A multiscale texture analysis procedure for improved forest stand classification

References

• ATKINSON , P. M . 1993 . The effect of spatial resolution on the experimental variogram of airborne MSS imagery . International Journal of Remote Sensing , 14 : 1005 – 1011 .
   Web of Science ®Google Scholar
• BARBER , D. G and LEDREW , E. F . 1991 . SAR sea ice discrimination using texture statistics: a multivariate approach . Photogrammetric Engineering and Remote Sensing , 50 : 385 – 395 .
   Google Scholar
• BRITISH COLUMBIA COMMISSION ON RESOURCES AND ENVIRONMENT 1994 Cariboo-Chilcotin Land Use Plan (Victoria, British Columbia: Province of British Columbia), vol. 1
   Google Scholar
• CHICA-OLMO , M and ABARCA-HERNANDEZ , F . 2000 . Computing geostatisitcal image texture for remotely sensed data classification . Computers and Geosciences , 26 : 373 – 383 .
   Web of Science ®Google Scholar
• COHEN , W. B , SPIES , T. A and BRADSHAW , G. A . 1990 . Semivariograms of digital imagery for analysis of conifer canopy structure . Remote Sensing of Environment , 34 : 167 – 178 .
   Web of Science ®Google Scholar
• COLLINS , J. B and WOODCOCK , C. E . 1999 . Geostatistical estimation of resolution-dependant variance in remotely sensed images . Photogrammetric Engineering and Remote Sensing , 65 : 41 – 50 .
   Web of Science ®Google Scholar
• CROSS , G. R and JAIN , A. K . 1983 . Markov random field texture models . IEEE Transactions on Pattern Analysis and Machine Intelligence , 5 : 25 – 39 .
   PubMed Web of Science ®Google Scholar
• CSILLAG , F and KABOS , S . 1996 . Hierarchical decomposition of variance with applications in environmental mapping based on satellite images . Mathematical Geology , 28 : 385 – 405 .
   Google Scholar
• CURRAN , P . 1988 . The semivariogram in remote sensing: An introduction . Remote Sensing of Environment , 32 : 493 – 507 .
   Web of Science ®Google Scholar
• DESOUZA , P . 1982 . Texture recognition via autoregression . Pattern Recognition , 15 : 471 – 475 .
   Web of Science ®Google Scholar
• DOBBERTIN , M and BIGING , G . 1996 . A simulation study of the effect of scene autocorrelation, training sample size and sampling method on classification accuracy . Canadian Journal of Remote Sensing , 22 : 360 – 367 .
   Google Scholar
• DU BUF , J. M. H , KARDAN , M and SPANN , M . 1990 . Texture feature performance for image segmentation . Pattern Recognition , 23 : 291 – 309 .
   Web of Science ®Google Scholar
• EYTON , J. R . 1993 . Urban land use classification and modelling using cover-type frequencies . Applied Geography , 13 : 111 – 121 .
   Web of Science ®Google Scholar
• FRANKLIN , S. E and MCDERMID , G. J . 1993 . Empirical relations between digital SPOT HRV and CASI spectral response and lodgepole pine (Pinus contorta) forest stand parameters . International Journal of Remote Sensing , 14 : 2331 – 2348 .
   Web of Science ®Google Scholar
• FRANKLIN , S. E and PEDDLE , D. R . 1987 . Texture analysis of digital image data using spatial co-occurrence . Computers and Geosciences , 13 : 293 – 311 .
   Web of Science ®Google Scholar
• FRANKLIN , S and PEDDLE , D . 1989 . Spectral texture for improved class discrimination in complex terrain . International Journal of Remote Sensing , 10 : 1437 – 1443 .
   Web of Science ®Google Scholar
• FRANKLIN , S and PEDDLE , D . 1990 . Classification of SPOT HRV imagery and texture features . International Journal of Remote Sensing , 11 : 551 – 556 .
