Tree species classification in tropical forests using visible to shortwave infrared WorldView-3 images and texture analysis
暂无分享,去创建一个
[1] O. Phillips,et al. Individual tree crown delineation in a highly diverse tropical forest using very high resolution satellite images , 2018, ISPRS Journal of Photogrammetry and Remote Sensing.
[2] P. Brancalion,et al. Genetic diversity of reintroduced tree populations in restoration plantations of the Brazilian Atlantic Forest , 2018 .
[3] Marco Heurich,et al. Tree species classification using plant functional traits from LiDAR and hyperspectral data , 2018, Int. J. Appl. Earth Obs. Geoinformation.
[4] Jean-Baptiste Féret,et al. Retrieving structural and chemical properties of individual tree crowns in a highly diverse tropical forest with 3D radiative transfer modeling and imaging spectroscopy , 2018, Remote Sensing of Environment.
[5] Andrew K. Skidmore,et al. Connecting infrared spectra with plant traits to identify species : abstract + powerpoint , 2018 .
[6] Weiqi Zhou,et al. Mapping vegetation functional types in urban areas with WorldView-2 imagery: integrating object-based classification with phenology. , 2018 .
[7] P. Couteron,et al. Disturbance Regimes Drive The Diversity of Regional Floristic Pools Across Guianan Rainforest Landscapes , 2018, Scientific Reports.
[8] Markus Immitzer,et al. Estimating stand density, biomass and tree species from very high resolution stereo-imagery- towards an all-in-one sensor for forestry applications? , 2017 .
[9] Stefan Hinz,et al. Tree species classification using within crown localization of waveform LiDAR attributes , 2017 .
[10] O. Mutanga,et al. Mapping leaf nitrogen and carbon concentrations of intact and fragmented indigenous forest ecosystems using empirical modeling techniques and WorldView-2 data , 2017 .
[11] Jingjing Zhou,et al. The Effects of GLCM parameters on LAI estimation using texture values from Quickbird Satellite Imagery , 2017, Scientific Reports.
[12] Onisimo Mutanga,et al. Multi-phenology WorldView-2 imagery improves remote sensing of savannah tree species , 2017, Int. J. Appl. Earth Obs. Geoinformation.
[13] M. Cho,et al. Improving the classification of six evergreen subtropical tree species with multi-season data from leaf spectra simulated to WorldView-2 and RapidEye , 2017 .
[14] Michael A. Lefsky,et al. Review of studies on tree species classification from remotely sensed data , 2016 .
[15] Susan L. Ustin,et al. Canopy structural attributes derived from AVIRIS imaging spectroscopy data in a mixed broadleaf/conifer forest , 2016 .
[16] Y. Shimabukuro,et al. Mapping tree species in tropical seasonal semi-deciduous forests with hyperspectral and multispectral data , 2016 .
[17] Huili Gong,et al. Object-Based Urban Tree Species Classification Using Bi-Temporal WorldView-2 and WorldView-3 Images , 2015, Remote. Sens..
[18] Galal Omer,et al. Performance of Support Vector Machines and Artificial Neural Network for Mapping Endangered Tree Species Using WorldView-2 Data in Dukuduku Forest, South Africa , 2015, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[19] Moses Azong Cho,et al. Assessing the utility WorldView-2 imagery for tree species mapping in South African subtropical humid forest and the conservation implications: Dukuduku forest patch as case study , 2015, Int. J. Appl. Earth Obs. Geoinformation.
[20] Lars T. Waser,et al. Evaluating the Potential of WorldView-2 Data to Classify Tree Species and Different Levels of Ash Mortality , 2014, Remote. Sens..
[21] William J. Emery,et al. The Importance of Physical Quantities for the Analysis of Multitemporal and Multiangular Optical Very High Spatial Resolution Images , 2014, IEEE Transactions on Geoscience and Remote Sensing.
[22] B. Manly,et al. Forest destructuring as revealed by the temporal dynamics of fundamental species - Case study of Santa Genebra Forest in Brazil , 2014 .
