22.5.9.4 Forest Extraction, Forest Analysis

Chapter Contents (Back)
Forest. See also Trees, Forest Canopy Analysis. See also Trees, Forest, Stem Volume, Biomass Measurements. See also Forest Fire Evaluation, Wildfire Analysis, Fire Detection, Fire Damage Assessment. See also Mangrove Analysis.

Sayn-Wittgenstein, L.,
Patterns of spatial variation in forests and other natural populations,
PR(2), No. 4, December 1970, pp. 245-248.
Elsevier DOI 0309
BibRef

Holopainen, M., Wang, G.X.,
The Calibration of Digitized Aerial Photographs for Forest Stratification,
JRS(19), No. 4, March 10 1998, pp. 677-696. 9803
BibRef

Varekamp, C., Hoekman, D.H.,
High-resolution InSAR image simulation for forest canopies,
GeoRS(40), No. 7, July 2002, pp. 1648-1655.
IEEE Top Reference. 0210
BibRef

Pu, R.[Ruiliang], Gong, P.[Peng], Biging, G.S., Larrieu, M.R.,
Extraction of red edge optical parameters from Hyperion data for estimation of forest leaf area index,
GeoRS(41), No. 4, April 2003, pp. 916-921.
IEEE Abstract. 0307
BibRef

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

Fang, H.L.[Hong-Liang], Liang, S.L.[Shun-Lin],
Retrieving leaf area index with a neural network method: simulation and validation,
GeoRS(41), No. 9, September 2003, pp. 2052-2062.
IEEE Abstract. 0310
BibRef

Vincini, M., Frazzi, E.,
Multitemporal evaluation of topographic normalization methods on Deciduous Forest TM Data,
GeoRS(41), No. 11, November 2003, pp. 2586-2590.
IEEE Abstract. 0311
BibRef

Franklin, S.E., Lavigne, M.B., Moskal, L.M., Wulder, M.A., and McCaffrey, T.M.,
Interpretation of partial harvest forest conditions in New Brunswick using Landsat TM enhanced wetness difference imagery (EWDI),
Can. J. Remote Sens.(27), 2001, pp. 118-128. BibRef 0100

Richardson, J.J.[Jeffrey J.], Moskal, L.M.[L. Monika],
An Integrated Approach for Monitoring Contemporary and Recruitable Large Woody Debris,
RS(8), No. 9, 2016, pp. 778.
DOI Link 1610
BibRef

Nelson, T.[Trisalyn], Boots, B.[Barry], Wulder, M.[Mike], Feick, R.[Rob],
Predicting Forest Age Classes from High Spatial Resolution Remotely Sensed Imagery Using Voronoi Polygon Aggregation,
GeoInfo(8), No. 2, June 2004, pp. 143-155.
DOI Link 0403
BibRef

Lipowezky, U.[Uri],
Groves decipherment from space photos using prototype matching,
PRL(25), No. 13, 1 October 2004, pp. 1479-1489.
Elsevier DOI 0410
BibRef

Santoro, M., Askne, J., Dammert, P.B.G.,
Tree height influence on ERS interferometric phase in boreal forest,
GeoRS(43), No. 2, February 2005, pp. 207-217.
IEEE Abstract. 0501
BibRef

Askne, J., Santoro, M.,
Multitemporal Repeat Pass SAR Interferometry of Boreal Forests,
GeoRS(43), No. 6, June 2005, pp. 1219-1228.
IEEE Abstract. 0506
BibRef
Earlier: Add A3, A4: Smith, G., Fransson, J.E.S., GeoRS(41), No. 7, July 2003, pp. 1540-1550.
IEEE Abstract. 0308
BibRef

Gislason, P.O.[Pall Oskar], Benediktsson, J.A.[Jon Atli], Sveinsson, J.R.[Johannes R.],
Random Forests for land cover classification,
PRL(27), No. 4, March 2006, pp. 294-300.
Elsevier DOI Random Forests; Classification; Decision trees; Multisource remote sensing data 0604
BibRef

Izzawati, Wallington, E.D., Woodhouse, I.H.,
Forest Height Retrieval From Commercial X-Band SAR Products,
GeoRS(44), No. 4, April 2006, pp. 863-870.
IEEE DOI 0604
BibRef

Cheng, L.[Li], Caelli, T.M., Sanchez-Azofeifa, A.[Arturo],
Component Optimization for Image Understanding: A Bayesian Approach,
PAMI(28), No. 5, May 2006, pp. 684-693.
IEEE DOI 0604
Integrate segmentation/annotation, 3D sensing (stereo) and 3D fitting within a Bayesian framework. Apply to forest inventory. See also Bayesian Stereo Matching. BibRef

Cheng, L.[Li], Caelli, T.M.[Terry M.],
Forestry Scene Geometry Estimation Via Statistical Learning,
LCV04(103).
IEEE DOI 0406
BibRef

Trias-Sanz, R.[Roger],
Texture Orientation and Period Estimator for Discriminating Between Forests, Orchards, Vineyards, and Tilled Fields,
GeoRS(44), No. 10, October 2006, pp. 2755-2760.
IEEE DOI 0609
BibRef

Trias-Sanz, R.[Roger], Boldo, D.[Didier],
A High-Reliability, High-Resolution Method for Land Cover Classification Into Forest and Non-forest,
SCIA05(831-840).
Springer DOI 0506
BibRef

Simard, M., Saatchi, S.S., de Grandi, G.,
The Use of Decision Tree and Multiscale Texture for Classification of JERS-1 SAR Data over Tropical Forest,
GeoRS(38), No. 5, September 2000, pp. 2310-2321.
IEEE Top Reference. 0010
BibRef

Chubey, M.S.[Michael S.], Franklin, S.E.[Steven E.], Wulder, M.A.[Michael A.],
Object-based Analysis of Ikonos-2 Imagery for Extraction of Forest Inventory Parameters,
PhEngRS(72), No. 4, April 2006, pp. 383-394.
WWW Link. 0610
A new approach for extracting forest inventory parameters from high spatial resolution satellite imagery based on analysis of image objects. BibRef

Musy, R.[Rebecca], Wynne, R.H.[Randolph H.], Blinn, C.E.[Christine E.], Scrivani, J.A.[John A.], McRoberts, R.[Ronald],
Automated Forest Area Estimation Using Iterative Guided Spectral Class Rejection,
PhEngRS(72), No. 8, August 2006, pp. 949-960.
WWW Link. 0610
USDA Forest Service Inventory and Analysis (FIA) forest area estimates were successfully derived from Landsat EMT+ images classified using an automated hybrid classifier. BibRef

Phillips, R.D., Watson, L.T., Wynne, R.H., Ramakrishnan, N.,
Continuous Iterative Guided Spectral Class Rejection Classification Algorithm,
GeoRS(50), No. 6, June 2012, pp. 2303-2317.
IEEE DOI 1205
BibRef

Phillips, R.D., Blinn, C.E., Watson, L.T., Wynne, R.H.,
An Adaptive Noise-Filtering Algorithm for AVIRIS Data With Implications for Classification Accuracy,
GeoRS(47), No. 9, September 2009, pp. 3168-3179.
IEEE DOI 0909
BibRef

