23.2.10 LiDAR for Land Cover, Laser Scanners for Land Cover, Remote Sensing

Chapter Contents (Back)
Classification. LiDAR. Remote Sensing.

Wang, C.K.[Cheng-Kai], Tseng, Y.H.[Yi-Hsing], Chu, H.J.[Hone-Jay],
Airborne Dual-Wavelength LiDAR Data for Classifying Land Cover,
RS(6), No. 1, 2014, pp. 700-715.
DOI Link 1402
BibRef

Liu, X.L.[Xiao-Long], Bo, Y.C.[Yan-Chen],
Object-Based Crop Species Classification Based on the Combination of Airborne Hyperspectral Images and LiDAR Data,
RS(7), No. 1, 2015, pp. 922-950.
DOI Link 1502
BibRef

Sankey, J.B.[Joel B.], Munson, S.M.[Seth M.], Webb, R.H.[Robert H.], Wallace, C.S.A.[Cynthia S. A.], Duran, C.M.[Cesar M.],
Remote Sensing of Sonoran Desert Vegetation Structure and Phenology with Ground-Based LiDAR,
RS(7), No. 1, 2014, pp. 342-359.
DOI Link 1502
BibRef

Eitel, J.U.H.[Jan U.H.], Magney, T.S.[Troy S.], Vierling, L.A.[Lee A.], Dittmar, G.[Günter],
Assessment of crop foliar nitrogen using a novel dual-wavelength laser system and implications for conducting laser-based plant physiology,
PandRS(97), No. 1, 2014, pp. 229-240.
Elsevier DOI 1410
Foliar biochemistry BibRef

Lindgren, N.[Nils], Christensen, P.[Pernilla], Nilsson, B.[Björn], Åkerholm, M.[Marianne], Allard, A.[Anna], Reese, H.[Heather], Olsson, H.[Håkan],
Using Optical Satellite Data and Airborne Lidar Data for a Nationwide Sampling Survey,
RS(7), No. 4, 2015, pp. 4253-4267.
DOI Link 1505
BibRef

Zhu, X.[Xi], Wang, T.J.[Tie-Jun], Darvishzadeh, R.[Roshanak], Skidmore, A.K.[Andrew K.], Niemann, K.O.[K. Olaf],
3D leaf water content mapping using terrestrial laser scanner backscatter intensity with radiometric correction,
PandRS(110), No. 1, 2015, pp. 14-23.
Elsevier DOI 1601
Leaf surface BibRef

Luo, S.Z.[She-Zhou], Wang, C.[Cheng], Xi, X.H.[Xiao-Huan], Zeng, H.C.[Hong-Cheng], Li, D.[Dong], Xia, S.B.[Shao-Bo], Wang, P.[Pinghua],
Fusion of Airborne Discrete-Return LiDAR and Hyperspectral Data for Land Cover Classification,
RS(8), No. 1, 2016, pp. 3.
DOI Link 1602
BibRef

Junttila, S.[Samuli], Vastaranta, M.[Mikko], Liang, X.[Xinlian], Kaartinen, H.[Harri], Kukko, A.[Antero], Kaasalainen, S.[Sanna], Holopainen, M.[Markus], Hyyppä, H.[Hannu], Hyyppä, J.[Juha],
Measuring Leaf Water Content with Dual-Wavelength Intensity Data from Terrestrial Laser Scanners,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702
BibRef

Varvia, P.[Petri], Lähivaara, T.[Timo], Maltamo, M.[Matti], Packalen, P.[Petteri], Tokola, T.[Timo], Seppänen, A.[Aku],
Uncertainty Quantification in ALS-Based Species-Specific Growing Stock Volume Estimation,
GeoRS(55), No. 3, March 2017, pp. 1671-1681.
IEEE DOI 1703
Bayes methods BibRef

Matikainen, L.[Leena], Karila, K.[Kirsi], Hyyppä, J.[Juha], Litkey, P.[Paula], Puttonen, E.[Eetu], Ahokas, E.[Eero],
Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating,
PandRS(128), No. 1, 2017, pp. 298-313.
Elsevier DOI 1706
Laser scanning BibRef

