24.4.13.6.3 Tree Species Determination, Forest Analysis

Chapter Contents (Back)
Forest. Tree Species.
See also Eucalypt Trees, Eucalyptus.

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.C.[Xing-Chang], Wang, C.K.[Chuan-Kuan],
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

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.L.[Xiao-Li],
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.[Gabriela Takahashi], dos Santos Arruda, M.[Mauro], Osco, L.P.[Lucas Prado], Junior, J.M.[José Marcato], Gonçalves, D.N.[Diogo Nunes], Imai, N.N.[Nilton Nobuhiro], Tommaselli, A.M.G.[Antonio Maria Garcia], Honkavaara, E.[Eija], Gonçalves, W.N.[Wesley Nunes],
A Novel Deep Learning Method to Identify Single Tree Species in UAV-Based Hyperspectral Images,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link 2004
BibRef

Host, T.K.[Trevor K.], Russell, M.B.[Matthew B.], Windmuller-Campione, M.A.[Marcella A.], Slesak, R.A.[Robert A.], Knight, J.F.[Joseph F.],
Ash Presence and Abundance Derived from Composite Landsat and Sentinel-2 Time Series and Lidar Surface Models in Minnesota, USA,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link 2004
BibRef

Scholl, V.M.[Victoria M.], Cattau, M.E.[Megan E.], Joseph, M.B.[Maxwell B.], Balch, J.K.[Jennifer K.],
Integrating National Ecological Observatory Network (NEON) Airborne Remote Sensing and In-Situ Data for Optimal Tree Species Classification,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Xu, K.J.[Kai-Jian], Tian, Q.J.[Qing-Jiu], Zhang, Z.Y.[Zhao-Ying], Yue, J.[Jibo], Chang, C.T.[Chung-Te],
Tree Species (Genera) Identification with GF-1 Time-Series in A Forested Landscape, Northeast China,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Legaard, K.[Kasey], Simons-Legaard, E.[Erin], Weiskittel, A.[Aaron],
Multi-Objective Support Vector Regression Reduces Systematic Error in Moderate Resolution Maps of Tree Species Abundance,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Viinikka, A.[Arto], Hurskainen, P.[Pekka], Keski-Saari, S.[Sarita], Kivinen, S.[Sonja], Tanhuanpää, T.[Topi], Mäyrä, J.[Janne], Poikolainen, L.[Laura], Vihervaara, P.[Petteri], Kumpula, T.[Timo],
Detecting European Aspen (Populus tremula L.) in Boreal Forests Using Airborne Hyperspectral and Airborne Laser Scanning Data,
RS(12), No. 16, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Deepak, M.[Maya], Keski-Saari, S.[Sarita], Fauch, L.[Laure], Granlund, L.[Lars], Oksanen, E.[Elina], Keinänen, M.[Markku],
Spectral Reflectance in Silver Birch Genotypes from Three Provenances in Finland,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Biswas, S.[Sumalika], Huang, Q.Y.[Qiong-Yu], Anand, A.[Anupam], Mon, M.S.[Myat Su], Arnold, F.E.[Franz-Eugen], Leimgruber, P.[Peter],
A Multi Sensor Approach to Forest Type Mapping for Advancing Monitoring of Sustainable Development Goals (SDG) in Myanmar,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Guo, Y.[Ying], Li, Z.Y.[Zeng-Yuan], Chen, E.[Erxue], Zhang, X.[Xu], Zhao, L.[Lei], Xu, E.[Enen], Hou, Y.[Yanan], Sun, R.[Rui],
An End-to-End Deep Fusion Model for Mapping Forests at Tree Species Levels with High Spatial Resolution Satellite Imagery,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Guo, Y.[Ying], Li, Z.Y.[Zeng-Yuan], Chen, E.[Erxue], Zhang, X.[Xu], Zhao, L.[Lei], Xu, E.[Enen], Hou, Y.[Yanan], Liu, L.Z.[Li-Zhi],
A Deep Fusion uNet for Mapping Forests at Tree Species Levels with Multi-Temporal High Spatial Resolution Satellite Imagery,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Riddell, A.P.[Audrey P.], Fitzgerald, S.A.[Stephen A.], Qi, C.[Chu], Strimbu, B.M.[Bogdan M.],
Classification Strategies for Unbalanced Binary Maps: Finding Ponderosa Pine (Pinus ponderosa) in the Willamette Valley,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Schiefer, F.[Felix], Kattenborn, T.[Teja], Frick, A.[Annett], Frey, J.[Julian], Schall, P.[Peter], Koch, B.[Barbara], Schmidtlein, S.[Sebastian],
Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks,
PandRS(170), 2020, pp. 205-215.
Elsevier DOI 2011
Deep learning, Forest inventory, Convolutional neural networks, Tree species classification, Unmanned aerial systems, Temperate forests BibRef