Vaiphasa, C.[Chaichoke], Skidmore, A.K.[Andrew K.], de Boer, W.F.[Willem F.],
A post-classifier for mangrove mapping using ecological data,
PandRS(61), No. 1, October 2006, pp. 1-10.
Elsevier DOI 0610
expert system; multispectral; remote sensing; vegetation BibRef

Wang, Z., Boesch, R.,
Color- and Texture-Based Image Segmentation for Improved Forest Delineation,
GeoRS(45), No. 10, October 2007, pp. 3055-3062.
IEEE DOI 0711
BibRef

Tottrup, C.[Christian],
Forest and Land Cover Mapping in a Tropical Highland Region,
PhEngRS(73), No. 9, September 2007, pp. 1057-1066.
WWW Link. 0709
Tropical forest and land-cover classes within a topographically complex area are mapped from a terrain corrected SPOT HRVIR image and using linear mixture modeling in combination with a decision tree classifier. 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

Potere, D.[David], Woodcock, C.[Curtis], Schneider, A.[Annemarie], Ozdogan, M.[Mutlu], Baccini, A.[Alessandro],
Patterns in Forest Clearing Along the Appalachian Trail Corridor,
PhEngRS(73), No. 7, July 2007, pp. 783-792.
WWW Link. 0709
The GeoCover Landsat dataset was used to estimate that 75,000 hectares of forest were cleared on a corridor 3,500 km long. BibRef

Nelson, M.[Mark], Moisen, G.[Gretchen], Finco, M.[Mark], Brewer, K.[Ken],
Forest Inventory and Analysis in the United States: Remote Sensing and Geospatial Activities (Adobe PDF 202Kb),
PhEngRS(73), No. 7, July 2007, pp. 729-735.
WWW Link. 0709
BibRef

Walker, J.S.[Jason S.], Briggs, J.M.[John M.],
An Object-oriented Approach to Urban Forest Mapping in Phoenix,
PhEngRS(73), No. 5, May 2007, pp. 577-584.
WWW Link. 0709
A object-oriented approach technique for regular monitoring of structural vegetation detection using high-resolution, color imagery. BibRef

Garestier, F., Dubois-Fernandez, P.C., Papathanassiou, K.P.,
Pine Forest Height Inversion Using Single-Pass X-Band PolInSAR Data,
GeoRS(46), No. 1, January 2008, pp. 59-68.
IEEE DOI 0712
BibRef

Garestier, F., Dubois-Fernandez, P.C., Champion, I.,
Forest Height Inversion Using High-Resolution P-Band Pol-InSAR Data,
GeoRS(46), No. 11, November 2008, pp. 3544-3559.
IEEE DOI 0812
BibRef

Garestier, F., Le Toan, T.,
Forest Modeling For Height Inversion Using Single-Baseline InSAR/Pol-InSAR Data,
GeoRS(48), No. 3, March 2010, pp. 1528-1539.
IEEE DOI 1003
BibRef

Mallinis, G.[Georgios], Koutsias, N.[Nikos], Tsakiri-Strati, M.[Maria], Karteris, M.[Michael],
Object-based classification using Quickbird imagery for delineating forest vegetation polygons in a Mediterranean test site,
PandRS(63), No. 2, March 2008, pp. 237-250.
Elsevier DOI 0803
Forest classification; Texture; Quickbird; Object-based; Multi-scale BibRef

Mallinis, G., Karamanolis, D., Karteris, M., Gitas, I.,
An object oriented approach for the discrimination of forest areas under the criteria of forest legislation in Greece using very high resolution data,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Haapanen, R.[Reija], Tuominen, S.[Sakari],
Data Combination and Feature Selection for Multisource Forest Inventory,
PhEngRS(74), No. 7, July 2008, pp. 869-880.
WWW Link. 0804
Feature selection and weighting among satellite image features and aerial photograph spectral and textural features were used to boost the accuracy when estimating forest variables. 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

Lee, H.,
Mapping Deforestation and Age of Evergreen Trees by Applying a Binary Coding Method to Time-Series Landsat November Images,
GeoRS(46), No. 11, November 2008, pp. 3926-3936.
IEEE DOI 0812
BibRef

Lippitt, C.D.[Christopher D.], Rogan, J.[John], Li, Z.[Zhe], Eastman, J.R.[J. Ronald], Jones, T.G.[Trevor G.],
Mapping Selective Logging in Mixed Deciduous Forest: A Comparison of Machine Learning Algorithms,
PhEngRS(74), No. 10, October 2008, pp. 1201-1212.
WWW Link. 0804
A back-propagation multilayer perceptron, self-organizing map, fuzzy ARTMAP, and gini and entropy univariate decision trees compared in terms of their ability to cope with small, unrepresentative, and variable training sets. BibRef

Peuhkurinen, J.[Jussi], Maltamo, M.[Matti], Vesa, L.[Lauri], Packalén, P.[Petteri],
Estimation of Forest Stand Characteristics Using Spectral Histograms Derived from an Ikonos Satellite Image,
PhEngRS(74), No. 11, November 2008, pp. 1335-1342.
WWW Link. 0804
The potential of Ikonos satellite images for estimating forest stand characteristics studied in boreal conditions. BibRef

Kushida, K.[Keiji], Yoshino, K.[Kunihiko], Nagano, T.[Toshihide], Ishida, T.[Tomoyasu],
Automated 3D Forest Surface Model Extraction from Balloon Stereo Photographs,
PhEngRS(75), No. 1, January 2009, pp. 25-37.
WWW Link. 0902
An automated forest digital surface model (DSM) extraction method from balloon stereo photographs upgraded through the evaluations of the image matching accuracy and forest surface height estimation of a tropical peat swamp forest in Narathiwat, Thailand BibRef

de Grandi, G.D., Lucas, R.M., Kropacek, J.,
Analysis by Wavelet Frames of Spatial Statistics in SAR Data for Characterizing Structural Properties of Forests,
GeoRS(47), No. 2, February 2009, pp. 494-507.
IEEE DOI 0903
BibRef

Yang, C.H.[Cheng-Hai], Everitt, J.H.[James H.], Fletcher, R.S.[Reginald S.], Jensen, R.R.[Ryan R.], Mausel, P.W.[Paul W.],
Evaluating AISA+ Hyperspectral Imagery for Mapping Black Mangrove along the South Texas Gulf Coast,
PhEngRS(75), No. 4, April 2009, pp. 425-436.
WWW Link. 0903
Airborne hyperspectral imagery combined with image transformation and classification techniques can be a useful tool for monitoring and mapping black mangrove distributions in coastal environments. BibRef

Johansen, K.[Kasper], Phinn, S.R.[Stuart R.], Witte, C.[Christian], Philip, S.[Seonaid], Newton, L.[Lisa],
Mapping Banana Plantations from Object-oriented Classification of SPOT-5 Imagery,
PhEngRS(75), No. 9, September 2009, pp. 1069-1082.
WWW Link. 0910
The extent of banana plantations was mapped using panchromatic and multispectral SPOT-5 imagery and object-oriented segmentation and classification in Definiens Professional 5. BibRef

Garestier, F., Dubois-Fernandez, P.C., Guyon, D., Le Toan, T.,
Forest Biophysical Parameter Estimation Using L- and P-Band Polarimetric SAR Data,
GeoRS(47), No. 10, October 2009, pp. 3379-3388.
IEEE DOI 0910
BibRef

