Mapping tropical dry forest succession using multiple criteria spectral mixture analysis
暂无分享,去创建一个
Benoit Rivard | Jilu Feng | Sen Cao | Qiuyan Yu | Arturo Sanchez-Azofeifa | Zhujun Gu | Z. Gu | B. Rivard | S. Cao | Qiuyan Yu | Jilu Feng | A. Sánchez-Azofeifa
[1] Jan Verbesselt,et al. Magnitude- and Shape-Related Feature Integration in Hyperspectral Mixture Analysis to Monitor Weeds in Citrus Orchards , 2009, IEEE Transactions on Geoscience and Remote Sensing.
[2] Tangao Hu,et al. Mapping Cropland Distributions Using a Hard and Soft Classification Model , 2012, IEEE Transactions on Geoscience and Remote Sensing.
[3] G. Powell,et al. Terrestrial Ecoregions of the World: A New Map of Life on Earth , 2001 .
[4] Pol Coppin,et al. Endmember variability in Spectral Mixture Analysis: A review , 2011 .
[5] Xavier Pons,et al. Effects of Topography on the Radiometry of CHRIS/PROBA Images of Successional Stages Within Tropical Dry Forests , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[6] Xuefei Hu,et al. Estimating impervious surfaces from medium spatial resolution imagery using the self-organizing map and multi-layer perceptron neural networks. , 2009 .
[7] D. Roberts,et al. A comparison of error metrics and constraints for multiple endmember spectral mixture analysis and spectral angle mapper , 2004 .
[8] Margaret Kalacska,et al. Leaf area index measurements in a tropical moist forest: A case study from Costa Rica , 2004 .
[9] F. Giorgi,et al. Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the reliability ensemble averaging (REA) method , 2002 .
[10] Margaret Kalacska,et al. Differences in leaf traits, leaf internal structure, and spectral reflectance between two communities of lianas and trees: Implications for remote sensing in tropical environments , 2009 .
[11] G. Sánchez‐Azofeifa,et al. Extent and conservation of tropical dry forests in the Americas , 2010 .
[12] F. Baret,et al. Leaf optical properties with explicit description of its biochemical composition: Direct and inverse problems , 1996 .
[13] Alan T. Murray,et al. Estimating impervious surface distribution by spectral mixture analysis , 2003 .
[14] Anil K. Bera,et al. Efficient tests for normality, homoscedasticity and serial independence of regression residuals , 1980 .
[15] A. Goetz,et al. Software for the derivation of scaled surface reflectances from AVIRIS data , 1992 .
[16] Xiaojun Yang,et al. Mapping vegetation in an urban area with stratified classification and multiple endmember spectral mixture analysis , 2013 .
[17] Margaret Kalacska,et al. Effects of Season and Successional Stage on Leaf Area Index and Spectral Vegetation Indices in Three Mesoamerican Tropical Dry Forests1 , 2005 .
[18] Benoit Rivard,et al. Delineation of secondary succession mechanisms for tropical dry forests using LiDAR , 2011 .
[19] N. Campbell,et al. Derivation and applications of probabilistic measures of class membership from the maximum-likelihood classification , 1992 .
[20] D. Roberts,et al. Mapping two Eucalyptus subgenera using multiple endmember spectral mixture analysis and continuum-removed imaging spectrometry data , 2011 .
[21] Stefan A. Schnitzer,et al. Density and diversity of lianas along a chronosequence in a central Panamanian lowland forest , 2000, Journal of Tropical Ecology.
[22] G. M. Foody,et al. Relating the land-cover composition of mixed pixels to artificial neural network classification outpout , 1996 .
[23] D. Roberts,et al. Endmember selection for multiple endmember spectral mixture analysis using endmember average RMSE , 2003 .
[24] Susan L. Ustin,et al. Evaluation of the potential of Hyperion for fire danger assessment by comparison to the Airborne Visible/Infrared Imaging Spectrometer , 2003, IEEE Trans. Geosci. Remote. Sens..
[25] Mathew R. Schwaller,et al. On the blending of the Landsat and MODIS surface reflectance: predicting daily Landsat surface reflectance , 2006, IEEE Transactions on Geoscience and Remote Sensing.
[26] Derek Rogge,et al. Integration of spatial–spectral information for the improved extraction of endmembers , 2007 .
[27] Giles M. Foody,et al. Latent Class Modeling for Site- and Non-Site-Specific Classification Accuracy Assessment Without Ground Data , 2012, IEEE Transactions on Geoscience and Remote Sensing.
[28] M. Kalacska,et al. Calibration and assessment of seasonal changes in leaf area index of a tropical dry forest in different stages of succession. , 2005, Tree physiology.
[29] S. Ustin,et al. Application of multiple endmember spectral mixture analysis (MESMA) to AVIRIS imagery for coastal salt marsh mapping: a case study in China Camp, CA, USA , 2005 .
[30] Paul J. Curran,et al. Spatial correlation in reflected radiation from the ground and its implications for sampling and mapping by ground-based radiometry , 1989 .
[31] Margaret E. Gardner,et al. Mapping Chaparral in the Santa Monica Mountains Using Multiple Endmember Spectral Mixture Models , 1998 .
[32] Terry Caelli,et al. Hyperspectral discrimination of tropical dry forest lianas and trees: Comparative data reduction approaches at the leaf and canopy levels , 2007 .
[33] Margaret Kalacska,et al. Estimating leaf area index from satellite imagery using Bayesian networks , 2005, IEEE Transactions on Geoscience and Remote Sensing.
[34] C. Deng,et al. A spatially adaptive spectral mixture analysis for mapping subpixel urban impervious surface distribution , 2013 .
