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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.,
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The Calibration of Digitized Aerial Photographs for
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9803
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Pu, R.L.[Rui-Liang],
Gong, P.[Peng],
Biging, G.S.,
Larrieu, M.R.,
Extraction of red edge optical parameters from Hyperion data for
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GeoRS(41), No. 4, April 2003, pp. 916-921.
IEEE Abstract.
0307
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,
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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),
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0100
Richardson, J.J.[Jeffrey J.],
Moskal, L.M.[L. Monika],
An Integrated Approach for Monitoring Contemporary and Recruitable
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Nelson, T.[Trisalyn],
Boots, B.[Barry],
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Feick, R.[Rob],
Predicting Forest Age Classes from High Spatial Resolution Remotely
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DOI Link
0403
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Lipowezky, U.[Uri],
Groves decipherment from space photos using prototype matching,
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Elsevier DOI
0410
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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,
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Elsevier DOI Random Forests; Classification; Decision trees; Multisource remote sensing data
0604
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Cheng, L.[Li],
Caelli, T.M.,
Sanchez-Azofeifa, G.A.[G. 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
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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,
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
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.
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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),
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WWW Link.
0709
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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.
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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
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
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
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
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
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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
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
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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,
PFG(2010), No. 4, 2010, pp. 267-271.
WWW Link.
1211
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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
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
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
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
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Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Forest Extraction, Forest Analysis, Sentinel Based .