Cuevas, G.[Gabriela], Benítez, J.[Jorge], Vega-Guzmán, Á.[Álvaro], Coria-Tapia, V.[Valdemar],
An Accuracy Index with Positional and Thematic Fuzzy Bounds for Land-use / Land-cover Maps,
PhEngRS(75), No. 7, July 2009, pp. 789-806.
WWW Link. 0910
A framework for assessing taxonomically detailed landcover/land-use maps at regional scale is proposed and illustrated on the Mexican National Forest Inventory map of a subtropical densely forested area. BibRef

Kim, M.H.[Min-Ho], Madden, M.[Marguerite], Warner, T.A.[Timothy A.],
Forest Type Mapping using Object-specific Texture Measures from Multispectral Ikonos Imagery: Segmentation Quality and Image Classification Issues,
PhEngRS(75), No. 7, July 2009, pp. 819-830.
WWW Link. 0910
The effect of scale and associated segmentation quality on classification results of forest types in a National Park, U.S. was investigated with spectral and spatial information of multispectral Ikonos imagery. BibRef

Tebaldini, S.,
Algebraic Synthesis of Forest Scenarios From Multibaseline PolInSAR Data,
GeoRS(47), No. 12, December 2009, pp. 4132-4142.
IEEE DOI 0912
BibRef

Bellez, S., Dahon, C., Roussel, H.,
Analysis of the Main Scattering Mechanisms in Forested Areas: An Integral Representation Approach for Monostatic Radar Configurations,
GeoRS(47), No. 12, December 2009, pp. 4153-4166.
IEEE DOI 0912
BibRef

Zhang, J.P.[Jun-Ping], Zhang, X.[Xiao], Zou, B.[Bin], Chen, D.L.[Dong-Lai],
On Hyperspectral Image Simulation of a Complex Woodland Area,
GeoRS(48), No. 11, November 2010, pp. 3889-3902.
IEEE DOI 1011
BibRef

Zhang, J.P.[Jun-Ping], Chen, J.W.[Jia-Wei], Zou, B.[Bin], Zhang, Y.[Ye],
Modeling and Simulation of Polarimetric Hyperspectral Imaging Process,
GeoRS(50), No. 6, June 2012, pp. 2238-2253.
IEEE DOI 1205
BibRef

Zhang, J.P.[Jun-Ping], Zhang, Y.[Ye], Zou, B.[Bin], Zhou, T.X.[Ting-Xian],
Fusion Classification of Hyperspectral Image Based on Adaptive Subspace Decomposition,
ICIP00(Vol III: 472-475).
IEEE DOI 0008
BibRef

Zhang, L.M.[La-Mei], Zou, B.[Bin], Zhang, J.P.[Jun-Ping], Zhang, Y.[Ye],
Inversion of Forest Parameters Based on Genetic Algorithm using L-Band Polinsar Data,
ICIP06(2325-2328).
IEEE DOI 0610
BibRef

Pisek, J., Chen, J.M., Miller, J.R., Freemantle, J.R., Peltoniemi, J.I., Simic, A.,
Mapping Forest Background Reflectance in a Boreal Region Using Multiangle Compact Airborne Spectrographic Imager Data,
GeoRS(48), No. 1, January 2010, pp. 499-510.
IEEE DOI 1001
BibRef

Simic, A., Chen, J.M., Freemantle, J., Miller, J.R., Pisek, J.,
Improving Clumping and LAI Algorithms Based on Multiangle Airborne Imagery and Ground Measurements,
GeoRS(48), No. 4, April 2010, pp. 1742-1759.
IEEE DOI 1003
LAI: Leaf Area Index BibRef

Pisek, J.[Jan], Govind, A.[Ajit], Arndt, S.K.[Stefan K.], Hocking, D.[Darren], Wardlaw, T.J.[Timothy J.], Fang, H.L.[Hong-Liang], Matteucci, G.[Giorgio], Longdoz, B.[Bernard],
Intercomparison of clumping index estimates from POLDER, MODIS, and MISR satellite data over reference sites,
PandRS(101), No. 1, 2015, pp. 47-56.
Elsevier DOI 1503
Multi-angle remote sensing BibRef

Honkavaara, E.[Eija], Markelin, L.[Lauri], Hakala, T.[Teemu], Peltoniemi, J.I.[Jouni I.],
The Metrology of Directional, Spectral Reflectance Factor Measurements Based on Area Format Imaging by UAVs,
PFG(2014), No. 3, 2014, pp. 175-188.
DOI Link 1407
BibRef
Earlier: A1, A3, A2, A4:
Metrology of Image Processing in Spectral Reflectance Measurement by UAV,
EuroCOW14(53-58).
DOI Link 1404
BibRef

Huang, Y., Ferro-Famil, L., Reigber, A.,
Under-Foliage Object Imaging Using SAR Tomography and Polarimetric Spectral Estimators,
GeoRS(50), No. 6, June 2012, pp. 2213-2225.
IEEE DOI 1205
BibRef

Tebaldini, S.,
Single and Multipolarimetric SAR Tomography of Forested Areas: A Parametric Approach,
GeoRS(48), No. 5, May 2010, pp. 2375-2387.
IEEE DOI 1006
BibRef

Verrelst, J., Clevers, J.G.P.W., Schaepman, M.E.,
Merging the Minnaert-k Parameter With Spectral Unmixing to Map Forest Heterogeneity With CHRIS/PROBA Data,
GeoRS(48), No. 11, November 2010, pp. 4014-4022.
IEEE DOI 1011
BibRef

Mustafa, Y.T., van Laake, P.E., Stein, A.,
Bayesian Network Modeling for Improving Forest Growth Estimates,
GeoRS(49), No. 2, February 2011, pp. 639-649.
IEEE DOI 1102
BibRef

López-Martínez, C.[Carlos], Fŕbregas, X.[Xavier], Pipia, L.[Luca],
Forest parameter estimation in the Pol-InSAR context employing the multiplicative-additive speckle noise model,
PandRS(66), No. 5, September 2011, pp. 597-607.
Elsevier DOI 1110
Synthetic aperture radar; Polarimetric interferometry; Polarimetry; Coherence; Speckle BibRef

Antropov, O., Rauste, Y., Hame, T.,
Volume Scattering Modeling in PolSAR Decompositions: Study of ALOS PALSAR Data Over Boreal Forest,
GeoRS(49), No. 10, October 2011, pp. 3838-3848.
IEEE DOI 1110
BibRef

Frey, O., Meier, E.,
3-D Time-Domain SAR Imaging of a Forest Using Airborne Multibaseline Data at L- and P-Bands,
GeoRS(49), No. 10, October 2011, pp. 3660-3664.
IEEE DOI 1110
BibRef

Frey, O., Meier, E.,
Analyzing Tomographic SAR Data of a Forest With Respect to Frequency, Polarization, and Focusing Technique,
GeoRS(49), No. 10, October 2011, pp. 3648-3659.
IEEE DOI 1110
BibRef

