6 Integrating GIS and Remotely Sensed Data for Mapping Forest Disturbance and Change

[1]  P. Treitz,et al.  Integrating spectral, spatial, and terrain variables for forest ecosystem classification , 2000 .

[2]  J. Ross Quinlan,et al.  C4.5: Programs for Machine Learning , 1992 .

[3]  David J. Mladenoff,et al.  Issues and Perspectives in Landscape Ecology: The promise of landscape modeling: successes, failures, and evolution , 2005 .

[4]  X. Lee,et al.  Introduction to wildland fire , 1997 .

[5]  Michael A. Wulder,et al.  Optical remote-sensing techniques for the assessment of forest inventory and biophysical parameters , 1998 .

[6]  Robert N. Colwell,et al.  Manual of remote sensing , 1983 .

[7]  D. A. Stow,et al.  Using multiple image endmember spectral mixture analysis to study chaparral regrowth in southern California , 2003 .

[8]  J. Vogelmann,et al.  Regional Land Cover Characterization Using Landsat Thematic Mapper Data and Ancillary Data Sources , 1998 .

[9]  Paul Siqueira,et al.  A continental-scale mosaic of the Amazon basin using JERS-1 SAR , 2000, IEEE Trans. Geosci. Remote. Sens..

[10]  P. McCullagh,et al.  Generalized Linear Models , 1992 .

[11]  H. Olsson,et al.  Thinning-caused change in reflectance of ground vegetation in boreal forest , 2001 .

[12]  L. Irland ICE STORM 1998 AND THE FORESTS OF THE NORTHEAST : A PRELIMINARY ASSESSMENT , 1998 .

[13]  Antoine Guisan,et al.  Predictive habitat distribution models in ecology , 2000 .

[14]  M. Ehlers,et al.  A framework for the modelling of uncertainty between remote sensing and geographic information systems , 2000 .

[15]  David M. Stoms,et al.  Validating large‐area land cover databases with Maplets , 1996 .

[16]  Alexis J. Comber,et al.  Application of knowledge for automated land cover change monitoring , 2004 .

[17]  N. Lam,et al.  Environmental analysis using integrated GIS and remotely sensed data - Some research needs and priorities , 1991 .

[18]  Emilio Chuvieco,et al.  Assessment of vegetation regeneration after fire through multitemporal analysis of AVIRIS images in the Santa Monica Mountains , 2002 .

[19]  Limin Yang,et al.  Regional Forest Land Cover Characterisation using Medium Spatial Resolution Satellite Data , 2003 .

[20]  Michael A. Wulder,et al.  Remote sensing methods in medium spatial resolution satellite data land cover classification of large areas , 2002 .

[21]  D. Roberts,et al.  Combining spectral and spatial information to map canopy damage from selective logging and forest fires , 2005 .

[22]  P. Bolstad,et al.  An evaluation of DEM accuracy: elevation, slope, and aspect , 1994 .

[23]  Tomorrow’s Forests: Adapting to a Changing Climate , 2005 .

[24]  R. D. Ramsey,et al.  The relationship between NOAA-AVHRR NDVI and ecoregions in Utah , 1995 .

[25]  Roger Wheate,et al.  Detection of red attack stage mountain pine beetle infestation with high spatial resolution satellite imagery , 2005 .

[26]  S. E. Franklin,et al.  Satellite remote sensing of spruce budworm forest defoliation in Western Newfoundland , 1994 .

[27]  Ola Ahlqvist,et al.  A Parameterized Representation of Uncertain Conceptual Spaces , 2004, Trans. GIS.

[28]  Ale Raza,et al.  An Object-Oriented Approach for Modeling Urban Land-Use Changes , 2007 .

[29]  A. Millward,et al.  Physical influences of landscape on a large-extent ecological disturbance: the northeastern North American ice storm of 1998 , 2004, Landscape Ecology.

[30]  Shawn W. Laffan,et al.  Effect of error in the DEM on environmental variables for predictive vegetation modelling , 2004 .

