KL B. 1994 . Fractal-based textural descriptors for remotely sensed forestry data . Canadian Journal of Remote Sensing , 20 : 59 – 70 .
   Google Scholar
• ROY , A. G. , GRAVEL , G. and GAUTHIER , C. Measuring the dimension of surfaces . Proceedings of the Eighth International Symposium on Computer-assisted Cartography (Auto-Carto8) . Baltimore . Edited by: Chrisman , Nicholas R. pp. 68 – 77 . ASPRS .
   Google Scholar
• Voss , R. 1986 . “ Random fractals: characterization and measurement ” . In Scaling Phenomena in Disordered Systems , Edited by: Pynn , R. and Skjeltorp , A. 1 – 11 . New York : Plenum .
   Google Scholar
• WANG , L. and HE , D. C. 1990 . A new statistical approach for texture analysis . Photogrammetric Engineering and Remote Sensing , 56 : 61 – 66 .
   Web of Science ®Google Scholar
• XlA , Z. 1993 . “ The uses and limitations of fractal geometry in digital terrain modelling ” . 252 City University of New York . Ph.D. Thesis,
   Google Scholar