Accuracy Assessment for Classification and Modeling
暂无分享,去创建一个
[1] Giles M. Foody,et al. Harshness in image classification accuracy assessment , 2008 .
[2] M. Harmon,et al. Total carbon stocks in a tropical forest landscape of the Porce region, Colombia , 2007 .
[3] Alan B. Anderson,et al. Mapping and uncertainty of predictions based on multiple primary variables from joint co-simulation with Landsat TM image and polynomial regression , 2002 .
[4] Guangxing Wang,et al. Uncertainty Analysis of Predicted Disturbance from Off-Road Vehicular Traffic in Complex Landscapes at Fort Hood , 2002, Environmental management.
[5] R. Pontius. QUANTIFICATION ERROR VERSUS LOCATION ERROR IN COMPARISON OF CATEGORICAL MAPS , 2000 .
[6] George Z. Gertner,et al. Uncertainty and sensitivity analysis for models with correlated parameters , 2008, Reliab. Eng. Syst. Saf..
[7] Shoufan Fang,et al. Estimation of sensitivity coefficients of nonlinear model input parameters which have a multinormal distribution , 2004 .
[8] Robert Gilmore Pontius,et al. A generalized cross‐tabulation matrix to compare soft‐classified maps at multiple resolutions , 2006, Int. J. Geogr. Inf. Sci..
[9] J. V. Soares,et al. Distribution of aboveground live biomass in the Amazon basin , 2007 .
[10] Richard A. Birdsey,et al. Toward error analysis of large-scale forest carbon budgets , 2000 .
[11] H Christopher Frey,et al. Comparison of Sensitivity Analysis Methods Based on Applications to a Food Safety Risk Assessment Model , 2004, Risk analysis : an official publication of the Society for Risk Analysis.
[12] J. C. Helton,et al. An Investigation of Uncertainty and Sensitivity Analysis Techniques for Computer Models , 1988 .
[13] Guangxing Wang,et al. Mapping Multiple Variables for Predicting Soil Loss by Geostatistical Methods with TM Images and a Slope Map , 2003 .
[14] Guangxing Wang,et al. A Methodology for Spatial Uncertainty Analysis Of Remote Sensing and GIS Products , 2005 .
[15] R. Congalton. Accuracy assessment and validation of remotely sensed and other spatial information , 2001 .
[16] Sarah Parks,et al. An effective assessment protocol for continuous geospatial datasets of forest characteristics using USFS Forest Inventory and Analysis (FIA) data , 2010 .
[17] Tonny J. Oyana,et al. Mapping and spatial uncertainty analysis of forest vegetation carbon by combining national forest inventory data and satellite images , 2009 .
[18] Giles M. Foody,et al. Status of land cover classification accuracy assessment , 2002 .
[19] Gregory P. Asner,et al. Controls over aboveground forest carbon density on Barro Colorado Island, Panama , 2010 .
[20] Daniel A. Griffith,et al. Error Propagation Modelling in Raster GIS: Overlay Operations , 1998, Int. J. Geogr. Inf. Sci..
[21] P. Reed,et al. Hydrology and Earth System Sciences Discussions Comparing Sensitivity Analysis Methods to Advance Lumped Watershed Model Identification and Evaluation , 2022 .
[22] Tonny J. Oyana,et al. Uncertainties of mapping aboveground forest carbon due to plot locations using national forest inventory plot and remotely sensed data , 2011 .
[23] M. Jansen. Analysis of variance designs for model output , 1999 .
[24] George Z. Gertner,et al. A general first-order global sensitivity analysis method , 2008, Reliab. Eng. Syst. Saf..
[25] Raymond L. Czaplewski,et al. Misclassification Bias in Areal Estimates , 1992 .
[26] Roland L. Redmond,et al. Estimation and Mapping of Misclassification Probabilities for Thematic Land Cover Maps , 1998 .
[27] Patrick M. Reed,et al. Advancing the identification and evaluation of distributed rainfall‐runoff models using global sensitivity analysis , 2007 .
[28] Oleg Chertov,et al. Uncertainty analysis in carbon cycle models of forest ecosystems: Research needs and development of a theoretical framework to estimate error propagation , 2008 .
[29] Qiming Zhou,et al. Accuracy assessment on multi‐temporal land‐cover change detection using a trajectory error matrix , 2009 .
[30] Alan B. Anderson,et al. Improved generalized Fourier amplitude sensitivity test (FAST) for model assessment , 2003, Stat. Comput..
[31] S. Carpenter,et al. Global Consequences of Land Use , 2005, Science.
[32] M. Nilsson,et al. Combining national forest inventory field plots and remote sensing data for forest databases , 2008 .