[31]  B. Turner Toward Integrated Land-Change Science: Advances in 1.5 Decades of Sustained International Research on Land-Use and Land-Cover Change , 2002 .

[32]  R. Colombo,et al.  Integration of remote sensing data and GIS for accurate mapping of flooded areas , 2002 .

[33]  Andrew K. Skidmore,et al.  Forest mapping accuracies are improved using a supervised nonparametric classifier with SPOT data , 1988 .

[34]  K. Coates Windthrow damage 2 years after partial cutting at the Date Creek silvicultural systems study in the Interior Cedar-Hemlock forests of northwestern British Columbia , 1997 .

[35]  Lisa M. Levien,et al.  A MACHINE-LEARNING APPROACH TO CHANGE DETECTION USING MULTI-SCALE IMAGERY , 1999 .

[36]  Thomas R. Loveland,et al.  USING MULTISOURCE DATA IN GLOBAL LAND-COVER CHARACTERIZATION: CONCEPTS, REQUIREMENTS, AND METHODS , 1993 .

[37]  Russell D. Johnson Change vector analysis for disaster assessment: A case study of Hurricane Andrew , 1994 .

[38]  T. Frank Mapping dominant vegetation communities in the Colorado Rocky Mountain Front Range with Landsat Thematic Mapper and digital terrain data , 1988 .

[39]  Giles M. Foody,et al.  Status of land cover classification accuracy assessment , 2002 .

[40]  D. Stow Reducing the effects of misregistration on pixel-level change detection , 1999 .

[41]  Alan H. Strahler,et al.  Maximizing land cover classification accuracies produced by decision trees at continental to global scales , 1999, IEEE Trans. Geosci. Remote. Sens..

[42]  W. Klenner,et al.  Windthrow following four harvest treatments in an Engelmann spruce - subalpine fir forest in southern interior British Columbia, Canada , 1999 .

[43]  C. Woodcock,et al.  An assessment of several linear change detection techniques for mapping forest mortality using multitemporal landsat TM data , 1996 .

[44]  M. J. Cosentino,et al.  Describing the Brushfire Hazard in Southern California , 1985 .

[45]  J. Borak Feature selection and land cover classification of a MODIS-like data set for a semiarid environment , 1999 .

[46]  Donato Malerba,et al.  Machine learning for information extraction from topographic maps , 2001 .

[47]  T. Warner,et al.  Multitemporal censusing of a population of eastern hemlock (Tsuga canadensis L.) from remotely sensed imagery using an automated segmentation and reconciliation procedure , 2005 .

[48]  S. Yool,et al.  Improving thematic mapper based classification of wildfire induced vegetation mortality , 1997 .

[49]  Michael L. Clutter,et al.  The future of digital remote sensing for production forestry organizations , 2003 .

[50]  K. Chen,et al.  An approach to linking remotely sensed data and areal census data , 2002 .

[51]  Mark Gahegan,et al.  Is inductive machine learning just another wild goose (or might it lay the golden egg)? , 2003, Int. J. Geogr. Inf. Sci..

[52]  Mark Noonan,et al.  The post-fire measurement of fire severity and intensity in the Christmas 2001 Sydney wildfires , 2004 .

[53]  M. Flood,et al.  LiDAR remote sensing of forest structure , 2003 .

[54]  J. Franklin Predictive vegetation mapping: geographic modelling of biospatial patterns in relation to environmental gradients , 1995 .

[55]  Michael A. Wulder,et al.  Sensitivity of the thematic mapper enhanced wetness difference index to detect mountain pine beetle red-attack damage , 2003 .

[56]  Volker C. Radeloff,et al.  Detecting Jack Pine Budworm Defoliation Using Spectral Mixture Analysis: Separating Effects from Determinants , 1999 .

[57]  James Williamson,et al.  A Gaussian adaptive resonance theory neural network classification algorithm applied to supervised land cover mapping using multitemporal vegetation index data , 2001, IEEE Trans. Geosci. Remote. Sens..

