Sugumaran, R.,
Pavuluri, M.K.,
Zerr, D.,
The use of high-resolution imagery for identification of urban climax
forest species using traditional and rule-based classification approach,
GeoRS(41), No. 9, September 2003, pp. 1933-1939.
IEEE Abstract.
0310
BibRef
Plourde, L.C.[Lucie C.],
Ollinger, S.V.[Scott V.],
Smith, M.L.[Marie-Louise],
Martin, M.E.[Mary E.],
Estimating Species Abundance in a Northern Temperate Forest Using
Spectral Mixture Analysis,
PhEngRS(73), No. 7, July 2007, pp. 829-840.
WWW Link.
0709
Spectral mixture analysis is used to classify sugar maple and
American beech abundance in a heterogeneous forest in the northeastern U.S.
BibRef
Xie, Z.X.[Zhi-Xiao],
Roberts, C.[Charles],
Johnson, B.[Brian],
Object-based target search using remotely sensed data: A case study in
detecting invasive exotic Australian Pine in south Florida,
PandRS(63), No. 6, November 2008, pp. 647-660.
Elsevier DOI
0811
Geographic image retrieval; Object based; Regression tree; Similarity
threshold; Invasive exotic species
BibRef
Hassan, Q.,
Bourque, C.,
Potential Species Distribution of Balsam Fir Based on the Integration
of Biophysical Variables Derived with Remote Sensing and Process-Based
Methods,
RS(1), No. 3, September 2009, pp. 393-407.
DOI Link
1203
BibRef
Evangelista, P.,
Stohlgren, T.,
Morisette, J.,
Kumar, S.,
Mapping Invasive Tamarisk (Tamarix): A Comparison of Single-Scene and
Time-Series Analyses of Remotely Sensed Data,
RS(1), No. 3, September 2009, pp. 519-533.
DOI Link
1203
BibRef
Martins, J.,
Oliveira, L.S.,
Nisgoski, S.,
Sabourin, R.,
A database for automatic classification of forest species,
MVA(24), No. 3, April 2013, pp. 567-578.
WWW Link.
1303
BibRef
Heiskanen, J.[Janne],
Rautiainen, M.[Miina],
Stenberg, P.[Pauline],
Mõttus, M.[Matti],
Vesanto, V.H.[Veli-Heikki],
Sensitivity of narrowband vegetation indices to boreal forest LAI,
reflectance seasonality and species composition,
PandRS(78), No. 1, April 2013, pp. 1-14.
Elsevier DOI
1304
Boreal forest; Hyperion; Hyperspectral; Imaging spectroscopy; Leaf area
index
BibRef
Peerbhay, K.Y.[Kabir Yunus],
Mutanga, O.[Onisimo],
Ismail, R.[Riyad],
Commercial tree species discrimination using airborne AISA Eagle
hyperspectral imagery and partial least squares discriminant analysis
(PLS-DA) in KwaZulu-Natal, South Africa,
PandRS(79), No. 1, May 2013, pp. 19-28.
Elsevier DOI
1305
Commercial forest species; Partial least squares discriminant analysis
(PLS-DA); Variable importance in the projection (VIP)
BibRef
Dalponte, M.[Michele],
Ørka, H.O.[Hans Ole],
Gobakken, T.[Terje],
Gianelle, D.[Damiano],
Næsset, E.[Erik],
Tree Species Classification in Boreal Forests With Hyperspectral Data,
GeoRS(51), No. 5, May 2013, pp. 2632-2645.
IEEE DOI
1305
BibRef
Sothe, C.[Camile],
Dalponte, M.[Michele],
de Almeida, C.M.[Cláudia Maria],
Schimalski, M.B.[Marcos Benedito],
Lima, C.L.[Carla Luciane],
Liesenberg, V.[Veraldo],
Miyoshi, G.T.[Gabriela Takahashi],
Tommaselli, A.M.G.[Antonio Maria Garcia],
Tree Species Classification in a Highly Diverse Subtropical Forest
Integrating UAV-Based Photogrammetric Point Cloud and Hyperspectral
Data,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link
1906
BibRef
Stavrakoudis, D.G.[Dimitris G.],
Dragozi, E.[Eleni],
Gitas, I.Z.[Ioannis Z.],
Karydas, C.G.[Christos G.],
Decision Fusion Based on Hyperspectral and Multispectral Satellite
Imagery for Accurate Forest Species Mapping,
RS(6), No. 8, 2014, pp. 6897-6928.