[33] Janne Heiskanen,et al. Estimating biomass for boreal forests using ASTER satellite data combined with standwise forest inventory data , 2005 .
[34] C. Willmott. Some Comments on the Evaluation of Model Performance , 1982 .
[35] R. Congalton,et al. Accuracy assessment: a user's perspective , 1986 .
[36] S. Hubbell,et al. Spatial and temporal variation of biomass in a tropical forest: results from a large census plot in Panama , 2003 .
[37] David Saah,et al. Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates , 2012 .
[38] L.L.F. Janssen,et al. Accuracy assessment of satellite derived land - cover data : a review , 1994 .
[39] Stephen V. Stehman,et al. Statistical Rigor and Practical Utility in Thematic Map Accuracy Assessment , 2001 .
[40] George Z. Gertner,et al. Extending a global sensitivity analysis technique to models with correlated parameters , 2007, Comput. Stat. Data Anal..
[41] George Gertner,et al. Simulating Spatial Pattern and Dynamics of Military Training Impacts for Allocation of Land Repair Using Images , 2009, Environmental management.
[42] Linda S. Heath,et al. An assessment of uncertainty in forest carbon budget projections , 2000 .
[43] Stefano Tarantola,et al. Random balance designs for the estimation of first order global sensitivity indices , 2006, Reliab. Eng. Syst. Saf..
[44] Guangxing Wang,et al. Spatial uncertainty analysis for mapping soil erodibility based on joint sequential simulation , 2003 .
[45] G. Foody,et al. Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions , 2003 .
[46] George Z. Gertner,et al. A quality assessment of a Weibull based growth projection system , 1995 .
[47] Giles M. Foody,et al. Assessing the ground data requirements for regional scale remote sensing of tropical forest biophysical properties , 2000 .
[48] M. Keller,et al. Biomass estimation in the Tapajos National Forest, Brazil: Examination of sampling and allometric uncertainties , 2001 .
[49] G. Asner,et al. Evaluating uncertainty in mapping forest carbon with airborne LiDAR , 2011 .
[50] L. Ji,et al. An Agreement Coefficient for Image Comparison , 2006 .
[51] P. Mielke. The application of multivariate permutation methods based on distance functions in the earth sciences , 1991 .
[52] Jon C. Helton,et al. Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal , 1993 .
[53] Max D. Morris,et al. Factorial sampling plans for preliminary computational experiments , 1991 .
[54] G. Foody. Monitoring the magnitude of land-cover change around the southern limits of the Sahara , 2001 .
[55] G. Asner,et al. Environmental and Biotic Controls over Aboveground Biomass Throughout a Tropical Rain Forest , 2009, Ecosystems.
[56] Limin Yang,et al. Urban Land-Cover Change Detection through Sub-Pixel Imperviousness Mapping Using Remotely Sensed Data , 2003 .
[57] Guangxing Wang,et al. Improvement in mapping vegetation cover factor for the universal soil loss equation by geostatistical methods with Landsat Thematic Mapper images , 2002 .
[58] Stephen V. Stehman,et al. A Critical Evaluation of the Normalized Error Matrix in Map Accuracy Assessment , 2004 .
[59] Wenzhong Shi,et al. A stochastic process-based model for the positional error of line segments in GIS , 2000, Int. J. Geogr. Inf. Sci..
[60] C. Willmott. ON THE VALIDATION OF MODELS , 1981 .
[61] Alan B. Anderson,et al. Spatial uncertainty in prediction of the topographical factor for the revised universal soil loss equation (RUSLE) , 2002 .
[62] Michael A. Wulder,et al. Remote sensing methods in medium spatial resolution satellite data land cover classification of large areas , 2002 .
[63] B. van Putten,et al. Comparison of uncertainties in carbon sequestration estimates for a tropical and a temperate forest , 2008 .
[64] R. G. Pontius. Statistical Methods to Partition Effects of Quantity and Location During Comparison of Categorical Maps at Multiple Resolutions , 2002 .
[65] Robert Gilmore Pontius,et al. Range of Categorical Associations for Comparison of Maps with Mixed Pixels , 2009 .
[66] Michael A. Wulder,et al. An accuracy assessment framework for large‐area land cover classification products derived from medium‐resolution satellite data , 2006 .
[67] Stefano Tarantola,et al. Sensitivity analysis of spatial models , 2009, Int. J. Geogr. Inf. Sci..
[68] J. Wickham,et al. Thematic accuracy of the 1992 National Land-Cover Data for the eastern United States: Statistical methodology and regional results , 2003 .
[69] Russell G. Congalton,et al. Mapping and Monitoring Agricultural Crops and Other Land Cover in the Lower Colorado River Basin , 1998 .