[58]  J. Franklin,et al.  Rationale and conceptual framework for classification approaches to assess forest resources and properties , 2003 .

[59]  S. Franklin Remote Sensing for Sustainable Forest Management , 2001 .

[60]  W. Michener,et al.  Impacts of hurricane Hugo on a coastal forest: Assessment using Landsat TM data , 1994 .

[61]  Douglas J. King,et al.  Modelling Deciduous Forest Ice Storm Damage Using Aerial CIR Imagery and Hemispheric Photography , 2000 .

[62]  J. Rogan,et al.  Remote sensing technology for mapping and monitoring land-cover and land-use change , 2004 .

[63]  S. C. Ahearn,et al.  A comparison of the SPOT and Landsat thematic mapper satellite systems for detecting gypsy moth defoliation in Michigan , 1991 .

[64]  Rick L. Lawrence,et al.  Land use and land cover change in the greater yellowstone ecosystem: 1975-1995 , 2003 .

[65]  K. Holmesa,et al.  Error in a USGS 30-meter digital elevation model and its impact on terrain modeling , 2000 .

[66]  W. Baker A review of models of landscape change , 1989, Landscape Ecology.

[67]  李幼升,et al.  Ph , 1989 .

[68]  J. Shipman,et al.  Using landform and vegetative factors to improve the interpretation of Landsat imagery: land-cover units associated with major landform conditions were readily classified with reasonable accuracy to level 3 and at times to level 4 , 1984 .

[69]  Brian G. Lees,et al.  Decision-tree and rule-induction approach to integration of remotely sensed and GIS data in mapping vegetation in disturbed or hilly environments , 1991 .

[70]  Fraser Gemmell,et al.  Utility of Reflectance Model Inversion Versus Two Spectral Indices for Estimating Biophysical Characteristics in a Boreal Forest Test Site , 1999 .

[71]  Kathleen S. Shields,et al.  Using Satellite Images to Classify and Analyze the Health of Hemlock Forests Infested by the Hemlock Woolly Adelgid , 1999, Biological Invasions.

[72]  Curtis E. Woodcock,et al.  Mapping and monitoring conifer mortality using remote sensing in the Lake Tahoe Basin , 1994 .

[73]  B. Rock,et al.  Preliminary assessment of airborne imaging spectrometer and airborne thematic mapper data acquired for forest decline areas in the Federal Republic of Germany , 1988 .

[74]  Jeremiah D. Lindemann,et al.  Using GIS to analyse a severe forest blowdown in the Southern Rocky Mountains , 2002, Int. J. Geogr. Inf. Sci..

[75]  M. Hansen,et al.  A comparison of the IGBP DISCover and University of Maryland 1 km global land cover products , 2000 .

[76]  Siamak Khorram,et al.  Land-cover change detection enhanced with generalized linear models , 1999 .

[77]  A. Finley,et al.  Timber harvesting as ongoing disturbance in a landscape of diverse ownership , 2003 .

[78]  J. Heikkonen,et al.  Forest change detection applying Landsat Thematic Mapper difference features: A comparison of different classifiers in boreal forest conditions , 2004 .

[79]  M. Austin,et al.  A new model for the continuum concept , 1989, Vegetatio.

[80]  Jennifer A. Miller,et al.  Land-Cover Change Monitoring with Classification Trees Using Landsat TM and Ancillary Data , 2003 .

[81]  B. Xu,et al.  Remote Sensing of Forests Over Time , 2003 .

[82]  Michael A. Wulder,et al.  Inclusion of topographic variables in an unsupervised classification of satellite imagery , 2004 .

[83]  Xueqiao Huang,et al.  A Machine-Learning Approach to Automated Knowledge-Base Building for Remote Sensing Image Analysis with GIs Data , 1997 .

[84]  C. Potter,et al.  Large-scale impoverishment of Amazonian forests by logging and fire , 1999, Nature.

[85]  Stephen V. Stehman,et al.  A Strategy for Estimating the Rates of Recent United States Land-Cover Changes , 2002 .

