Früher|Nächster

Global Ecosystems and Environment Observation： Annual Report from China （GEOARC）： 2012—2021

  • role： First author第一作者
  • Affiliation：

    National Remote sensing center of China, Beijing 100036, China

  • Email：liuyiliang@nrscc.gov.cn
  • Introduction：刘一良，研究方向为生态环境遥感。E-mail： liuyiliang@nrscc.gov.cn
LIU Yiliang1,  
  • Affiliation：

    National Remote sensing center of China, Beijing 100036, China

ZHANG Jing1,  
  • Affiliation：

    National Remote sensing center of China, Beijing 100036, China

WANG Sisi1,  
  • Affiliation：

    National Remote sensing center of China, Beijing 100036, China

MIAO Chen1,  
  • Affiliation：

    National Remote sensing center of China, Beijing 100036, China

LI Han1,  
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

SONG Wanjuan2,  
  • role： Corresponding author通信作者
  • Affiliation：

    National Remote sensing center of China, Beijing 100036, China

  • Email：frances.zhang@163.com
  • Introduction：张松梅，研究方向为咨询环境遥感。E-mail： frances.zhang@163.com
ZHANG Songmei1*

Resümee

Remote sensing observation on ecosystems and environment can continuously provide global insights of scientific significance on the sustainability of ecosystems and the status of human environment. It is also a concrete practice to advance the capability of global comprehensive earth observation and address ecological and environmental challenges in line with the goals and visions of advancing ecological civilization and building a shared future for all life on Earth. National Remote Sensing Center of China (NRSCC) initiated Global Ecosystems and Environment Observation: Annual Report from China (GEOARC) and has been continuously releasing 29 reports and more than 100 open-access datasets in ten years from 2012 to 2021, focusing on the priorities of Sustainable Development, Climate Change, Disaster Risk Reduction and Urban Resilience, the outcomes have been accomplished through the collaboration of governmental agencies, research institutions, international organizations and the public. The primary achievements are: (1) A batch of innovative algorithm models and data products with independent intellectual property rights have been obtained based on domestic high-resolution satellite and multi-source remote sensing images for fine-scaled remote sensing monitoring of ecosystem conditions and human footprints. (2) It has significantly improved the public's scientific cognition on key topics such as food security, climate change, urban expansion, land degradation, and natural disaster risk. (3) Fine-scaled observation and assessment were carried out on key regions such as the Belt and Road , Antarctica, Africa, ASEAN and ecologically fragile areas. This is also China's substantial contribution to the international community as the co-chair of GEO (Group on Earth Observations), and provides important information reference for decision making by relevant agencies and departments. On the occasion of 10th anniversary, this paper systematically elaborated and summarized the contents and highlights of the annual reports, and put forward the prospect of GEOARC.