[70] Gerard B. M. Heuvelink,et al. Error Propagation in Cartographic Modelling Using Boolean Logic and Continuous Classification , 1993, Int. J. Geogr. Inf. Sci..
[71] Paul D. Bates,et al. Distributed Sensitivity Analysis of Flood Inundation Model Calibration , 2005 .
[72] Janet L. Ohmann,et al. Predictive mapping of forest composition and structure with direct gradient analysis and nearest- neighbor imputation in coastal Oregon, U.S.A. , 2002 .
[73] D. Lu. The potential and challenge of remote sensing‐based biomass estimation , 2006 .
[74] Frédéric Baret,et al. Developments in the 'validation' of satellite sensor products for the study of the land surface , 2000 .
[75] I. Sobol. On the distribution of points in a cube and the approximate evaluation of integrals , 1967 .
[76] Stefano Tarantola,et al. Uncertainty and sensitivity analysis: tools for GIS-based model implementation , 2001, Int. J. Geogr. Inf. Sci..
[77] M. Lefsky,et al. Forest carbon densities and uncertainties from Lidar, QuickBird, and field measurements in California , 2010 .
[78] D. Roberts,et al. Sources of error in accuracy assessment of thematic land-cover maps in the Brazilian Amazon , 2004 .
[79] Giles M. Foody,et al. On the compensation for chance agreement in image classification accuracy assessment, Photogram , 1992 .
[80] K. Shuler,et al. Nonlinear sensitivity analysis of multiparameter model systems , 1977 .
[81] Alan B. Anderson,et al. Assessing and predicting changes in vegetation cover associated with military land use activities using field monitoring data at Fort Hood, Texas , 2005 .
[82] Richard Condit,et al. Error propagation and scaling for tropical forest biomass estimates. , 2004, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[83] Javier Montero,et al. Accuracy statistics for judging soft classification , 2008 .
[84] C. Homer,et al. Updating the 2001 National Land Cover Database Impervious Surface Products to 2006 using Landsat Imagery Change Detection Methods , 2010 .
[85] David E. Knapp,et al. High-resolution carbon mapping on the million-hectare Island of Hawaii , 2011 .
[86] Gerard B. M. Heuvelink,et al. Propagation of errors in spatial modelling with GIS , 1989, Int. J. Geogr. Inf. Sci..
[87] George Z. Gertner,et al. Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST) , 2011, Comput. Stat. Data Anal..
[88] A. Saltelli,et al. Making best use of model evaluations to compute sensitivity indices , 2002 .
[89] J. Scepan,et al. Thematic validation of high-resolution Global Land-Cover Data sets , 1999 .
[90] Giles M. Foody,et al. Mapping the biomass of Bornean tropical rain forest from remotely sensed data , 2001 .
[91] Roni Avissar,et al. An Evaluation with the Fourier Amplitude Sensitivity Test (FAST) of Which Land-Surface Parameters Are of Greatest Importance in Atmospheric Modeling , 1994 .
[92] Andrea Saltelli,et al. An effective screening design for sensitivity analysis of large models , 2007, Environ. Model. Softw..
[93] Philip B Woodford,et al. Spatial variability and temporal dynamics analysis of soil erosion due to military land use activities: uncertainty and implications for land management , 2007 .
[94] Alan B. Anderson,et al. Mapping vegetation cover change using geostatistical methods and bitemporal Landsat TM images , 2004, IEEE Transactions on Geoscience and Remote Sensing.
[95] Weldon A. Lodwick,et al. Attribute error and sensitivity analysis of map operations in geographical informations systems: suitability analysis , 1990, Int. J. Geogr. Inf. Sci..
[96] Russell G. Congalton,et al. A review of assessing the accuracy of classifications of remotely sensed data , 1991 .
[97] Chonggang Xu,et al. Uncertainties in the response of a forest landscape to global climatic change , 2009 .
[98] W. Cohen,et al. Landsat's Role in Ecological Applications of Remote Sensing , 2004 .
[99] Stephen V. Stehman,et al. Design and Analysis for Thematic Map Accuracy Assessment: Fundamental Principles , 1998 .
[100] G. Powell,et al. High-resolution forest carbon stocks and emissions in the Amazon , 2010, Proceedings of the National Academy of Sciences.
[101] Philip A. Townsend,et al. A Quantitative Fuzzy Approach to Assess Mapped Vegetation Classifications for Ecological Applications , 2000 .
[102] C. Fortuin,et al. Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory , 1973 .
[103] Nathan P. Gillett,et al. Natural and anthropogenic climate change: incorporating historical land cover change, vegetation dynamics and the global carbon cycle , 2004 .
[104] A. Saltelli,et al. A quantitative model-independent method for global sensitivity analysis of model output , 1999 .