Hou, Z.Y.[Zheng-Yang], Xu, Q.[Qing], Tokola, T.[Timo],
Use of ALS, Airborne CIR and ALOS AVNIR-2 data for estimating tropical forest attributes in Lao PDR,
PandRS(66), No. 6, November 2011, pp. 776-786.
Elsevier DOI 1112
ALS; Airborne CIR; ALOS AVNIR-2; Tropical forest; Forest monitoring BibRef

Xu, Q.[Qing], Hou, Z.Y.[Zheng-Yang], Tokola, T.[Timo],
Relative radiometric correction of multi-temporal ALOS AVNIR-2 data for the estimation of forest attributes,
PandRS(68), No. 1, March 2012, pp. 69-78.
Elsevier DOI 1204
Multi-temporal images; Pseudo-invariant features; Multivariate alteration detection (MAD) transformation; Bi-temporal principle component analysis; Local radiometric correction; Estimation accuracy BibRef

Manninen, T., Korhonen, L., Voipio, P., Lahtinen, P., Stenberg, P.,
Airborne Estimation of Boreal Forest LAI in Winter Conditions: A Test Using Summer and Winter Ground Truth,
GeoRS(50), No. 1, January 2012, pp. 68-74.
IEEE DOI 1201
BibRef

Manninen, T., Korhonen, L., Voipio, P., Lahtinen, P., Stenberg, P.,
Leaf Area Index (LAI) Estimation of Boreal Forest Using Wide Optics Airborne Winter Photos,
RS(1), No. 4, December 2009, pp. 1380-1394.
DOI Link 1203
BibRef

Manninen, T., Stenberg, P., Rautiainen, M., Voipio, P.,
Leaf Area Index Estimation of Boreal and Subarctic Forests Using VV/HH ENVISAT/ASAR Data of Various Swaths,
GeoRS(51), No. 7, 2013, pp. 3899-3909.
IEEE DOI 1307
Forestry; microwave measurements BibRef

Lehmann, E.A., Caccetta, P.A., Zhou, Z.S.[Zheng-Shu], McNeill, S.J., Wu, X.L.[Xiao-Liang], Mitchell, A.L.,
Joint Processing of Landsat and ALOS-PALSAR Data for Forest Mapping and Monitoring,
GeoRS(50), No. 1, January 2012, pp. 55-67.
IEEE DOI 1201
BibRef

Xiao, X., Biradar, C., Czarnecki, C., Alabi, T., Keller, M.,
A Simple Algorithm for Large-Scale Mapping of Evergreen Forests in Tropical America, Africa and Asia,
RS(1), No. 3, September 2009, pp. 355-374.
DOI Link 1203
BibRef

Zahira, S., Abderrahmane, H., Mederbal, K., Frederic, D.,
Mapping Latent Heat Flux in the Western Forest Covered Regions of Algeria Using Remote Sensing Data and a Spatialized Model,
RS(1), No. 4, December 2009, pp. 795-817.
DOI Link 1203
BibRef

Hassan, Q., Bourque, C.,
Spatial Enhancement of MODIS-based Images of Leaf Area Index: Application to the Boreal Forest Region of Northern Alberta, Canada,
RS(2), No. 1, January 2010, pp. 278-289.
DOI Link 1203
BibRef

Al-Hamdan, M., Cruise, J., Rickman, D., Quattrochi, D.,
Effects of Spatial and Spectral Resolutions on Fractal Dimensions in Forested Landscapes,
RS(2), No. 3, March 2010, pp. 611-640.
DOI Link 1203
BibRef

Parent, M., Verbyla, D.,
The Browning of Alaska's Boreal Forest,
RS(2), No. 12, December 2010, pp. 2729-2747.
DOI Link 1203
BibRef

Bandara, K., Samarakoon, L., Shrestha, R., Kamiya, Y.,
Automated Generation of Digital Terrain Model using Point Clouds of Digital Surface Model in Forest Area,
RS(3), No. 5, May 2011, pp. 845-858.
DOI Link 1203
BibRef

Gómez, C., Wulder, M., Montes, F., Delgado, J.,
Modeling Forest Structural Parameters in the Mediterranean Pines of Central Spain using QuickBird-2 Imagery and Classification and Regression Tree Analysis (CART),
RS(4), No. 1, January 2012, pp. 135-159.
DOI Link 1203
BibRef

Propastin, P., Kappas, M.,
Retrieval of Coarse-Resolution Leaf Area Index over the Republic of Kazakhstan Using NOAA AVHRR Satellite Data and Ground Measurements,
RS(4), No. 1, January 2012, pp. 220-246.
DOI Link 1203
BibRef

Hashimoto, H., Wang, W., Milesi, C., White, M., Ganguly, S., Gamo, M., Hirata, R., Myneni, R., Nemani, R.,
Exploring Simple Algorithms for Estimating Gross Primary Production in Forested Areas from Satellite Data,
RS(4), No. 1, January 2012, pp. 303-326.
DOI Link 1203
BibRef

Hashimoto, H., Wang, W., Milesi, C., Xiong, J., Ganguly, S., Zhu, Z., Nemani, R.,
Structural Uncertainty in Model-Simulated Trends of Global Gross Primary Production,
RS(5), No. 3, March 2013, pp. 1258-1273.
DOI Link 1304
BibRef

Pekin, B., Macfarlane, C.,
Measurement of Crown Cover and Leaf Area Index Using Digital Cover Photography and Its Application to Remote Sensing,
RS(1), No. 4, December 2009, pp. 1298-1320.
DOI Link 1203
BibRef

Kuenzer, C.[Claudia], Bluemel, A.[Andrea], Gebhardt, S.[Steffen], Quoc, T.V.[Tuan Vo], Dech, S.[Stefan],
Remote Sensing of Mangrove Ecosystems: A Review,
RS(3), No. 5, May 2011, pp. 878-928.
DOI Link 1203
Award, Remote Sensing, Review. 2015. BibRef

Alatorre, L., Sánchez-Andrés, R., Cirujano, S., Beguería, S., Sánchez-Carrillo, S.,
Identification of Mangrove Areas by Remote Sensing: The ROC Curve Technique Applied to the Northwestern Mexico Coastal Zone Using Landsat Imagery,
RS(3), No. 8, August 2011, pp. 1568-1583.
DOI Link 1203
BibRef

Kamal, M., Phinn, S.R.,
Hyperspectral Data for Mangrove Species Mapping: A Comparison of Pixel-Based and Object-Based Approach,
RS(3), No. 10, October 2011, pp. 2222-2242.
DOI Link 1203
BibRef

Heumann, B.,
An Object-Based Classification of Mangroves Using a Hybrid Decision Tree: Support Vector Machine Approach,
RS(3), No. 11, November 2011, pp. 2440-2460.
DOI Link 1203
BibRef