Vosselman, G.[George], Coenen, M.[Maximilian], Rottensteiner, F.[Franz],
Contextual segment-based classification of airborne laser scanner data,
PandRS(128), No. 1, 2017, pp. 354-371.
Elsevier DOI 1706
Point cloud BibRef

Estrada, J.[Jesús], Sánchez, H.[Héctor], Hernanz, L.[Lorena], Checa, M.J.[María José], Roman, D.[Dumitru],
Enabling the Use of Sentinel-2 and LiDAR Data for Common Agriculture Policy Funds Assignment,
IJGI(6), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Pan, X.[Xuran], Gao, L.[Lianru], Marinoni, A.[Andrea], Zhang, B.[Bing], Yang, F.[Fan], Gamba, P.[Paolo],
Semantic Labeling of High Resolution Aerial Imagery and LiDAR Data with Fine Segmentation Network,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Xu, Z.W.[Ze-Wei], Guan, K.Y.[Kai-Yu], Casler, N.[Nathan], Peng, B.[Bin], Wang, S.W.[Shao-Wen],
A 3D convolutional neural network method for land cover classification using LiDAR and multi-temporal Landsat imagery,
PandRS(144), 2018, pp. 423-434.
Elsevier DOI 1809
Big data analysis, Convolutional neural network, Land cover classification, LiDAR, Multi-temporal Landsat imagery BibRef

Lucas, C.[Chris], Bouten, W.[Willem], Koma, Z.[Zsófia], Kissling, W.D.[W. Daniel], Seijmonsbergen, A.C.[Arie C.],
Identification of Linear Vegetation Elements in a Rural Landscape Using LiDAR Point Clouds,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link 1902
BibRef

Ma, Y.[Yue], Zhang, W.H.[Wen-Hao], Sun, J.Y.[Jin-Yan], Li, G.Y.[Guo-Yuan], Wang, X.H.[Xiao Hua], Li, S.[Song], Xu, N.[Nan],
Photon-Counting Lidar: An Adaptive Signal Detection Method for Different Land Cover Types in Coastal Areas,
RS(11), No. 4, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Okhrimenko, M.[Maxim], Hopkinson, C.[Chris],
Investigating the Consistency of Uncalibrated Multispectral Lidar Vegetation Indices at Different Altitudes,
RS(11), No. 13, 2019, pp. xx-yy.
DOI Link 1907
BibRef

Okhrimenko, M.[Maxim], Coburn, C.[Craig], Hopkinson, C.[Chris],
Multi-Spectral Lidar: Radiometric Calibration, Canopy Spectral Reflectance, and Vegetation Vertical SVI Profiles,
RS(11), No. 13, 2019, pp. xx-yy.
DOI Link 1907
BibRef

Jiang, C.H.[Chang-Hui], Chen, Y.W.[Yu-Wei], Wu, H.H.[Hao-Hao], Li, W.[Wei], Zhou, H.[Hui], Bo, Y.M.[Yu-Ming], Shao, H.[Hui], Song, S.J.[Shao-Jing], Puttonen, E.[Eetu], Hyyppä, J.[Juha],
Study of a High Spectral Resolution Hyperspectral LiDAR in Vegetation Red Edge Parameters Extraction,
RS(11), No. 17, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Zorzi, S., Maset, E., Fusiello, A., Crosilla, F.,
Full-Waveform Airborne LiDAR Data Classification Using Convolutional Neural Networks,
GeoRS(57), No. 10, October 2019, pp. 8255-8261.
IEEE DOI 1910
cartography, convolutional neural nets, geophysical image processing, image classification, Light Detection and Ranging (LiDAR) BibRef

Maset, E., Padova, B., Fusiello, A.,
Efficient Large-scale Airborne Lidar Data Classification Via Fully Convolutional Network,
ISPRS20(B3:527-532).
DOI Link 2012
BibRef