[86]  E. Chuvieco,et al.  Mapping and inventory of forest fires from digital processing of tm data , 1988 .

[87]  Håkan Olsson,et al.  Reflectance calibration of thematic mapper data for forest change detection , 1995 .

[88]  Owen P. Bricker,et al.  TOWARD A NATIONAL PROGRAM FOR MONITORING ENVIRONMENTAL RESOURCES , 1998 .

[89]  C. Souza,et al.  An alternative approach for detecting and monitoring selectively logged forests in the Amazon , 2000 .

[90]  J. Franklin,et al.  Coniferous Forest Classification and Inventory Using Landsat and Digital Terrain Data , 1986, IEEE Transactions on Geoscience and Remote Sensing.

[91]  Michael A. Wulder,et al.  Mountain Pine Beetle Red-Attack Forest Damage Classification Using Stratified Landsat TM Data in British Columbia, Canada , 2003 .

[92]  Darrel L. Williams,et al.  Use of Remotely Sensed Data for Assessing Forest Stand Conditions in the Eastern United States , 1986, IEEE Transactions on Geoscience and Remote Sensing.

[93]  Mark Gahegan,et al.  The Integration of Scene Understanding within a Geographic Information System: A Prototype Approach for Agricultural Applications , 1999, Trans. GIS.

[94]  J. E. Dobson Commentary: a conceptual framework for integrating remote sensing, GIS, and geography , 1993 .

[95]  Curtis E. Woodcock,et al.  Uncertainty in Remote Sensing , 2006 .

[96]  Igor V. Florinsky,et al.  Combined analysis of digital terrain models and remotely sensed data in landscape investigations , 1998 .

[97]  Pol Coppin,et al.  Review ArticleDigital change detection methods in ecosystem monitoring: a review , 2004 .

[98]  Xiangming Xiao,et al.  Land-cover classification of China: Integrated analysis of AVHRR imagery and geophysical data , 2003 .

[99]  Janne Uuttera,et al.  Clear-cut Detection in Boreal Forest Aided by Remote Sensing , 2003 .

[100]  Damien Raclot,et al.  Updating land cover classification using a rule‐based decision system , 2005 .

[101]  M. Emch,et al.  Forest Cover Change in the Toledo District, Belize from 1975 to 1999: A Remote Sensing Approach* , 2005 .

[102]  R. Bailey Delineation of ecosystem regions , 1983 .

[103]  R. G. Pontius Statistical Methods to Partition Effects of Quantity and Location During Comparison of Categorical Maps at Multiple Resolutions , 2002 .

[104]  S. Ustin Remote sensing for natural resource management and environmental monitoring , 2004 .

[105]  Evaristo Ricchetti,et al.  Multispectral Satellite Image and Ancillary Data Integration for Geological Classification , 2000 .

[106]  S. Khorram,et al.  Modeling And Multitemporal Evaluation Of Forest Decline With Landsat Tm Digital Data , 1990 .

[107]  J. Conway,et al.  Comparison of the detection of deforested areas using the ERS-1 ATSR and the NOAA-11 AVHRR with reference to ERS-1 SAR data: a case study in the Brazilian Amazon , 1996 .

[108]  J. Townshend,et al.  Global land cover classi(cid:142) cation at 1 km spatial resolution using a classi(cid:142) cation tree approach , 2004 .

[109]  Janet Franklin,et al.  A Neural Network Method for Efficient Vegetation Mapping , 1999 .

[110]  J. Wiens,et al.  Issues and Perspectives in Landscape Ecology , 2005 .

[111]  Michael Batty,et al.  GIS, spatial analysis, and modeling , 2005 .

[112]  M. Wulder,et al.  Enhancing forest inventories with mountain pine beetle infestation information , 2005 .

[113]  R. Lawrence Rule-Based Classification Systems Using Classification and Regression Tree (CART) Analysis , 2001 .

[114]  G. Fischer,et al.  Land-use and land-cover change. Science/research plan , 1995 .