Carter, G., Lucas, K., Blossom, G., Lassitter, C., Holiday, D., Mooneyhan, D., Fastring, D., Holcombe, T., Griffith, J.,
Remote Sensing and Mapping of Tamarisk along the Colorado River, USA: A Comparative Use of Summer-Acquired Hyperion, Thematic Mapper and QuickBird Data,
RS(1), No. 3, September 2009, pp. 318-329.
DOI Link 1203
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Hassan, Q., Bourque, C.,
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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,
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Peduzzi, A., Wynne, R., Thomas, V., Nelson, R., Reis, J., Sanford, M.,
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Clerici, N., Weissteiner, C., Gerard, F.,
Exploring the Use of MODIS NDVI-Based Phenology Indicators for Classifying Forest General Habitat Categories,
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Stagakis, S., González-Dugo, V., Cid, P., Guillén-Climent, M.L., Zarco-Tejada, P.J.,
Monitoring water stress and fruit quality in an orange orchard under regulated deficit irrigation using narrow-band structural and physiological remote sensing indices,
PandRS(71), No. 1, July 2012, pp. 47-61.
Elsevier DOI 1208
Water stress; Remote sensing; Narrow-band indices; Fruit quality; Regulated deficit; PRI BibRef

Hildebrandt, G.[Gerd],
The Beginnings of Aerial Photogrammetry and Interpretation in German Forestry after 1945,
PFG(2010), No. 4, 2010, pp. 235-242.
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Detection and Classification of Bark Beetle Infestation in Pure Norway Spruce Stands with Multi-temporal RapidEye Imagery and Data Mining Techniques,
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Franken, F.[Frank], Hoffmann, K.[Karina],
Requirements for Digital / Digitized Aerial Imagery A Manual of the Working Group of Forest Interpreters of Aerial Photographs,
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Buck, G.[Gudrun], Seitz, R.[Rudolf], Troycke, A.[Armin],
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Tits, L.[Laurent], De Keersmaecker, W.[Wanda], Somers, B.[Ben], Asner, G.P.[Gregory P.], Farifteh, J.[Jamshid], Coppin, P.[Pol],
Hyperspectral shape-based unmixing to improve intra- and interclass variability for forest and agro-ecosystem monitoring,
PandRS(74), No. 1, November 2012, pp. 163-174.
Elsevier DOI 1212
Hyperspectral; Spectral unmixing; Shape-based metrics; Agriculture; Forestry; Virtual reality 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.
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Heiskanen, J.[Janne], Rautiainen, M.[Miina], Stenberg, P.[Pauline], Mőttus, 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

Mello, M.P., Vieira, C.A.O., Rudorff, B.F.T., Aplin, P., Santos, R.D.C., Aguiar, D.A.,
STARS: A New Method for Multitemporal Remote Sensing,
GeoRS(51), No. 4, April 2013, pp. 1897-1913.
IEEE DOI 1304
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Mello, M.P.[Marcio Pupin], Martins, F.S.R.V.[Flora S.R.V.], Sato, L.Y.[Luciane Y.], Cantinho, R.Z.[Roberta Z.], Aguiar, D.A.[Daniel A.], Rudorff, B.F.T.[Bernardo F.T.], Santos, R.D.C.[Rafael D.C.],
Spectral-Temporal Analysis by Response Surface applied to detect deforestation in the Brazilian Amazon,
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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., Orka, H.O., Gobakken, T., Gianelle, D., Naesset, E.,
Tree Species Classification in Boreal Forests With Hyperspectral Data,
GeoRS(51), No. 5, May 2013, pp. 2632-2645.
IEEE DOI 1305
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Couturier, S., Gastellu-Etchegorry, J.P., Martin, E., Patino, P.,
Building a Forward-Mode Three-Dimensional Reflectance Model for Topographic Normalization of High-Resolution (1-5 m) Imagery: Validation Phase in a Forested Environment,
GeoRS(51), No. 7, 2013, pp. 3910-3921.
IEEE DOI 1307
Atmospheric measurements; forest classification; topographic correction BibRef

Banskota, A.[Asim], Wynne, R.H.[Randolph H.], Thomas, V.A.[Valerie A.], Serbin, S.P.[Shawn P.], Kayastha, N.[Nilam], Gastellu-Etchegorry, J.P.[Jean P.], Townsend, P.A.[Philip A.],
Investigating the Utility of Wavelet Transforms for Inverting a 3-D Radiative Transfer Model Using Hyperspectral Data to Retrieve Forest LAI,
RS(5), No. 6, 2013, pp. 2639-2659.
DOI Link 1307
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Mellor, A.[Andrew], Haywood, A.[Andrew], Stone, C.[Christine], Jones, S.[Simon],
The Performance of Random Forests in an Operational Setting for Large Area Sclerophyll Forest Classification,
RS(5), No. 6, 2013, pp. 2838-2856.
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Herrmann, S.M.[Stefanie M.], Wickhorst, A.J.[Andrew J.], Marsh, S.E.[Stuart E.],
Estimation of Tree Cover in an Agricultural Parkland of Senegal Using Rule-Based Regression Tree Modeling,
RS(5), No. 10, 2013, pp. 4900-4918.
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Kobayashi, T.[Toshiyuki], Tsend-Ayush, J.[Javzandulam], Tateishi, R.[Ryutaro],
A New Tree Cover Percentage Map in Eurasia at 500 m Resolution Using MODIS Data,
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Ni, W., Sun, G., Ranson, K.J., Zhang, Z., He, Y., Huang, W., Guo, Z.,
Model-Based Analysis of the Influence of Forest Structures on the Scattering Phase Center at L-Band,
GeoRS(52), No. 7, July 2014, pp. 3937-3946.
IEEE DOI 1403
Analytical models BibRef

Forster, M., Kleinschmit, B.,
Significance Analysis of Different Types of Ancillary Geodata Utilized in a Multisource Classification Process for Forest Identification in Germany,
GeoRS(52), No. 6, June 2014, pp. 3453-3463.
IEEE DOI 1403
Accuracy BibRef

Li, C.C.[Cong-Cong], Wang, J.[Jie], Hu, L.[Luanyun], Yu, L.[Le], Clinton, N.[Nicholas], Huang, H.[Huabing], Yang, J.[Jun], Gong, P.[Peng],
A Circa 2010 Thirty Meter Resolution Forest Map for China,
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Attarchi, S.[Sara], Gloaguen, R.[Richard],
Classifying Complex Mountainous Forests with L-Band SAR and Landsat Data Integration: A Comparison among Different Machine Learning Methods in the Hyrcanian Forest,
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DOI Link 1407
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Fan, W.L.[Wei-Liang], Chen, J.M., Ju, W.M.[Wei-Min], Nesbitt, N.,
Hybrid Geometric Optical-Radiative Transfer Model Suitable for Forests on Slopes,
GeoRS(52), No. 9, Sept 2014, pp. 5579-5586.
IEEE DOI 1407
geophysical techniques BibRef

Podest, E., McDonald, K.C., Kimball, J.S.,
Multisensor Microwave Sensitivity to Freeze/Thaw Dynamics Across a Complex Boreal Landscape,
GeoRS(52), No. 11, November 2014, pp. 6818-6828.
IEEE DOI 1407
Backscatter BibRef

Heenkenda, M.K.[Muditha K.], Joyce, K.E.[Karen E.], Maier, S.W.[Stefan W.], Bartolo, R.[Renee],
Mangrove Species Identification: Comparing WorldView-2 with Aerial Photographs,
RS(6), No. 7, 2014, pp. 6064-6088.
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Brolly, M.[Matthew], Woodhouse, I.H.[Iain H.],
Long Wavelength SAR Backscatter Modelling Trends as a Consequence of the Emergent Properties of Tree Populations,
RS(6), No. 8, 2014, pp. 7081-7109.
DOI Link 1410
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Liang, L.[Liang], Schwartz, M.D., Wang, Z.[Zhuosen], Gao, F.[Feng], Schaaf, C.B., Tan, B.[Bin], Morisette, J.T., Zhang, X.Y.[Xiao-Yang],
A Cross Comparison of Spatiotemporally Enhanced Springtime Phenological Measurements From Satellites and Ground in a Northern U.S. Mixed Forest,
GeoRS(52), No. 12, December 2014, pp. 7513-7526.
IEEE DOI 1410
remote sensing BibRef