DOI Link
1410
BibRef
Al-Hamdan, M.[Mohammad],
Cruise, J.[James],
Rickman, D.[Douglas],
Quattrochi, D.[Dale],
Forest Stand Size-Species Models Using Spatial Analyses of Remotely
Sensed Data,
RS(6), No. 10, 2014, pp. 9802-9828.
DOI Link
1411
BibRef
Martins, J.G.,
Oliveira, L.S.,
Britto, Jr., A.S.,
Sabourin, R.,
Forest species recognition based on dynamic classifier selection and
dissimilarity feature vector representation,
MVA(26), No. 2-3, April 2015, pp. 279-293.
Springer DOI
1504
BibRef
Mureriwa, N.[Nyasha],
Adam, E.[Elhadi],
Sahu, A.[Anshuman],
Tesfamichael, S.[Solomon],
Examining the Spectral Separability of Prosopis Glandulosa from
Co-Existent Species Using Field Spectral Measurement and Guided
Regularized Random Forest,
RS(8), No. 2, 2016, pp. 144.
DOI Link
1603
Honey mesquite tree or shrub
BibRef
Omer, G.[Galal],
Mutanga, O.[Onisimo],
Abdel-Rahman, E.M.[Elfatih M.],
Adam, E.[Elhadi],
Empirical Prediction of Leaf Area Index (LAI) of Endangered Tree
Species in Intact and Fragmented Indigenous Forests Ecosystems Using
WorldView-2 Data and Two Robust Machine Learning Algorithms,
RS(8), No. 4, 2016, pp. 324.
DOI Link
1604
BibRef
Stagakis, S.[Stavros],
Vanikiotis, T.[Theofilos],
Sykioti, O.[Olga],
Estimating forest species abundance through linear unmixing of
CHRIS/PROBA imagery,
PandRS(119), No. 1, 2016, pp. 79-89.
Elsevier DOI
1610
Hyperspectral
BibRef
Mohajane, M.[Meriame],
Essahlaoui, A.[Ali],
Oudija, F.[Fatiha],
El Hafyani, M.[Mohammed],
Teodoro, A.C.[Ana Cláudia],
Mapping Forest Species in the Central Middle Atlas of Morocco (Azrou
Forest) through Remote Sensing Techniques,
IJGI(6), No. 9, 2017, pp. xx-yy.
DOI Link
1710
BibRef
Tuominen, S.[Sakari],
Näsi, R.[Roope],
Honkavaara, E.[Eija],
Balazs, A.[Andras],
Hakala, T.[Teemu],
Viljanen, N.[Niko],
Pölönen, I.[Ilkka],
Saari, H.[Heikki],
Ojanen, H.[Harri],
Assessment of Classifiers and Remote Sensing Features of
Hyperspectral Imagery and Stereo-Photogrammetric Point Clouds for
Recognition of Tree Species in a Forest Area of High Species
Diversity,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link
1806
BibRef
Raczko, E.[Edwin],
Zagajewski, B.[Bogdan],
Tree Species Classification of the UNESCO Man and the Biosphere
Karkonoski National Park (Poland) Using Artificial Neural Networks
and APEX Hyperspectral Images,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link
1808
BibRef
Wessel, M.[Mathias],
Brandmeier, M.[Melanie],
Tiede, D.[Dirk],
Evaluation of Different Machine Learning Algorithms for Scalable
Classification of Tree Types and Tree Species Based on Sentinel-2
Data,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link
1810
BibRef
Dabiri, Z.[Zahra],
Lang, S.[Stefan],
Comparison of Independent Component Analysis, Principal Component
Analysis, and Minimum Noise Fraction Transformation for Tree Species
Classification Using APEX Hyperspectral Imagery,
IJGI(7), No. 12, 2018, pp. xx-yy.