   Web of Science ®Google Scholar
• FRANKLIN , S. E , WULDER , M. A and GERYLO , G. R . 2001 . Texture analysis of IKONOS panchromatic data for Douglas-fir forest age class separability in British Columbia . International Journal of Remote Sensing , 22 : 2627 – 2632 .
   Web of Science ®Google Scholar
• GONG , P and HOWARTH , P. J . 1992 . Frequency-based contextual classification and grey level vector reduction for land-use identification . Photogrammetric Engineering and Remote Sensing , 58 : 423 – 437 .
   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
• HARALICK , R. M . 1979 . Statistical and structural approaches to texture . Proceedings of the IEEE , 67 : 786 – 804 .
   Web of Science ®Google Scholar
• HARALICK , R. M , SHAUNMMUGAM , K and DINSTEIN , I . 1973 . Textural features for image classification . IEEE Transactions on Systems, Man, and Cybernetics , 3 : 610 – 621 .
   Web of Science ®Google Scholar
• HAY , G. J and NIEMANN , K. O . 1994 . Visualizing 3-D texture: A three-dimensional structural approach to model forest texture . Canadian Journal of Remote Sensing , 20 : 90 – 101 .
   Google Scholar
• HSU , S . 1980 . Texture perception and the RADC/Hsu texture feature extractor . Photogrammetric Engineering and Remote Sensing , 46 : 1051 – 1058 .
   Web of Science ®Google Scholar
• JENSEN , J. R . 1982 . Detecting residential land-use development at the urban fringe . Photogrammetric Engineering and Remote Sensing , 48 : 629 – 643 .
   Web of Science ®Google Scholar
• JENSEN J. R 1996 Introductory Digital Image Processing: A Remote Sensing Perspective, 2nd edn (Englewood Cliffs, New Jersey: Prentice-Hall)
   Google Scholar
• JULESZ , B . 1962 . Visual pattern discrimination . IRE Transactions on Information Theory , 8 : 84 – 92 .
   Google Scholar
• JUPP , D. B , STRAHLER , A. H and WOODCOCK , C. E . 1988 . Autocorrelation and regularization in digital images I. Basic theory . IEEE Transactions on Geoscience and Remote Sensing , 26 : 463 – 473 .
   Web of Science ®Google Scholar
• LARK , R. M . 1996 . Geostatistical description of texture on an aerial photograph for discriminating classes of land cover . International Journal of Remote Sensing , 17 : 2115 – 2133 .
   Web of Science ®Google Scholar
• LILLESAND T. M KIEFER R. W 2000 Remote Sensing and Image Interpretation, 4th edn (New York: Wiley)
   Google Scholar
• MAO , J and JAIN , A. K . 1992 . Texture classification and segmentation using multiresolution simultaneous autoregressive models . Pattern Recognition , 25 : 173 – 188 .
   Web of Science ®Google Scholar
• MIRANDA , F. P , MACDONALD , J. A and Carr , J. R . 1992 . Application of the semivariogram textural classifier (STC) for vegetation discrimination using SIR-B data of Borneo . International Journal of Remote Sensing , 13 : 2349 – 2354 .
   Web of Science ®Google Scholar
• PANNATIER Y 1996 Variowin: Software for spatial data analysis in 2D (New York: Springer-Verlag)
   Google Scholar
• PEDDLE , D. R . 1995 . Knowledge formulation for supervised evidential classification . Photogrammetric Engineering and Remote Sensing , 61 : 409 – 417 .
   Web of Science ®Google Scholar
• PEDDLE , D. R and FRANKLIN , S. E . 1991 . Image texture processing and data integration for surface pattern discrimination . Photogrammetric Engineering and Remote Sensing , 57 : 413 – 420 .
   Web of Science ®Google Scholar
• REED , T and DU BUF , J. M. H . 1993 . A review of recent texture segmentation and feature extraction techniques . Computer Vision, Graphics, and Image Processing: Image Understanding , 57 : 359 – 372 .