Abdollahnejad, A.[Azadeh], Panagiotidis, D.[Dimitrios],
Tree Species Classification and Health Status Assessment for a Mixed Broadleaf-Conifer Forest with UAS Multispectral Imaging,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Plakman, V.[Veerle], Janssen, T.[Thomas], Brouwer, N.[Nienke], Veraverbeke, S.[Sander],
Mapping Species at an Individual-Tree Scale in a Temperate Forest, Using Sentinel-2 Images, Airborne Laser Scanning Data, and Random Forest Classification,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Deur, M.[Martina], Gašparovic, M.[Mateo], Balenovic, I.[Ivan],
Tree Species Classification in Mixed Deciduous Forests Using Very High Spatial Resolution Satellite Imagery and Machine Learning Methods,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Deur, M.[Martina], Gašparovic, M.[Mateo], Balenovic, I.[Ivan],
An Evaluation of Pixel- and Object-Based Tree Species Classification in Mixed Deciduous Forests Using Pansharpened Very High Spatial Resolution Satellite Imagery,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Egli, S.[Sebastian], Höpke, M.[Martin],
CNN-Based Tree Species Classification Using High Resolution RGB Image Data from Automated UAV Observations,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Vila-Viçosa, C.[Carlos], Arenas-Castro, S.[Salvador], Marcos, B.[Bruno], Honrado, J.[João], García, C.[Cristina], Vázquez, F.M.[Francisco M.], Almeida, R.[Rubim], Gonçalves, J.[João],
Combining Satellite Remote Sensing and Climate Data in Species Distribution Models to Improve the Conservation of Iberian White Oaks (Quercus L.),
IJGI(9), No. 12, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Wan, H.M.[Hao-Ming], Tang, Y.W.[Yun-Wei], Jing, L.H.[Lin-Hai], Li, H.[Hui], Qiu, F.[Fang], Wu, W.J.[Wen-Jin],
Tree Species Classification of Forest Stands Using Multisource Remote Sensing Data,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Bhattarai, R.[Rajeev], Rahimzadeh-Bajgiran, P.[Parinaz], Weiskittel, A.[Aaron], Meneghini, A.[Aaron], MacLean, D.A.[David A.],
Spruce budworm tree host species distribution and abundance mapping using multi-temporal Sentinel-1 and Sentinel-2 satellite imagery,
PandRS(172), 2021, pp. 28-40.
Elsevier DOI 2101
Random forest, Sentinel-2, Synthetic aperture radar, Tree species BibRef

Michalowska, M.[Maja], Rapinski, J.[Jacek],
A Review of Tree Species Classification Based on Airborne LiDAR Data and Applied Classifiers,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Yan, S.J.[Shi-Jie], Jing, L.H.[Lin-Hai], Wang, H.[Huan],
A New Individual Tree Species Recognition Method Based on a Convolutional Neural Network and High-Spatial Resolution Remote Sensing Imagery,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Bohlin, J.[Jonas], Wallerman, J.[Jörgen], Fransson, J.E.S.[Johan E. S.],
Extraction of Spectral Information from Airborne 3D Data for Assessment of Tree Species Proportions,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Gyamfi-Ampadu, E.[Enoch], Gebreslasie, M.[Michael], Mendoza-Ponce, A.[Alma],
Evaluating Multi-Sensors Spectral and Spatial Resolutions for Tree Species Diversity Prediction,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Chen, L.[Long], Tian, X.M.[Xiao-Min], Chai, G.Q.[Guo-Qi], Zhang, X.L.[Xiao-Li], Chen, E.[Erxue],
A New CBAM-P-Net Model for Few-Shot Forest Species Classification Using Airborne Hyperspectral Images,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Harikumar, A.[Aravind], Paris, C.[Claudia], Bovolo, F.[Francesca], Bruzzone, L.[Lorenzo],
A Crown Quantization-Based Approach to Tree-Species Classification Using High-Density Airborne Laser Scanning Data,
GeoRS(59), No. 5, May 2021, pp. 4444-4453.
IEEE DOI 2104
Vegetation, Quantization (signal), Feature extraction, Forestry, Histograms, Laser radar, tree species BibRef

