23.4.12.9 Forest Change Evaluation, Change Detection, Temporal Analysis

Chapter Contents (Back)
Forest Changes. Forest. Change Detection. Temporal Analysis. Specifically:
See also Forest Disturbance, Regeneration, Regrowth.
See also Deforestation, Degradation.
See also Forest Change Evaluation, Bark Beetle, Pine Shoot Beetle, Other Insects.
See also Forest Fire Evaluation, Wildfire Analysis, Brushfire Analysis, Fire Detection.
See also Storm Damage Assessment, Wind Throw.

Muchoney, D.M., Haack, B.N.,
Change Detection For Monitoring Forest Defoliation,
PhEngRS(60), No. 10, October 1994, pp. 1243-1251. BibRef 9410

Cohen, W., Fiorella, M., Gray, J., Helmer, E., and Anderson, K.,
An efficient and accurate method for mapping forest clearcuts in the Pacific northwest using Landsat imagery,
PhEngRS(64), 1998, pp. 293-300. BibRef 9800

Coppin, P., and Bauer, M.,
Digital change detection in forest ecosystems with remote sensing imagery,
Remote Sens. Rev.(13), 1996, pp. 207-234. BibRef 9600

Hame, T., Heiler, I., San Miguel-Ayanz, J.,
An Unsupervised Change Detection and Recognition System for Forestry,
JRS(19), No. 6, April 1998, pp. 1079-1099. 9805
BibRef

Song, C.H.[Cong-He], Woodcock, C.E.,
Monitoring forest succession with multitemporal landsat images: Factors of Uncertainty,
GeoRS(41), No. 11, November 2003, pp. 2557-2567.
IEEE Abstract. 0311
BibRef

Maselli, F., Moriondo, M., Chiesi, M., Chirici, G., Puletti, N., Barbati, A., Corona, P.,
Evaluating the Effects of Environmental Changes on the Gross Primary Production of Italian Forests,
RS(1), No. 4, December 2009, pp. 1108-1124.
DOI Link 1203
BibRef

Vastaranta, M., Kantola, T., Lyytikäinen-Saarenmaa, P., Holopainen, M., Kankare, V., Wulder, M., Hyyppä, J., Hyyppä, H.,
Area-Based Mapping of Defoliation of Scots Pine Stands Using Airborne Scanning LiDAR,
RS(5), No. 3, March 2013, pp. 1220-1234.
DOI Link 1304
BibRef

Battista, P.[Piero], Chiesi, M.[Marta], Rapi, B.[Bernardo], Romani, M.[Maurizio], Cantini, C.[Claudio], Giovannelli, A.[Alessio], Cocozza, C.[Claudia], Tognetti, R.[Roberto], Maselli, F.[Fabio],
Integration of Ground and Multi-Resolution Satellite Data for Predicting the Water Balance of a Mediterranean Two-Layer Agro-Ecosystem,
RS(8), No. 9, 2016, pp. 731.
DOI Link 1610
BibRef

Eva, H.[Hugh], Carboni, S.[Silvia], Achard, F.[Frederic], Stach, N.[Nicolas], Durieux, L.[Laurent], Faure, J.F.[Jean-Francois], Mollicone, D.[Danilo],
Monitoring forest areas from continental to territorial levels using a sample of medium spatial resolution satellite imagery,
PandRS(65), No. 2, March 2010, pp. 191-197.
Elsevier DOI 1003
Forestry; Change detection; Sampling; Landsat; SPOT BibRef

Eva, H., Achard, F., Beuchle, R., de Miranda, E., Carboni, S., Seliger, R., Vollmar, M., Holler, W., Oshiro, O., Barrena Arroyo, V., Gallego, J.,
Forest Cover Changes in Tropical South and Central America from 1990 to 2005 and Related Carbon Emissions and Removals,
RS(4), No. 5, May 2012, pp. 1369-1391.
DOI Link 1205
BibRef

Somers, B., Asner, G.,
Hyperspectral Time Series Analysis of Native and Invasive Species in Hawaiian Rainforests,
RS(4), No. 9, September 2012, pp. 2510-2529.
DOI Link 1210
BibRef

Adhikari, S., Southworth, J.,
Simulating Forest Cover Changes of Bannerghatta National Park Based on a CA-Markov Model: A Remote Sensing Approach,
RS(4), No. 10, October 2012, pp. 3215-3243.
DOI Link 1210
BibRef

Canavesi, V., Alvalá, R.,
Changes in Vegetation Cover in Reforested Areas in the State of São Paulo, Brazil and the Implication for Landslide Processes,
IJGI(1), No. 2, 2012, pp. 209-227.
DOI Link 1210
BibRef

Frolking, S., Hagen, S., Milliman, T., Palace, M., Shimbo, J.Z., Fahnestock, M.,
Detection of Large-Scale Forest Canopy Change in Pan-Tropical Humid Forests 2000-2009 With the SeaWinds Ku-Band Scatterometer,
GeoRS(50), No. 7, July 2012, pp. 2603-2617.
IEEE DOI 1208
BibRef

Bodart, C.[Catherine], Eva, H.[Hugh], Beuchle, R.[René], Raši, R.[Rastislav], Simonetti, D.[Dario], Stibig, H.J.[Hans-Jürgen], Brink, A.[Andreas], Lindquist, E.[Erik], Achard, F.[Frédéric],
Pre-processing of a sample of multi-scene and multi-date Landsat imagery used to monitor forest cover changes over the tropics,
PandRS(66), No. 5, September 2011, pp. 555-563.
Elsevier DOI 1110
Forestry; Calibration; Matching; Landsat; Global BibRef

Günthert, S.[Sebastian], Wieland, M.[Marc], Siegmund, A.[Alexander],
Change Detection Analysis for Assessing the Vulnerability and Protective Effect of Beach Forests in Case of the Tsunami 2004 in Thailand,
PFG(2011), No. 4, 2011, pp. 247-260.
WWW Link. 1211
BibRef

Frate, L., Carranza, M.,
Quantifying Landscape-Scale Patterns of Temperate Forests over Time by Means of Neutral Simulation Models,
IJGI(2), No. 1, 2013, pp. 94-109.
DOI Link 1303
BibRef

Giree, N., Stehman, S., Potapov, P., Hansen, M.,
A Sample-Based Forest Monitoring Strategy Using Landsat, AVHRR and MODIS Data to Estimate Gross Forest Cover Loss in Malaysia between 1990 and 2005,
RS(5), No. 4, April 2013, pp. 1842-1855.
DOI Link 1305
BibRef

Tian, J.J., Reinartz, P., d'Angelo, P., Ehlers, M.,
Region-Based Automatic Building and Forest Change Detection on Cartosat-1 Stereo Imagery,
PandRS(79), No. 1, May 2013, pp. 226-239.
Elsevier DOI 1305
Stereo imagery; Digital Surface Model (DSM); Change detection; Forest change; Industrial area change BibRef

d'Angelo, P., Kuschk, G., Reinartz, P.,
Evaluation of Skybox Video and Still Image products,
LandImaging14(95-99).
DOI Link 1411
BibRef

Tian, J.J.[Jiao-Jiao], Cui, S.Y.[Shi-Yong], Reinartz, P.,
Building Change Detection Based on Satellite Stereo Imagery and Digital Surface Models,
GeoRS(52), No. 1, January 2014, pp. 406-417.
IEEE DOI 1402
feature extraction BibRef

Mu, J., Cui, S., Reinartz, P.,
Building Detection Using Aerial Images and Digital Surface Models,
Hannover17(159-165).
DOI Link 1805
BibRef

Tian, J.J., Leitloff, J., Krauß, T., Reinartz, P.,
Region Based Forest Change Detection from CARTOSAT-1 Stereo Imagery,
HighRes11(xx-yy).
PDF File. 1106

See also Comparison of Two Fusion Based Building Change Detection Methods Using Satellite Stereo Imagery and DSMS. BibRef

Solberg, S.[Svein], Astrup, R.[Rasmus], Weydahl, D.J.[Dan J.],
Detection of Forest Clear-Cuts with Shuttle Radar Topography Mission (SRTM) and Tandem-X InSAR Data,
RS(5), No. 11, 2013, pp. 5449-5462.
DOI Link 1312
BibRef

Oumar, Z.[Zakariyyaa], Mutanga, O.[Onisimo],
Integrating environmental variables and WorldView-2 image data to improve the prediction and mapping of Thaumastocoris peregrinus (bronze bug) damage in plantation forests,
PandRS(87), No. 1, 2014, pp. 39-46.
Elsevier DOI 1402
Thaumastocoris peregrinus BibRef

Hamunyela, E.[Eliakim], Verbesselt, J.[Jan], Roerink, G.[Gerbert], Herold, M.[Martin],
Trends in Spring Phenology of Western European Deciduous Forests,
RS(5), No. 12, 2013, pp. 6159-6179.
DOI Link 1412
BibRef

Abdel-Rahman, E.M.[Elfatih M.], Mutanga, O.[Onisimo], Adam, E.[Elhadi], Ismail, R.[Riyad],
Detecting Sirex noctilio grey-attacked and lightning-struck pine trees using airborne hyperspectral data, random forest and support vector machines classifiers,
PandRS(88), No. 1, 2014, pp. 48-59.
Elsevier DOI 1402
Sirex grey stage BibRef