DOI Link
1901
BibRef
Lim, J.[Joongbin],
Kim, K.M.[Kyoung-Min],
Jin, R.[Ri],
Tree Species Classification Using Hyperion and Sentinel-2 Data with
Machine Learning in South Korea and China,
IJGI(8), No. 3, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Hoscilo, A.[Agata],
Lewandowska, A.[Aneta],
Mapping Forest Type and Tree Species on a Regional Scale Using
Multi-Temporal Sentinel-2 Data,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link
1905
BibRef
Liu, F.[Fan],
Wang, X.[Xingchang],
Wang, C.[Chuankuan],
Measuring Vegetation Phenology with Near-Surface Remote Sensing in a
Temperate Deciduous Forest: Effects of Sensor Type and Deployment,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link
1905
BibRef
Feng, X.X.[Xiao-Xue],
Li, P.J.[Pei-Jun],
A Tree Species Mapping Method from UAV Images over Urban Area Using
Similarity in Tree-Crown Object Histograms,
RS(11), No. 17, 2019, pp. xx-yy.
DOI Link
1909
BibRef
Fricker, G.A.[Geoffrey A.],
Ventura, J.D.[Jonathan D.],
Wolf, J.A.[Jeffrey A.],
North, M.P.[Malcolm P.],
Davis, F.W.[Frank W.],
Franklin, J.[Janet],
A Convolutional Neural Network Classifier Identifies Tree Species in
Mixed-Conifer Forest from Hyperspectral Imagery,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link
1910
BibRef
Fromm, M.[Michael],
Schubert, M.[Matthias],
Castilla, G.[Guillermo],
Linke, J.[Julia],
McDermid, G.[Greg],
Automated Detection of Conifer Seedlings in Drone Imagery Using
Convolutional Neural Networks,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Karasiak, N.[Nicolas],
Dejoux, J.F.[Jean-François],
Fauvel, M.[Mathieu],
Willm, J.[Jérôme],
Monteil, C.[Claude],
Sheeren, D.[David],
Statistical Stability and Spatial Instability in Mapping Forest Tree
Species by Comparing 9 Years of Satellite Image Time Series,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Immitzer, M.[Markus],
Neuwirth, M.[Martin],
Böck, S.[Sebastian],
Brenner, H.[Harald],
Vuolo, F.[Francesco],
Atzberger, C.[Clement],
Optimal Input Features for Tree Species Classification in Central
Europe Based on Multi-Temporal Sentinel-2 Data,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Amiri, N.[Nina],
Krzystek, P.[Peter],
Heurich, M.[Marco],
Skidmore, A.[Andrew],
Classification of Tree Species as Well as Standing Dead Trees Using
Triple Wavelength ALS in a Temperate Forest,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Osinska-Skotak, K.[Katarzyna],
Radecka, A.[Aleksandra],
Piórkowski, H.[Hubert],
Michalska-Hejduk, D.[Dorota],
Kopec, D.[Dominik],
Tokarska-Guzik, B.[Barbara],
Ostrowski, W.[Wojciech],
Kania, A.[Adam],
Niedzielko, J.[Jan],
Mapping Succession in Non-Forest Habitats by Means of Remote Sensing:
Is the Data Acquisition Time Critical for Species Discrimination?,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Knauer, U.[Uwe],
von Rekowski, C.S.[Cornelius Styp],
Stecklina, M.[Marianne],
Krokotsch, T.[Tilman],
Minh, T.P.[Tuan Pham],
Hauffe, V.[Viola],
Kilias, D.[David],
Ehrhardt, I.[Ina],
Sagischewski, H.[Herbert],
Chmara, S.[Sergej],
Seiffert, U.[Udo],
Tree Species Classification Based on Hybrid Ensembles of a
Convolutional Neural Network (CNN) and Random Forest Classifiers,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link
1912
BibRef
Meiforth, J.J.[Jane J.],