[115]  Danielle Marceau,et al.  Spatial pattern of coniferous and deciduous forest patches in an Eastern North America agricultural landscape: the influence of land use and physical attributes , 2001, Landscape Ecology.

[116]  D. Civco,et al.  Road Extraction Using SVM and Image Segmentation , 2004 .

[117]  P. A. Jacobberger-Jellison Detection of Post-Drought Environmental-Conditions in the Tombouctou Region , 1994 .

[118]  Gerald Joseph Pellegrini,et al.  Terrain shape classification of digital elevation models using eigenvectors and Fourier transforms , 1996 .

[119]  Richard Aspinall,et al.  A LAND-COVER DATA INFRASTRUCTURE FOR MEASUREMENT, MODELING, AND ANALYSIS OF LAND-COVER CHANGE DYNAMICS , 2002 .

[120]  M. Cochrane Linear mixture model classification of burned forests in the Eastern Amazon , 1998 .

[121]  Anatoly A. Saveliev,et al.  THE USE OF KOHONEN'S NEURAL NETS FOR THE DETECTION OF LAND-COVER TRANSITIONS , 2002 .

[122]  R. DeFries,et al.  Classification trees: an alternative to traditional land cover classifiers , 1996 .

[123]  Andrew K. Skidmore,et al.  A comparison of techniques for calculating gradient and aspect from a gridded digital elevation model , 1989, Int. J. Geogr. Inf. Sci..

[124]  David R. Foster,et al.  Land-Use History as Long-Term Broad-Scale Disturbance: Regional Forest Dynamics in Central New England , 1998, Ecosystems.

[125]  Jill Jäger,et al.  Challenges of a Changing Earth , 2002 .

[126]  E. Lambin,et al.  Prediction of the impact of logging activities on forest cover: a case-study in the east province of Cameroon. , 2001, Journal of environmental management.

[127]  Mark A. Friedl,et al.  Using prior probabilities in decision-tree classification of remotely sensed data , 2002 .

[128]  B. Reed,et al.  Satellite assessment of drought impact on native plant communities of southeastern New Mexico, U.S.A. , 1993 .

[129]  R. Nelson Detecting forest canopy change due to insect activity using Landsat MSS , 1983 .

[130]  Eric R. Ziegel,et al.  Generalized Linear Models , 2002, Technometrics.

[131]  Alan H. Strahler,et al.  Fuzzy Neural Network Classification of Global Land Cover from a 1° AVHRR Data Set , 1999 .

[132]  Geoff Smith,et al.  The characterisation and measurement of land cover change through remote sensing: problems in operational applications? , 2003 .

[133]  E. Lambin Monitoring forest degradation in tropical regions by remote sensing: some methodological issues , 1999 .

[134]  J. Rogan,et al.  Remote sensing for mapping and monitoring land-cover and land-use change—an introduction , 2004 .

[135]  P. Attiwill The disturbance of forest ecosystems: the ecological basis for conservative management , 1994 .

[136]  J. Franklin,et al.  Mapping Wildfire Burn Severity in Southern California Forests and Shrublands Using Enhanced Thematic Mapper Imagery , 2001 .

[137]  Emily Hoffhine Wilson,et al.  Satellite Change Detection of Forest Harvest Patterns on an Industrial Forest Landscape , 2003, Forest Science.

[138]  John Rogan,et al.  Mapping fire-induced vegetation depletion in the Peloncillo Mountains, Arizona and New Mexico , 2001 .

[139]  C. Woodcock,et al.  Monitoring land-use change in the Pearl River Delta using Landsat TM , 2002 .

[140]  D. Roberts,et al.  Sources of error in accuracy assessment of thematic land-cover maps in the Brazilian Amazon , 2004 .

[141]  I. Moore,et al.  Digital terrain modelling: A review of hydrological, geomorphological, and biological applications , 1991 .

[142]  K. Murphy,et al.  Overview of Machine Learning , 2022, International Journal of Advanced Research in Science, Communication and Technology.

[143]  Russell G. Congalton,et al.  Evaluating remotely sensed techniques for mapping riparian vegetation , 2002 .