Wang, Q.[Qian], Zhang, L.F.[Li-Fu], Wu, T.X.[Tai-Xia], Cen, Y.[Yi], Huang, C.P.[Chang-Ping], Tong, Q.X.[Qing-Xi],
Evaluation of Multiple Spring Phenological Indicators of Yearly GPP and NEP at Three Canadian Forest Sites,
RS(6), No. 3, 2014, pp. 1991-2007.
DOI Link 1404
BibRef

Tian, J., Nielsen, A.A., Reinartz, P.,
Improving Change Detection in Forest Areas Based on Stereo Panchromatic Imagery Using Kernel MNF,
GeoRS(52), No. 11, November 2014, pp. 7130-7139.
IEEE DOI 1407
Accuracy BibRef

Song, X.P.[Xiao-Peng], Huang, C.Q.[Cheng-Quan], Sexton, J.O.[Joseph O.], Channan, S.[Saurabh], Townshend, J.R.[John R.],
Annual Detection of Forest Cover Loss Using Time Series Satellite Measurements of Percent Tree Cover,
RS(6), No. 9, 2014, pp. 8878-8903.
DOI Link 1410
BibRef

Zhu, X.L.[Xiao-Lin], Liu, D.[Desheng],
Accurate Mapping of Forest Types Using Dense Seasonal Landsat Time-Series,
PandRS(96), No. 1, 2014, pp. 1-11.
Elsevier DOI 1410
Forest types
See also Improving Forest Aboveground Biomass Estimation Using Seasonal Landsat NDVI Time-Series. BibRef

Frate, L.[Ludovico], Saura, S.[Santiago], Minotti, M.[Michele], Martino, P.D.[Paolo Di], Giancola, C.[Carmen], Carranza, M.L.[Maria Laura],
Quantifying Forest Spatial Pattern Trends at Multiple Extents: An Approach to Detect Significant Changes at Different Scales,
RS(6), No. 10, 2014, pp. 9298-9315.
DOI Link 1411
BibRef

Liu, J.[Jia], Rambal, S.[Serge], Mouillot, F.[Florent],
Soil Drought Anomalies in MODIS GPP of a Mediterranean Broadleaved Evergreen Forest,
RS(7), No. 1, 2015, pp. 1154-1180.
DOI Link 1502
BibRef

van Deventer, H., Cho, M.A., Mutanga, O., Ramoelo, A.,
Capability of models to predict leaf N and P across four seasons for six sub-tropical forest evergreen trees,
PandRS(101), No. 1, 2015, pp. 209-220.
Elsevier DOI 1503
Foliar N and P BibRef

Gao, T.[Tian], Zhu, J.J.[Jiao-Jun], Zheng, X.[Xiao], Shang, G.[Guiduo], Huang, L.Y.[Li-Yan], Wu, S.[Shangrong],
Mapping Spatial Distribution of Larch Plantations from Multi-Seasonal Landsat-8 OLI Imagery and Multi-Scale Textures Using Random Forests,
RS(7), No. 2, 2015, pp. 1702-1720.
DOI Link 1503
BibRef

Song, D.X.[Dan-Xia], Huang, C.Q.[Cheng-Quan], Sexton, J.O.[Joseph O.], Channan, S.[Saurabh], Feng, M.[Min], Townshend, J.R.[John R.],
Use of Landsat and Corona data for mapping forest cover change from the mid-1960s to 2000s: Case studies from the Eastern United States and Central Brazil,
PandRS(103), No. 1, 2015, pp. 81-92.
Elsevier DOI 1504
Corona BibRef

Lui, G.V.[Gillian V.], Coomes, D.A.[David A.],
A Comparison of Novel Optical Remote Sensing-Based Technologies for Forest-Cover/Change Monitoring,
RS(7), No. 3, 2015, pp. 2781-2807.
DOI Link 1504
BibRef

Lambert, J.[Jonas], Denux, J.P.[Jean-Philippe], Verbesselt, J.[Jan], Balent, G.[Gérard], Cheret, V.[Véronique],
Detecting Clear-Cuts and Decreases in Forest Vitality Using MODIS NDVI Time Series,
RS(7), No. 4, 2015, pp. 3588-3612.
DOI Link 1505
BibRef

Thonfeld, F.[Frank], Hecheltjen, A.[Antje], Menz, G.[Gunter],
Bi-temporal Change Detection, Change Trajectories and Time Series Analysis for Forest Monitoring,
PFG(2015), No. 2, 2015, pp. 129-141.
DOI Link 1506
BibRef

Shimada, M.[Masanobu], Itoh, T.[Takuya], Motooka, T.[Takeshi], Watanabe, M.[Manabu], Thapa, R.[Rajesh],
High-resolution satellite radar for mapping changes in global forest cover,
SPIE(Newsroom), June 5, 2015.
DOI Link 1507
Radar backscatter using L-band microwave frequencies from the Advanced Land Observing Satellite enables the generation of maps of global forest cover for 2007-2010. BibRef

Wang, H.[Hong], Zhao, Y.[Yu], Pu, R.L.[Rui-Liang], Zhang, Z.Z.[Zhen-Zhen],
Mapping Robinia Pseudoacacia Forest Health Conditions by Using Combined Spectral, Spatial, and Textural Information Extracted from IKONOS Imagery and Random Forest Classifier,
RS(7), No. 7, 2015, pp. 9020.
DOI Link 1506
BibRef

Duguay, Y.[Yannick], Bernier, M.[Monique], Lévesque, E.[Esther], Tremblay, B.[Benoit],
Potential of C and X Band SAR for Shrub Growth Monitoring in Sub-Arctic Environments,
RS(7), No. 7, 2015, pp. 9410.
DOI Link 1506
BibRef

Dutrieux, L.P.[Loïc Paul], Verbesselt, J.[Jan], Kooistra, L.[Lammert], Herold, M.[Martin],
Monitoring forest cover loss using multiple data streams, a case study of a tropical dry forest in Bolivia,
PandRS(107), No. 1, 2015, pp. 112-125.
Elsevier DOI 1508
Landsat BibRef

Walker, J.[Jessica], de Beurs, K.[Kirsten], Wynne, R.H.[Randolph H.],
Phenological Response of an Arizona Dryland Forest to Short-Term Climatic Extremes,
RS(7), No. 8, 2015, pp. 10832.
DOI Link 1509
BibRef

Dotzler, S.[Sandra], Hill, J.[Joachim], Buddenbaum, H.[Henning], Stoffels, J.[Johannes],
The Potential of EnMAP and Sentinel-2 Data for Detecting Drought Stress Phenomena in Deciduous Forest Communities,
RS(7), No. 10, 2015, pp. 14227.
DOI Link 1511
BibRef

Cao, S.[Sen], Yu, Q.[Qiuyan], Sanchez-Azofeifa, G.A.[G. Arturo], Feng, J.[Jilu], Rivard, B.[Benoit], Gu, Z.[Zhujun],
Mapping tropical dry forest succession using multiple criteria spectral mixture analysis,
PandRS(109), No. 1, 2015, pp. 17-29.
Elsevier DOI 1512
Secondary tropical dry forest BibRef

Tortini, R.[Riccardo], Mayer, A.L.[Audrey L.], Maianti, P.[Pieralberto],
Using an OBCD Approach and Landsat TM Data to Detect Harvesting on Nonindustrial Private Property in Upper Michigan,
RS(7), No. 6, 2015, pp. 7809.
DOI Link 1507
BibRef

Wang, X.Y.[Xiao-Yi], Huang, H.[Huabing], Gong, P.[Peng], Biging, G.S.[Gregory S.], Xin, Q.[Qinchuan], Chen, Y.[Yanlei], Yang, J.[Jun], Liu, C.[Caixia],
Quantifying Multi-Decadal Change of Planted Forest Cover Using Airborne LiDAR and Landsat Imagery,
RS(8), No. 1, 2016, pp. 62.
DOI Link 1602
BibRef

Coops, N.C.[Nicholas C.], Waring, R.H.[Richard H.], Plowright, A.[Andrew], Lee, J.[Joanna], Dilts, T.E.[Thomas E.],
Using Remotely-Sensed Land Cover and Distribution Modeling to Estimate Tree Species Migration in the Pacific Northwest Region of North America,
RS(8), No. 1, 2016, pp. 65.
DOI Link 1602
BibRef

Mišurec, J.[Jan], Kopacková, V.[Veronika], Lhotáková, Z.[Zuzana], Campbell, P.[Petya], Albrechtová, J.[Jana],
Detection of Spatio-Temporal Changes of Norway Spruce Forest Stands in Ore Mountains Using Landsat Time Series and Airborne Hyperspectral Imagery,
RS(8), No. 2, 2016, pp. 92.
DOI Link 1603
BibRef

Jjumba, A.[Anthony], Dragicevic, S.[Suzana],
Towards a voxel-based geographic automata for the simulation of geospatial processes,
PandRS(117), No. 1, 2016, pp. 206-216.
Elsevier DOI 1605
Voxel BibRef

Zeng, H.C.[Hong-Cheng], Lu, T.[Tao], Jenkins, H.[Hillary], Negrón-Juárez, R.I.[Robinson I.], Xu, J.[Jiceng],
Assessing Earthquake-Induced Tree Mortality in Temperate Forest Ecosystems: A Case Study from Wenchuan, China,
RS(8), No. 3, 2016, pp. 252.
DOI Link 1604
BibRef

