A shape-based approach to change detection of lakes using time series remote sensing images

Shape analysis has not been considered in remote sensing as extensively as in other pattern recognition applications. However, shapes such as those of geometric patterns in agriculture and irregular boundaries of lakes can be extracted from the remotely sensed imagery even at relatively coarse spatial resolutions. This paper presents a procedure for efficiently retrieving and representing shapes of interesting features in remotely sensed imagery using supervised classification, object recognition, parametric contour tracing, and proposed piecewise linear polygonal approximation techniques. In addition, shape similarity can be measured by means of a computationally efficient metric. The study was conducted on a time series of radiometric and geometric rectified Landsat Multispectral Scanner (MSS) images and Thematic Mapper (TM) images, covering the scenes containing lakes in the Nebraska Sand Hills region. The results validate the effectiveness of the proposed processing chain in change detection of lake shapes and show that shape similarity is an important parameter in quantitatively measuring the spatial variations of objects.

[1]  John R. Jensen,et al.  Introductory Digital Image Processing: A Remote Sensing Perspective , 1986 .

[2]  S. Fukuda,et al.  Support vector machine classification of land cover: application to polarimetric SAR data , 2001, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).

[3]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[4]  Leen-Kiat Soh,et al.  Texture analysis of SAR sea ice imagery using gray level co-occurrence matrices , 1999, IEEE Trans. Geosci. Remote. Sens..

[5]  Thorsten Joachims,et al.  Estimating the Generalization Performance of an SVM Efficiently , 2000, ICML.

[6]  Azriel Rosenfeld,et al.  Sequential Operations in Digital Picture Processing , 1966, JACM.

[7]  Jon Atli Benediktsson,et al.  A new approach for the morphological segmentation of high-resolution satellite imagery , 2001, IEEE Trans. Geosci. Remote. Sens..

[8]  James C. Tilton,et al.  Interactive analysis of hierarchical image segmentation , 2000, IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120).

[9]  John A. Richards,et al.  Remote Sensing Digital Image Analysis: An Introduction , 1999 .

[10]  Ivan Tomek,et al.  Two Algorithms for Piecewise-Linear Continuous Approximation of Functions of One Variable , 1974, IEEE Transactions on Computers.

[11]  Peter Z. Revesz,et al.  Introduction to Constraint Databases , 2002, Texts in Computer Science.

[12]  D. Rundquist,et al.  THE RELATIONSHIP BETWEEN SUMMER‐SEASON RAINFALL EVENTS AND LAKE‐SURFACE AREA , 1987 .

[13]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[14]  Azriel Rosenfeld,et al.  Computer Vision , 1988, Adv. Comput..

[15]  M.R. Azimi-Sadjadi,et al.  Cloud classification using support vector machines , 2000, IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120).

[16]  Seong-Dae Kim,et al.  A new chain-coding algorithm for binary images using run-length codes , 1988, Comput. Vis. Graph. Image Process..

[17]  Karin Wall,et al.  A fast sequential method for polygonal approximation of digitized curves , 1984, Comput. Vis. Graph. Image Process..

[18]  V. Vapnik,et al.  Bounds on Error Expectation for Support Vector Machines , 2000, Neural Computation.

[19]  Andrew W. Fitzgibbon,et al.  An Experimental Comparison of Range Image Segmentation Algorithms , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Steven L. Tanimoto.  The Elements of Artificial Intelligence Using Common Lisp , 1995 .

[21]  Derek R. Magee,et al.  Building Shape Models from Image Sequences using Piecewise Linear Approximation , 1998, BMVC.

[22]  Linda G. Shapiro,et al.  Computer Vision , 2001 .

[23]  Sayan Mukherjee,et al.  Choosing Multiple Parameters for Support Vector Machines , 2002, Machine Learning.

[24]  Silvana G. Dellepiane,et al.  Extraction of intensity connectedness for image processing , 1995, Pattern Recognit. Lett..

[25]  Luciano da Fontoura Costa,et al.  Shape Analysis and Classification: Theory and Practice , 2000 .

[26]  A. Weisberg,et al.  Spectral angle automatic cluster routine (SAALT): an unsupervised multispectral clustering algorithm , 1999, 1999 IEEE Aerospace Conference. Proceedings (Cat. No.99TH8403).

[27]  Nello Cristianini,et al.  An introduction to Support Vector Machines , 2000 .

[28]  Min Ouyang,et al.  Approximating Data in Constraint Databases , 2000, SARA.

[29]  Herbert Freeman,et al.  Computer Processing of Line-Drawing Images , 1974, CSUR.

[30]  Bernhard Schölkopf,et al.  Comparing support vector machines with Gaussian kernels to radial basis function classifiers , 1997, IEEE Trans. Signal Process..

[31]  Esther M. Arkin,et al.  An efficiently computable metric for comparing polygonal shapes , 1991, SODA '90.

[32]  W. Alley.  The Palmer Drought Severity Index: Limitations and Assumptions , 1984 .

[33]  Robert F. Cromp,et al.  Support Vector Machine Classifiers as Applied to AVIRIS Data , 1999 .

[34]  E. Work,et al.  Utilization of satellite data for inventorying prairie ponds and lakes , 1976 .

[35]  J. Le Moigne.  Refining Image Segmentation by Integration of Edge and Region Data , 1992, [Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium.

[36]  Olivier Chapelle,et al.  Model Selection for Support Vector Machines , 1999, NIPS.

[37]  Paolo Gamba,et al.  Query-by-shape in meteorological image archives using the point diffusion technique , 2001, IEEE Trans. Geosci. Remote. Sens..

[38]  Remco C. Veltkamp,et al.  State of the Art in Shape Matching , 2001, Principles of Visual Information Retrieval.

[39]  Linda G. Shapiro,et al.  A new connected components algorithm for virtual memory computers , 1983, Comput. Vis. Graph. Image Process..

[40]  Aldo Cumani,et al.  Edge detection in multispectral images , 1991, CVGIP Graph. Model. Image Process..

[41]  Leen-Kiat Soh,et al.  Segmentation of satellite imagery of natural scenes using data mining , 1999, IEEE Trans. Geosci. Remote. Sens..

[42]  David C. Gosselin,et al.  REMOTE MONITORING OF SELECTED GROUND‐WATER DOMINATED LAKES IN THE NEBRASKA SAND HILLS 1 , 2000 .