Pearse, G.D.[Grant D.], Watt, M.S.[Michael S.], Soewarto, J.[Julia], Tan, A.Y.S.[Alan Y. S.],
Deep Learning and Phenology Enhance Large-Scale Tree Species Classification in Aerial Imagery during a Biosecurity Response,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Kuzmin, A.[Anton], Korhonen, L.[Lauri], Kivinen, S.[Sonja], Hurskainen, P.[Pekka], Korpelainen, P.[Pasi], Tanhuanpää, T.[Topi], Maltamo, M.[Matti], Vihervaara, P.[Petteri], Kumpula, T.[Timo],
Detection of European Aspen (Populus tremula L.) Based on an Unmanned Aerial Vehicle Approach in Boreal Forests,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Wang, L.[Lin], Zhou, Y.Z.[Yu-Zhen], Hu, Q.[Qiao], Tang, Z.H.[Zheng-Hong], Ge, Y.F.[Yu-Feng], Smith, A.[Adam], Awada, T.[Tala], Shi, Y.[Yeyin],
Early Detection of Encroaching Woody Juniperus Virginiana and Its Classification in Multi-Species Forest Using UAS Imagery and Semantic Segmentation Algorithms,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Elbaz, S.[Shelly], Sheffer, E.[Efrat], Lensky, I.M.[Itamar M.], Levin, N.[Noam],
The Impacts of Spatial Resolution, Viewing Angle, and Spectral Vegetation Indices on the Quantification of Woody Mediterranean Species Seasonality Using Remote Sensing,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Aygunes, B.[Bulut], Cinbis, R.G.[Ramazan Gokberk], Aksoy, S.[Selim],
Weakly supervised instance attention for multisource fine-grained object recognition with an application to tree species classification,
PandRS(176), 2021, pp. 262-274.
Elsevier DOI 2106
Multisource classification, Fine-grained object recognition, Weakly supervised learning, Deep learning BibRef

Madonsela, S.[Sabelo], Cho, M.A.[Moses A.], Ramoelo, A.[Abel], Mutanga, O.[Onisimo],
Investigating the Relationship between Tree Species Diversity and Landsat-8 Spectral Heterogeneity across Multiple Phenological Stages,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Grybas, H.[Heather], Congalton, R.G.[Russell G.],
A Comparison of Multi-Temporal RGB and Multispectral UAS Imagery for Tree Species Classification in Heterogeneous New Hampshire Forests,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Tatum, J.[Julia], Wallin, D.[David],
Using Discrete-Point LiDAR to Classify Tree Species in the Riparian Pacific Northwest, USA,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Xu, K.J.[Kai-Jian], Zhang, Z.Y.[Zhao-Ying], Yu, W.[Wanwan], Zhao, P.[Ping], Yue, J.[Jibo], Deng, Y.P.[Ya-Ping], Geng, J.[Jun],
How Spatial Resolution Affects Forest Phenology and Tree-Species Classification Based on Satellite and Up-Scaled Time-Series Images,
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DOI Link 2107
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Noumonvi, K.D.[Koffi Dodji], Oblišar, G.[Gal], Žust, A.[Ana], Vilhar, U.[Urša],
Empirical Approach for Modelling Tree Phenology in Mixed Forests Using Remote Sensing,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108
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La Rosa, L.E.C.[Laura Elena Cué], Sothe, C.[Camile], Feitosa, R.Q.[Raul Queiroz], de-Almeida, C.M.[Cláudia Maria], Schimalski, M.B.[Marcos Benedito], Oliveira, D.A.B.[Dário Augusto Borges],
Multi-task fully convolutional network for tree species mapping in dense forests using small training hyperspectral data,
PandRS(179), 2021, pp. 35-49.
Elsevier DOI 2108
Semantic segmentation, Tree species identification, Multi-task learning, Fully convolutional network, Sparse annotations BibRef

Udali, A.[Alberto], Lingua, E.[Emanuele], Persson, H.J.[Henrik J.],
Assessing Forest Type and Tree Species Classification Using Sentinel-1 C-Band SAR Data in Southern Sweden,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
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Rodriguez, R.[Roberto], Perroy, R.L.[Ryan L.], Leary, J.[James], Jenkins, D.[Daniel], Panoff, M.[Max], Mandel, T.[Travis], Perez, P.[Patricia],
Comparing Interpretation of High-Resolution Aerial Imagery by Humans and Artificial Intelligence to Detect an Invasive Tree Species,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
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Marzialetti, F.[Flavio], Frate, L.[Ludovico], de Simone, W.[Walter], Frattaroli, A.R.[Anna Rita], Acosta, A.T.R.[Alicia Teresa Rosario], Carranza, M.L.[Maria Laura],
Unmanned Aerial Vehicle (UAV)-Based Mapping of Acacia saligna Invasion in the Mediterranean Coast,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Tamburlin, D.[Daniel], Torresani, M.[Michele], Tomelleri, E.[Enrico], Tonon, G.[Giustino], Rocchini, D.[Duccio],
Testing the Height Variation Hypothesis with the R rasterdiv Package for Tree Species Diversity Estimation,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Waser, L.T.[Lars T.], Rüetschi, M.[Marius], Psomas, A.[Achilleas], Small, D.[David], Rehush, N.[Nataliia],
Mapping dominant leaf type based on combined Sentinel-1/-2 data: Challenges for mountainous countries,
PandRS(180), 2021, pp. 209-226.
Elsevier DOI 2109
Broadleaved, Coniferous, Deep learning, Forestry practice, Random forest, Wall-to-wall, National forest inventory BibRef

