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Articles

Application of geographically weighted regression to fill gaps in SLC-off Landsat ETM+ satellite imagery

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Pages 7650-7672 | Received 30 Dec 2013, Accepted 01 Jul 2014, Published online: 19 Nov 2014

References

  • Addink, E. A. 1999. “A Comparison of Conventional and Geostatistical Methods to Replace Clouded Pixels in NOAA-AVHRR Images.” International Journal of Remote Sensing 20: 961–977. doi:10.1080/014311699213028.
  • Bédard, F., G. Reichert, R. Dobbins, and I. Trépanier. 2008. “Evaluation of Segment-Based Gap-Filled Landsat ETM+SLC-Off Satellite Data for Land Cover Classification in Southern Saskatchewan, Canada.” International Journal of Remote Sensing 29: 2041–2054. doi:10.1080/01431160701281064.
  • Boloorani, A. D., S. Erasmi, and M. Kappas. 2008. “Multi-Source Remotely Sensed Data Combination: Projection Transformation Gap-Fill Procedure.” Sensors 8: 4429–4440. doi:10.3390/s8074429.
  • Brunsdon, C., A. S. Fotheringham, and M. E. Charlton. 1996. “Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity.” Geographical Analysis 28: 281–298. doi:10.1111/j.1538-4632.1996.tb00936.x.
  • Chen, J., X. Zhu, J. E. Vogelmann, F. Gao, and S. Jin. 2011. “A Simple and Effective Method for Filling Gaps in Landsat ETM+ SLC-Off Images.” Remote Sensing of Environment 115: 1053–1064. doi:10.1016/j.rse.2010.12.010.
  • Civco, D. L., J. D. Hurd, E. H. Wilson, C. L. Arnold, and S. Prisloe. 2002. “Quantifying and Describing Urbanizing Landscapes in the Northeast United States.” Photogrammetric Engineering and Remote Sensing 68 (10): 1083–1090.
  • Cohen, W. B., T. K. Maiersperger, S. T. Gower, and D. P. Turner. 2003. “An Improved Strategy for Regression of Biophysical Variables and Landsat ETM+ Data.” Remote Sensing of Environment 84: 561–571. doi:10.1016/S0034-4257(02)00173-6.
  • Comber, A., P. Fisher, C. Brunsdon, and A. Khmag. 2012. “Spatial Analysis of Remote Sensing Image Classification Accuracy.” Remote Sensing of Environment 127: 237–246. doi:10.1016/j.rse.2012.09.005.
  • Curran, P. J., and P. M. Atkinson. 1998. “Geostatistics and Remote Sensing.” Progress in Physical Geography 22: 61–78. doi:10.1177/030913339802200103.
  • Foody, G. M. 2003. “Geographical Weighting as a Further Refinement to Regression Modelling: An Example Focused on the NDVI–Rainfall Relationship.” Remote Sensing of Environment 88: 283–293. doi:10.1016/j.rse.2003.08.004.
  • Fotheringham, A. S., C. A. Brunsdon, and M. E. Charlton. 2002. Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. New York: John Wiley & Sons.
  • Fotheringham, A. S., M. E. Charlton, and C. Brunsdon. 1998. “Geographically Weighted Regression: A Natural Evolution of the Expansion Method for Spatial Data Analysis.” Environment and Planning A 30: 1905–1927. doi:10.1068/a301905.
  • Goovaerts, P. 1997. Geostatistics for Natural Resources Evaluation. New York: Oxford University Press.
  • Hurd, J. D., and D. L. Civco. 2004. “Temporal Characterization of Impervious Surfaces for the State of Connecticut.” Proceedings of 2004 ASPRS Annual Convention, Denver, CO, May 23–28, 12p. CD-ROM.
  • Isaaks, E. H., and R. M. Srivastava. 1989. An Introduction to Applied Geostatistics. New York: Oxford University Press.
  • Journel, A., and C. J. Huijbregts. 1978. Mining Geostatistics. New York: Academic Press.
  • Journel, A. G. 1989. Fundamentals of Geostatistics in Five Lessons (Short Course in Geology). Washington, DC: American Geophysical Union.
