22.5.11.4.1 Tree Species Determination, Forest Analysis

Chapter Contents (Back)
Forest. Tree Species.

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

Ferreira, M.P.[Matheus Pinheiro], Wagner, F.H.[Fabien Hubert], Aragão, L.E.O.C.[Luiz E.O.C.], Shimabukuro, Y.E.[Yosio Edemir], de Souza Filho, C.R.[Carlos Roberto],
Tree species classification in tropical forests using visible to shortwave infrared WorldView-3 images and texture analysis,
PandRS(149), 2019, pp. 119-131.
Elsevier DOI 1903
Tropical forests, Biodiversity, Tree species discrimination, Very-high resolution, Canopy structure, GLCM 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


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 .


Last update:Jun 24, 2019 at 10:45:36