Hologa, R.[Rafael], Scheffczyk, K.[Konstantin], Dreiser, C.[Christoph], Gärtner, S.[Stefanie],
Tree Species Classification in a Temperate Mixed Mountain Forest Landscape Using Random Forest and Multiple Datasets,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Malcolm, J.R.[Jay R.], Brousseau, B.[Braiden], Jones, T.[Trevor], Thomas, S.C.[Sean C.],
Use of Sentinel-2 Data to Improve Multivariate Tree Species Composition in a Forest Resource Inventory,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Yang, R.R.[Ran-Ran], Wang, L.[Lei], Tian, Q.J.[Qing-Jiu], Xu, N.Z.[Nian-Zxu], Yang, Y.J.[Yan-Jun],
Estimation of the Conifer-Broadleaf Ratio in Mixed Forests Based on Time-Series Data,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
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Chen, J.C.[Jian-Chang], Chen, Y.M.[Yi-Ming], Liu, Z.J.[Zheng-Jun],
Classification of Typical Tree Species in Laser Point Cloud Based on Deep Learning,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
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Räty, J.[Janne], Varvia, P.[Petri], Korhonen, L.[Lauri], Savolainen, P.[Pekka], Maltamo, M.[Matti], Packalen, P.[Petteri],
A Comparison of Linear-Mode and Single-Photon Airborne LiDAR in Species-Specific Forest Inventories,
GeoRS(60), 2022, pp. 1-14.
IEEE DOI 2112
Laser radar, Forestry, Vegetation, Photonics, Vegetation mapping, Measurement by laser beam, Green products, photon-counting LiDAR BibRef

Roth, B.D.[Benjamin D.], Saunders, M.G.[M. Grady], Bachmann, C.M.[Charles M.], van Aardt, J.[Jan],
Leaf Bidirectional Transmittance Distribution Function Estimates and Models for Select Deciduous Tree Species,
GeoRS(60), 2022, pp. 1-14.
IEEE DOI 2112
Remote sensing, Scattering, Wavelength measurement, Vegetation, Lighting, Data models, Goniometers, spectroradiometer BibRef

Li, Z.P.[Zhi-Peng], Ding, J.[Jie], Zhang, H.[Heyu], Feng, Y.M.[Yi-Ming],
Classifying Individual Shrub Species in UAV Images: A Case Study of the Gobi Region of Northwest China,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Jackson, C.M.[Colbert M.], Adam, E.[Elhadi],
Machine Learning Classification of Endangered Tree Species in a Tropical Submontane Forest Using WorldView-2 Multispectral Satellite Imagery and Imbalanced Dataset,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Zhang, X.Y.[Xin-Yu], Yuan, Y.X.[Ya-Xin], Zhu, Z.[Zequn], Ma, Q.S.[Qing-Shan], Yu, H.Y.[Hong-Yan], Li, M.[Meng], Ma, J.H.[Jian-Hai], Yi, S.H.[Shu-Hua], He, X.Z.[Xiong-Zhao], Sun, Y.[Yi],
Predicting the Distribution of Oxytropis ochrocephala Bunge in the Source Region of the Yellow River (China) Based on UAV Sampling Data and Species Distribution Model,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
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Finn, A.[Anthony], Kumar, P.[Pankaj], Peters, S.[Stefan], O'Hehir, J.[Jim],
Unsupervised spectral-spatial processing of drone imagery for identification of pine seedlings,
PandRS(183), 2022, pp. 363-388.
Elsevier DOI 2201
UAV, Seedling identification, Forest establishment, Object detection, Unsupervised learning BibRef

Carbonell-Rivera, J.P.[Juan Pedro], Torralba, J.[Jesús], Estornell, J.[Javier], Ruiz, L.Á.[Luis Ángel], Crespo-Peremarch, P.[Pablo],
Classification of Mediterranean Shrub Species from UAV Point Clouds,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
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Rana, P.[Parvez], St-Onge, B.[Benoit], Prieur, J.F.[Jean-François], Cristina Budei, B.[Brindusa], Tolvanen, A.[Anne], Tokola, T.[Timo],
Effect of feature standardization on reducing the requirements of field samples for individual tree species classification using ALS data,
PandRS(184), 2022, pp. 189-202.
Elsevier DOI 2202
LiDAR, Model transferability, Species classification, Multispectral, Forestry, Remote sensing BibRef