[35] Simon J. Hook,et al. Synergies Between VSWIR and TIR Data for the Urban Environment: An Evaluation of the Potential for the Hyperspectral Infrared Imager (HyspIRI) , 2012 .
[36] E. Helmer,et al. The Landscape Ecology of Tropical Secondary Forest in Montane Costa Rica , 2000, Ecosystems.
[37] D. Janzen,et al. Secondary Forest Detection in a Neotropical Dry Forest Landscape Using Landsat 7 ETM+ and IKONOS Imagery 1 , 2005 .
[38] John A. Richards,et al. Remote Sensing Digital Image Analysis: An Introduction , 1999 .
[39] J. Woolley. Reflectance and transmittance of light by leaves. , 1971, Plant physiology.
[40] T. Ricketts,et al. Confronting a biome crisis: global disparities of habitat loss and protection , 2004 .
[41] G. F. Hughes,et al. On the mean accuracy of statistical pattern recognizers , 1968, IEEE Trans. Inf. Theory.
[42] T. Brandeis,et al. Mapping tropical dry forest height, foliage height profiles and disturbance type and age with a time series of cloud-cleared Landsat and ALI image mosaics to characterize avian habitat , 2010 .
[43] D. Roberts,et al. Sub-pixel mapping of urban land cover using multiple endmember spectral mixture analysis: Manaus, Brazil , 2007 .
[44] E. Bedini. Mapping lithology of the Sarfartoq carbonatite complex, southern West Greenland, using HyMap imaging spectrometer data , 2009 .
[45] S. Delalieux,et al. An automated waveband selection technique for optimized hyperspectral mixture analysis , 2010 .
[46] T. Caelli,et al. Ecological fingerprinting of ecosystem succession: Estimating secondary tropical dry forest structure and diversity using imaging spectroscopy , 2007 .
[47] G. Sánchez‐Azofeifa,et al. Costa Rica's Payment for Environmental Services Program: Intention, Implementation, and Impact , 2007, Conservation biology : the journal of the Society for Conservation Biology.
[48] D. Roberts,et al. Hierarchical Multiple Endmember Spectral Mixture Analysis (MESMA) of hyperspectral imagery for urban environments , 2009 .
[49] Margaret Kalacska,et al. Species composition, similarity and diversity in three successional stages of a seasonally dry tropical forest , 2004 .
[50] P. Curran. The semivariogram in remote sensing: An introduction , 1988 .
[51] Susan G. Letcher,et al. Lianas and self-supporting plants during tropical forest succession. , 2009 .
[52] Conghe Song,et al. Spectral mixture analysis for subpixel vegetation fractions in the urban environment: How to incorporate endmember variability? , 2005 .
[53] Alfred Stein,et al. Abundance Estimation of Spectrally Similar Minerals by Using Derivative Spectra in Simulated Annealing , 2006, IEEE Transactions on Geoscience and Remote Sensing.
[54] Eduardo S Brondízio,et al. Area and Age of Secondary Forests in Brazilian Amazonia 1978–2002: An Empirical Estimate , 2006, Ecosystems.
[55] D. Roberts,et al. Green vegetation, nonphotosynthetic vegetation, and soils in AVIRIS data , 1993 .
[56] G. Asner. Biophysical and Biochemical Sources of Variability in Canopy Reflectance , 1998 .
[57] David B. Lobell,et al. Subpixel canopy cover estimation of coniferous forests in Oregon using SWIR imaging spectrometry , 2001 .
[58] João Roberto dos Santos,et al. Use of MISR/Terra data to study intra- and inter-annual EVI variations in the dry season of tropical forest , 2012 .
[59] R. Dawes. Judgment under uncertainty: The robust beauty of improper linear models in decision making , 1979 .
[60] Åke Björck,et al. Numerical methods for least square problems , 1996 .
[61] Benoit Rivard,et al. Quantifying tropical dry forest succession in the Americas using CHRIS/PROBA , 2014 .
[62] D. Roberts,et al. Wildfire temperature and land cover modeling using hyperspectral data , 2006 .
[63] G. Arturo Sánchez-Azofeifa,et al. The effect of seasonal spectral variation on species classification in the Panamanian tropical forest , 2012 .
[64] G. Vieilledent,et al. Estimating deforestation in tropical humid and dry forests in Madagascar from 2000 to 2010 using multi-date Landsat satellite images and the random forests classifier , 2013 .
[65] E. Wilson,et al. Tropical Dry Forests The Most Endangered Major Tropical Ecosystem , 1988 .
[66] J. Gamon,et al. Functional regeneration and spectral reflectance of trees during succession in a highly diverse tropical dry forest ecosystem. , 2012, American journal of botany.
[67] Antonio J. Plaza,et al. Automated Extraction of Image-Based Endmember Bundles for Improved Spectral Unmixing , 2012, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[68] D. Roberts,et al. Mapping tree and shrub leaf area indices in an ombrotrophic peatland through multiple endmember spectral unmixing , 2007 .
[69] G. Sánchez‐Azofeifa,et al. Monitoring secondary tropical forests using space-borne data: Implications for Central America , 2003 .
[70] D. Lobell,et al. A Biogeophysical Approach for Automated SWIR Unmixing of Soils and Vegetation , 2000 .
[71] Benoit Rivard,et al. LIDAR remote sensing for secondary Tropical Dry Forest identification , 2012 .
[72] P. Curran,et al. Mapping the regional extent of tropical forest regeneration stages in the Brazilian Legal Amazon using NOAA AVHRR data , 2000 .