24.4.13.7.4 Rubber Trees, Plantations, Analysis

Chapter Contents (Back)
Orchards. Rubber Trees.
See also Palm Trees, Oil Palms, Trees as Crops.

Dong, J.W.[Jin-Wei], Xiao, X.M.[Xiang-Ming], Sheldon, S.[Sage], Biradar, C.[Chandrashekhar], Xie, G.S.[Gui-Shui],
Mapping tropical forests and rubber plantations in complex landscapes by integrating PALSAR and MODIS imagery,
PandRS(74), No. 1, November 2012, pp. 20-33.
Elsevier DOI 1212
PALSAR; MODIS; Evergreen forest; Deciduous forest; Rubber plantation; Hainan BibRef

Senf, C.[Cornelius], Pflugmacher, D.[Dirk], van der Linden, S.[Sebastian], Hostert, P.[Patrick],
Mapping Rubber Plantations and Natural Forests in Xishuangbanna (Southwest China) Using Multi-Spectral Phenological Metrics from MODIS Time Series,
RS(5), No. 6, 2013, pp. 2795-2812.
DOI Link 1307
BibRef

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

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
BibRef

Kou, W.[Weili], Xiao, X.M.[Xiang-Ming], Dong, J.W.[Jin-Wei], Gan, S.[Shu], Zhai, D.L.[De-Li], Zhang, G.[Geli], Qin, Y.W.[Yuan-Wei], Li, L.[Li],
Mapping Deciduous Rubber Plantation Areas and Stand Ages with PALSAR and Landsat Images,
RS(7), No. 1, 2015, pp. 1048-1073.
DOI Link 1502
BibRef

Ye, S.[Su], Rogan, J.[John], Sangermano, F.[Florencia],
Monitoring rubber plantation expansion using Landsat data time series and a Shapelet-based approach,
PandRS(136), 2018, pp. 134-143.
Elsevier DOI 1802
Time series, Shapelet, Rubber plantations, Landsat, Forest mapping BibRef

Zhai, D.L.[De-Li], Dong, J.[Jinwei], Cadisch, G.[Georg], Wang, M.C.[Ming-Cheng], Kou, W.L.[Wei-Li], Xu, J.C.[Jian-Chu], Xiao, X.M.[Xiang-Ming], Abbas, S.[Sawaid],
Comparison of Pixel- and Object-Based Approaches in Phenology-Based Rubber Plantation Mapping in Fragmented Landscapes,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link 1802
BibRef

Chen, B.Q.[Bang-Qian], Xiao, X.M.[Xiang-Ming], Wu, Z.X.[Zhi-Xiang], Yun, T.[Tin], Kou, W.[Weili], Ye, H.C.[Hui-Chun], Lin, Q.H.[Qing-Huo], Doughty, R.[Russell], Dong, J.[Jinwei], Ma, J.[Jun], Luo, W.[Wei], Xie, G.S.[Gui-Shui], Cao, J.H.[Jian-Hua],
Identifying Establishment Year and Pre-Conversion Land Cover of Rubber Plantations on Hainan Island, China Using Landsat Data during 1987-2015,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef

Chen, G.[Gang], Thill, J.C.[Jean-Claude], Anantsuksomsri, S.[Sutee], Tontisirin, N.[Nij], Tao, R.[Ran],
Stand age estimation of rubber (Hevea brasiliensis) plantations using an integrated pixel- and object-based tree growth model and annual Landsat time series,
PandRS(144), 2018, pp. 94-104.
Elsevier DOI 1809
Stand age estimation, Rubber plantation, Geographic object-based image analysis, Landsat time series, Tree growth model BibRef

Gao, S.P.[Shu-Peng], Liu, X.L.[Xiao-Long], Bo, Y.C.[Yan-Chen], Shi, Z.T.[Zheng-Tao], Zhou, H.M.[Hong-Min],
Rubber Identification Based on Blended High Spatio-Temporal Resolution Optical Remote Sensing Data: A Case Study in Xishuangbanna,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link 1903
Rubber trees. BibRef

Yun, T.[Ting], Jiang, K.[Kang], Hou, H.[Hu], An, F.[Feng], Chen, B.Q.[Bang-Qian], Jiang, A.[Anna], Li, W.Z.[Wei-Zheng], Xue, L.F.[Lian-Feng],
Rubber Tree Crown Segmentation and Property Retrieval Using Ground-Based Mobile LiDAR after Natural Disturbances,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Huang, Z.X.[Zhi-Xian], Huang, X.[Xiao], Fan, J.C.[Jiang-Chuan], Eichhorn, M.[Markus], An, F.[Feng], Chen, B.Q.[Bang-Qian], Cao, L.[Lin], Zhu, Z.L.[Zheng-Li], Yun, T.[Ting],
Retrieval of Aerodynamic Parameters in Rubber Tree Forests Based on the Computer Simulation Technique and Terrestrial Laser Scanning Data,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link 2004
BibRef