Ling, Y.X.[Yu-Xiang], Teng, S.[Shiwen], Liu, C.[Chao], Dash, J.[Jadunandan], Morris, H.[Harry], Pastor-Guzman, J.[Julio],
Assessing the Accuracy of Forest Phenological Extraction from Sentinel-1 C-Band Backscatter Measurements in Deciduous and Coniferous Forests,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
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Lu, T.T.[Ting-Ting], Brandt, M.[Martin], Tong, X.Y.[Xiao-Ye], Hiernaux, P.[Pierre], Leroux, L.[Louise], Ndao, B.[Babacar], Fensholt, R.[Rasmus],
Mapping the Abundance of Multipurpose Agroforestry Faidherbia albida Trees in Senegal,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Rusnák, T.[Tomáš], Halabuk, A.[Andrej], Halada, L.[Luboš], Hilbert, H.[Hubert], Gerhátová, K.[Katarína],
Detection of Invasive Black Locust (Robinia pseudoacacia) in Small Woody Features Using Spatiotemporal Compositing of Sentinel-2 Data,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
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Perles-Garcia, M.D.[Maria D.], Kunz, M.[Matthias], Fichtner, A.[Andreas], Meyer, N.[Nora], Härdtle, W.[Werner], von Oheimb, G.[Goddert],
Neighbourhood Species Richness Reduces Crown Asymmetry of Subtropical Trees in Sloping Terrain,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Yang, R.C.[Rong-Chao], Kan, J.M.[Jiang-Ming],
Classification of Tree Species in Different Seasons and Regions Based on Leaf Hyperspectral Images,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
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Jolly, B.[Ben], Dymond, J.R.[John R.], Shepherd, J.D.[James D.], Greene, T.[Terry], Schindler, J.[Jan],
Detection of Southern Beech Heavy Flowering Using Sentinel-2 Imagery,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
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Onishi, M.[Masanori], Watanabe, S.[Shuntaro], Nakashima, T.[Tadashi], Ise, T.[Takeshi],
Practicality and Robustness of Tree Species Identification Using UAV RGB Image and Deep Learning in Temperate Forest in Japan,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
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Olariu, H.G.[Horia G.], Malambo, L.[Lonesome], Popescu, S.C.[Sorin C.], Virgil, C.[Clifton], Wilcox, B.P.[Bradford P.],
Woody Plant Encroachment: Evaluating Methodologies for Semiarid Woody Species Classification from Drone Images,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
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Hoffmann, J.[Janik], Muro, J.[Javier], Dubovyk, O.[Olena],
Predicting Species and Structural Diversity of Temperate Forests with Satellite Remote Sensing and Deep Learning,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
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Cetin, Z.[Zehra], Yastikli, N.[Naci],
The Use of Machine Learning Algorithms in Urban Tree Species Classification,
IJGI(11), No. 4, 2022, pp. xx-yy.
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Lechner, M.[Michael], Dostálová, A.[Alena], Hollaus, M.[Markus], Atzberger, C.[Clement], Immitzer, M.[Markus],
Combination of Sentinel-1 and Sentinel-2 Data for Tree Species Classification in a Central European Biosphere Reserve,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
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Choi, K.[Kwanghun], Lim, W.[Wontaek], Chang, B.[Byungwoo], Jeong, J.[Jinah], Kim, I.[Inyoo], Park, C.R.[Chan-Ryul], Ko, D.W.W.[Dong-Wook W.],
An automatic approach for tree species detection and profile estimation of urban street trees using deep learning and Google street view images,
PandRS(190), 2022, pp. 165-180.
Elsevier DOI 2208
Deep learning, Innovation, Sustainable forest management, Monitoring and data collection BibRef

Li, Y.[Yingbo], Chai, G.Q.[Guo-Qi], Wang, Y.T.[Yue-Ting], Lei, L.T.[Ling-Ting], Zhang, X.L.[Xiao-Li],
ACE R-CNN: An Attention Complementary and Edge Detection-Based Instance Segmentation Algorithm for Individual Tree Species Identification Using UAV RGB Images and LiDAR Data,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
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Rösch, M.[Moritz], Sonnenschein, R.[Ruth], Buchelt, S.[Sebastian], Ullmann, T.[Tobias],
Comparing PlanetScope and Sentinel-2 Imagery for Mapping Mountain Pines in the Sarntal Alps, Italy,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
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Welle, T.[Torsten], Aschenbrenner, L.[Lukas], Kuonath, K.[Kevin], Kirmaier, S.[Stefan], Franke, J.[Jonas],
Mapping Dominant Tree Species of German Forests,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
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Hartley, R.J.L.[Robin J. L.], Jayathunga, S.[Sadeepa], Massam, P.D.[Peter D.], de Silva, D.[Dilshan], Estarija, H.J.[Honey Jane], Davidson, S.J.[Sam J.], Wuraola, A.[Adedamola], Pearse, G.D.[Grant D.],
Assessing the Potential of Backpack-Mounted Mobile Laser Scanning Systems for Tree Phenotyping,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
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Gara, T.W.[Tawanda W.], Rahimzadeh-Bajgiran, P.[Parinaz], Weiskittel, A.[Aaron],
Determination of foliar traits in an ecologically distinct conifer species in Maine using Sentinel-2 imagery and site variables: Assessing the effect of leaf trait expression and upscaling approach on prediction accuracy,
PandRS(193), 2022, pp. 150-163.
Elsevier DOI 2210
Leaf traits, Content, Concentration, Scaling, Sentinel-2, Site variables BibRef