Beguet, B.[Benoit], Guyon, D.[Dominique], Boukir, S.[Samia], Chehata, N.[Nesrine],
Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery,
PandRS(96), No. 1, 2014, pp. 164-178.
Elsevier DOI 1410
Forestry 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.
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Getzin, S.[Stephan], Nuske, R.S.[Robert S.], Wiegand, K.[Kerstin],
Using Unmanned Aerial Vehicles (UAV) to Quantify Spatial Gap Patterns in Forests,
RS(6), No. 8, 2014, pp. 6988-7004.
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Torabzadeh, H.[Hossein], Morsdorf, F.[Felix], Schaepman, M.E.[Michael E.],
Fusion of imaging spectroscopy and airborne laser scanning data for characterization of forest ecosystems: A review,
PandRS(97), No. 1, 2014, pp. 25-35.
Elsevier DOI 1410
Forest ecosystems 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
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Bakula, M., Przestrzelski, P., Kazmierczak, R.,
Reliable Technology of Centimeter GPS/GLONASS Surveying in Forest Environments,
GeoRS(53), No. 2, February 2015, pp. 1029-1038.
IEEE DOI 1411
Global Positioning System BibRef

Andre, F., Jonard, M., Lambot, S.,
Non-Invasive Forest Litter Characterization Using Full-Wave Inversion of Microwave Radar Data,
GeoRS(53), No. 2, February 2015, pp. 828-840.
IEEE DOI 1411
ground penetrating radar BibRef

Zhang, C.H.[Chun-Hua], Kovacs, J.M.[John M.], Liu, Y.[Yali], Flores-Verdugo, F.[Francisco], Flores-de-Santiago, F.[Francisco],
Separating Mangrove Species and Conditions Using Laboratory Hyperspectral Data: A Case Study of a Degraded Mangrove Forest of the Mexican Pacific,
RS(6), No. 12, 2014, pp. 11673-11688.
DOI Link 1412
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Ortega-Terol, D.[Damian], Moreno, M.A.[Miguel A.], Hernández-López, D.[David], Rodríguez-Gonzálvez, P.[Pablo],
Survey and Classification of Large Woody Debris (LWD) in Streams Using Generated Low-Cost Geomatic Products,
RS(6), No. 12, 2014, pp. 11770-11790.
DOI Link 1412
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Yang, W.[Wei], Kobayashi, H.[Hideki], Suzuki, R.[Rikie], Nasahara, K.N.[Kenlo Nishida],
A Simple Method for Retrieving Understory NDVI in Sparse Needleleaf Forests in Alaska Using MODIS BRDF Data,
RS(6), No. 12, 2014, pp. 11936-11955.
DOI Link 1412
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Li, L.[Li], Dong, J.W.[Jin-Wei], Tenku, S.N.[Simon Njeudeng], Xiao, X.M.[Xiang-Ming],
Mapping Oil Palm Plantations in Cameroon Using PALSAR 50-m Orthorectified Mosaic Images,
RS(7), No. 2, 2015, pp. 1206-1224.
DOI Link 1503
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Mallegowda, P.[Paramesha], Rengaian, G.[Ganesan], Krishnan, J.[Jayalakshmi], Niphadkar, M.[Madhura],
Assessing Habitat Quality of Forest-Corridors through NDVI Analysis in Dry Tropical Forests of South India: Implications for Conservation,
RS(7), No. 2, 2015, pp. 1619-1639.
DOI Link 1503
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Chen, B.Q.[Bang-Qian], Wu, Z.X.[Zhi-Xiang], Wang, J.[Jikun], Dong, J.W.[Jin-Wei], Guan, L.M.[Li-Ming], Chen, J.M.[Jun-Ming], Yang, K.[Kai], Xie, G.S.[Gui-Shui],
Spatio-temporal prediction of leaf area index of rubber plantation using HJ-1A/1B CCD images and recurrent neural network,
PandRS(102), No. 1, 2015, pp. 148-160.
Elsevier DOI 1503
Leaf area index 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
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Lu, L.J.[Li-Jun], Xie, W.J.[Wen-Jun], Zhang, J.X.[Ji-Xian], Huang, G.M.[Guo-Man], Li, Q.W.[Qi-Wei], Zhao, Z.[Zheng],
Woodland Extraction from High-Resolution CASMSAR Data Based on Dempster-Shafer Evidence Theory Fusion,
RS(7), No. 4, 2015, pp. 4068-4091.
DOI Link 1505
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Neumann, M.[Mathias], Zhao, M.[Maosheng], Kindermann, G.[Georg], Hasenauer, H.[Hubert],
Comparing MODIS Net Primary Production Estimates with Terrestrial National Forest Inventory Data in Austria,
RS(7), No. 4, 2015, pp. 3878-3906.
DOI Link 1505
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Ginzler, C.[Christian], Hobi, M.L.[Martina L.],
Countrywide Stereo-Image Matching for Updating Digital Surface Models in the Framework of the Swiss National Forest Inventory,
RS(7), No. 4, 2015, pp. 4343-4370.
DOI Link 1505
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Eivazi, A.[Anna], Kolesnikov, A.[Alexander], Junttila, V.[Virpi], Kauranne, T.[Tuomo],
Variance-preserving mosaicing of multiple satellite images for forest parameter estimation: Radiometric normalization,
PandRS(105), No. 1, 2015, pp. 120-127.
Elsevier DOI 1506
Relative normalization BibRef

Fagan, M.E.[Matthew E.], De Fries, R.S.[Ruth S.], Sesnie, S.E.[Steven E.], Arroyo-Mora, J.P.[J. Pablo], Soto, C.[Carlomagno], Singh, A.[Aditya], Townsend, P.A.[Philip A.], Chazdon, R.L.[Robin L.],
Mapping Species Composition of Forests and Tree Plantations in Northeastern Costa Rica with an Integration of Hyperspectral and Multitemporal Landsat Imagery,
RS(7), No. 5, 2015, pp. 5660-5696.
DOI Link 1506
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Ghulam, A.[Abduwasit], Ghulam, O.[Oghlan], Maimaitijiang, M.[Maitiniyazi], Freeman, K.[Karen], Porton, I.[Ingrid], Maimaitiyiming, M.[Matthew],
Remote Sensing Based Spatial Statistics to Document Tropical Rainforest Transition Pathways,
RS(7), No. 5, 2015, pp. 6257-6279.
DOI Link 1506
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Fan, H.[Hui], Fu, X.H.[Xiao-Hua], Zhang, Z.[Zheng], Wu, Q.[Qiong],
Phenology-Based Vegetation Index Differencing for Mapping of Rubber Plantations Using Landsat OLI Data,
RS(7), No. 5, 2015, pp. 6041-6058.
DOI Link 1506
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Yuan, H.[Huili], Ma, R.[Ronghua], Atzberger, C.[Clement], Li, F.[Fei], Loiselle, S.A.[Steven Arthur], Luo, J.[Juhua],
Estimating Forest fAPAR from Multispectral Landsat-8 Data Using the Invertible Forest Reflectance Model INFORM,
RS(7), No. 6, 2015, pp. 7425.
DOI Link 1507
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Basu, S., Ganguly, S., Nemani, R.R., Mukhopadhyay, S., Zhang, G.[Gong], Milesi, C., Michaelis, A., Votava, P., Dubayah, R., Duncanson, L., Cook, B., Yu, Y.F.[Yi-Fan], Saatchi, S., DiBiano, R., Karki, M., Boyda, E., Kumar, U., Li, S.[Shuang],
A Semiautomated Probabilistic Framework for Tree-Cover Delineation From 1-m NAIP Imagery Using a High-Performance Computing Architecture,
GeoRS(53), No. 10, October 2015, pp. 5690-5708.
IEEE DOI 1509
forestry BibRef

