数据集(库)目录

出版期刊|区域分类

2021年第12期
2019年第02期
数据详情

基于MOD09GQ计算的西双版纳橡胶人工林落叶日数据集(2003-2019)


陈燕玲1,2周瑞伍3陈耀亮*1,2张晶1刘雅琪1
1 中国科学院西双版纳热带植物园,勐腊6663032 福建师范大学地理科学学院,福州 3500073 玉溪师范学院地理与土地工程学院,玉溪 653100

DOI:10.3974/geodb.2022.12.06.V1

出版时间:2022年12月

网页浏览次数:5157       数据下载次数:29      
数据下载量:22.06 MB      数据DOI引用次数:

关键词:

橡胶人工林,落叶日,物候,MOD09GQ,2003-2019

摘要:

西双版纳橡胶人工林具有与当地天然林和其他植被不同的物候现象,即干季时出现短暂落叶期,因此监测橡胶林物候动态变化对深入理解橡胶林对气候变化的响应具有重要的理论意义。然而由于热带地区多云雨天气,利用遥感技术对橡胶林物候进行精确反演仍是一个挑战。基于2003-2019年前一年10月至当年5月每日MOD09GQ地表反射率数据,计算归一化植被指数(NDVI)时间序列;结合每年橡胶林分布影像,对时间序列进行插补、滤波、去除异常值等信号还原处理;采用TIMESAT软件对橡胶林的落叶物候进行提取,得到基于MOD09GQ计算的西双版纳橡胶人工林落叶日数据集(2003-2019)。该数据集包括:(1)研究区域的边界数据;(2)2003-2019每年的橡胶人工林落叶日数据。数据集存储为.shp和.tif格式,由25个数据文件组成,数据量为89.3 MB(压缩为1个文件,779 KB)。

基金项目:

中国科学院热带森林生态学重点实验室(20-CAS-TFE-01);国家自然科学基金(41901124)

数据引用方式:

陈燕玲, 周瑞伍, 陈耀亮*, 张晶, 刘雅琪. 基于MOD09GQ计算的西双版纳橡胶人工林落叶日数据集(2003-2019)[J/DB/OL]. 全球变化数据仓储电子杂志(中英文), 2022. https://doi.org/10.3974/geodb.2022.12.06.V1.

参考文献:

[1] Priyadarshan, P. M. Biology of Hevea rubber [M]. Springer, 2011.
     [2] 肖池伟, 封志明, 李鹏. 1961-2013 年全球橡胶生产时空演变特征[J]. 地理科学进展, 2016, 35(10): 1228-36.
     [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] 崔林丽, 史军, 杜华强. 植被物候的遥感提取及其影响因素研究进展[J]. 地球科学进展, 2021, 36(1): 9-16.
     [10] Verhegghen, A., Bontemps, S., Defourny, P. A global NDVI and EVI reference dataset 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] 陈效逑, 王林海. 遥感物候学研究进展[J]. 地理科学进展, 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.
     

数据下载:

序号 数据名 数据大小 操作
1 XSBN_Rubber_Phenology.rar 779.07KB
主管单位