Sivanandam, P.[Poornima], Lucieer, A.[Arko],
Tree Detection and Species Classification in a Mixed Species Forest Using Unoccupied Aircraft System (UAS) RGB and Multispectral Imagery,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Chen, W.H.[Wei-Hua], Pan, J.[Jie], Sun, Y.L.[Yu-Lin],
Tree Species Classification Based on Fusion Images by GF-5 and Sentinel-2A,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
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Lei, Z.L.[Zhong-Lu], Li, H.[Hui], Zhao, J.[Jie], Jing, L.H.[Lin-Hai], Tang, Y.W.[Yun-Wei], Wang, H.K.[Hong-Kun],
Individual Tree Species Classification Based on a Hierarchical Convolutional Neural Network and Multitemporal Google Earth Images,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
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Lombardi, E.[Erica], Rodríguez-Puerta, F.[Francisco], Santini, F.[Filippo], Chambel, M.R.[Maria Regina], Climent, J.[José], Resco-de Dios, V.[Víctor], Voltas, J.[Jordi],
UAV-LiDAR and RGB Imagery Reveal Large Intraspecific Variation in Tree-Level Morphometric Traits across Different Pine Species Evaluated in Common Gardens,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
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Zhang, Y.[Yicen], Wang, J.J.[Jun-Jie], Wu, Z.F.[Zhi-Feng], Lian, J.[Juyu], Ye, W.[Wanhui], Yu, F.Y.[Fang-Yuan],
Tree Species Classification Using Plant Functional Traits and Leaf Spectral Properties along the Vertical Canopy Position,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
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Mielczarek, D.[Dominik], Sikorski, P.[Piotr], Archicinski, P.[Piotr], Ciezkowski, W.[Wojciech], Zaniewska, E.[Ewa], Chormanski, J.[Jaroslaw],
The Use of an Airborne Laser Scanner for Rapid Identification of Invasive Tree Species Acer negundo in Riparian Forests,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
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Gong, Y.L.[Yu-Lin], Li, X.J.[Xue-Jian], Du, H.Q.[Hua-Qiang], Zhou, G.[Guomo], Mao, F.J.[Fang-Jie], Zhou, L.[Lv], Zhang, B.[Bo], Xuan, J.[Jie], Zhu, D.[Dien],
Tree Species Classifications of Urban Forests Using UAV-LiDAR Intensity Frequency Data,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
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Polyakova, A.[Alika], Mukharamova, S.[Svetlana], Yermolaev, O.[Oleg], Shaykhutdinova, G.[Galiya],
Automated Recognition of Tree Species Composition of Forest Communities Using Sentinel-2 Satellite Data,
RS(15), No. 2, 2023, pp. xx-yy.
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Kluczek, M.[Marcin], Zagajewski, B.[Bogdan], Zwijacz-Kozica, T.[Tomasz],
Mountain Tree Species Mapping Using Sentinel-2, PlanetScope, and Airborne HySpex Hyperspectral Imagery,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
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Sesnie, S.E.[Steven E.], Espinosa, C.I.[Carlos I.], Jara-Guerrero, A.K.[Andrea K.], Tapia-Armijos, M.F.[María F.],
Ensemble Machine Learning for Mapping Tree Species Alpha-Diversity Using Multi-Source Satellite Data in an Ecuadorian Seasonally Dry Forest,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

