Dataset List


Data Details

Dataset of Rubber Plantation‘s Start Defoliation Date in Xishuangbanna Based on MOD09GQ (2003-2019)

CHEN Yanling1,2ZHOU Ruiwu3CHEN Yaoliang*1,2ZHANG Jing1LIU Yaqi1
1 CAS Key Laboratory of Tropical Forest Ecology,Xishuangbanna Tropical Botanical Garden,Chinese Academy of Sciences,Mengla 666303,China2 School of Geographical Sciences,Fujian Normal University,Fuzhou 350007,China3 School of Geography and Land Engineering,Yuxi Normal University,Yuxi 653100,China


Published:Dec. 2022

Visitors:4127       Data Files Downloaded:24      
Data Downloaded:18.26 MB      Citations:

Key Words:

rubber plantation,defoliation date,phenology,MOD09GQ,2003-2019


The rubber plantation in Xishuangbanna has different phenological phenomena from the local natural forest and other vegetation, that is, the short deciduous period occurs in the dry season. Therefore, monitoring the dynamic change of the rubber plantation phenology is of great theoretical significance for the in-depth understanding of the rubber forest's response to climate change. The dataset of rubber plantation’s defoliation date in Xishuangbanna based on MOD09GQ (2003-2019) was developed based on the time series of daily MOD09GQ. The authors calculated the Normalized Difference Vegetation Index (NDVI) from October of the previous year to May of the current year during 2003-2019, and preprocessed the data integrated with the annual distribution images of rubber forest, then used TIMESAT to extract defoliation phenology of rubber forest. The dataset includes: 1) boundary data of the study area; (2) annual defoliation date of rubber forest from 2003 to 2019. The dataset is archived in .shp and .tif formats, and consists of 25 data files with data size of 89.3 MB (Compressed into one file with 779 KB).

Foundation Item:

Key Laboratory of Tropical Forest Ecology, Chinese Academy of Sciences (20-CAS-TFE-01); National Natural Science Foundation of China (41901124)

Data Citation:

CHEN Yanling, ZHOU Ruiwu, CHEN Yaoliang*, ZHANG Jing, LIU Yaqi. Dataset of Rubber Plantation‘s Start Defoliation Date in Xishuangbanna Based on MOD09GQ (2003-2019)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2022.


[1] Priyadarshan, P. M. Biology of Hevea rubber [M]. Springer, 2011.
     [2] Xiao, C. W., Feng, Z. M., Li, P. Spatiotemporal changes of global rubber production during 1961-2013[J]. Progress in Geography, 2016, 35(10): 1228-1236
     [3] Chen, J. W., Cao, K. F. A possible link between hydraulic properties and leaf habits in Hevea brasiliensis [J]. Functional Plant Biology, 2015, 42(8): 718-26.
     [4] Chen, Y. L., Wang, S. S., Zhou, R. W., et al. What leads to rubber leaf senescence in the northern edge of the Asian tropics? [J]. Industrial Crops and Products, 2022, 178: 114617.
     [5] Chen, B. Q., Xiao, X. M., Wu, Z. X., et al. Identifying establishment year and pre-conversion land cover of rubber plantations on Hainan Island, China using landsat data during 1987–2015 [J]. Remote Sensing, 2018, 10(8): 1240.
     [6] Dong, J. W., Xiao, X. M., Chen, B. Q., et al. Mapping deciduous rubber plantations through integration of PALSAR and multi-temporal Landsat imagery [J]. Remote Sensing of Environment, 2013, 134: 392-402.
     [7] Kou, W. L., Dong, J. W., Xiao, X. M., et al. Expansion dynamics of deciduous rubber plantations in Xishuangbanna, China during 2000–2010 [J]. GIScience & Remote Sensing, 2018, 55(6): 905-25.
     [8] Xiao, C. W., Li, P., Feng, Z. M. Monitoring annual dynamics of mature rubber plantations in Xishuangbanna during 1987-2018 using Landsat time series data: A multiple normalization approach [J]. International Journal of Applied Earth Observation and Geoinformation, 2019, 77: 30-41.
     [9] Cui, L.L., Shi, J., Du, H.Q. Advances in Remote Sensing Extraction of Vegetation Phenology and Its Driving Factors[J]. Advances in Earth Science, 2021, 36(01): 9-16.
     [10] Verhegghen, A., Bontemps, S., Defourny, P. A global NDVI and EVI reference data set for land-surface phenology using 13 years of daily SPOT-VEGETATION observations [J]. International Journal of Remote Sensing, 2014, 35(7): 2440-71.
     [11] Li, Q., Shen, M. G., Chen, X. H., et al. Optimal color composition method for generating high-quality daily photographic time series from PhenoCam [J]. IEEE Journal of Selected Topics in Applied Earth Observations Remote Sensing, 2021, 14: 6179-93.
     [12] Richardson, A. D., Hufkens, K., Li, X. L., et al. Testing Hopkins’ bioclimatic law with PhenoCam data [J]. Applications in Plant Sciences, 2019, 7(3): e01228.
     [13] White, M. A., Thornton, P. E., Running, S. W. A continental phenology model for monitoring vegetation responses to interannual climatic variability [J]. Global biogeochemical cycles, 1997, 11(2): 217-34.
     [14] Gao, F., Zhang, X. Y. Mapping crop phenology in near real-time using satellite remote sensing: Challenges and opportunities [J]. Journal of Remote Sensing, 2021, 2021.
     [15] Chen, X. Q., Wang, L. H. Progress in remote sensing phenological research [J]. Progress in Geography, 2009, (1): 33-40.
     [16] Fan, H., Fu, X. H., Zhang, Z., et al. Phenology-based vegetation index differencing for mapping of rubber plantations using Landsat OLI data [J]. Remote Sensing, 2015, 7(5): 6041-58.
     [17] Jonsson, P., Eklundh, L. TIMESAT—a program for analyzing time-series of satellite sensor data [J]. Computers & geosciences, 2004, 30(8): 833-45.
     [18] Tucker, C. J. Red and photographic infrared linear combinations for monitoring vegetation [J]. Remote sensing of Environment, 1979, 8(2): 127-50.
     [19] Jonsson, P., Eklundh, L. Seasonality extraction by function fitting to time-series of satellite sensor data [J]. IEEE transactions on Geoscience and Remote Sensing, 2002, 40(8): 1824-32.
     [20] Azizan, F. A., Astuti, I. S., Aditya, M. I., et al. Using multi-temporal satellite data to analyze phenological responses of Rubber (Hevea brasiliensis) to climatic variations in South Sumatra, Indonesia [J]. Remote Sensing, 2021, 13(15): 2932.

Data Product:

ID Data Name Data Size Operation
1 XSBN_Rubber_Phenology.rar 779.07KB