Tanaka, K.[Kenichiro], Mukaigawa, Y.[Yasuhiro], Funatomi, T.[Takuya], Kubo, H.[Hiroyuki], Matsushita, Y.[Yasuyuki], Yagi, Y.S.[Yasu-Shi],
Material Classification from Time-of-Flight Distortions,
PAMI(41), No. 12, December 2019, pp. 2906-2918.
IEEE DOI 1911
Depth is distorted by certain materials. Image classification, Distortion measurement, Time-domain analysis, Optical distortion, Optical imaging, temporal point spread functions BibRef

Yang, X.Y.[Xing-Yu], Huang, Y.C.[Yu-Chun], Zhang, Q.L.[Qiu-Lan],
Automatic Stockpile Extraction and Measurement Using 3D Point Cloud and Multi-Scale Directional Curvature,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link 2003
Coal stockpiles. BibRef

Kwan, C.[Chiman], Gribben, D.[David], Ayhan, B.[Bulent], Bernabe, S.[Sergio], Plaza, A.[Antonio], Selva, M.[Massimo],
Improving Land Cover Classification Using Extended Multi-Attribute Profiles (EMAP) Enhanced Color, Near Infrared, and LiDAR Data,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Li, W.[Wuzhao], Wang, F.D.[Fu-Dong], Xia, G.S.[Gui-Song],
A geometry-attentional network for ALS point cloud classification,
PandRS(164), 2020, pp. 26-40.
Elsevier DOI 2005
Deep learning, ALS Point clouds, Semantic labelling, Geometry-attentional network BibRef

Cucchiaro, S.[Sara], Fallu, D.J.[Daniel J.], Zhang, H.[He], Walsh, K.[Kevin], van Oost, K.[Kristof], Brown, A.G.[Antony G.], Tarolli, P.[Paolo],
Multiplatform-SfM and TLS Data Fusion for Monitoring Agricultural Terraces in Complex Topographic and Landcover Conditions,
RS(12), No. 12, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Pan, S.Y.[Suo-Yan], Guan, H.Y.[Hai-Yan], Chen, Y.T.[Ya-Ting], Yu, Y.T.[Yong-Tao], Nunes Gonçalves, W.[Wesley], Marcato Junior, J.[José], Li, J.[Jonathan],
Land-cover classification of multispectral LiDAR data using CNN with optimized hyper-parameters,
PandRS(166), 2020, pp. 241-254.
Elsevier DOI 2007
Multi-spectral LiDAR, CNN, Land-cover classification, Hyper-parameters BibRef

Briechle, S., Molitor, N., Krzystek, P., Vosselman, G.,
Detection of radioactive waste sites in the Chornobyl exclusion zone using UAV-based lidar data and multispectral imagery,
PandRS(167), 2020, pp. 345-362.
Elsevier DOI 2008
UAV, Lidar, Multispectral imagery, Radioactive waste sites, 3D vegetation mapping, Machine learning BibRef

Jin, S.C.[Shi-Chao], Sun, X.L.[Xi-Liang], Wu, F.F.[Fang-Fang], Su, Y.J.[Yan-Jun], Li, Y.[Yumei], Song, S.L.[Shi-Ling], Xu, K.[Kexin], Ma, Q.[Qin], Baret, F.[Frédéric], Jiang, D.[Dong], Ding, Y.F.[Yan-Feng], Guo, Q.H.[Qing-Hua],
Lidar sheds new light on plant phenomics for plant breeding and management: Recent advances and future prospects,
PandRS(171), 2021, pp. 202-223.
Elsevier DOI 2012
Lidar, Traits, Phenomics, Breeding, Management, Multi-omics BibRef

Widyaningrum, E.[Elyta], Bai, Q.[Qian], Fajari, M.K.[Marda K.], Lindenbergh, R.C.[Roderik C.],
Airborne Laser Scanning Point Cloud Classification Using the DGCNN Deep Learning Method,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Bai, Q.[Qian], Lindenbergh, R.C.[Roderik C.], Vijverberg, J., Guelen, J.A.P.,
Road Type Classification of Mls Point Clouds Using Deep Learning,
ISPRS21(B2-2021: 115-122).
DOI Link 2201
BibRef

