Dataset List

Vol.|Area

Data Details

Vegetation Phenology Dataset Based on MOD13Q1 in Mongolia (2001-2019)


SHAO Yating1WANG Juanle*1
1 Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China

DOI:10.3974/geodb.2022.03.05.V1

Published:Mar. 2022

Visitors:8141       Data Files Downloaded:161      
Data Downloaded:45027.89 MB      Citations:

Key Words:

Mongolia,vegetation phenology,length of growing season

Abstract:

Mongolia is an important part of the Mongolian Plateau, and an important response region to global ecological and environmental changes. The vegetation phenology dataset based on MOD13Q1 in Mongolia (2001-2019) was developed based on the data integration between the MOD13Q1 NDVI product with dynamic threshold method on the TIMESAT platform. The day when the NDVI value reaches 50% of the amplitude of NDVI change in spring was determined as beginning of the growing season; when the NDVI value drops to 55% of the NDVI amplitude in autumn, the day was taken as end of the growing season. The result shows that the average length of vegetation growing season was 90-207 d in Mongolia during 2001-2019. The dataset includes annual and average data of the start of growing season (SOS), end of growing season (EOS), and length of growing season (LOS) in Mongolian vegetation from 2001 to 2019. The spatial resolution is 250 m. The dataset is archived in.tif data format, and consists of 60 data files with data size of 944 MB (Compressed into three files with 844 MB). The research paper based on this dataset was published in Geographical Research, Vol. 40, No. 11, 2021.Browse

Foundation Item:

National Natural Science Foundation of China (32161143025, 41971385); Chinese Academy of Sciences (XDA2003020302)

Data Citation:

SHAO Yating, WANG Juanle*. Vegetation Phenology Dataset Based on MOD13Q1 in Mongolia (2001-2019)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2022. https://doi.org/10.3974/geodb.2022.03.05.V1.

SHAO Yating, WANG Juanle. Vegetation phenology dataset in Mongolia (2001–2019) [J] Journal of Global Data & Discovery, 2022, 6(2): 241–248.

References:

[1] Wang, Z. B., Chen, J., Xing, F. F., et al. Response of cotton phenology to climate change on the North China Plain from 1981 to 2012 [J]. Scientific Reports, 2017, 7: 6628. https://doi.org/10.1038/s41598-017-07056-4.
     [2] Wang, J. M, Xi, Z. X., He, X. J., et al. Contrasting temporal variations in responses of leaf unfolding to daytime and nighttime warming [J]. Global Change Biology. 2021. DOI: 10.1111/gcb.15777.
     [3] Liu, X. G., Chen, Y. N., Li, Z., et al. Driving forces of the changes in vegetation phenology in the Qinghai-Tibet Plateau [J]. Remote Sensing. 2021, 13: 4952. https://doi.org/.10.3390/rs13234952.
     [4] Liu, H. Y., Wang, H., Li, N. et al. Phenological mismatches between above- and belowground plant responses to climate warming [J]. Nature Climate Change. 2022, 12: 97-102. https://doi.org/10.1038/s41558-021-01244-x.
     [5] Miao, L. J., Muller, D., Cui, X. F., et al. Changes in vegetation phenology on the Mongolian Plateau and their climatic determinants [J]. Plos One, 2017, 12(12): e0190313. DOI: 10.1371/journal.pone.0190313.
     [6] Dugarsuren, N., Lin, C. Investigation of vegetation dynamics of Mongolia using time series of NDVI in response to temperature and precipitation [J]. Mongolian Journal of Biological Sciences, 2011, 9(1-2): 9-17. DOI: 10.22353/mjbs.2011.09.02.
     [7] Dugarsuren, N., Lin, C. Temporal variations in phenological events of forests, grasslands and desert steppe ecosystems in Mongolia: A remote sensing approach [J]. Annals of Forest Research, 2016, 59(2): 175-190. DOI: 10.15287/afr.2016.400.
     [8] Schulz, C., Koch, R., Cierjacks, A., et al. Land change and loss of landscape diversity at the Caatinga phytogeographical domain: Analysis of pattern-process relationships with MODIS land cover products (2001-2012) [J]. Journal of Arid Environments, 2017, 136: 54-74.
     [9] Zhou, W., Gang, C., Zhou, L., et al. Dynamic of grassland vegetation degradation and its quantitative assessment in the northwest China [J]. Acta Oecologica, 2014, 55(2): 86-96.
     [10] Zhou, W., Gang, C., Chen, Y., et al. Grassland coverage inter-annual variation and its coupling relation with hydrothermal factors in China during 1982-2010 [J]. Journal of Geographical Sciences, 2014, 24(4): 593-611.
     [11] Wu, C., Wang, X., Wang, H., et al. Contrasting responses of autumn-leaf senescence to daytime and night-time warming [J]. Nature Climate Change 2018(8): 1092-1096. https://doi.org/10.1038/s41558-018-0346-z.
     [12] Shao, Y. T., Wang, J. L., Yan, X. R. The phenological characteristics of Mongolian vegetation and its response to geographical elements [J]. Geographical Research, 2021, 40(11): 3029-3045.
     [13] Clinton, N., Yu, L., Fu, H. H., et al. Global-Scale Associations of Vegetation Phenology with Rainfall and Temperature at a High Spatio-Temporal Resolution [J]. Remote Sensing, 2014, 6(8): 7320-7338.
     [14] Wang, J., Wei, H., Cheng, K., et al. Updatable dataset revealing decade changes in land cover types in Mongolia [J]. Geoscience Data Journal, 2022, 00, 1-14. DOI: 10.1002/gdj3.149.
     [15] Cong, N., Shen, M. G. Variation of satellite-based spring vegetation phenology and the relationship with climate in the Northern Hemisphere over 1982 to 2009 [J]. Chinese Journal of Applied Ecology, 2016, 27(9): 2737-2746. DOI:10.13287/j.1001-9332.201609.028.
     [16] Zu, J. X., Zhang, Y. J., Huang, K., et al. Biological and climate factors co-regulated spatial-temporal dynamics of vegetation autumn phenology on the Tibetan Plateau [J]. International Journal of Applied Earth Observation and Geoinformation, 2018, 69: 198-205.
     [17] Fu, Y., Chen, H., Zhang, S. Q., et al. Phenological characteristics of alpine arid region based on biome type and its responses to climate factors: A case study of Qaidam Basin from 2000 to 2019. Geographical Research, 2021, 40(1): 52-66. DOI: 10.11821/dlyj020200327.
     [18] Huang, W. L., Zhang, Q., Kong, D. D., et al. Response of vegetation phenology to drought in Inner Mongolia from 1982 to 2013 [J].Acta Ecologica Sinica, 2019, 39(13) : 4953-4965.
     [19] Bi, Z. R. Temporal and spatial changes of snow depth in Mongolia plateau and its impact on grassland vegetation phenology [D]. Hohhot: Inner Mongolia Normal University, 2020: 40-42.
     [20] Sun, Z. G., Wang, Q. X., Xiao, Q. G., et al. Diverse responses of remotely sensed grassland phenology to interannual climate variability over frozen ground regions in Mongolia [J]. Remote Sensing, 2015, 7(1): 360-377. DOI: 10.3390/rs70100360.
     [21] Li, C. H., Study on the variation of snow cover and its impact on grassland vegetation phenology in Mongolian Plateau [D]. Hohhot: Inner Mongolia Normal University, 2019: 76-79.
     [22] Jiang, K. Changes in phenology and their main factors in the grassland of China-Mongolia border [D]. Hohhot: Inner Mongolia Normal University, 2020.
     [23] Jiang, K., Bao, G., Ulantuya., et al. Variations in spring phenology of different vegetation types in the Mongolian plateau and its responses to climate change during 2001—2017 [J]. Chinese Journal of Ecology, 2019, 38(8): 2490-2499. DOI: 10.13292/j.1000-4890.201908.027.
     [24] Li, Z., Bo, Y. C., He, Y. Q. Comparison of Natural Vegetation Phenology Metrics from Remote Sensing LAI Products [J]. Remote Sensing Technology and Application, 2015, 30(06): 1103-1112.
     

Data Product:

ID Data Name Data Size Operation
0Datapaper_VPD_Mongolia_2001-2019.pdf1437.00kbDownLoad
1 VPD_EOS_2001-2019.rar 262225.88KB
2 VPD_LOS_2001-2019.rar 332173.23KB
3 VPD_SOS_2001-2019.rar 270242.63KB
Co-Sponsors
Superintend