Puliti, S.[Stefano], Řrka, H.O.[Hans Ole], Gobakken, T.[Terje], Nćsset, E.[Erik],
Inventory of Small Forest Areas Using an Unmanned Aerial System,
RS(7), No. 8, 2015, pp. 9632.
DOI Link 1509
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Watanabe, M., Motohka, T., Shiraishi, T., Thapa, R.B., Yonezawa, C., Nakamura, K., Shimada, M.,
Multitemporal Fluctuations in L-Band Backscatter From a Japanese Forest,
GeoRS(53), No. 11, November 2015, pp. 5799-5813.
IEEE DOI 1509
remote sensing by radar BibRef

Carreno-Luengo, H.[Hugo], Amčzaga, A.[Adriá], Vidal, D.[David], Olivé, R.[Roger], Munoz, J.F.[Juan Fran], Camps, A.[Adriano],
First Polarimetric GNSS-R Measurements from a Stratospheric Flight over Boreal Forests,
RS(7), No. 10, 2015, pp. 13120.
DOI Link 1511
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Helman, D.[David], Lensky, I.M.[Itamar M.], Tessler, N.[Naama], Osem, Y.[Yagil],
A Phenology-Based Method for Monitoring Woody and Herbaceous Vegetation in Mediterranean Forests from NDVI Time Series,
RS(7), No. 9, 2015, pp. 12314.
DOI Link 1511
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Baghdadi, N.[Nicolas], Zribi, M.[Mehrez], Paloscia, S.[Simonetta], Verhoest, N.E.C.[Niko E. C.], Lievens, H.[Hans], Baup, F.[Frederic], Mattia, F.[Francesco],
Semi-Empirical Calibration of the Integral Equation Model for Co-Polarized L-Band Backscattering,
RS(7), No. 10, 2015, pp. 13626.
DOI Link 1511
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Qin, Y.W.[Yuan-Wei], Xiao, X.M.[Xiang-Ming], Dong, J.W.[Jin-Wei], Zhang, G.[Geli], Shimada, M.[Masanobu], Liu, J.Y.[Ji-Yuan], Li, C.A.[Chung-An], Kou, W.[Weili], Moore, III, B.[Berrien],
Forest cover maps of China in 2010 from multiple approaches and data sources: PALSAR, Landsat, MODIS, FRA, and NFI,
PandRS(109), No. 1, 2015, pp. 1-16.
Elsevier DOI 1512
Forest BibRef

O'Connell, J.[Jerome], Bradter, U.[Ute], Benton, T.G.[Tim G.],
Wide-area mapping of small-scale features in agricultural landscapes using airborne remote sensing,
PandRS(109), No. 1, 2015, pp. 165-177.
Elsevier DOI 1512
Random forest. Scattered non crop areas (trees). Not large enough to call them a forest. BibRef

Gu, L.J.[Ling-Jia], Zhao, K.[Kai], Huang, B.[Bormin],
Microwave Unmixing With Video Segmentation for Inferring Broadleaf and Needleleaf Brightness Temperatures and Abundances From Mixed Forest Observations,
GeoRS(54), No. 1, January 2016, pp. 279-286.
IEEE DOI 1601
geophysical image processing BibRef

Fatehi, P.[Parviz], Damm, A.[Alexander], Schaepman, M.E.[Michael E.], Kneubühler, M.[Mathias],
Estimation of Alpine Forest Structural Variables from Imaging Spectrometer Data,
RS(7), No. 12, 2015, pp. 15830.
DOI Link 1601
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Zhang, Q.[Qian], Ju, W.M.[Wei-Min], Chen, J.M.[Jing M.], Wang, H.[Huimin], Yang, F.[Fengting], Fan, W.L.[Wei-Liang], Huang, Q.[Qing], Zheng, T.[Ting], Feng, Y.[Yongkang], Zhou, Y.[Yanlian], He, M.[Mingzhu], Qiu, F.[Feng], Wang, X.[Xiaojie], Wang, J.[Jun], Zhang, F.[Fangmin], Chou, S.[Shuren],
Ability of the Photochemical Reflectance Index to Track Light Use Efficiency for a Sub-Tropical Planted Coniferous Forest,
RS(7), No. 12, 2015, pp. 15860.
DOI Link 1601
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Barbosa, J.M.[Jomar M.], Asner, G.P.[Gregory P.], Martin, R.E.[Roberta E.], Baldeck, C.A.[Claire A.], Hughes, F.[Flint], Johnson, T.[Tracy],
Determining Subcanopy Psidium cattleianum Invasion in Hawaiian Forests Using Imaging Spectroscopy,
RS(8), No. 1, 2016, pp. 33.
DOI Link 1602
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Giardino, C.[Claudia], Bresciani, M.[Mariano], Fava, F.[Francesco], Matta, E.[Erica], Brando, V.E.[Vittorio E.], Colombo, R.[Roberto],
Mapping Submerged Habitats and Mangroves of Lampi Island Marine National Park (Myanmar) from in Situ and Satellite Observations,
RS(8), No. 1, 2016, pp. 2.
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Krofcheck, D.J.[Dan J.], Eitel, J.U.H.[Jan U. H.], Lippitt, C.D.[Christopher D.], Vierling, L.A.[Lee A.], Schulthess, U.[Urs], Litvak, M.E.[Marcy E.],
Remote Sensing Based Simple Models of GPP in Both Disturbed and Undisturbed Pińon-Juniper Woodlands in the Southwestern U.S.,
RS(8), No. 1, 2016, pp. 20.
DOI Link 1602
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Krofcheck, D.J.[Dan J.], Litvak, M.E.[Marcy E.], Lippitt, C.D.[Christopher D.], Neuenschwander, A.[Amy],
Woody Biomass Estimation in a Southwestern U.S. Juniper Savanna Using LiDAR-Derived Clumped Tree Segmentation and Existing Allometries,
RS(8), No. 6, 2016, pp. 453.
DOI Link 1608
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Meng, J.H.[Jing-Hui], Li, S.M.[Shi-Ming], Wang, W.[Wei], Liu, Q.W.[Qing-Wang], Xie, S.Q.[Shi-Qin], Ma, W.[Wu],
Estimation of Forest Structural Diversity Using the Spectral and Textural Information Derived from SPOT-5 Satellite Images,
RS(8), No. 2, 2016, pp. 125.
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Meng, J.H.[Jing-Hui], Li, S.M.[Shi-Ming], Wang, W.[Wei], Liu, Q.W.[Qing-Wang], Xie, S.Q.[Shi-Qin], Ma, W.[Wu],
Mapping Forest Health Using Spectral and Textural Information Extracted from SPOT-5 Satellite Images,
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Qiao, H.L.[Hai-Lang], Wu, M.Q.[Ming-Quan], Shakir, M.[Muhammad], Wang, L.[Li], Kang, J.[Jun], Niu, Z.[Zheng],
Classification of Small-Scale Eucalyptus Plantations Based on NDVI Time Series Obtained from Multiple High-Resolution Datasets,
RS(8), No. 2, 2016, pp. 117.
DOI Link 1603
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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