Ding, H.[Hu], Na, J.M.[Jia-Ming], Jiang, S.J.[Shang-Jing], Zhu, J.[Jie], Liu, K.[Kai], Fu, Y.C.[Ying-Chun], Li, F.Y.[Fa-Yuan],
Evaluation of Three Different Machine Learning Methods for Object-Based Artificial Terrace Mapping: A Case Study of the Loess Plateau, China,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Quan, Y.H.[Ying-Hui], Tong, Y.P.[Ying-Ping], Feng, W.[Wei], Dauphin, G.[Gabriel], Huang, W.J.[Wen-Jiang], Zhu, W.T.[Wen-Tao], Xing, M.D.[Meng-Dao],
Relative Total Variation Structure Analysis-Based Fusion Method for Hyperspectral and LiDAR Data Classification,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Polák, M.[Michal], Mirijovský, J.[Jakub], Hernándiz, A.E.[Alba E.], Špíšek, Z.[Zdenek], Koprna, R.[Radoslav], Humplík, J.F.[Jan F.],
Innovative UAV LiDAR Generated Point-Cloud Processing Algorithm in Python for Unsupervised Detection and Analysis of Agricultural Field-Plots,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Zhang, F.[Fei], Hassanzadeh, A.[Amirhossein], Kikkert, J.[Julie], Pethybridge, S.J.[Sarah Jane], van Aardt, J.[Jan],
Comparison of UAS-Based Structure-from-Motion and LiDAR for Structural Characterization of Short Broadacre Crops,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Shi, S.[Shuo], Bi, S.[Sifu], Gong, W.[Wei], Chen, B.[Biwu], Chen, B.[Bowen], Tang, X.T.[Xing-Tao], Qu, F.F.[Fang-Fang], Song, S.L.[Sha-Lei],
Land Cover Classification with Multispectral LiDAR Based on Multi-Scale Spatial and Spectral Feature Selection,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Camarretta, N.[Nicolò], Ehbrecht, M.[Martin], Seidel, D.[Dominik], Wenzel, A.[Arne], Zuhdi, M.[Mohd.], Merk, M.S.[Miryam Sarah], Schlund, M.[Michael], Erasmi, S.[Stefan], Knohl, A.[Alexander],
Using Airborne Laser Scanning to Characterize Land-Use Systems in a Tropical Landscape Based on Vegetation Structural Metrics,
RS(13), No. 23, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Borowiec, N.[Natalia], Marmol, U.[Urszula],
Using LiDAR System as a Data Source for Agricultural Land Boundaries,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Wu, G.T.[Guo-Tong], You, Y.C.[Ying-Chang], Yang, Y.[Yibin], Cao, J.C.[Jia-Chen], Bai, Y.J.[Yu-Jie], Zhu, S.J.[Sheng-Jie], Wu, L.P.[Li-Ping], Wang, W.W.[Wei-Wen], Chang, M.[Ming], Wang, X.M.[Xue-Mei],
UAV-LiDAR Measurement of Vegetation Canopy Structure Parameters and Their Impact on Land-Air Exchange Simulation Based on Noah-MP Model,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Wei, C.T.[Chun-Ta], Tsai, M.D.[Ming-Da], Chang, Y.L.[Yu-Lung], Wang, M.C.J.[Ming-Chih Jason],
Enhancing the Accuracy of Land Cover Classification by Airborne LiDAR Data and WorldView-2 Satellite Imagery,
IJGI(11), No. 7, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Zhang, Z.W.[Zhi-Wen], Li, T.[Teng], Tang, X.B.[Xue-Bin], Lei, X.D.[Xiang-Da], Peng, Y.X.[Yuan-Xi],
Introducing Improved Transformer to Land Cover Classification Using Multispectral LiDAR Point Clouds,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Szostak, M.[Marta], Pajak, M.[Marek],
LiDAR Point Clouds Usage for Mapping the Vegetation Cover of the 'Fryderyk' Mine Repository,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Xiao, F.J.[Feng-Jin], Liu, Q.[Qiufeng], Li, S.[Shuai], Qin, Y.[Yun], Huang, D.P.[Da-Peng], Wang, Y.J.[Yan-Jiao], Wang, L.[Lei],
A Study of the Method for Retrieving the Vegetation Index from FY-3D MERSI-II Data,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Fareed, N.[Nadeem], Flores, J.P.[Joao Paulo], Das, A.K.[Anup Kumar],
Analysis of UAS-LiDAR Ground Points Classification in Agricultural Fields Using Traditional Algorithms and PointCNN,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Wu, H.[Hao], Lin, C.[Chao], Li, C.L.[Cheng-Liang], Zhang, J.[Jialun], Gaoqu, Y.[Youyang], Wang, S.[Shuo], Wang, L.[Long], Xue, H.[Hao], Sun, W.Q.[Wen-Qiang], Zheng, Y.[Yuquan],
Vision-Aided Hyperspectral Full-Waveform LiDAR System to Improve Detection Efficiency,
RS(15), No. 13, 2023, pp. 3448.
DOI Link 2307
BibRef

