22.5.11.4 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. Tree Species Determination See also Tree Species Determination, Forest Analysis. For trees grown as crops: See also Orchards, Plantations, Trees as Crops. See also Tropical Forest Analysis. See also Mangrove Analysis. Changes: See also Forest Change Evaluation, Change Detection, Temporal Analysis.

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Patterns of spatial variation in forests and other natural populations,
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Elsevier DOI 0309
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Holopainen, M., Wang, G.X.,
The Calibration of Digitized Aerial Photographs for Forest Stratification,
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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
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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
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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
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Franklin, S.E., Lavigne, M.B., Moskal, L.M., Wulder, M.A., and McCaffrey, T.M.,
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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,
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Lipowezky, U.[Uri],
Groves decipherment from space photos using prototype matching,
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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
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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,
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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,
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IEEE DOI 1205
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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

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

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

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

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

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

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

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

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

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

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
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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
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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
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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
BibRef

Clerici, N., Weissteiner, C., Gerard, F.,
Exploring the Use of MODIS NDVI-Based Phenology Indicators for Classifying Forest General Habitat Categories,
RS(4), No. 6, June 2012, pp. 1781-1803.
DOI Link 1208
BibRef

Hildebrandt, G.[Gerd],
The Beginnings of Aerial Photogrammetry and Interpretation in German Forestry after 1945,
PFG(2010), No. 4, 2010, pp. 235-242.
WWW Link. 1211
BibRef

Marx, A.[Alexander],
Detection and Classification of Bark Beetle Infestation in Pure Norway Spruce Stands with Multi-temporal RapidEye Imagery and Data Mining Techniques,
PFG(2010), No. 4, 2010, pp. 243-252.
WWW Link. 1211
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Förster, M.[Michael], Spengler, D.[Daniel], Buddenbaum, H.[Henning], Hill, J.[Joachim], Kleinschmit, B.[Birgit],
A review of the combination of spectral and geometric modelling for the application in forest remote sensing,
PFG(2010), No. 4, 2010, pp. 253-265.
WWW Link. 1211
BibRef

Franken, F.[Frank], Hoffmann, K.[Karina],
Requirements for Digital / Digitized Aerial Imagery A Manual of the Working Group of Forest Interpreters of Aerial Photographs,
PFG(2010), No. 4, 2010, pp. 267-271.
WWW Link. 1211
BibRef

Buck, G.[Gudrun], Seitz, R.[Rudolf], Troycke, A.[Armin],
Remote Sensing at Bavarian State Institute of Forestry Transfer of Research Results in Forestry Practice,
PFG(2010), No. 4, 2010, pp. 295-303.
WWW Link. 1211
BibRef

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

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
BibRef

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.
DOI Link 1307
BibRef

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.
DOI Link 1311
BibRef

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,
RS(6), No. 1, 2013, pp. 209-232.
DOI Link 1402
BibRef

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,
RS(6), No. 6, 2014, pp. 5325-5343.
DOI Link 1407
BibRef

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

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

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.
DOI Link 1410
BibRef

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

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
BibRef

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
BibRef

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
BibRef

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
BibRef

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

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
BibRef

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
BibRef

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
BibRef

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
BibRef

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
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,
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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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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.
DOI Link 1603
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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],
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DOI Link 1610
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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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DOI Link 1604
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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,
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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,
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DOI Link 1604
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DOI Link 1608
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Ayerdi, B., Grańa Romay, M.,
Hyperspectral Image Analysis by Spectral: Spatial Processing and Anticipative Hybrid Extreme Rotation Forest Classification,
GeoRS(54), No. 5, May 2016, pp. 2627-2639.
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

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Scatterometer Backscatter Imaging Using Backus-Gilbert Inversion,
GeoRS(57), No. 6, June 2019, pp. 3179-3190.
IEEE DOI 1906
Radar measurements, Backscatter, Microwave radiometry, Antenna measurements, Microwave measurement, Imaging, variable aperture BibRef

Omer, G.[Galal], Mutanga, O.[Onisimo], Abdel-Rahman, E.M.[Elfatih M.], Peerbhay, K.[Kabir], Adam, E.[Elhadi],
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Elsevier DOI 1709
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Jiang, Y.T.[Yi-Tong], Weng, Q.[Qihao], Speer, J.H.[James H.], Baker, S.[Steven],
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DOI Link 1606
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Yan, G., Hu, R., Wang, Y., Ren, H., Song, W., Qi, J., Chen, L.,
Scale Effect in Indirect Measurement of Leaf Area Index,
GeoRS(54), No. 6, June 2016, pp. 3475-3484.
IEEE DOI 1606
forestry BibRef