  • Kamarianakis, Y., H. Feidas, G. Kokolatos, N. Chrysoulakis, and V. Karatzias. 2008. “Evaluating Remotely Sensed Rainfall Estimates Using Nonlinear Mixed Models and Geographically Weighted Regression.” Environmental Modelling & Software 23: 1438–1447. doi:10.1016/j.envsoft.2008.04.007.
  • Koutsias, N., J. Martínez-Fernández, and B. Allgöwer. 2010. “Do Factors Causing Wildfires Vary in Space? Evidence from Geographically Weighted Regression.” GIScience & Remote Sensing 47: 221–240. doi:10.2747/1548-1603.47.2.221.
  • Leica Geosystems. 2003. ERDAS Field Guide, Leica Geosystems GIS & Mapping. Atlanta, GA: LLC.
  • Lo, C. P., and J. Choi. 2004. “A Hybrid Approach to Urban Land Use/Cover Mapping Using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) Images.” International Journal of Remote Sensing 25 (14): 2687–2700. doi:10.1080/01431160310001618428.
  • Markogianni, V., E. Dimitriou, and D. P. Kalivas. 2013. “Land-Use and Vegetation Change Detection in Plastira Artificial Lake Catchment (Greece) by Using Remote-Sensing and GIS Techniques.” International Journal of Remote Sensing 34 (4): 1265–1281. doi:10.1080/01431161.2012.718454.
  • Matheron, G. 1963. “Principles of Geostatistics.” Economic Geology 58: 1246–1266. doi:10.2113/gsecongeo.58.8.1246.
  • Matheron, G. 1971. The Theory of Regionalized Variables and its Applications. Fontainebleu: Les Cahiers du center de Morphologie Mathematique de Fontainebleau 5. CMMF.
  • Maxwell, S. K. 2004. “Filling Landsat ETM+ SLC-Off Gaps Using a Segmentation Model Approach.” Photogrammetric Engineering and Remote Sensing 70: 1109–1111.
  • Maxwell, S. K., G. L. Schmidt, and J. C. Storey. 2007. “A Multi-Scale Segmentation Approach to Filling Gaps in Landsat ETM+ SLC-Off Images.” International Journal of Remote Sensing 28: 5339–5356. doi:10.1080/01431160601034902.
  • Mundia, C. N., and M. Aniya. 2005. “Analysis of Land Use/Cover Changes and Urban Expansion of Nairobi City Using Remote Sensing and GIS.” International Journal of Remote Sensing 26 (13): 2831–2849. doi:10.1080/01431160500117865.
  • Pardo-Igúzquiza, E., M. Chica-olmo, and P. M. Atkinson. 2006. “Downscaling Cokriging for Image Sharpening.” Remote Sensing of Environment 102: 86–98. doi:10.1016/j.rse.2006.02.014.
  • Pineda Jaimes, N. B., J. Bosque Sendra, M. Gómez Delgado, and R. Franco Plata. 2010. “Exploring the Driving Forces behind Deforestation in the State of Mexico (Mexico) Using Geographically Weighted Regression.” Applied Geography 30: 576–591. doi:10.1016/j.apgeog.2010.05.004.
  • Pringle, M. J., M. Schmidt, and J. S. Muir. 2009. “Geostatistical Interpolation of SLC-Off Landsat ETM+ Images.” ISPRS Journal of Photogrammetry and Remote Sensing 64: 654–664. doi:10.1016/j.isprsjprs.2009.06.001.
  • Propastin, P. A. 2009. “Spatial Non-Stationarity and Scale-Dependency of Prediction Accuracy in the Remote Estimation of LAI over a Tropical Rainforest in Sulawesi, Indonesia.” Remote Sensing of Environment 113: 2234–2242. doi:10.1016/j.rse.2009.06.007.
  • Rossi, R. E., J. L. Dungan, and L. R. Beck. 1994. “Kriging in the Shadows: Geostatistical Interpolation for Remote Sensing.” Remote Sensing of Environment 49: 32–40. doi:10.1016/0034-4257(94)90057-4.
  • Salas, C., L. Ene, T. G. Gregoire, E. Næsset, and T. Gobakken. 2010. “Modelling Tree Diameter from Airborne Laser Scanning Derived Variables: A Comparison of Spatial Statistical Models.” Remote Sensing of Environment 114: 1277–1285. doi:10.1016/j.rse.2010.01.020.
  • Scaramuzza, P., E. Micijevic, and G. Chander. 2004. “SLC Gap-Filled Products: Phase One Methodology.” Accessed October 31, 2013. http://landsat.usgs.gov/documents/SLC_Gap_Fill_Methodology.pdf.
