23.4.12.7.3 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

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


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:Oct 16, 2021 at 11:54:21