23.4.12.10.1 Forest Change Evaluation, Bark Beetle, Pine Shoot Beetle, Other Insects

Chapter Contents (Back)
Forest Changes. Forest. Bark Beetle. For insects themselves:
See also Insects, Detection, Identification. Not trees:
See also Plant Disease Analysis, General Plant Diseasses.

Delalieux, S., Auwerkerken, A., Verstraeten, W., Somers, B., Valcke, R., Lhermitte, S., Keulemans, J., Coppin, P.,
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Ortiz, S., Breidenbach, J., Kändler, G.,
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Immitzer, M.[Markus], Atzberger, C.[Clement],
Early Detection of Bark Beetle Infestation in Norway Spruce (Picea abies, L.) using WorldView-2 Data,
PFG(2014), No. 5, 2014, pp. 351-367.
DOI Link 1411
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Liang, L.[Lu], Chen, Y.L.[Yan-Lei], Hawbaker, T.J.[Todd J.], Zhu, Z.L.[Zhi-Liang], Gong, P.[Peng],
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Näsi, R.[Roope], Honkavaara, E.[Eija], Lyytikäinen-Saarenmaa, P.[Päivi], Blomqvist, M.[Minna], Litkey, P.[Paula], Hakala, T.[Teemu], Viljanen, N.[Niko], Kantola, T.[Tuula], Tanhuanpää, T.[Topi], Holopainen, M.[Markus],
Using UAV-Based Photogrammetry and Hyperspectral Imaging for Mapping Bark Beetle Damage at Tree-Level,
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Anderson, T.[Taylor], Dragicevic, S.[Suzana],
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Murfitt, J.[Justin], He, Y.H.[Yu-Hong], Yang, J.[Jian], Mui, A.[Amy], de Mille, K.[Kevin],
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Hais, M.[Martin], Wild, J.[Jan], Berec, L.[Ludek], Bruna, J.[Josef], Kennedy, R.[Robert], Braaten, J.[Justin], Brož, Z.[Zdenek],
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RS(8), No. 8, 2016, pp. 687.
DOI Link 1609
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Anees, A.[Asim], Aryal, J.[Jagannath], O'Reilly, M.M.[Malgorzata M.], Gale, T.J.[Timothy J.], Wardlaw, T.[Tim],
A robust multi-kernel change detection framework for detecting leaf beetle defoliation using Landsat 7 ETM+ data,
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Elsevier DOI 1612
Change detection BibRef