[23] Gregory Asner,et al. Tree Species Discrimination in Tropical Forests Using Airborne Imaging Spectroscopy , 2013, IEEE Transactions on Geoscience and Remote Sensing.
[24] Clement Atzberger,et al. Tree Species Classification with Random Forest Using Very High Spatial Resolution 8-Band WorldView-2 Satellite Data , 2012, Remote. Sens..
[25] P. Stevenson,et al. The Genus Cecropia: A Biological Clock to Estimate the Age of Recently Disturbed Areas in the Neotropics , 2012, PloS one.
[26] Baoxin Hu,et al. Individual Urban Tree Species Classification Using Very High Spatial Resolution Airborne Multi-Spectral Imagery Using Longitudinal Profiles , 2012, Remote. Sens..
[27] G. Arturo Sánchez-Azofeifa,et al. The effect of seasonal spectral variation on species classification in the Panamanian tropical forest , 2012 .
[28] Taghi M. Khoshgoftaar,et al. RUSBoost: A Hybrid Approach to Alleviating Class Imbalance , 2010, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.
[29] R. Kokaly,et al. Characterizing canopy biochemistry from imaging spectroscopy and its application to ecosystem studies , 2009 .
[30] Jean Paul Metzger,et al. The Brazilian Atlantic Forest: How much is left, and how is the remaining forest distributed? Implications for conservation , 2009 .
[31] Liangpei Zhang,et al. Evaluation of Morphological Texture Features for Mangrove Forest Mapping and Species Discrimination Using Multispectral IKONOS Imagery , 2009, IEEE Geoscience and Remote Sensing Letters.
[32] Bruno Aiazzi,et al. A Comparison Between Global and Context-Adaptive Pansharpening of Multispectral Images , 2009, IEEE Geoscience and Remote Sensing Letters.
[33] Manfred Ehlers. Multi-image Fusion in Remote Sensing: Spatial Enhancement vs. Spectral Characteristics Preservation , 2008, ISVC.
[34] Lorenzo Bruzzone,et al. Fusion of Hyperspectral and LIDAR Remote Sensing Data for Classification of Complex Forest Areas , 2008, IEEE Transactions on Geoscience and Remote Sensing.
[35] Nikos Koutsias,et al. Object-based classification using Quickbird imagery for delineating forest vegetation polygons in a Mediterranean test site , 2008 .
[36] Frans Bongers,et al. Architecture of 54 moist-forest tree species: traits, trade-offs, and functional groups. , 2006, Ecology.
[37] D. Roberts,et al. Hyperspectral discrimination of tropical rain forest tree species at leaf to crown scales , 2005 .
[38] Nathalie Japkowicz,et al. The class imbalance problem: A systematic study , 2002, Intell. Data Anal..
[39] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[40] John A. Richards,et al. Remote Sensing Digital Image Analysis: An Introduction , 1999 .
[41] Margaret E. Gardner,et al. Mapping Chaparral in the Santa Monica Mountains Using Multiple Endmember Spectral Mixture Models , 1998 .
[42] G. Asner. Biophysical and Biochemical Sources of Variability in Canopy Reflectance , 1998 .
[43] Vladimir Cherkassky,et al. Learning from Data: Concepts, Theory, and Methods , 1998 .
[44] D. Doak,et al. The Keystone-Species Concept in Ecology and ConservationManagement and policy must explicitly consider the complexity of interactions in natural systems , 1993 .
[45] H. P. Veloso,et al. Classificação da vegetação brasileira, adaptada a um sistema universal , 1991 .
[46] E Theodorsson-Norheim,et al. Kruskal-Wallis test: BASIC computer program to perform nonparametric one-way analysis of variance and multiple comparisons on ranks of several independent samples. , 1986, Computer methods and programs in biomedicine.
[47] R.M. Haralick,et al. Statistical and structural approaches to texture , 1979, Proceedings of the IEEE.
[48] P. Tomlinson,et al. Tropical Trees and Forests: An Architectural Analysis , 1978 .
[49] Robert M. Haralick,et al. Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..
[50] T. Kailath. The Divergence and Bhattacharyya Distance Measures in Signal Selection , 1967 .