Zheng, P.F.[Peng-Fei], Fang, P.[Panfei], Wang, L.G.[Lei-Guang], Ou, G.L.[Guang-Long], Xu, W.[Weiheng], Dai, F.[Fei], Dai, Q.L.[Qin-Ling],
Synergism of Multi-Modal Data for Mapping Tree Species Distribution: A Case Study from a Mountainous Forest in Southwest China,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
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Wang, B.[Bin], Liu, J.Y.[Jian-Yang], Li, J.N.[Jia-Ning], Li, M.Z.[Ming-Ze],
UAV LiDAR and Hyperspectral Data Synergy for Tree Species Classification in the Maoershan Forest Farm Region,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
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Zhang, X.W.[Xian-Wei], Huang, W.J.[Wen-Jiang], Ye, H.[Huichun], Lu, L.[Longhui],
Study on the Identification of Habitat Suitability Areas for the Dominant Locust Species Dasyhippus Barbipes in Inner Mongolia,
RS(15), No. 6, 2023, pp. 1718.
DOI Link 2304
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Luo, H.J.[Hong-Jian], Ming, D.P.[Dong-Ping], Xu, L.[Lu], Ling, X.[Xiao],
Tree Species Classification Based on ASDER and MALSTM-FCN,
RS(15), No. 7, 2023, pp. 1723.
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Shi, W.[Weibo], Liao, X.H.[Xiao-Han], Sun, J.[Jia], Zhang, Z.J.[Zheng-Jian], Wang, D.L.[Dong-Liang], Wang, S.Q.[Shao-Qiang], Qu, W.Q.[Wen-Qiu], He, H.B.[Hong-Bo], Ye, H.[Huping], Yue, H.[Huanyin], Tagesson, T.[Torbern],
Optimizing Observation Plans for Identifying Faxon Fir (Abies fargesii var. Faxoniana) Using Monthly Unmanned Aerial Vehicle Imagery,
RS(15), No. 8, 2023, pp. 2205.
DOI Link 2305
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Lee, E.R.[Eu-Ru], Baek, W.K.[Won-Kyung], Jung, H.S.[Hyung-Sup],
Mapping Tree Species Using CNN from Bi-Seasonal High-Resolution Drone Optic and LiDAR Data,
RS(15), No. 8, 2023, pp. 2140.
DOI Link 2305
BibRef

Usman, M.[Muhammad], Ejaz, M.[Mahnoor], Nichol, J.E.[Janet E.], Farid, M.S.[Muhammad Shahid], Abbas, S.[Sawaid], Khan, M.H.[Muhammad Hassan],
A Comparison of Machine Learning Models for Mapping Tree Species Using WorldView-2 Imagery in the Agroforestry Landscape of West Africa,
IJGI(12), No. 4, 2023, pp. 142.
DOI Link 2305
BibRef

Chen, X.G.[Xiang-Gang], Shen, X.[Xin], Cao, L.[Lin],
Tree Species Classification in Subtropical Natural Forests Using High-Resolution UAV RGB and SuperView-1 Multispectral Imageries Based on Deep Learning Network Approaches: A Case Study within the Baima Snow Mountain National Nature Reserve, China,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef

Rina, S.[Su], Ying, H.[Hong], Shan, Y.[Yu], Du, W.[Wala], Liu, Y.[Yang], Li, R.[Rong], Deng, D.Z.[Ding-Zhu],
Application of Machine Learning to Tree Species Classification Using Active and Passive Remote Sensing: A Case Study of the Duraer Forestry Zone,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef

Huang, Y.K.[Ying-Kang], Wen, X.R.[Xiao-Rong], Gao, Y.[Yuanyun], Zhang, Y.L.[Yan-Li], Lin, G.Z.[Guo-Zhong],
Tree Species Classification in UAV Remote Sensing Images Based on Super-Resolution Reconstruction and Deep Learning,
RS(15), No. 11, 2023, pp. 2942.
DOI Link 2306
BibRef

Immitzer, M.[Markus], Atzberger, C.[Clement],
Tree Species Diversity Mapping: Success Stories and Possible Ways Forward,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link 2307
BibRef

Huang, Z.[Zehua], Zhong, L.[Liheng], Zhao, F.[Feng], Wu, J.[Jin], Tang, H.[Hao], Lv, Z.G.[Zhen-Gang], Xu, B.Y.[Bin-Yuan], Zhou, L.F.[Long-Fei], Sun, R.[Rui], Meng, R.[Ran],
A spectral-temporal constrained deep learning method for tree species mapping of plantation forests using time series Sentinel-2 imagery,
PandRS(204), 2023, pp. 397-420.
Elsevier DOI 2310
Tree species mapping, Key phenological stage, Transformer, Attention mechanism, Deep learning, Plantation forests BibRef