   Google Scholar
• ROBERTS , A. C. B . 1995 . Integrated MSV airborne remote sensing . Canadian Journal of Remote Sensing , 21 : 214 – 224 .
   Google Scholar
• ROSENFIELD , G and FITZPATRICK-LINS , K . 1986 . A coefficient of agreement as a measure of thematic classification accuracy . Photogrammetric Engineering and Remote Sensing , 52 : 223 – 227 .
   Web of Science ®Google Scholar
• RYHERD , S and WOODCOCK , C. E . 1996 . Combining spectral and texture data in the segmentation of remotely sensed images . Photogrammetic Engineering and Remote Sensing , 62 : 181 – 194 .
   Web of Science ®Google Scholar
• SALI , E and WOLFSON , H . 1992 . Texture classification in aerial photographs and satellite data . International Journal of Remote Sensing , 13 : 3395 – 3408 .
   Web of Science ®Google Scholar
• SCHACHTER , B. J , ROSENFELD , A and DAVIS , L. S . 1978 . Random mosaic models for textures . IEEE Transactions on Systems, Man, and Cybernetics , 8 : 694 – 702 .
   Web of Science ®Google Scholar
• ST-ONGE , B and CAVAYAS , F . 1995 . Estimating forest stand structure from high resolution imagery using the directional variogram . International Journal of Remote Sensing , 16 : 1999 – 2021 .
   Web of Science ®Google Scholar
• TREITZ , P . 2001 . Variogram analysis of high spatial resolution remote sensing data: An examination of boreal forest ecosystems . International Journal of Remote Sensing , 22 : 3895 – 3900 .
   Web of Science ®Google Scholar
• VAN GOOL , L , DEWAELE , P and OOSTERLINCK , A . 1985 . Texture analysis annon 1983 . Computer Vision, Graphics, and Image Processing , 29 : 336 – 357 .
   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
• WESZKA , J. S , DYER , C. R and ROSENFELD , A . 1976 . A comparative study of texture measures for terrain classification . IEEE Transactions on Systems, Man, and Cybernetics , 6 : 269 – 285 .
   Web of Science ®Google Scholar
• WHARTON , S. W . 1982 . A contextual classification method for recognizing land use patterns in high resolution remotely sensed data . Pattern Recognition , 15 : 317 – 324 .
   Web of Science ®Google Scholar
• WOODCOCK , C. E and STRAHLER , A. H . 1987 . The factor of scale in remote sensing . Remote Sensing of Environment , 21 : 311 – 332 .
   Web of Science ®Google Scholar
• WOODCOCK , C. E , STRAHLER , A. H and JUPP , D . 1988a . The use of variograms in remote sensing: I. Scene models and simulated images . Remote Sensing of Environment , 25 : 323 – 348 .
   Web of Science ®Google Scholar
• WOODCOCK , C. E , STRAHLER , A. H and JUPP , D . 1988b . The use of variograms in remote sensing: II. Real digital images . Remote Sensing of Environment , 25 : 348 – 379 .
   Web of Science ®Google Scholar
• WULDER , M , LAVIGNE , M and FRANKLIN , S . 1996 . High spatial resolution optical image texture for improved estimation of forest stand leaf area index . Canadian Journal of Remote Sensing , 22 : 441 – 449 .
   Google Scholar
• WULDER , M , LEDREW , E. F , FRANKLIN , S. E and LAVIGNE , M. B . 1998 . Aerial image texture information in the estimation of northern deciduous and mixed wood leaf area index (LAI) . Remote Sensing of Environment , 64 : 64 – 76 .
   Web of Science ®Google Scholar
• Xu , B , Gong , P , Seto , E and Spear , R . 2003 . Comparison of gray level reduction schemes with a revised texture spectrum method for land-use classification using IKONOS imagery . Photogrammetric Engineering and Remote Sensing , 69 : 529 – 536 .
   Web of Science ®Google Scholar