Bi, J.[Jian], Myneni, R.[Ranga], Lyapustin, A.[Alexei], Wang, Y.[Yujie], Park, T.[Taejin], Chi, C.[Chen], Yan, K.[Kai], Knyazikhin, Y.[Yuri],
Amazon Forests' Response to Droughts: A Perspective from the MAIAC Product,
RS(8), No. 4, 2016, pp. 356.
DOI Link 1604
BibRef

Ningthoujam, R.K.[Ramesh K.], Tansey, K.[Kevin], Balzter, H.[Heiko], Morrison, K.[Keith], Johnson, S.C.M.[Sarah C. M.], Gerard, F.[France], George, C.[Charles], Burbidge, G.[Geoff], Doody, S.[Sam], Veck, N.[Nick], Llewellyn, G.M.[Gary M.], Blythe, T.[Thomas],
Mapping Forest Cover and Forest Cover Change with Airborne S-Band Radar,
RS(8), No. 7, 2016, pp. 577.
DOI Link 1608
BibRef

Hernández-Clemente, R., Kolari, P., Porcar-Castell, A., Korhonen, L., Mõttus, M.,
Tracking the Seasonal Dynamics of Boreal Forest Photosynthesis Using EO-1 Hyperion Reflectance: Sensitivity to Structural and Illumination Effects,
GeoRS(54), No. 9, September 2016, pp. 5105-5116.
IEEE DOI 1609
forestry BibRef

Lindquist, E.J.[Erik J.], d'Annunzio, R.[Rémi],
Assessing Global Forest Land-Use Change by Object-Based Image Analysis,
RS(8), No. 8, 2016, pp. 678.
DOI Link 1609
BibRef

Grogan, K.[Kenneth], Pflugmacher, D.[Dirk], Hostert, P.[Patrick], Verbesselt, J.[Jan], Fensholt, R.[Rasmus],
Mapping Clearances in Tropical Dry Forests Using Breakpoints, Trend, and Seasonal Components from MODIS Time Series: Does Forest Type Matter?,
RS(8), No. 8, 2016, pp. 657.
DOI Link 1609
BibRef

Lewinska, K.E.[Katarzyna Ewa], Ivits, E.[Eva], Schardt, M.[Mathias], Zebisch, M.[Marc],
Alpine Forest Drought Monitoring in South Tyrol: PCA Based Synergy between scPDSI Data and MODIS Derived NDVI and NDII7 Time Series,
RS(8), No. 8, 2016, pp. 639.
DOI Link 1609
BibRef

Luo, H.[Hui], Zhou, T.[Tao], Wu, H.[Hao], Zhao, X.[Xiang], Wang, Q.F.[Qian-Feng], Gao, S.[Shan], Li, Z.[Zheng],
Contrasting Responses of Planted and Natural Forests to Drought Intensity in Yunnan, China,
RS(8), No. 8, 2016, pp. 635.
DOI Link 1609
BibRef

Wingate, V.R.[Vladimir R.], Phinn, S.R.[Stuart R.], Kuhn, N.[Nikolaus], Bloemertz, L.[Lena], Dhanjal-Adams, K.L.[Kiran L.],
Mapping Decadal Land Cover Changes in the Woodlands of North Eastern Namibia from 1975 to 2014 Using the Landsat Satellite Archived Data,
RS(8), No. 8, 2016, pp. 681.
DOI Link 1609
BibRef

Fujiki, S.[Shogoro], Okada, K.I.[Kei-Ichi], Nishio, S.[Shogo], Kitayama, K.[Kanehiro],
Estimation of the stand ages of tropical secondary forests after shifting cultivation based on the combination of WorldView-2 and time-series Landsat images,
PandRS(119), No. 1, 2016, pp. 280-293.
Elsevier DOI 1610
Object-based image analysis BibRef

Tarantino, C.[Cristina], Lovergine, F.[Francesco], Niphadkar, M.[Madhura], Lucas, R.[Richard], Nativi, S.[Stefano], Blonda, P.[Palma],
Towards Operational Detection of Forest Ecosystem Changes in Protected Areas,
RS(8), No. 10, 2016, pp. 850.
DOI Link 1609
BibRef

Qin, Y.W.[Yuan-Wei], Xiao, X.M.[Xiang-Ming], Wang, J.[Jie], Dong, J.[Jinwei], Ewing, K.[Kayti], Hoagland, B.[Bruce], Hough, D.J.[Daniel J.], Fagin, T.D.[Todd D.], Zou, Z.H.[Zhen-Hua], Geissler, G.L.[George L.], Xian, G.Z.[George Z.], Loveland, T.R.[Thomas R.],
Mapping Annual Forest Cover in Sub-Humid and Semi-Arid Regions through Analysis of Landsat and PALSAR Imagery,
RS(8), No. 11, 2016, pp. 933.
DOI Link 1612
BibRef

Lausch, A.[Angela], Erasmi, S.[Stefan], King, D.J.[Douglas J.], Magdon, P.[Paul], Heurich, M.[Marco],
Understanding Forest Health with Remote Sensing -Part I: A Review of Spectral Traits, Processes and Remote-Sensing Characteristics,
RS(8), No. 12, 2016, pp. 1029.
DOI Link 1612
BibRef
And:
Understanding Forest Health with Remote Sensing-Part II: A Review of Approaches and Data Models,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703
BibRef

Liu, Z.H.[Zhi-Hua], Wimberly, M.C.[Michael C.], Dwomoh, F.K.[Francis K.],
Vegetation Dynamics in the Upper Guinean Forest Region of West Africa from 2001 to 2015,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702
BibRef

Dwomoh, F.K.[Francis K.], Wimberly, M.C.[Michael C.],
Fire Regimes and Their Drivers in the Upper Guinean Region of West Africa,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Santos, F.[Fabián], Dubovyk, O.[Olena], Menz, G.[Gunter],
Monitoring Forest Dynamics in the Andean Amazon: The Applicability of Breakpoint Detection Methods Using Landsat Time-Series and Genetic Algorithms,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702
BibRef

Ulsig, L.[Laura], Nichol, C.J.[Caroline J.], Huemmrich, K.F.[Karl F.], Landis, D.R.[David R.], Middleton, E.M.[Elizabeth M.], Lyapustin, A.I.[Alexei I.], Mammarella, I.[Ivan], Levula, J.[Janne], Porcar-Castell, A.[Albert],
Detecting Inter-Annual Variations in the Phenology of Evergreen Conifers Using Long-Term MODIS Vegetation Index Time Series,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702
BibRef

Tian, J.J.[Jiao-Jiao], Schneider, T.[Thomas], Straub, C.[Christoph], Kugler, F.[Florian], Reinartz, P.[Peter],
Exploring Digital Surface Models from Nine Different Sensors for Forest Monitoring and Change Detection,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704
BibRef

Hird, J.N.[Jennifer N.], Montaghi, A.[Alessandro], McDermid, G.J.[Gregory J.], Kariyeva, J.[Jahan], Moorman, B.J.[Brian J.], Nielsen, S.E.[Scott E.], McIntosh, A.C.S.[Anne C. S.],
Use of Unmanned Aerial Vehicles for Monitoring Recovery of Forest Vegetation on Petroleum Well Sites,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Springer, K.R.[Kyle R.], Wang, R.[Ran], Gamon, J.A.[John A.],
Parallel Seasonal Patterns of Photosynthesis, Fluorescence, and Reflectance Indices in Boreal Trees,
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Sothe, C.[Camile], de Almeida, C.M.[Cláudia Maria], Liesenberg, V.[Veraldo], Schimalski, M.B.[Marcos Benedito],
Evaluating Sentinel-2 and Landsat-8 Data to Map Sucessional Forest Stages in a Subtropical Forest in Southern Brazil,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Dash, J.P.[Jonathan P.], Watt, M.S.[Michael S.], Pearse, G.D.[Grant D.], Heaphy, M.[Marie], Dungey, H.S.[Heidi S.],
Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak,
PandRS(131), No. 1, 2017, pp. 1-14.
Elsevier DOI 1709
UAV BibRef

Khan, S.H., He, X., Porikli, F.M.[Fatih Murat], Bennamoun, M.,
Forest Change Detection in Incomplete Satellite Images With Deep Neural Networks,
GeoRS(55), No. 9, September 2017, pp. 5407-5423.
IEEE DOI 1709
geomorphology, geophysical image processing, image classification, land cover, vegetation mapping, deep neural networks, disaster management, environmental planning, forest change detection, incomplete satellite images, land cover change monitoring, surface reflectance information, Clouds, Spatial resolution, Change detection, deep learning, multitemporal spectral data, BibRef

Smigaj, M.[Magdalena], Gaulton, R.[Rachel], Suárez, J.C.[Juan C.], Barr, S.L.[Stuart L.],
Use of Miniature Thermal Cameras for Detection of Physiological Stress in Conifers,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link 1711
BibRef
Earlier: A1, A2, A4, A3:
UAV-Borne Thermal Imaging for Forest Health Monitoring: Detection of Disease-Induced Canopy Temperature Increase,
GeoUAV15(349-354).
DOI Link 1602
BibRef