Yuan, X.G.[Xiao-Guang], Liang, Y.[Yiduo], Feng, W.[Wei], Li, J.H.[Jun-Hang], Ren, H.T.[Hong-Tao], Han, S.[Shuo], Liu, M.Q.[Meng-Qi],
Classification of Coniferous and Broad-Leaf Forests in China Based on High-Resolution Imagery and Local Samples in Google Earth Engine,
RS(15), No. 20, 2023, pp. 5026.
DOI Link 2310
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Yao, Z.Q.[Zong-Qi], Chai, G.Q.[Guo-Qi], Lei, L.T.[Ling-Ting], Jia, X.[Xiang], Zhang, X.L.[Xiao-Li],
Individual Tree Species Identification and Crown Parameters Extraction Based on Mask R-CNN: Assessing the Applicability of Unmanned Aerial Vehicle Optical Images,
RS(15), No. 21, 2023, pp. 5164.
DOI Link 2311
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Xiong, N.[Nina], Chen, H.L.[Hai-Long], Li, R.P.[Rui-Ping], Su, H.M.[Hui-Min], Dai, S.Z.[Shou-Zheng], Wang, J.[Jia],
A Method of Chestnut Forest Identification Based on Time Series and Key Phenology from Sentinel-2,
RS(15), No. 22, 2023, pp. 5374.
DOI Link 2311
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Hou, C.C.[Cheng-Chao], Liu, Z.J.[Zheng-Jun], Chen, Y.M.[Yi-Ming], Wang, S.[Shuo], Liu, A.[Aixia],
Tree Species Classification from Airborne Hyperspectral Images Using Spatial-Spectral Network,
RS(15), No. 24, 2023, pp. 5679.
DOI Link 2401
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Gaubert, T.[Thierry], Adeline, K.[Karine], Huesca, M.[Margarita], Ustin, S.[Susan], Briottet, X.[Xavier],
Estimation of Oak Leaf Functional Traits for California Woodland Savannas and Mixed Forests: Comparison between Statistical, Physical, and Hybrid Methods Using Spectroscopy,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link 2401
BibRef

Murray, B.A.[Brent A.], Coops, N.C.[Nicholas C.], Winiwarter, L.[Lukas], White, J.C.[Joanne C.], Dick, A.[Adam], Barbeito, I.[Ignacio], Ragab, A.[Ahmed],
Estimating tree species composition from airborne laser scanning data using point-based deep learning models,
PandRS(207), 2024, pp. 282-297.
Elsevier DOI Code:
WWW Link. 2401
Tree species proportions, PointAugment, DGCNN, Single-photon lidar, Forest resource inventory BibRef

Jia, W.[Wen], Pang, Y.[Yong], Tortini, R.[Riccardo],
The influence of BRDF effects and representativeness of training data on tree species classification using multi-flightline airborne hyperspectral imagery,
PandRS(207), 2024, pp. 245-263.
Elsevier DOI 2401
Tree species classification, BRDF effects, Airborne hyperspectral imagery, Training data selection, Random Forest BibRef

Liu, P.[Pan], Ren, C.Y.[Chun-Ying], Wang, Z.M.[Zong-Ming], Jia, M.M.[Ming-Ming], Yu, W.S.[Wen-Sen], Ren, H.X.[Hui-Xin], Xia, C.Z.[Chen-Zhen],
Evaluating the Potential of Sentinel-2 Time Series Imagery and Machine Learning for Tree Species Classification in a Mountainous Forest,
RS(16), No. 2, 2024, pp. 293.
DOI Link 2402
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Chaity, M.D.[Manisha Das], van Aardt, J.[Jan],
Exploring the Limits of Species Identification via a Convolutional Neural Network in a Complex Forest Scene through Simulated Imaging Spectroscopy,
RS(16), No. 3, 2024, pp. 498.
DOI Link 2402
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McGaughey, R.J.[Robert J.], Kruper, A.[Ally], Bobsin, C.R.[Courtney R.], Bormann, B.T.[Bernard T.],
Tree Species Classification Based on Upper Crown Morphology Captured by Uncrewed Aircraft System Lidar Data,
RS(16), No. 4, 2024, pp. 603.
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Ke, J.[Jing], Wang, F.W.[Fu-Wei], Li, D.[Dong], Ke, Y.[Yu], Li, B.Y.[Bu-Ying],
Research on Tree Classification Algorithm Based on Morphology and Leaf,
CVIDL20(227-231)
IEEE DOI 2102
feature extraction, forestry, image classification, learning (artificial intelligence), neural nets, Transfer Learning BibRef

Tusa, E., Monnet, J.M., Barré, J.B., Mura, M.D.[M. Dalla], Chanussot, J.,
Fusion of Lidar and Hyperspectral Data for Semantic Segmentation Of Forest Tree Species,
ISPRS20(B3:487-494).
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Ganschow, L., Thiele, T., Deckers, N., Reulke, R.,
Classification of Tree Species On The Basis of Tree Bark Texture,
HyperMLPA19(1855-1859).
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Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Orchards, Plantations, Trees as Crops .


Last update:Mar 16, 2024 at 20:36:19