Fareed, N.[Nadeem], Das, A.K.[Anup Kumar], Flores, J.P.[Joao Paulo], Mathew, J.J.[Jitin Jose], Mukaila, T.[Taofeek], Numata, I.[Izaya], Janjua, U.U.R.[Ubaid Ur Rehman],
UAS Quality Control and Crop Three-Dimensional Characterization Framework Using Multi-Temporal LiDAR Data,
RS(16), No. 4, 2024, pp. 699.
DOI Link 2402
BibRef

Wang, A.[Ailing], Shi, S.[Shuo], Man, W.H.[Wei-Hui], Qu, F.F.[Fang-Fang],
Enhanced Land-Cover Classification through a Multi-Stage Classification Strategy Integrating LiDAR and SIF Data,
RS(16), No. 11, 2024, pp. 1916.
DOI Link 2406
BibRef


Yang, M.S.[Meng-Shi], Li, M.H.[Meng-Hua], Huang, C.[Cheng], Zhang, R.[Ruisi], Liu, R.[Rui],
Exploring the InSAR Deformation Series Using Unsupervised Learning in a Built Environment,
RS(16), No. 8, 2024, pp. 1375.
DOI Link 2405
BibRef

Liu, Y.S.[Yan-Song], Piramanayagam, S.[Sankaranarayanan], Monteiro, S.T.[Sildomar T.], Saber, E.[Eli],
Dense Semantic Labeling of Very-High-Resolution Aerial Imagery and LiDAR with Fully-Convolutional Neural Networks and Higher-Order CRFs,
EarthVision17(1561-1570)
IEEE DOI 1709
Labeling, Laser radar, Neural networks, Optical imaging, Remote sensing, Semantics, Training BibRef

Kumazakia, R., Kunii, Y.,
3d Modeling Of Components Of A Garden By Using Point Cloud Data,
ISPRS16(B5: 305-309).
DOI Link 1610
Rocks, shrubs, etc. BibRef

Bakula, K., Kupidura, P., Jelowicki, L.,
Testing Of Land Cover Classification From Multispectral Airborne Laser Scanning Data,
ISPRS16(B7: 161-169).
DOI Link 1610
BibRef

Yastikli, N., Cetin, Z.,
Classification Of Lidar Data With Point Based Classification Methods,
ISPRS16(B3: 441-445).
DOI Link 1610
BibRef

Zhou, M., Li, C.R., Ma, L., Guan, H.C.,
Land Cover Classification From Full-waveform Lidar Data Based On Support Vector Machines,
ISPRS16(B3: 447-452).
DOI Link 1610
BibRef

Umemura, M.[Masaki], Hotta, K.[Kazuhiro], Nonaka, H.[Hideki], Oda, K.[Kazuo],
Segmentation of LiDAR Intensity Using CNN Feature Based on Weighted Voting,
ICIAR17(578-585).
Springer DOI 1706
BibRef
Earlier:
Image Labeling For Lidar Intensity Image Using K-nn Of Feature Obtained By Convolutional Neural Network,
ISPRS16(B3: 931-935).
DOI Link 1610
BibRef