Zhou, W.[Weiqi], Zhang, S.[Sai], Yu, W.J.[Wen-Juan], Wang, J.[Jing], Wang, W.M.[Wei-Min],
Effects of Urban Expansion on Forest Loss and Fragmentation in Six Megaregions, China,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Mulatu, K.A.[Kalkidan Ayele], Mora, B.[Brice], Kooistra, L.[Lammert], Herold, M.[Martin],
Biodiversity Monitoring in Changing Tropical Forests: A Review of Approaches and New Opportunities,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Qiu, B.[Bingwen], Chen, G.[Gong], Tang, Z.H.[Zheng-Hong], Lu, D.F.[Di-Fei], Wang, Z.Z.[Zhuang-Zhuang], Chen, C.C.[Chong-Chen],
Assessing the Three-North Shelter Forest Program in China by a novel framework for characterizing vegetation changes,
PandRS(133), No. Supplement C, 2017, pp. 75-88.
Elsevier DOI 1711
Temporal similarity trajectory, Jeffries-Matusita distance, Three-North Shelter Forest Program (TNSFP), Vegetation trend, BibRef

Byer, S.[Sarah], Jin, Y.[Yufang],
Detecting Drought-Induced Tree Mortality in Sierra Nevada Forests with Time Series of Satellite Data,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Pádua, L.[Luís], Hruška, J.[Jonáš], Bessa, J.[José], Adão, T.[Telmo], Martins, L.M.[Luís M.], Gonçalves, J.A.[José A.], Peres, E.[Emanuel], Sousa, A.M.R.[António M. R.], Castro, J.P.[João P.], Sousa, J.J.[Joaquim J.],
Multi-Temporal Analysis of Forestry and Coastal Environments Using UASs,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link 1802
BibRef

Rüetschi, M.[Marius], Schaepman, M.E.[Michael E.], Small, D.[David],
Using Multitemporal Sentinel-1 C-band Backscatter to Monitor Phenology and Classify Deciduous and Coniferous Forests in Northern Switzerland,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link 1802
BibRef

House, M.N.[Matthew N.], Wynne, R.H.[Randolph H.],
Identifying Forest Impacted by Development in the Commonwealth of Virginia through the Use of Landsat and Known Change Indicators,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link 1802
BibRef

Cazcarra-Bes, V.[Victor], Tello-Alonso, M.[Maria], Fischer, R.[Rico], Heym, M.[Michael], Papathanassiou, K.[Konstantinos],
Monitoring of Forest Structure Dynamics by Means of L-Band SAR Tomography,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802
BibRef

Zhang, L.J.[Li-Juan], Pan, T.[Tao], Zhang, H.W.[Hong-Wen], Li, X.X.[Xia-Xiang], Jiang, L.Q.[Lan-Qi],
The Effects of Forest Area Changes on Extreme Temperature Indexes between the 1900s and 2010s in Heilongjiang Province, China,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802
BibRef

Wilson, B.T.[Barry T.], Knight, J.F.[Joseph F.], McRoberts, R.E.[Ronald E.],
Harmonic regression of Landsat time series for modeling attributes from national forest inventory data,
PandRS(137), 2018, pp. 29-46.
Elsevier DOI 1802
Landsat time series, Image compositing, Harmonic regression, National forest inventory, Regression models, Classification models BibRef

Zarco-Tejada, P.J., Hornero, A., Hernández-Clemente, R., Beck, P.S.A.,
Understanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery,
PandRS(137), 2018, pp. 134-148.
Elsevier DOI 1802
Hyperspectral, Red edge, Forest decline, Chlorophyll, Sentinel-2a, Radiative transfer BibRef

Solberg, S.[Svein], May, J.[Johannes], Bogren, W.[Wiley], Breidenbach, J.[Johannes], Torp, T.[Torfinn], Gizachew, B.[Belachew],
Interferometric SAR DEMs for Forest Change in Uganda 2000-2012,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Tompalski, P.[Piotr], Coops, N.C.[Nicholas C.], Marshall, P.L.[Peter L.], White, J.C.[Joanne C.], Wulder, M.A.[Michael A.], Bailey, T.[Todd],
Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804

See also Comment on Tompalski et al. Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling. Remote Sens. 2018, 10, 347. BibRef

Tompalski, P.[Piotr], Coops, N.C.[Nicholas C.], Marshall, P.L.[Peter L.], White, J.C.[Joanne C.], Wulder, M.A.[Michael A.], Bailey, T.[Todd],
Reply to Vauhkonen: Comment on Tompalski et al. Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling. Remote Sens. 2018, 10, 347,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810

See also Comment on Tompalski et al. Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling. Remote Sens. 2018, 10, 347.
See also Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling. BibRef

Vauhkonen, J.[Jari],
Comment on Tompalski et al. Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling. Remote Sens. 2018, 10, 347,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810

See also Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling.
See also Reply to Vauhkonen: Comment on Tompalski et al. Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling. Remote Sens. 2018, 10, 347. BibRef

Zhu, C.H.[Cheng-Hao], Zhang, X.L.[Xiao-Li], Zhang, N.[Ning], Hassan, M.A.[Mohammed Abdelmanan], Zhao, L.[Lin],
Assessing the Defoliation of Pine Forests in a Long Time-Series and Spatiotemporal Prediction of the Defoliation Using Landsat Data,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Asner, G.P.[Gregory P.], Martin, R.E.[Roberta E.], Keith, L.M.[Lisa M.], Heller, W.P.[Wade P.], Hughes, M.A.[Marc A.], Vaughn, N.R.[Nicholas R.], Hughes, R.F.[R. Flint], Balzotti, C.[Christopher],
A Spectral Mapping Signature for the Rapid Ohia Death (ROD) Pathogen in Hawaiian Forests,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Melendy, L., Hagen, S.C., Sullivan, F.B., Pearson, T.R.H., Walker, S.M., Ellis, P., Kustiyo, Sambodo, A.K.[Ari Katmoko], Roswintiarti, O., Hanson, M.A., Klassen, A.W., Palace, M.W., Braswell, B.H., Delgado, G.M.,
Automated method for measuring the extent of selective logging damage with airborne LiDAR data,
PandRS(139), 2018, pp. 228-240.
Elsevier DOI 1804
Lidar, Selective logging, Tropical forest monitoring, REDD+, Automated logging algorithm, Kalimantan, Indonesia, Reduced impact logging (RIL) BibRef

Langner, A.[Andreas], Miettinen, J.[Jukka], Vaughn, N.R.[Nicholas R.], Asner, G.P.[Gregory P.], Brodrick, P.G.[Philip G.], Martin, R.E.[Roberta E.], Heckler, J.W.[Joseph W.], Knapp, D.E.[David E.], Hughes, R.F.[R. Flint],
An Approach for High-Resolution Mapping of Hawaiian Metrosideros Forest Mortality Using Laser-Guided Imaging Spectroscopy,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Hruza, P.[Petr], Mikita, T.[Tomáš], Tyagur, N.[Nataliya], Krejza, Z.[Zdenek], Cibulka, M.[Miloš], Procházková, A.[Andrea], Patocka, Z.[Zdenek],
Detecting Forest Road Wearing Course Damage Using Different Methods of Remote Sensing,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Silveira, E.M.O.[Eduarda M. O.], Bueno, I.T.[Inácio T.], Acerbi-Junior, F.W.[Fausto W.], Mello, J.M.[José M.], Scolforo, J.R.S.[José Roberto S.], Wulder, M.A.[Michael A.],
Using Spatial Features to Reduce the Impact of Seasonality for Detecting Tropical Forest Changes from Landsat Time Series,
RS(10), No. 6, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Goodbody, T.R.H.[Tristan R.H.], Coops, N.C.[Nicholas C.], Hermosilla, T.[Txomin], Tompalski, P.[Piotr], McCartney, G.[Grant], MacLean, D.A.[David A.],
Digital aerial photogrammetry for assessing cumulative spruce budworm defoliation and enhancing forest inventories at a landscape-level,
PandRS(142), 2018, pp. 1-11.
Elsevier DOI 1807
Digital aerial photogrammetry, Forest monitoring, Spruce budworm, Cumulative defoliation, Partial least squares BibRef

Lin, C.S.[Chin-Su], Chen, S.Y.[Shih-Yu], Chen, C.C.[Chia-Chun], Tai, C.H.[Chia-Huei],
Detecting newly grown tree leaves from unmanned-aerial-vehicle images using hyperspectral target detection techniques,
PandRS(142), 2018, pp. 174-189.
Elsevier DOI 1807
Phenological events, New foliage detection, Anomaly detection, Tree growth, Climate change BibRef

Chen, S.Y.[Shih-Yu], Lin, C.S.[Chin-Su], Chuang, S.J.[Shang-Ju], Kao, Z.Y.[Zhe-Yuan],
Weighted Background Suppression Target Detection Using Sparse Image Enhancement Technique for Newly Grown Tree Leaves,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Lausch, A.[Angela], Borg, E.[Erik], Bumberger, J.[Jan], Dietrich, P.[Peter], Heurich, M.[Marco], Huth, A.[Andreas], Jung, A.[András], Klenke, R.[Reinhard], Knapp, S.[Sonja], Mollenhauer, H.[Hannes], Paasche, H.[Hendrik], Paulheim, H.[Heiko], Pause, M.[Marion], Schweitzer, C.[Christian], Schmulius, C.[Christiane], Settele, J.[Josef], Skidmore, A.K.[Andrew K.], Wegmann, M.[Martin], Zacharias, S.[Steffen], Kirsten, T.[Toralf], Schaepman, M.E.[Michael E.],
Understanding Forest Health with Remote Sensing, Part III: Requirements for a Scalable Multi-Source Forest Health Monitoring Network Based on Data Science Approaches,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef

Kobayashi, H.[Hideki], Nagai, S.[Shin], Kim, Y.[Yongwon], Yang, W.[Wei], Ikeda, K.[Kyoko], Ikawa, H.[Hiroki], Nagano, H.[Hirohiko], Suzuki, R.[Rikie],
In Situ Observations Reveal How Spectral Reflectance Responds to Growing Season Phenology of an Open Evergreen Forest in Alaska,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef

Morrison, J.[Jacqueline], Higginbottom, T.P.[Thomas P.], Symeonakis, E.[Elias], Jones, M.J.[Martin J.], Omengo, F.[Fred], Walker, S.L.[Susan L.], Cain, B.[Bradley],
Detecting Vegetation Change in Response to Confining Elephants in Forests Using MODIS Time-Series and BFAST,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef

Mõttus, M.[Matti], Hernández-Clemente, R.[Rocío], Perheentupa, V.[Viljami], Markiet, V.[Vincent], Aalto, J.H.[Ju-Ho], Bäck, J.[Jaana], Nichol, C.J.[Caroline J.],
Measurement of Diurnal Variation in Needle PRI and Shoot Photosynthesis in a Boreal Forest,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef
And: Correction: RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Li, L.[Le], Zhao, Y.[Yaolong], Fu, Y.C.[Ying-Chun], Xin, Q.C.[Qin-Chuan],
Satellite-Based Models Need Improvements on Simulating Annual Gross Primary Productivity: A Comparison of Six Models for Regional Modeling of Deciduous Broadleaf Forests,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef

Kranz, O.[Olaf], Schoepfer, E.[Elisabeth], Tegtmeyer, R.[Reiner], Lang, S.[Stefan],
Earth observation based multi-scale assessment of logging activities in the Democratic Republic of the Congo,
PandRS(144), 2018, pp. 254-267.
Elsevier DOI 1809
Multi-scale assessment, Logging, Conflict resources, Pixel-based change detection, Object-based change detection BibRef

Yuan, H.H.[Huan-Huan], Wu, C.Y.[Chao-Yang], Lu, L.L.[Lin-Lin], Wang, X.Y.[Xiao-Yue],
A new algorithm predicting the end of growth at five evergreen conifer forests based on nighttime temperature and the enhanced vegetation index,
PandRS(144), 2018, pp. 390-399.
Elsevier DOI 1809
Phenology, Evergreen conifer forests, T, T, NDVI/EVI BibRef

Luo, Y.P.[Yun-Peng], El-Madany, T.S.[Tarek S.], Filippa, G.[Gianluca], Ma, X.[Xuanlong], Ahrens, B.[Bernhard], Carrara, A.[Arnaud], Gonzalez-Cascon, R.[Rosario], Cremonese, E.[Edoardo], Galvagno, M.[Marta], Hammer, T.W.[Tiana W.], Pacheco-Labrador, J.[Javier], Martín, M.P.[M. Pilar], Moreno, G.[Gerardo], Perez-Priego, O.[Oscar], Reichstein, M.[Markus], Richardson, A.D.[Andrew D.], Römermann, C.[Christine], Migliavacca, M.[Mirco],
Using Near-Infrared-Enabled Digital Repeat Photography to Track Structural and Physiological Phenology in Mediterranean Tree-Grass Ecosystems,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef
And: Correction: RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Dash, J.P.[Jonathan P.], Pearse, G.D.[Grant D.], Watt, M.S.[Michael S.],
UAV Multispectral Imagery Can Complement Satellite Data for Monitoring Forest Health,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef

Guo, J.[Jing], Gong, P.[Peng],
The Potential of Spectral Indices in Detecting Various Stages of Afforestation over the Loess Plateau Region of China,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810
BibRef

Santos, M.J.[Maria J.], Disney, M.[Mathias], Chave, J.[Jérôme],
Detecting Human Presence and Influence on Neotropical Forests with Remote Sensing,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Rybakov, G.[Georgy], Peuhkurinen, J.[Jussi], Latva-Käyrä, P.[Petri], Villikka, M.[Maria], Sirparanta, S.[Sanna], Kolesnikov, A.[Alexander], Junttila, V.[Virpi], Kauranne, T.[Tuomo],
Combining Camera Relascope-Measured Field Plots and Multi-Seasonal Landsat 8 Imagery for Enhancing the Forest Inventory of Boreal Forests in Central Russia,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Berveglieri, A.[Adilson], Imai, N.N.[Nilton N.], Tommaselli, A.M.G.[Antonio M.G.], Casagrande, B.[Baltazar], Honkavaara, E.[Eija],
Successional stages and their evolution in tropical forests using multi-temporal photogrammetric surface models and superpixels,
PandRS(146), 2018, pp. 548-558.
Elsevier DOI 1812
DSM, Forest classification, Forest succession, Temporal superpixel, Segmentation BibRef

McCarthy, M.J.[Matthew J.], Dimmitt, B.[Benjamin], Muller-Karger, F.E.[Frank E.],
Rapid Coastal Forest Decline in Florida's Big Bend,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Honeck, E.[Erica], Castello, R.[Roberto], Chatenoux, B.[Bruno], Richard, J.P.[Jean-Philippe], Lehmann, A.[Anthony], Giuliani, G.[Gregory],
From a Vegetation Index to a Sustainable Development Goal Indicator: Forest Trend Monitoring Using Three Decades of Earth Observations across Switzerland,
IJGI(7), No. 12, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Garcia-Millan, V.E.[Virginia E.], Sanchez-Azofeifa, G.A.[G. Arturo],
Quantifying Changes on Forest Succession in a Dry Tropical Forest Using Angular-Hyperspectral Remote Sensing,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Haro-Carrión, X.[Xavier], Southworth, J.[Jane],
Understanding Land Cover Change in a Fragmented Forest Landscape in a Biodiversity Hotspot of Coastal Ecuador,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Moreno, A.[Adam], Neumann, M.[Mathias], Mohebalian, P.M.[Phillip M.], Thurnher, C.[Christopher], Hasenauer, H.[Hubert],
The Continental Impact of European Forest Conservation Policy and Management on Productivity Stability,
RS(11), No. 1, 2019, pp. xx-yy.
DOI Link 1901
BibRef

Bai, B.X.[Bing-Xin], Tan, Y.M.[Yu-Min], Guo, D.[Dong], Xu, B.[Bo],
Dynamic Monitoring of Forest Land in Fuling District Based on Multi-Source Time Series Remote Sensing Images,
IJGI(8), No. 1, 2019, pp. xx-yy.
DOI Link 1901
BibRef

Burke, M.W.V.[Morgen W.V.], Rundquist, B.C.[Bradley C.], Zheng, H.[Haochi],
Detection of Shelterbelt Density Change Using Historic APFO and NAIP Aerial Imagery,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link 1902
Evaluate changes in windbreaks. BibRef

Watt, M.S.[Michael S.], Pearse, G.D.[Grant D.], Dash, J.P.[Jonathan P.], Melia, N.[Nathanael], Leonardo, E.M.C.[Ellen Mae C.],
Application of remote sensing technologies to identify impacts of nutritional deficiencies on forests,
PandRS(149), 2019, pp. 226-241.
Elsevier DOI 1903
ALS, Aerial laser scanning, Hyperspectral, Light detection and ranging BibRef

Shen, W.J.[Wen-Juan], Li, M.[Mingshi], Huang, C.Q.[Cheng-Quan], Tao, X.[Xin], Li, S.[Shu], Wei, A.[Anshi],
Mapping Annual Forest Change Due to Afforestation in Guangdong Province of China Using Active and Passive Remote Sensing Data,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Tomppo, E.[Erkki], Antropov, O.[Oleg], Praks, J.[Jaan],
Boreal Forest Snow Damage Mapping Using Multi-Temporal Sentinel-1 Data,
RS(11), No. 4, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Marshak, C.[Charlie], Simard, M.[Marc], Denbina, M.[Michael],
Monitoring Forest Loss in ALOS/PALSAR Time-Series with Superpixels,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Pinagé, E.R.[Ekena Rangel], Keller, M.[Michael], Duffy, P.[Paul], Longo, M.[Marcos], dos-Santos, M.N.[Maiza Nara], Morton, D.C.[Douglas C.],
Long-Term Impacts of Selective Logging on Amazon Forest Dynamics from Multi-Temporal Airborne LiDAR,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Rossi, F.[Fernando], Breidenbach, J.[Johannes], Puliti, S.[Stefano], Astrup, R.[Rasmus], Talbot, B.[Bruce],
Assessing Harvested Sites in a Forested Boreal Mountain Catchment through Global Forest Watch,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Voight, C.[Carly], Hernandez-Aguilar, K.[Karla], Garcia, C.[Christina], Gutierrez, S.[Said],
Predictive Modeling of Future Forest Cover Change Patterns in Southern Belize,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904
BibRef

Dalagnol, R.[Ricardo], Phillips, O.L.[Oliver L.], Gloor, E.[Emanuel], Galvão, L.S.[Lênio S.], Wagner, F.H.[Fabien H.], Locks, C.J.[Charton J.], Aragão, L.E.O.C.[Luiz E. O. C.],
Quantifying Canopy Tree Loss and Gap Recovery in Tropical Forests under Low-Intensity Logging Using VHR Satellite Imagery and Airborne LiDAR,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904
BibRef