Chen, B.Q.[Bang-Qian], Yun, T.[Tin], Ma, J.[Jun], Kou, W.[Weili], Li, H.L.[Hai-Liang], Yang, C.[Chuan], Xiao, X.M.[Xiang-Ming], Zhang, X.[Xian], Sun, R.[Rui], Xie, G.S.[Gui-Shui], Wu, Z.X.[Zhi-Xiang],
High-Precision Stand Age Data Facilitate the Estimation of Rubber Plantation Biomass: A Case Study of Hainan Island, China,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
BibRef
And: Correction: RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Azizan, F.A.[Fathin Ayuni], Kiloes, A.M.[Adhitya Marendra], Astuti, I.S.[Ike Sari], Aziz, A.A.[Ammar Abdul],
Application of Optical Remote Sensing in Rubber Plantations: A Systematic Review,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Yang, J.B.[Jian-Bo], Xu, J.C.[Jian-Chu], Zhai, D.L.[De-Li],
Integrating Phenological and Geographical Information with Artificial Intelligence Algorithm to Map Rubber Plantations in Xishuangbanna,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Azizan, F.A.[Fathin Ayuni], Astuti, I.S.[Ike Sari], Aditya, M.I.[Mohammad Irvan], Febbiyanti, T.R.[Tri Rapani], Williams, A.[Alwyn], Young, A.[Anthony], Aziz, A.A.[Ammar Abdul],
Using Multi-Temporal Satellite Data to Analyse Phenological Responses of Rubber (Hevea brasiliensis) to Climatic Variations in South Sumatra, Indonesia,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108
BibRef

Sari, I.L.[Inggit Lolita], Weston, C.J.[Christopher J.], Newnham, G.J.[Glenn J.], Volkova, L.[Liubov],
Developing Multi-Source Indices to Discriminate between Native Tropical Forests, Oil Palm and Rubber Plantations in Indonesia,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Cui, B.[Bei], Huang, W.J.[Wen-Jiang], Ye, H.C.[Hui-Chun], Chen, Q.X.[Quan-Xi],
The Suitability of PlanetScope Imagery for Mapping Rubber Plantations,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
BibRef

Li, H.Z.[Hong-Zhong], Zhao, L.L.[Long-Long], Sun, L.[Luyi], Li, X.L.[Xiao-Li], Wang, J.[Jin], Han, Y.[Yu], Liang, S.Z.[Shou-Zhen], Chen, J.S.[Jin-Song],
Capability of Phenology-Based Sentinel-2 Composites for Rubber Plantation Mapping in a Large Area with Complex Vegetation Landscapes,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Huang, C.[Chong], Zhang, C.C.[Chen-Chen], Li, H.[He],
Assessment of the Impact of Rubber Plantation Expansion on Regional Carbon Storage Based on Time Series Remote Sensing and the InVEST Model,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Li, X.[Xin], Wang, X.C.[Xin-Cheng], Gao, Y.F.[Yuan-Feng], Wu, J.H.[Jiu-Hao], Cheng, R.X.[Ren-Xi], Ren, D.H.[Dong-Hao], Bao, Q.[Qing], Yun, T.[Ting], Wu, Z.X.[Zhi-Xiang], Xie, G.S.[Gui-Shui], Chen, B.Q.[Bang-Qian],
Comparison of Different Important Predictors and Models for Estimating Large-Scale Biomass of Rubber Plantations in Hainan Island, China,
RS(15), No. 13, 2023, pp. 3447.
DOI Link 2307
BibRef

Fang, J.H.[Jia-Hao], Shi, Y.L.[Yong-Liang], Cao, J.H.[Jian-Hua], Sun, Y.[Yao], Zhang, W.M.[Wei-Min],
Active Navigation System for a Rubber-Tapping Robot Based on Trunk Detection,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link 2308
BibRef

Zhou, H.[Hang], Zhang, G.[Gan], Zhang, J.X.[Jun-Xiong], Zhang, C.L.[Chun-Long],
Mapping of Rubber Forest Growth Models Based on Point Cloud Data,
RS(15), No. 21, 2023, pp. 5083.
DOI Link 2311
BibRef

Cheng, X.Z.[Xiang-Zhe], Feng, Y.Y.[Yu-Yun], Guo, A.T.[An-Ting], Huang, W.J.[Wen-Jiang], Cai, Z.Y.[Zhi-Ying], Dong, Y.Y.[Ying-Ying], Guo, J.[Jing], Qian, B.X.[Bin-Xiang], Hao, Z.Q.[Zhuo-Qing], Chen, G.[Guiliang], Liu, Y.X.[Yi-Xian],
Detection of Rubber Tree Powdery Mildew from Leaf Level Hyperspectral Data Using Continuous Wavelet Transform and Machine Learning,
RS(16), No. 1, 2024, pp. xx-yy.
DOI Link 2401
BibRef

Cheng, X.Z.[Xiang-Zhe], Huang, M.N.[Meng-Ning], Guo, A.[Anting], Huang, W.J.[Wen-Jiang], Cai, Z.Y.[Zhi-Ying], Dong, Y.Y.[Ying-Ying], Guo, J.[Jing], Hao, Z.Q.[Zhuo-Qing], Huang, Y.[Yanru], Ren, K.[Kehui], Hu, B.[Bohai], Chen, G.[Guiliang], Su, H.P.[Hai-Peng], Li, L.[Lanlan], Liu, Y.X.[Yi-Xian],
Early Detection of Rubber Tree Powdery Mildew by Combining Spectral and Physicochemical Parameter Features,
RS(16), No. 9, 2024, pp. 1634.
DOI Link 2405
BibRef


Amaral, C.H., Almeida, T.I.R., Quitério, G.C.M., Alves, M.N., de Souza Filho, C.R.[Carlos Roberto],
Change Analysis of the Spectral Characteristics of Rubber Trees at Canopy and Leaf Scales During The Brazilian Autumn,
ISPRS12(XXXIX-B8:381-386).
DOI Link 1209
BibRef

Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Palm Trees, Oil Palms, Trees as Crops .


Last update:May 29, 2024 at 17:34:46