Shi, S.[Shuo], Gong, W.[Wei], Du, L.[Lin], Sun, J.[Jia], Yang, J.[Jian],
Potential Application Of Novel Hyperspectral Lidar For Monitoring Crops Nitrogen Stress,
ISPRS16(B8: 1043-1047).
DOI Link 1610
BibRef

Yang, J.[Jian], Gong, W.[Wei], Shi, S.[Shuo], Du, L.[Lin], Sun, J.[Jia], Song, S.[Shalei],
The Effective Of Different Excitation Wavelengths On The Identification Of Plant Species Based On Fluorescence Lidar,
ISPRS16(B1: 147-150).
DOI Link 1610
BibRef

Villar, R.G.[Ricardo G.], Pelayo, J.L.[Jigg L.], Mozo, R.M.N.[Ray Mari N.], Salig Jr., J.B.[James B.], Bantugan, J.[Jojemar],
Non-trivial Feature Derivation For Intensifying Feature Detection Using Lidar Datasets Through Allometric Aggregation Data Analysis Applying Diffused Hierarchical Clustering For Discriminating Agricultural Land Cover In Portions Of Northern Mindanao, Philippines,
ISPRS16(B8: 1009-1016).
DOI Link 1610
BibRef

Blanco, A.C., Tamondong, A., Perez, A.M., Ang, M.R.C., Paringit, E., Alberto, R., Alibuyog, N., Aquino, D., Ballado, A., Garcia, P., Japitana, M., Ignacio, M.T., Macandog, D., Novero, A., Otadoy, R.E., Regis, E., Rodriguez, M., Silapan, J., Villar, R.,
Nationwide Natural Resource Inventory Of The Philippines Using Lidar: Strategies, Progress, And Challenges,
ISPRS16(B6: 105-109).
DOI Link 1610
BibRef

Lin, Y.C.[Yu-Ching], Lin, C.[Chin_Su], Tsai, M.D.[Ming-Da], Lin, C.L.[Chun-Lin],
Object-based Analysis Of Lidar Geometric Features For Vegetation Detection In Shaded Areas,
ISPRS16(B1: 43-46).
DOI Link 1610
BibRef

Wang, J.H., Li, C.R., Tang, L.L., Zhou, M., Li, J.M.,
A Comparison of Two Different Approaches of Point Cloud Classification Based on Full-Waveform Lidar Data,
ISPRS12(XXXIX-B3:179-182).
DOI Link 1209
BibRef

Shaker, A., El-Ashmawy, N.,
Land Cover Information Extraction Using Lidar Data,
ISPRS12(XXXIX-B7:167-172).
DOI Link 1209
BibRef

Borkowski, A., Józków, G.,
Airborne Laser Scanning Data Filtering Using Flakes,
ISPRS08(B3b: 179 ff).
PDF File. 0807
BibRef

Tymkow, P., Borkowski, A.,
Land Cover Classification Using Airborne Laser Scanning Data and Photographs,
ISPRS08(B3b: 185 ff).
PDF File. 0807
BibRef

Alonso, M.C.[María C.], Malpica, J.A.[José A.],
Classification of Multispectral High-Resolution Satellite Imagery Using LIDAR Elevation Data,
ISVC08(II: 85-94).
Springer DOI 0812
BibRef

Levick, S., Rogers, K.H.,
LiDAR and object-based image analysis as tools for monitoring the structural diversity of savanna vegetation,
OBIA06(xx-yy).
PDF File. 0607
BibRef

Song, J.H.[Jeong Heon], Han, S.H.[Soo Hee], Yu, K.Y.[Ki Yun], Kim, Y.I.[Yong Il],
Assessing the Possibility of Land-Cover Classification Using LIDAR Intensity Data,
PCV02(B: 259). 0305
BibRef

Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Radar for Land Cover, SAR for Land Cover, Remote Sensing .


Last update:Nov 26, 2024 at 16:40:19