Chen, B.[Bin], Jin, Y.[Yufang], Brown, P.[Patrick],
Automatic mapping of planting year for tree crops with Landsat satellite time series stacks,
PandRS(151), 2019, pp. 176-188.
Elsevier DOI 1904
Planting year, Time series analysis, NDVI, Google Earth Engine, Crop dynamics, Change detection, California BibRef

Lima, T.A.[Thaís Almeida], Beuchle, R.[René], Langner, A.[Andreas], Grecchi, R.C.[Rosana Cristina], Griess, V.C.[Verena C.], Achard, F.[Frédéric],
Comparing Sentinel-2 MSI and Landsat 8 OLI Imagery for Monitoring Selective Logging in the Brazilian Amazon,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Pérez-Romero, J.[Javier], Navarro-Cerrillo, R.M.[Rafael María], Palacios-Rodriguez, G.[Guillermo], Acosta, C.[Cristina], Mesas-Carrascosa, F.J.[Francisco Javier],
Improvement of Remote Sensing-Based Assessment of Defoliation of Pinus spp. Caused by Thaumetopoea pityocampa Denis and Schiffermüller and Related Environmental Drivers in Southeastern Spain,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Mi, J.X.[Jia-Xin], Yang, Y.J.[Yong-Jun], Zhang, S.[Shaoliang], An, S.[Shi], Hou, H.[Huping], Hua, Y.[Yifei], Chen, F.[Fuyao],
Tracking the Land Use/Land Cover Change in an Area with Underground Mining and Reforestation via Continuous Landsat Classification,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Trujillo-Toro, J.[Jesus], Navarro-Cerrillo, R.M.[Rafael M.],
Analysis of Site-dependent Pinus halepensis Mill. Defoliation Caused by 'Candidatus Phytoplasma pini' through Shape Selection in Landsat Time Series,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Shimizu, K.[Katsuto], Ota, T.[Tetsuji], Mizoue, N.[Nobuya],
Detecting Forest Changes Using Dense Landsat 8 and Sentinel-1 Time Series Data in Tropical Seasonal Forests,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Gebru, B.M.[Belay Manjur], Lee, W.K.[Woo-Kyun], Khamzina, A.[Asia], Lee, S.G.[Sle-Gee], Negash, E.[Emnet],
Hydrological Response of Dry Afromontane Forest to Changes in Land Use and Land Cover in Northern Ethiopia,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Hamdi, Z.M.[Zayd Mahmoud], Brandmeier, M.[Melanie], Straub, C.[Christoph],
Forest Damage Assessment Using Deep Learning on High Resolution Remote Sensing Data,
RS(11), No. 17, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Noordermeer, L.[Lennart], Økseter, R.[Roar], Ørka, H.O.[Hans Ole], Gobakken, T.[Terje], Næsset, E.[Erik], Bollandsås, O.M.[Ole Martin],
Classifications of Forest Change by Using Bitemporal Airborne Laser Scanner Data,
RS(11), No. 18, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Salamanca, A.J.A.[Antonio Jesús Ariza], Navarro-Cerrillo, R.M.[Rafael María], Bonet-García, F.J.[Francisco J.], Pérez-Palazón, M.J.[Ma José], Polo, M.J.[María J.],
Integration of a Landsat Time-Series of NBR and Hydrological Modeling to Assess Pinus pinaster Aiton. Forest Defoliation in South-Eastern Spain,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Bozek, P.[Piotr], Janus, J.[Jaroslaw], Mitka, B.[Bartosz],
Analysis of Changes in Forest Structure using Point Clouds from Historical Aerial Photographs,
RS(11), No. 19, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Dorji, Y.[Yonten], Annighöfer, P.[Peter], Ammer, C.[Christian], Seidel, D.[Dominik],
Response of Beech (Fagus sylvatica L.) Trees to Competition: New Insights from Using Fractal Analysis,
RS(11), No. 22, 2019, pp. xx-yy.
DOI Link 1911
BibRef

Khare, S.[Siddhartha], Drolet, G.[Guillaume], Sylvain, J.D.[Jean-Daniel], Paré, M.C.[Maxime Charles], Rossi, S.[Sergio],
Assessment of Spatio-Temporal Patterns of Black Spruce Bud Phenology across Quebec Based on MODIS-NDVI Time Series and Field Observations,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Haarpaintner, J.[Jörg], Hindberg, H.[Heidi],
Multi-Temporal and Multi-Frequency SAR Analysis for Forest Land Cover Mapping of the Mai-Ndombe District (Democratic Republic of Congo),
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Clark, M.L.[Matthew L.],
Comparison of multi-seasonal Landsat 8, Sentinel-2 and hyperspectral images for mapping forest alliances in Northern California,
PandRS(159), 2020, pp. 26-40.
Elsevier DOI 1912
Land cover, Forest alliance, U.S. National Vegetation Classification (NVC), Support Vector Machine BibRef

Myroniuk, V.[Viktor], Kutia, M.[Mykola], Sarkissian, A.J.[Arbi J.], Bilous, A.[Andrii], Liu, S.G.[Shu-Guang],
Regional-Scale Forest Mapping over Fragmented Landscapes Using Global Forest Products and Landsat Time Series Classification,
RS(12), No. 1, 2020, pp. xx-yy.
DOI Link 2001
BibRef

Hufkens, K.[Koen], de Haulleville, T.[Thalès], Kearsley, E.[Elizabeth], Jacobsen, K.[Kim], Beeckman, H.[Hans], Stoffelen, P.[Piet], Vandelook, F.[Filip], Meeus, S.[Sofie], Amara, M.[Michael], van Hirtum, L.[Leen], van den Bulcke, J.[Jan], Verbeeck, H.[Hans], Wingate, L.[Lisa],
Historical Aerial Surveys Map Long-Term Changes of Forest Cover and Structure in the Central Congo Basin,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Adams, B.[Bryce], Iverson, L.[Louis], Matthews, S.[Stephen], Peters, M.[Matthew], Prasad, A.[Anantha], Hix, D.M.[David M.],
Mapping Forest Composition with Landsat Time Series: An Evaluation of Seasonal Composites and Harmonic Regression,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Bell, R.A.[Rose-Anne], Callow, J.N.[J. Nikolaus],
Investigating Banksia Coastal Woodland Decline Using Multi-Temporal Remote Sensing and Field-Based Monitoring Techniques,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Peereman, J.[Jonathan], Hogan, J.A.[James Aaron], Lin, T.C.[Teng-Chiu],
Landscape Representation by a Permanent Forest Plot and Alternative Plot Designs in a Typhoon Hotspot, Fushan, Taiwan,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Vilar, P.[Pedro], Morais, T.G.[Tiago G.], Rodrigues, N.R.[Nuno R.], Gama, I.[Ivo], Monteiro, M.L.[Marta L.], Domingos, T.[Tiago], Teixeira, R.F.M.[Ricardo F. M.],
Object-Based Classification Approaches for Multitemporal Identification and Monitoring of Pastures in Agroforestry Regions using Multispectral Unmanned Aerial Vehicle Products,
RS(12), No. 5, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Anaya, J.A.[Jesús A.], Gutiérrez-Vélez, V.H.[Víctor H.], Pacheco-Pascagaza, A.M.[Ana M.], Palomino-Ángel, S.[Sebastián], Han, N.[Natasha], Balzter, H.[Heiko],
Drivers of Forest Loss in a Megadiverse Hotspot on the Pacific Coast of Colombia,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link 2004
BibRef

van Passel, J.[Johanna], de Keersmaecker, W.[Wanda], Somers, B.[Ben],
Monitoring Woody Cover Dynamics in Tropical Dry Forest Ecosystems Using Sentinel-2 Satellite Imagery,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link 2004
BibRef

Balková, M.[Marie], Bajer, A.[Aleš], Patocka, Z.[Zdenek], Mikita, T.[Tomáš],
Visual Exposure of Rock Outcrops in the Context of a Forest Disease Outbreak Simulation Based on a Canopy Height Model and Spectral Information Acquired by an Unmanned Aerial Vehicle,
IJGI(9), No. 5, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Peereman, J.[Jonathan], Hogan, J.A.[James Aaron], Lin, T.C.[Teng-Chiu],
Assessing Typhoon-Induced Canopy Damage Using Vegetation Indices in the Fushan Experimental Forest, Taiwan,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Nazarova, T.[Tatiana], Martin, P.[Pascal], Giuliani, G.[Gregory],
Monitoring Vegetation Change in the Presence of High Cloud Cover with Sentinel-2 in a Lowland Tropical Forest Region in Brazil,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Galiatsatos, N.[Nikolaos], Donoghue, D.N.M.[Daniel N.M.], Watt, P.[Pete], Bholanath, P.[Pradeepa], Pickering, J.[Jeffrey], Hansen, M.C.[Matthew C.], Mahmood, A.R.J.[Abu R.J.],
An Assessment of Global Forest Change Datasets for National Forest Monitoring and Reporting,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Perroy, R.L.[Ryan L.], Hughes, M.[Marc], Keith, L.M.[Lisa M.], Collier, E.[Eszter], Sullivan, T.[Timo], Low, G.[Gabriel],
Examining the Utility of Visible Near-Infrared and Optical Remote Sensing for the Early Detection of Rapid Ohia Death,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Bernardino, P.N.[Paulo N.], Brandt, M.[Martin], de Keersmaecker, W.[Wanda], Horion, S.[Stéphanie], Fensholt, R.[Rasmus], Storms, I.[Ilié], Wigneron, J.P.[Jean-Pierre], Verbesselt, J.[Jan], Somers, B.[Ben],
Uncovering Dryland Woody Dynamics Using Optical, Microwave, and Field Data: Prolonged Above-Average Rainfall Paradoxically Contributes to Woody Plant Die-Off in the Western Sahel,
RS(12), No. 14, 2020, pp. xx-yy.
DOI Link 2007
BibRef