Pause, M.[Marion], Schweitzer, C.[Christian], Rosenthal, M.[Michael], Keuck, V.[Vanessa], Bumberger, J.[Jan], Dietrich, P.[Peter], Heurich, M.[Marco], Jung, A.[András], Lausch, A.[Angela],
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Creating a Regional MODIS Satellite-Driven Net Primary Production Dataset for European Forests,
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Montesano, P.M.[Paul Mannix], Neigh, C.S.R.[Christopher S. R.], Sexton, J.[Joseph], Feng, M.[Min], Channan, S.[Saurabh], Ranson, K.J.[Kenneth J.], Townshend, J.R.[John R.],
Calibration and Validation of Landsat Tree Cover in the Taiga-Tundra Ecotone,
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Large-Area, High-Resolution Tree Cover Mapping with Multi-Temporal SPOT5 Imagery, New South Wales, Australia,
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Elsevier DOI 1610
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Elsevier DOI 1708
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Elsevier DOI 1610
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Using Digital Aerial Photogrammetry and the Random Forest Approach to Model Forest Inventory Attributes in Beech- and Spruce-dominated Central European Forests,
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Connette, G.[Grant], Oswald, P.[Patrick], Songer, M.[Melissa], Leimgruber, P.[Peter],
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DOI Link 1612
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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.],
Photochemical reflectance ratio for tracking light use efficiency for sunlit leaves in two forest types,
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Elsevier DOI 1612
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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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Validation of PROBA-V GEOV1 and MODIS C5 & C6 fAPAR Products in a Deciduous Beech Forest Site in Italy,
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Accuracy Assessment and Inter-Comparison of Eight Medium Resolution Forest Products on the Loess Plateau, China,
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DOI Link 1804
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II: Integration of Remote Sensing Medium and Low Spatial Resolution Satellite Images,
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IEEE DOI 1807
geophysical image processing, image resolution, image sensors, infrared imaging, remote sensing, spectrometers, vegetation, vegetation structure BibRef

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Comparison of Seven Inversion Models for Estimating Plant and Woody Area Indices of Leaf-on and Leaf-off Forest Canopy Using Explicit 3D Forest Scenes,
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Mahoney, C.[Craig], Hall, R.J.[Ron J.], Hopkinson, C.[Chris], Filiatrault, M.[Michelle], Beaudoin, A.[Andre], Chen, Q.[Qi],
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More Than Meets the Eye: Using Sentinel-2 to Map Small Plantations in Complex Forest Landscapes,
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High-Resolution Mapping of Redwood (Sequoia sempervirens) Distributions in Three Californian Forests,
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Chang, T.[Tony], Rasmussen, B.P.[Brandon P.], Dickson, B.G.[Brett G.], Zachmann, L.J.[Luke J.],
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Increasing Precision for French Forest Inventory Estimates using the k-NN Technique with Optical and Photogrammetric Data and Model-Assisted Estimators,
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Multi-Scale Remote Sensing-Assisted Forest Inventory: A Glimpse of the State-of-the-Art and Future Prospects,
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Remote sensing, Tree mortality, Machine learning, Deep learning, Convolutional neural network, Ensemble learning BibRef

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Finn, A., Brinkworth, R., Griffiths, D., Peters, S.,
Determining Morphometric Properties of Radiata Pine Using Long Wave Infrared Sensing and Biologically-inspired Vision,
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Li, J., Yang, B., Cong, Y., Li, S., Yue, Y.,
Integration of a Low-cost Multisensory UAV System for Forest Application,
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Novo, A., González-Jorge, H., Martínez-Sánchez, J., González-de Santos, L.M., Lorenzo, H.,
Automatic Detection of Forest-road Distances to Improve Clearing Operations in Road Management,
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Ronoud, G., Darvish Sefat, A.A., Fatehi, P.,
Beech Tree Density Estimation Using Sentinel-2 Data (case Study: Khyroud Forest),
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Khairiah, R.N., Prasetyo, L.B., Setiawan, Y.,
Agroforestry Tree Density Estimation Based On Hemispherical Photos & Landsat 8 OLI/TIRS Image: A Case Study at Cidanau Watershed, Banten-indonesia,
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Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
Tropical Forest Analysis .


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