Lesiv, M.[Myroslava], Moltchanova, E.[Elena], Schepaschenko, D.[Dmitry], See, L.[Linda], Shvidenko, A.[Anatoly], Comber, A.J.[Alexis J.], Fritz, S.[Steffen],
Comparison of Data Fusion Methods Using Crowdsourced Data in Creating a Hybrid Forest Cover Map,
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Zhang, Y.[Yuan], Li, J.[Jun], Qin, Q.M.[Qi-Ming],
Identification of Factors Influencing Locations of Tree Cover Loss and Gain and Their Spatio-Temporally-Variant Importance in the Li River Basin, China,
RS(8), No. 3, 2016, pp. 201.
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Cavender-Bares, J.[Jeannine], Meireles, J.E.[Jose Eduardo], Couture, J.J.[John J.], Kaproth, M.A.[Matthew A], Kingdon, C.C.[Clayton C.], Singh, A.[Aditya], Serbin, S.P.[Shawn P.], Center, A.[Alyson], Zuniga, E.[Esau], Pilz, G.[George], Townsend, P.A.[Philip A.],
Associations of Leaf Spectra with Genetic and Phylogenetic Variation in Oaks: Prospects for Remote Detection of Biodiversity,
RS(8), No. 3, 2016, pp. 221.
DOI Link 1604
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DOI Link 1608
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Torbick, N.[Nathan], Ledoux, L.[Lindsay], Salas, W.[William], Zhao, M.[Meng],
Regional Mapping of Plantation Extent Using Multisensor Imagery,
RS(8), No. 3, 2016, pp. 236.
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IEEE DOI 1604
forestry BibRef

Carreno-Luengo, H., Camps, A., Querol, J., Forte, G.,
First Results of a GNSS-R Experiment From a Stratospheric Balloon Over Boreal Forests,
GeoRS(54), No. 5, May 2016, pp. 2652-2663.
IEEE DOI 1604
satellite navigation BibRef

Madsen, N.M., Long, D.G.,
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IEEE DOI 1604
atmospheric measuring apparatus 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,
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IEEE DOI 1606
forestry BibRef

Yan, D., Zhang, X., Yu, Y., Guo, W.,
A Comparison of Tropical Rainforest Phenology Retrieved From Geostationary (SEVIRI) and Polar-Orbiting (MODIS) Sensors Across the Congo Basin,
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IEEE DOI 1608
vegetation BibRef

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Exploring the Relationship between Remotely-Sensed Spectral Variables and Attributes of Tropical Forest Vegetation under the Influence of Local Forest Institutions,
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In Situ/Remote Sensing Integration to Assess Forest Health: A Review,
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Elsevier DOI 1610
Hyperspectral BibRef

Wang, R.[Rong], Chen, J.M.[Jing M.], Pavlic, G.[Goran], Arain, A.[Altaf],
Improving winter leaf area index estimation in coniferous forests and its significance in estimating the land surface albedo,
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Elsevier DOI 1610
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Wang, R.[Rong], Chen, J.M.[Jing M.], Liu, Z.[Zhili], Arain, A.[Altaf],
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Floristic composition and across-track reflectance gradient in Landsat images over Amazonian forests,
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Elsevier DOI 1610
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Straub, C.[Christoph], Stepper, C.[Christoph],
Using Digital Aerial Photogrammetry and the Random Forest Approach to Model Forest Inventory Attributes in Beech- and Spruce-dominated Central European Forests,
PFG(2016), No. 3, 2013, pp. 109-123.
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Connette, G.[Grant], Oswald, P.[Patrick], Songer, M.[Melissa], Leimgruber, P.[Peter],
Mapping Distinct Forest Types Improves Overall Forest Identification Based on Multi-Spectral Landsat Imagery for Myanmar's Tanintharyi Region,
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Yun, T.[Ting], An, F.[Feng], Li, W.[Weizheng], Sun, Y.[Yuan], Cao, L.[Lin], Xue, L.[Lianfeng],
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Zhang, Y., Liu, Q., Du, Y., Yang, L., Du, Y., Cao, B., Tan, L.,
Convenient Measurement and Modified Model for Broadleaf Permittivity,
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IEEE DOI 1612
geophysical techniques BibRef

Zheng, T.[Ting], Chen, J.M.[Jing M.],
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Heinzel, J.[Johannes], Huber, M.O.[Markus O.],
Detecting Tree Stems from Volumetric TLS Data in Forest Environments with Rich Understory,
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Tree Stem Diameter Estimation From Volumetric TLS Image Data,
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Multisource Remote Sensing Imagery Fusion Scheme Based on Bidimensional Empirical Mode Decomposition (BEMD) and Its Application to the Extraction of Bamboo Forest,
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Liu, X.[Xu], Liu, H.Y.[Hong-Yan], Qiu, S.[Shuang], Wu, X.[Xiuchen], Tian, Y.H.[Yu-Hong], Hao, Q.[Qian],
An Improved Estimation of Regional Fractional Woody/Herbaceous Cover Using Combined Satellite Data and High-Quality Training Samples,
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Validation of PROBA-V GEOV1 and MODIS C5 & C6 fAPAR Products in a Deciduous Beech Forest Site in Italy,
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Yang, Z.[Zhiqi], Dong, J.[Jinwei], Liu, J.Y.[Ji-Yuan], Zhai, J.[Jun], Kuang, W.H.[Wen-Hui], Zhao, G.S.[Guo-Song], Shen, W.[Wei], Zhou, Y.[Yan], Qin, Y.W.[Yuan-Wei], Xiao, X.M.[Xiang-Ming],
Accuracy Assessment and Inter-Comparison of Eight Medium Resolution Forest Products on the Loess Plateau, China,
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Retrieval and Comparison of Forest Leaf Area Index Based on Remote Sensing Data from AVNIR-2, Landsat-5 TM, MODIS, and PALSAR Sensors,
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The 2013 FLEX: US Airborne Campaign at the Parker Tract Loblolly Pine Plantation in North Carolina, USA,
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ICIVC17(559-565)
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Kanniah, K.D., Mohd Najib, N.E., Vu, T.T.,
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Huang, Y.L., Liu, H.F., Chen, J.C., Chen, C.T.,
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Chapter on Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR continues in
Forest Analysis, Depth, LiDAR, Laser Scanner, IFSAR .


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