Iordache, M.D.[Marian-Daniel], Mantas, V.[Vasco], Baltazar, E.[Elsa], Pauly, K.[Klaas], Lewyckyj, N.[Nicolas],
A Machine Learning Approach to Detecting Pine Wilt Disease Using Airborne Spectral Imagery,
RS(12), No. 14, 2020, pp. xx-yy.
DOI Link 2007
BibRef

Yamada, Y.[Yusuke], Okubo, T.[Toshihiro], Shimizu, K.[Katsuto],
Causal Analysis of Accuracy Obtained Using High-Resolution Global Forest Change Data to Identify Forest Loss in Small Forest Plots,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Shen, W.J.[Wen-Juan], He, J.Y.[Jia-Ying], Huang, C.Q.[Cheng-Quan], Li, M.S.[Ming-Shi],
Quantifying the Actual Impacts of Forest Cover Change on Surface Temperature in Guangdong, China,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Tripathi, S.[Shankar], Subedi, R.[Rajan], Adhikari, H.[Hari],
Forest Cover Change Pattern after the Intervention of Community Forestry Management System in the Mid-Hill of Nepal: A Case Study,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Xu, D.D.[Dan-Dan], Geng, Q.H.[Qing-Hong], Jin, C.S.[Chang-Shan], Xu, Z.K.[Zi-Kun], Xu, X.[Xia],
Tree Line Identification and Dynamics under Climate Change in Wuyishan National Park Based on Landsat Images,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Ruiz-Ramos, J.[Javier], Marino, A.[Armando], Boardman, C.[Carl], Suarez, J.[Juan],
Continuous Forest Monitoring Using Cumulative Sums of Sentinel-1 Timeseries,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Liu, Y.[Yang], Liu, R.G.[Rong-Gao],
A Simple Approach for Mapping Forest Cover from Time Series of Satellite Data,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Cunningham, D.[Daniel], Cunningham, P.[Paul], Fagan, M.E.[Matthew E.],
Evaluating Forest Cover and Fragmentation in Costa Rica with a Corrected Global Tree Cover Map,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Puhm, M.[Martin], Deutscher, J.[Janik], Hirschmugl, M.[Manuela], Wimmer, A.[Andreas], Schmitt, U.[Ursula], Schardt, M.[Mathias],
A Near Real-Time Method for Forest Change Detection Based on a Structural Time Series Model and the Kalman Filter,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Zhang, Y.[Yali], Shen, W.J.[Wen-Juan], Li, M.S.[Ming-Shi], Lv, Y.Y.[Ying-Ying],
Integrating Landsat Time Series Observations and Corona Images to Characterize Forest Change Patterns in a Mining Region of Nanjing, Eastern China from 1967 to 2019,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Furukawa, F.[Flavio], Morimoto, J.[Junko], Yoshimura, N.[Nobuhiko], Kaneko, M.[Masami],
Comparison of Conventional Change Detection Methodologies Using High-Resolution Imagery to Find Forest Damage Caused by Typhoons,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Fernandez-Carrillo, A.[Angel], Franco-Nieto, A.[Antonio], Pinto-Bañuls, E.[Erika], Basarte-Mena, M.[Miguel], Revilla-Romero, B.[Beatriz],
Designing a Validation Protocol for Remote Sensing Based Operational Forest Masks Applications. Comparison of Products Across Europe,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Fidelus-Orzechowska, J.[Joanna], Strzyzowski, D.[Dariusz], Cebulski, J.[Jaroslaw], Wronska-Walach, D.[Dominika],
A Quantitative Analysis of Surface Changes on an Abandoned Forest Road in the Lejowa Valley (Tatra Mountains, Poland),
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Brovelli, M.A.[Maria Antonia], Sun, Y.[Yaru], Yordanov, V.[Vasil],
Monitoring Forest Change in the Amazon Using Multi-Temporal Remote Sensing Data and Machine Learning Classification on Google Earth Engine,
IJGI(9), No. 10, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Xu, Z.H.[Zhi-Huo], Wang, Y.X.[Yue-Xia],
Radar Satellite Image Time Series Analysis for High-Resolution Mapping of Man-Made Forest Change in Chongming Eco-Island,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Chen, H.[He], Zeng, Z.Z.[Zhen-Zhong], Wu, J.[Jie], Peng, L.Q.[Li-Qing], Lakshmi, V.[Venkataraman], Yang, H.[Hong], Liu, J.[Junguo],
Large Uncertainty on Forest Area Change in the Early 21st Century among Widely Used Global Land Cover Datasets,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Devkota, R.S.[Ram Sharan], Field, R.[Richard], Hoffmann, S.[Samuel], Walentowitz, A.[Anna], Medina, F.M.[Félix Manuel], Vetaas, O.R.[Ole Reidar], Chiarucci, A.[Alessandro], Weiser, F.[Frank], Jentsch, A.[Anke], Beierkuhnlein, C.[Carl],
Assessing the Potential Replacement of Laurel Forest by a Novel Ecosystem in the Steep Terrain of an Oceanic Island,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Tian, L.[Lei], Fu, W.X.[Wen-Xue],
Bi-Temporal Analysis of Spatial Changes of Boreal Forest Cover and Species in Siberia for the Years 1985 and 2015,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Zang, Z.[Zhuo], Wang, G.X.[Guang-Xing], Lin, H.[Hui], Luo, P.[Peng],
Developing a spectral angle based vegetation index for detecting the early dying process of Chinese fir trees,
PandRS(171), 2021, pp. 253-265.
Elsevier DOI 2012
Hyperspectral data, Spectral angle, GRRSGI, Early stage damage detection, Chinese fir BibRef

Rose, M.B.[M. Brooke], Nagle, N.N.[Nicholas N.],
Characterizing Forest Dynamics with Landsat-Derived Phenology Curves,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Varo-Martínez, Á.[Ángeles], Navarro-Cerrillo, R.M.[Rafael M.],
Stand Delineation of Pinus sylvestris L. Plantations Suffering Decline Processes Based on Biophysical Tree Crown Variables: A Necessary Tool for Adaptive Silviculture,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Li, H.[Han], Xu, F.[Fu], Li, Z.C.[Zhi-Chao], You, N.[Nanshan], Zhou, H.[Hui], Zhou, Y.[Yan], Chen, B.Q.[Bang-Qian], Qin, Y.[Yuanwei], Xiao, X.M.[Xiang-Ming], Dong, J.[Jinwei],
Forest Changes by Precipitation Zones in Northern China after the Three-North Shelterbelt Forest Program in China,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Jorge, C.[Catarina], Silva, J.M.N.[João M. N.], Boavida-Portugal, J.[Joana], Soares, C.[Cristina], Cerasoli, S.[Sofia],
Using Digital Photography to Track Understory Phenology in Mediterranean Cork Oak Woodlands,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Pacheco-Angulo, C.[Carlos], Plata-Rocha, W.[Wenseslao], Serrano, J.[Julio], Vilanova, E.[Emilio], Monjardin-Armenta, S.[Sergio], González, A.[Alvaro], Camargo, C.[Cristopher],
A Low-Cost and Robust Landsat-Based Approach to Study Forest Degradation and Carbon Emissions from Selective Logging in the Venezuelan Amazon,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Piragnolo, M.[Marco], Pirotti, F.[Francesco], Zanrosso, C.[Carlo], Lingua, E.[Emanuele], Grigolato, S.[Stefano],
Responding to Large-Scale Forest Damage in an Alpine Environment with Remote Sensing, Machine Learning, and Web-GIS,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Liu, Y.[Yang],
Remote Sensing of Forest Structural Changes Due to the Recent Boom of Unconventional Shale Gas Extraction Activities in Appalachian Ohio,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Lukasová, V.[Veronika], Bucha, T.[Tomáš], Mareková, L.[Lubica], Buchholcerová, A.[Anna], Bicárová, S.[Svetlana],
Changes in the Greenness of Mountain Pine (Pinus mugo Turra) in the Subalpine Zone Related to the Winter Climate,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Chen, X.C.[Xin-Chuang], Li, F.[Feng], Li, X.Q.[Xiao-Qian], Hu, Y.H.[Yin-Hong], Hu, P.P.[Pan-Pan],
Quantifying the Compound Factors of Forest Land Changes in the Pearl River Delta, China,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Chernenkova, T.[Tatiana], Kotlov, I.[Ivan], Belyaeva, N.[Nadezhda], Suslova, E.[Elena],
Spatiotemporal Modeling of Coniferous Forests Dynamics along the Southern Edge of Their Range in the Central Russian Plain,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