Lin, Q.[Qinan], Huang, H.[Huaguo], Yu, L.F.[Lin-Feng], Wang, J.X.[Jing-Xu],
Detection of Shoot Beetle Stress on Yunnan Pine Forest Using a Coupled LIBERTY2-INFORM Simulation,
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Housman, I.W.[Ian W.], Chastain, R.A.[Robert A.], Finco, M.V.[Mark V.],
An Evaluation of Forest Health Insect and Disease Survey Data and Satellite-Based Remote Sensing Forest Change Detection Methods: Case Studies in the United States,
RS(10), No. 8, 2018, pp. xx-yy.
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Chávez, R.O.[Roberto O.], Rocco, R.[Ronald], Gutiérrez, Á.G.[Álvaro G.], Dörner, M.[Marcelo], Estay, S.A.[Sergio A.],
A Self-Calibrated Non-Parametric Time Series Analysis Approach for Assessing Insect Defoliation of Broad-Leaved Deciduous Nothofagus pumilio Forests,
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DOI Link 1902
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Abdullah, H.[Haidi], Darvishzadeh, R.[Roshanak], Skidmore, A.K.[Andrew K.], Heurich, M.[Marco],
Sensitivity of Landsat-8 OLI and TIRS Data to Foliar Properties of Early Stage Bark Beetle (Ips typographus, L.) Infestation,
RS(11), No. 4, 2019, pp. xx-yy.
DOI Link 1903
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Safonova, A.[Anastasiia], Tabik, S.[Siham], Alcaraz-Segura, D.[Domingo], Rubtsov, A.[Alexey], Maglinets, Y.[Yuriy], Herrera, F.[Francisco],
Detection of Fir Trees (Abies sibirica) Damaged by the Bark Beetle in Unmanned Aerial Vehicle Images with Deep Learning,
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DOI Link 1903
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Kloucek, T.[Tomáš], Komárek, J.[Jan], Surový, P.[Peter], Hrach, K.[Karel], Janata, P.[Premysl], Vašícek, B.[Bedrich],
The Use of UAV Mounted Sensors for Precise Detection of Bark Beetle Infestation,
RS(11), No. 13, 2019, pp. xx-yy.
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Lin, Q.[Qinan], Huang, H.G.[Hua-Guo], Wang, J.X.[Jing-Xu], Huang, K.[Kan], Liu, Y.Y.[Yang-Yang],
Detection of Pine Shoot Beetle (PSB) Stress on Pine Forests at Individual Tree Level using UAV-Based Hyperspectral Imagery and Lidar,
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Fernandez-Carrillo, A.[Angel], Patocka, Z.[Zdenek], Dobrovolný, L.[Lumír], Franco-Nieto, A.[Antonio], Revilla-Romero, B.[Beatriz],
Monitoring Bark Beetle Forest Damage in Central Europe. A Remote Sensing Approach Validated with Field Data,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link 2011
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Minarík, R.[Robert], Langhammer, J.[Jakub], Lendzioch, T.[Theodora],
Automatic Tree Crown Extraction from UAS Multispectral Imagery for the Detection of Bark Beetle Disturbance in Mixed Forests,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012
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Boucher, P.B.[Peter Brehm], Hancock, S.[Steven], Orwig, D.A.[David A], Duncanson, L.[Laura], Armston, J.[John], Tang, H.[Hao], Krause, K.[Keith], Cook, B.[Bruce], Paynter, I.[Ian], Li, Z.[Zhan], Elmes, A.[Arthur], Schaaf, C.[Crystal],
Detecting Change in Forest Structure with Simulated GEDI Lidar Waveforms: A Case Study of the Hemlock Woolly Adelgid (HWA; Adelges tsugae) Infestation,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link 2004
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Zhong, Y.[Yuan], Hu, B.X.[Bao-Xin], Hall, G.B.[G. Brent], Hoque, F.[Farah], Xu, W.[Wei], Gao, X.[Xin],
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Qin, J.[Jun], Wang, B.[Biao], Wu, Y.[Yanlan], Lu, Q.[Qi], Zhu, H.[Haochen],
Identifying Pine Wood Nematode Disease Using UAV Images and Deep Learning Algorithms,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
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Klimetzek, D.[Dietrich], Stancioiu, P.T.[Petru Tudor], Paraschiv, M.[Marius], Nita, M.D.[Mihai Daniel],
Ecological Monitoring with Spy Satellite Images: The Case of Red Wood Ants in Romania,
RS(13), No. 3, 2021, pp. xx-yy.
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Rodman, K.C.[Kyle C.], Andrus, R.A.[Robert A.], Butkiewicz, C.L.[Cori L.], Chapman, T.B.[Teresa B.], Gill, N.S.[Nathan S.], Harvey, B.J.[Brian J.], Kulakowski, D.[Dominik], Tutland, N.J.[Niko J.], Veblen, T.T.[Thomas T.], Hart, S.J.[Sarah J.],
Effects of Bark Beetle Outbreaks on Forest Landscape Pattern in the Southern Rocky Mountains, U.S.A.,
RS(13), No. 6, 2021, pp. xx-yy.
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Gdulová, K.[Katerina], Marešová, J.[Jana], Barták, V.[Vojtech], Szostak, M.[Marta], Cervenka, J.[Jaroslav], Moudrý, V.[Vítezslav],
Use of TanDEM-X and SRTM-C Data for Detection of Deforestation Caused by Bark Beetle in Central European Mountains,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108
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Migas-Mazur, R.[Robert], Kycko, M.[Marlena], Zwijacz-Kozica, T.[Tomasz], Zagajewski, B.[Bogdan],
Assessment of Sentinel-2 Images, Support Vector Machines and Change Detection Algorithms for Bark Beetle Outbreaks Mapping in the Tatra Mountains,
RS(13), No. 16, 2021, pp. xx-yy.
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Xia, L.[Lang], Zhang, R.[Ruirui], Chen, L.P.[Li-Ping], Li, L.L.[Long-Long], Yi, T.[Tongchuan], Wen, Y.[Yao], Ding, C.[Chenchen], Xie, C.[Chunchun],
Evaluation of Deep Learning Segmentation Models for Detection of Pine Wilt Disease in Unmanned Aerial Vehicle Images,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
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Pandey, P.[Piyush], Payn, K.G.[Kitt G.], Lu, Y.[Yuzhen], Heine, A.J.[Austin J.], Walker, T.D.[Trevor D.], Acosta, J.J.[Juan J.], Young, S.[Sierra],
Hyperspectral Imaging Combined with Machine Learning for the Detection of Fusiform Rust Disease Incidence in Loblolly Pine Seedlings,
RS(13), No. 18, 2021, pp. xx-yy.
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Faltan, V.[Vladimír], Petrovic, F.[František], Gábor, M.[Marián], Šagát, V.[Vladimír], Hruška, M.[Matej],
Mountain Landscape Dynamics after Large Wind and Bark Beetle Disasters and Subsequent Logging: Case Studies from the Carpathians,
RS(13), No. 19, 2021, pp. xx-yy.
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Yu, R.[Run], Luo, Y.Q.[You-Qing], Li, H.N.[Hao-Nan], Yang, L.Y.[Li-Yuan], Huang, H.G.[Hua-Guo], Yu, L.F.[Lin-Feng], Ren, L.[Lili],
Three-Dimensional Convolutional Neural Network Model for Early Detection of Pine Wilt Disease Using UAV-Based Hyperspectral Images,
RS(13), No. 20, 2021, pp. xx-yy.
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Honkavaara, E., Näsi, R., Oliveira, R., Viljanen, N., Suomalainen, J., Khoramshahi, E., Hakala, T., Nevalainen, O., Markelin, L., Vuorinen, M., Kankaanhuhta, V., Lyytikäinen-Saarenmaa, P., Haataja, L.,
Using Multitemporal Hyper- and Multispectral UAV Imaging for Detecting Bark Beetle Infestation on Norway Spruce,
ISPRS20(B3:429-434).
DOI Link 2012
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Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Deforestation, Degradation .


Last update:Nov 30, 2021 at 22:19:38