Buddenbaum, H.[Henning],
Hill, J.[Joachim],
Shepherd, J.[James],
Norton, D.A.[David A.],
Detection of New Zealand Kauri Trees with AISA Aerial Hyperspectral
Data for Use in Multispectral Monitoring,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link
1912
BibRef
Meiforth, J.J.[Jane J.],
Buddenbaum, H.[Henning],
Hill, J.[Joachim],
Shepherd, J.[James],
Monitoring of Canopy Stress Symptoms in New Zealand Kauri Trees
Analysed with AISA Hyperspectral Data,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Hastings, J.H.[Jack H.],
Ollinger, S.V.[Scott V.],
Ouimette, A.P.[Andrew P.],
Sanders-DeMott, R.[Rebecca],
Palace, M.W.[Michael W.],
Ducey, M.J.[Mark J.],
Sullivan, F.B.[Franklin B.],
Basler, D.[David],
Orwig, D.A.[David A.],
Tree Species Traits Determine the Success of LiDAR-Based Crown
Mapping in a Mixed Temperate Forest,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link
2001
BibRef
Hacker, P.W.[Paul W.],
Coops, N.C.[Nicholas C.],
Townsend, P.A.[Philip A.],
Wang, Z.H.[Zhi-Hui],
Retrieving Foliar Traits of Quercus garryana var. garryana across a
Modified Landscape Using Leaf Spectroscopy and LiDAR,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link
2001
BibRef
Miyoshi, G.T.[Gabriela Takahashi],
Imai, N.N.[Nilton Nobuhiro],
Tommaselli, A.M.G.[Antonio Maria Garcia],
de Moraes, M.V.A.[Marcus Vinícius Antunes],
Honkavaara, E.[Eija],
Evaluation of Hyperspectral Multitemporal Information to Improve Tree
Species Identification in the Highly Diverse Atlantic Forest,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link
2001
BibRef
Schneider, R.[Robert],
Calama, R.[Rafael],
Martin-Ducup, O.[Olivier],
Understanding Tree-to-Tree Variations in Stone Pine (Pinus pinea L.)
Cone Production Using Terrestrial Laser Scanner,
RS(12), No. 1, 2020, pp. xx-yy.
DOI Link
2001
BibRef
Dong, C.[Chao],
Zhao, G.X.[Geng-Xing],
Meng, Y.[Yan],
Li, B.H.[Bai-Hong],
Peng, B.[Bo],
The Effect of Topographic Correction on Forest Tree Species
Classification Accuracy,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Nezami, S.[Somayeh],
Khoramshahi, E.[Ehsan],
Nevalainen, O.[Olli],
Pölönen, I.[Ilkka],
Honkavaara, E.[Eija],
Tree Species Classification of Drone Hyperspectral and RGB Imagery
with Deep Learning Convolutional Neural Networks,
RS(12), No. 7, 2020, pp. xx-yy.
DOI Link
2004
BibRef
Cao, K.[Kaili],
Zhang, X.[Xiaoli],
An Improved Res-UNet Model for Tree Species Classification Using
Airborne High-Resolution Images,
RS(12), No. 7, 2020, pp. xx-yy.
DOI Link
2004
BibRef
Bourque, C.P.A.[Charles P.A.],
Gachon, P.[Philippe],
MacLellan, B.R.[Benjamin R.],
MacLellan, J.I.[James I.],
Projected Wind Impact on Abies balsamea (Balsam fir)-Dominated Stands
in New Brunswick (Canada) Based on Remote Sensing and Regional
Modelling of Climate and Tree Species Distribution,
RS(12), No. 7, 2020, pp. xx-yy.
DOI Link
2004
BibRef
Miyoshi, G.T.,
Imai, N.N.,
Tommaselli, A.M.G.,
Honkavaara, E.,
Comparison of Pixel and Region-based Approaches for Tree Species
Mapping in Atlantic Forest Using Hyperspectral Images Acquired By Uav,
HyperMLPA19(1875-1880).
DOI Link
1912
BibRef
Pap, M.,
Kiraly, S.,
Moljak, S.,
Investigating The Usability of UAV Obtained Multispectral Imagery In
Tree Species Segmentation,
Optical3D19(159-165).