  • Stein, A., F. Van Der Meer, and B. Gorte, eds. 1999. Spatial Statistics for Remote Sensing. Heidelberg: Kluwer Academic.
  • Tu, J., and Z. Xia. 2008. “Examining Spatially Varying Relationships between Land Use and Water Quality Using Geographically Weighted Regression I: Model Design and Evaluation.” The Science of the Total Environment 407: 358–378. doi:10.1016/j.scitotenv.2008.09.031.
  • USGS. 2004. “Phase 2 Gap-Fill Algorithm: SLC-Off Gap-Filled Products Gap-Fill Algorithm Methodology.” Accessed October 31, 2013. http://landsat.usgs.gov/documents/L7SLCGapFilledMethod.pdf.
  • van Wagtendonk, J. W., R. R. Root, and C. H. Key. 2004. “Comparison of AVIRIS and Landsat ETM+ Detection Capabilities for Burn Severity.” Remote Sensing of Environment 92: 397–408. doi:10.1016/j.rse.2003.12.015.
  • Wang, K., C. Zhang, W. Li, J. Lin, and D. Zhang 2013. “Mapping Soil Organic Matter with Limited Sample Data Using Geographically Weighted Regression.” Journal of Spatial Science. Accessed October 31, 2013. http://dx.doi.org/10.1080/14498596.2013.812024
  • Wang, K. U., C. Zhang, and W. Li. 2012. “Comparison of Geographically Weighted Regression and Regression Kriging for Estimating the Spatial Distribution of Soil Organic Matter.” GIScience & Remote Sensing 49 (6): 915–932. doi:10.2747/1548-1603.49.6.915.
  • Wang, K. U., C. Zhang, and W. Li. 2013. “Predictive Mapping of Soil Total Nitrogen at a Regional Scale: A Comparison between Geographically Weighted Regression and Cokriging.” Applied Geography 42: 73–85. doi:10.1016/j.apgeog.2013.04.002.
  • Wang, Q., J. Ni, and J. Tenhunen. 2005. “Application of a Geographically-Weighted Regression Analysis to Estimate Net Primary Production of Chinese Forest Ecosystems.” Global Ecology and Biogeography 14: 379–393. doi:10.1111/j.1466-822X.2005.00153.x.
  • Xie, Z., C. Zhang, and L. Berry. 2013. “Geographically Weighted Modelling of Surface Salinity in Florida Bay Using Landsat TM Data.” Remote Sensing Letters 4 (1): 75–83. doi:10.1080/2150704X.2012.693218.
  • Yang, L., C. Huang, C. G. Homer, B. K. Wylie, and M. J. Coan. 2003. “An Approach for Mapping Large-Area Impervious Surfaces: Synergistic Use of Landsat-7 ETM+ and High Spatial Resolution Imagery.” Canadian Journal of Remote Sensing 29 (2): 230–240. doi:10.5589/m02-098.
  • Yu, D., N. A. Peterson, and R. J. Reid. 2009. “Exploring the Impact of Non-Normality on Spatial Non-Stationarity in Geographically Weighted Regression Analyses: Tobacco Outlet Density in New Jersey.” GIScience & Remote Sensing 46: 329–346. doi:10.2747/1548-1603.46.3.329.
  • Yu, G., L. Di, and W. Yang. 2008. “Downscaling of Global Soil Moisture Using Auxiliary Data.” Accessed October 31, 2013. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4779325
  • Zeng, C., H. Shen, and L. Zhang. 2013. “Recovering Missing Pixels for Landsat ETM+ SLC-Off Imagery Using Multi-Temporal Regression Analysis and a Regularization Method.” Remote Sensing of Environment 131: 182–194. doi:10.1016/j.rse.2012.12.012.
  • Zhang, C., W. Li, and D. Travis. 2007. “Gaps-Fill of SLC-Off Landsat ETM+ Satellite Image Using a Geostatistical Approach.” International Journal of Remote Sensing 28 (22): 5103–5122. doi:10.1080/01431160701250416.
  • Zhang, C., W. Li, and D. J. Travis. 2009. “Restoration of Clouded Pixels in Multispectral Remotely Sensed Imagery with Co-Kriging.” International Journal of Remote Sensing 30 (9): 2173–2195. doi:10.1080/01431160802549294.
  • Zhu, X., D. Liu, and J. Chen. 2012. “A New Geostatistical Approach for Filling Gaps in Landsat ETM+ SLC-Off Images.” Remote Sensing of Environment 124: 49–60. doi:10.1016/j.rse.2012.04.019.

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