[144]  B. Chapman,et al.  The coregistration, calibration, and interpretation of multiseason JERS-1 SAR data over South America , 2003 .

[145]  Joan E. Luther,et al.  Forecasting the susceptibility and vulnerability of balsam fir stands to insect defoliation with Landsat Thematic Mapper data , 1997 .

[146]  Niklaus E. Zimmermann,et al.  A new GLM-based method for mapping tree cover continuous fields using regional MODIS reflectance data , 2005 .

[147]  Eric J. Gustafson,et al.  Change detection with heterogeneous data using ecoregional stratification, statistical summaries and a land allocation algorithm , 2005 .

[148]  Manfred Ehlers,et al.  Automated analysis of ultra high resolution remote sensing data for biotope type mapping: new possibilities and challenges , 2003 .

[149]  E. Wheaton,et al.  Tomorrow’s Forests: Adapting to A Changing Climate , 2005 .

[150]  J. Townshend,et al.  Detection of land cover changes using MODIS 250 m data , 2002 .

[151]  S. Talbot,et al.  Vegetation mapping of Nowitna National Wildlife Reguge, Alaska using Landsat MSS digital data , 1986 .

[152]  S. Ekstrand Detection Of Moderate Damage On Norway Spruce Using Landsat TM And Digital Stand Data , 1990, IEEE Transactions on Geoscience and Remote Sensing.

[153]  Martin J. Wooster,et al.  Testing the potential of multi-spectral remote sensing for retrospectively estimating fire severity in African savannahs , 2005 .

[154]  M. Bauer,et al.  Digital change detection in forest ecosystems with remote sensing imagery , 1996 .

[155]  Curtis E. Woodcock,et al.  Multi-Attribute Vegetation Maps of Forest Service Lands in California Supporting Resource Management Decisions , 2000 .

[156]  T. Lin,et al.  The Lambertian assumption and Landsat data. , 1980 .

[157]  Ian Olthof,et al.  Mapping deciduous forest ice storm damage using Landsat and environmental data , 2004 .

[158]  David M. Carneggie,et al.  Vegetation and terrain mapping in Alaska using Landsat MSS and digital terrain data , 1986 .

[159]  Alan H. Strahler,et al.  The Use of Prior Probabilities in Maximum Likelihood Classification , 1980 .

[160]  S. Running,et al.  Remote Sensing of Forest Fire Severity and Vegetation Recovery , 1996 .

[161]  D. Roy Multi-temporal active-fire based burn scar detection algorithm , 1999 .

[162]  D. Bowman,et al.  Contemporary landscape burning patterns in the far North Kimberley region of north‐west Australia: human influences and environmental determinants , 2004 .

[163]  W. M. Ciesla,et al.  Interpretation of SPOT-1 color composites for mapping defoliation of hardwood forests by gypsy moth , 1989 .

[164]  J. T. Gray,et al.  The Relative Merits Of Spot HRV And Landsat TM Images For Forest Cover Change Detection In Forillon National Park, Quebec, Canada , 1990 .

[165]  Timothy A. Warner,et al.  Rule-based geobotanical classification of topographic, aeromagnetic, and remotely sensed vegetation community data , 1994 .

[166]  Andres Kuusk,et al.  Comparison of measured boreal forest characteristics with estimates from TM data and limited ancillary information using reflectance model inversion , 2002 .

[167]  Steven E. Franklin,et al.  Interpretation and Classification of Partially Harvested Forest Stands in the Fundy Model Forest Using Multitemporal Landsat TM Digital Data , 2000 .

[168]  J. O'Leary,et al.  Comparison of High Spatial Resolution Imagery for Efficient Generation of GIs Vegetation Layers , 2000 .

[169]  Sotaro Tanaka,et al.  Improvement of forest type classification by SPOT HRV with 20 m mesh DTM. , 1990 .

[170]  S. Sader,et al.  Detection of forest harvest type using multiple dates of Landsat TM imagery , 2002 .