DOI Link
1912
BibRef
Guan, H.,
Yu, Y.,
Yan, W.,
Li, D.,
Li, J.,
3d-cnn Based Tree Species Classification Using Mobile Lidar Data,
Laser19(989-993).
DOI Link
1912
BibRef
Briechle, S.,
Krzystek, P.,
Vosselman, G.,
Semantic Labeling of Als Point Clouds for Tree Species Mapping Using
The Deep Neural Network Pointnet++,
Laser19(951-955).
DOI Link
1912
BibRef
Natesan, S.,
Armenakis, C.,
Vepakomma, U.,
Resnet-based Tree Species Classification Using UAV Images,
UAV-g19(475-481).
DOI Link
1912
BibRef
Iseli, C.,
Lucieer, A.,
Tree Species Classification Based On 3d Spectral Point Clouds And
Orthomosaics Acquired By Snapshot Hyperspectral Uas Sensor,
UAV-g19(379-384).
DOI Link
1912
BibRef
Hese, S.,
Thiel, C.,
Henkel, A.,
Uav Based Multi Seasonal Deciduous Tree Species Analysis in The Hainich
National Park Using Multi Temporal and Point Cloud Curvature Features,
UAV-g19(363-370).
DOI Link
1912
BibRef
Mizoguchi, T.,
Ishii, A.,
Nakamura, H.,
Individual Tree Species Classification Based On Terrestrial Laser
Scanning Using Curvature Estimation and Convolutional Neural Network,
Laser19(1077-1082).
DOI Link
1912
BibRef
Pilarska, M.,
Ostrowski, W.,
Evaluating The Possibility of Tree Species Classification With
Dual-Wavelength ALS Data,
Laser19(1097-1103).
DOI Link
1912
BibRef
Brovkina, O.,
Hanuš, J.,
Zemek, F.,
Mochalov, V.,
Grigorieva, O.,
Pikla, M.,
Evaluating The Potential Of Satellite Hyperspectral Resurs-p Data For
Forest Species Classification,
ISPRS16(B1: 443-448).
DOI Link
1610
BibRef
Chiang, S.H.[Shou Hao],
Valdez, M.[Miguel],
Chen, C.F.[Chi-Farn],
Forest Tree Species Distribution Mapping Using Landsat Satellite
Imagery And Topographic Variables With The Maximum Entropy Method In
Mongolia,
ISPRS16(B8: 593-596).
DOI Link
1610
BibRef
Näsi, R.,
Honkavaara, E.,
Tuominen, S.,
Saari, H.,
Pölönen, I.,
Hakala, T.,
Viljanen, N.,
Soukkamäki, J.,
Näkki, I.,
Ojanen, H.,
Reinikainen, J.,
UAS Based Tree Species Identification Using The Novel FPI Based
Hyperspectral Cameras In Visible, NIR and SWIR Spectral Ranges,
ISPRS16(B1: 1143-1148).
DOI Link
1610
BibRef
Tu, C.H.,
Lo, N.J.,
Chang, W.I.,
Huang, K.Y.,
Evaluating The Novel Methods On Species Distribution Modeling In
Complex Forest,
ISPRS12(XXXIX-B2:77-82).
DOI Link
1209
BibRef
Cord, A.[Anna],
Klein, D.[Doris],
Dech, S.[Stefan],
The impact of inter-annual variability in remote sensing time series on
modeling tree species distributions,
MultiTemp11(181-184).
IEEE DOI
1109
BibRef
Paula-Filho, P.L.[Pedro Luiz],
Oliveira, L.S.[Luiz S.],
de Souza Britto Jr., A.[Alceu],
Sabourin, R.[Robert],
Forest Species Recognition Using Color-Based Features,
ICPR10(4178-4181).
IEEE DOI
1008
BibRef
Hajek, F.,
Object analysis of Ikonos XS and pan-sharpened imagery in comparison
for purpose of tree species estimation,
OBIA06(xx-yy).
PDF File.
0607
BibRef
Reulke, R.[Ralf],
Haala, N.[Norbert],
Tree Species Recognition with Fuzzy Texture Parameters,
IWCIA04(607-620).
Springer DOI
0505
BibRef
Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
Orchards, Plantations, Trees as Crops .