van den Hoek, J.[Jamon], Smith, A.C.[Alexander C.], Hurni, K.[Kaspar], Saksena, S.[Sumeet], Fox, J.[Jefferson],
Shedding New Light on Mountainous Forest Growth: A Cross-Scale Evaluation of the Effects of Topographic Illumination Correction on 25 Years of Forest Cover Change across Nepal,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Zhang, B.Y.[Bi-Yao], Ye, H.C.[Hui-Chun], Lu, W.[Wei], Huang, W.J.[Wen-Jiang], Wu, B.[Bo], Hao, Z.Q.[Zhuo-Qing], Sun, H.[Hong],
A Spatiotemporal Change Detection Method for Monitoring Pine Wilt Disease in a Complex Landscape Using High-Resolution Remote Sensing Imagery,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Bórnez, K.[Kevin], Verger, A.[Aleixandre], Descals, A.[Adrià], Peñuelas, J.[Josep],
Monitoring the Responses of Deciduous Forest Phenology to 2000-2018 Climatic Anomalies in the Northern Hemisphere,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Morin, N.[Nathalie], Masse, A.[Antoine], Sannier, C.[Christophe], Siklar, M.[Martin], Kiesslich, N.[Norman], Sayadyan, H.[Hovik], Faucqueur, L.[Loïc], Seewald, M.[Michaela],
Development and Application of Earth Observation Based Machine Learning Methods for Characterizing Forest and Land Cover Change in Dilijan National Park of Armenia between 1991 and 2019,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Chen, S.S.[Shan-Shan], Wen, Z.[Zhaofei], Ma, M.[Maohua], Wu, S.J.[Sheng-Jun],
Disentangling Climatic Factors and Human Activities in Governing the Old and New Forest Productivity,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109
BibRef


Cortés, L., Acuña, M.P., Hernández, H.J.,
Spatiotemporal Dynamics of Forest Plantation Clearcutting At Landscape Level,
ISPRS20(B3:969-973).
DOI Link 2012
BibRef

Duong, N.D.,
Automated Classification of Natural Forests with Landsat Time Series Using Simplified Spectral Patterns,
ISPRS20(B3:983-988).
DOI Link 2012
BibRef

Legdou, A.[Anass], Chafik, H.[Hassan], Amine, A.[Aouatif], Lahssini, S.[Said], Berrada, M.[Mohamed],
A Random Forest-cellular Automata Modeling Approach to Predict Future Forest Cover Change in Middle Atlas Morocco, Under Anthropic, Biotic and Abiotic Parameters,
ICISP20(91-100).
Springer DOI 2009
BibRef

Taefi Feijani, M., Azadnejad, S., Homayouni, S., Moradi, M.,
Investigation of Forest Canopy Density Changes in Hyrcanian Forest Resources During 1987 to 2002 Using Remote Sensing Technology,
SMPR19(1031-1034).
DOI Link 1912
BibRef

Zoraghi, M., Saadi, R., Hasanlou, M.,
Investigating of Forest Change in Golestan Province Using Landsat Image,
SMPR19(1159-1162).
DOI Link 1912
BibRef

Koppad, A.G., Janagoudar, B.S.,
Vegetation Analysis And Land Use Land Cover Classification Of Forest In Uttara Kannada District India Through Geo-informatics Approach,
Hannover17(219-223).
DOI Link 1805
BibRef
And:
Vegetation Analysis And Land Use Land Cover Classification Of Forest In Uttara Kannada District India Using Remote Sensign And Gis Techniques,
GeoDisast17(121-125).
DOI Link 1805
BibRef

Deutscher, J., Gutjahr, K., Perko, R., Raggam, H., Hirschmugl, M., Schardt, M.,
Humid tropical forest monitoring with multi-temporal L-, C- and X-band SAR data,
MultiTemp17(1-4)
IEEE DOI 1712
geophysical techniques, synthetic aperture radar, vegetation mapping, ALOS PALSAR, Global Forest Watch, Landsat, time series analysis BibRef

Pencue-Fierro, E.L., Solano-Correa, Y.T., Corrales-Muñoz, J.C., Figueroa-Casas, A.,
Analysis of Riparian forest buffers dynamics in Colombian basins by Landsat Time Series,
MultiTemp17(1-4)
IEEE DOI 1712
digital elevation models, remote sensing, time series, Colombian Basins, Landsat time series, climate change, Riparian forest buffers BibRef

Carriello, F., Rezende, F.S., Neves, O.M.S., Rodriguez, D.A.,
Forestry Expansion During The Last Decades In The Paraiba Do Sul Basin, Brazil,
ISPRS16(B8: 857-861).
DOI Link 1610
BibRef

Kolecka, N., Kozak, J., Kaim, D., Dobosz, M., Ginzler, C., Psomas, A.,
Mapping Secondary Forest Succession On Abandoned Agricultural Land In The Polish Carpathians,
ISPRS16(B8: 931-935).
DOI Link 1610
BibRef

Bouzekri, A., Benmessaoud, H.,
Using Multi-criteria Analysis For The Study Of Human Impact On Agro-forestry-pastoral Ecosystem In The Region Of Khenchela (Algeria),
ISPRS16(B8: 779-783).
DOI Link 1610
BibRef

Nguyen, H.T.T.[Huong Thi Thanh],
Mapping Tropical Forest For Sustainable Management Using Spot 5 Satellite Image,
ISPRS16(B7: 319-323).
DOI Link 1610
BibRef

Khare, S., Latifi, H., Ghosh, K.,
Phenology Analysis Of Forest Vegetation To Environmental Variables During Pre- And Post-monsoon Seasons In Western Himalayan Region Of India,
ISPRS16(B2: 15-19).
DOI Link 1610
BibRef

Yuan, Y.[Yi], Hu, X.Y.[Xiang-Yun],
Random Forest And Objected-based Classification For Forest Pest Extraction From UAV Aerial Imagery,
ISPRS16(B1: 1093-1098).
DOI Link 1610
BibRef

Isaacson, S., Rachmilevitch, S., Ephrath, J.E., Maman, S., Blumberg, D.G.,
Monitoring Tree Population Dynamics In Arid Zone Through Multiple Temporal Scales: Integration Of Spatial Analysis, Change Detection And Field Long Term Monitoring,
ISPRS16(B7: 513-515).
DOI Link 1610
BibRef

Eberenz, J., Herold, M., Verbesselt, J., Wijaya, A., Linquist, E., Defourny, P., Gibbs, H., Arino, O., Achard, F.,
Consistent forest change maps 198-2000 from the AVHRR time series: Case studies for South America and Indonesia,
MultiTemp15(1-4)
IEEE DOI 1511
land cover BibRef

Gartner, P., Kleinschmit, B.,
Monitoring forest recovery with change metrics derived from Landsat time series stacks,
MultiTemp15(1-3)
IEEE DOI 1511
forestry BibRef

Symeonakis, E., Higginbottom, T.,
Bush encroachment monitoring using multi-temporal Landsat data and random forests,
Geospatial14(29-35).
DOI Link 1411
BibRef

Perera, K., Herath, S., Apan, A., Tateishi, R.,
Application of MODIS Data to Assess the Latest Forest Cover Changes of Sri Lanka,
AnnalsPRS(I-7), No. 2012, pp. 165-170.
HTML Version. 1209
BibRef

Castilla, G.[Guillermo], Ram, A.[Andrea], Linke, J.[Julia], McDermid, G.[Greg],
Semi-automated generation of a multi-temporal forest depletion layer with the Landcover Change Mapper (LCM),
MultiTemp11(97-100).
IEEE DOI 1109
BibRef

Johansen, K.[Kylie], Johansen, K.[Kasper],
Time-series analysis of rainforest clearing in Sabah, Borneo using Landsat imagery,
MultiTemp11(277-280).
IEEE DOI 1109
BibRef

Ernsta, C., Verhegghen, A., Bodart, C., Mayaux, P., de Wasseige, C., Bararwandika, A., Begoto, G., Mba, F.E.[F. Esono], Ibara, M., Shoko, A.K.[A. Kondjo], Kondjo, H.K.[H. Koy], Makak, J.S., Biang, J.D.M.[J-D. Menomo], Musampa, C., Motogo, R.N.[R. Ncogo], Shu, G.N.[G. Neba], Nkoumakali, B., Ouissikan, C.B., Defourny, P.,
Congo Basin Forest Cover Change Estimate for 1990, 2000 and 2005 by Landsat Interpretation Using an Automated Object-Based Processing Chain,
GEOBIA10(xx-yy).
PDF File. 1007
BibRef

Verhegghen, A., Ernst, C., Defourny, P., Beuchle, R.,
Automated Land Cover Mapping and Independent Change Detection in Tropical Forest Using Multi-Temporal High Resolution Data Set,
GEOBIA10(xx-yy).
PDF File. 1007
BibRef

Huang, C.Q.[Cheng-Quan],
Automated Forest Cover Change Analysis Using Landsat Observations,
VCGVA09(xx-yy). 0910
BibRef

Hese, S., Schmullius, C.,
Object context information for advanced forest change classification strategies,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Desclee, B., de Wasseige, C., Bogaert, P., Defourny, P.,
Tropical forest monitoring by object-based change detection: Towards an automated method in an operational perspective,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Heikkonen, J., Varjo, J., Vehtari, A.,
Forest Change Detection via Landsat TM Difference Features,
SCIA99(Remote Sensing). BibRef 9900

Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Forest Disturbance, Regeneration, Regrowth .


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