Schlüsselwort

ecosystems and environment;remote sensing observation;GEOARC;domestic satellites

References

  1. 1.
    Chen J, Liao A P, Chen L J, Zhang H W, He C Y, Peng S, Wu H, Zhang W W, Li R, Zheng X Y, Mei Y, Lu M, Lu N, Kang R, Xing H Q, Liu L F, Han G, Wang J, Yang A L, Sun L M, Song H, Chen W P, Zhou X M, Xia L, Jiang H B, Huo J, Zhang Y, Liu W D, Li Y X, Zhai L and Sang H Y. 2017. Content and composition of global artificial land surface dataset at 30 m resolution (2010). Journal of Global Change Data and Discovery, 1(2): 136-148
  2. 2.
    Chu W B and Larlee C. 2021. GEO Highlights 2021: GEO Secretariat[EB/OL].
  3. 3.
    Du S S, Liu L Y, Liu X J, Zhang X, Zhang X Y, Bi Y M and Zhang L C. 2018. Retrieval of global terrestrial solar-induced chlorophyll fluorescence from TanSat satellite. Science Bulletin, 63(22): 1502-1512
  4. 4.
    Gao S, Liu Q H, Kang J, Zhao J, Li J, Zhong B, Wu S L and Peng J J. 2017. 1 km resolution dataset of vegetation net primary productivity over China-ASEAN (2013). Journal of Global Change Data and Discovery, 1(3): 303-308
  5. 5.
    Gao Z H. 2020. The global land degradation situation since 2000[EB/OL]. Chinese Society of Surveying and Mapping.
  6. 6.
    Gong P, Wang J, Yu L, Zhao Y C, Zhao Y Y, Liang L, Niu Z G, Huang X M, Fu H H, Liu S, Li C C, Li X Y, Fu W, Liu C X, Xu Y, Wang X Y, Cheng Q, Hu L Y, Yao W B, Zhang H, Zhu P, Zhao Z Y, Zhang H Y, Zheng Y M, Ji L Y, Zhang Y W, Chen H, Yan A, Guo J H, Yu L, Wang L, Liu X J, Shi T T, Zhu M H, Chen Y L, Yang G W, Tang P, Xu B, Giri C, Clinton N, Zhu Z L, Chen J and Chen J. 2013. Finer resolution observation and monitoring of global land cover: first mapping results with Landsat TM and ETM+ data. International Journal of Remote Sensing, 34(7): 2607-2654
  7. 7.
    Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D and Moore R. 2017. Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202: 18-27
  8. 8.
    He X Q, Lin M S, Hao Z Z, Wang D F, Bai Y and Yu S J. 2019. Remote sensing monitoring of marine ecological environment in the region of the 21st-Century Maritime Silk Road. Beijing: Science Press
  9. 9.
    IGBP (International Geosphere-Biosphere Program). 1999. Land-Use and Land-Cover Change (LUCC) Implementation Strategy. IGBP Report No. 48/IHDP Report No 10. International Geosphere-Biosphere Programme (IGBP), International Human Dimension Programme on Global Environmental Change (IHDP)
  10. 10.
    Kim K, Wang M C, Ranjitkar S, Liu S H, Xu J C and Zomer R J. 2017. Using leaf area index (LAI) to assess vegetation response to drought in Yunnan province of China. Journal of Mountain Science, 14(9): 1863-1872
  11. 11.
    Kuang W H. 2019. Mapping global impervious surface area and green space within urban environments. Science China Earth Sciences, 62(10): 1591-1606
  12. 12.
    Kuang W H, Du G M, Lu D S, Dou Y Y, Li X Y, Zhang S, Chi W F, Dong J W, Chen G S, Yin Z R, Pan T, Hamdi R, Hou Y L, Chen C Y, Li H and Miao C. 2021. Global observation of urban expansion and land-cover dynamics using satellite big-data. Science Bulletin, 66(4): 297-300
  13. 13.
    Li Y X, Quan X W, Liao Z M and He B B. 2021. Forest fuel loads estimation from Landsat ETM + and ALOS PALSAR data. Remote Sensing, 13(6): 1189
  14. 14.
    Liang S L, Zhao X, Liu S H, Yuan W P, Cheng X, Xiao Z Q, Zhang X T, Liu Q, Cheng J, Tang H R, Qu Y H, Bo Y C, Qu Y, Ren H Z, Yu K and Townshend J. 2013. A long-term global land surface satellite (GLASS) data-set for environmental studies. International Journal of Digital Earth, 6(S1): 5-33
  15. 15.
    Liao X H. 2021. Scientific and technological progress and development prospect of the earth observation in China in the past 20 years. National Remote Sensing Bulletin, 25(1): 267-275
  16. 16.
    Liu J, Wang W and Zhong H. 2020. EarthDataMiner: a cloud-based big earth data intelligence analysis platform. IOP Conference Series: Earth and Environmental Science, 509(1): 012032
  17. 17.
    Liu Q H, Wang X H, Zhang Y L, Zhang H M and Li L H. 2019. Vegetation degradation and its driving factors in the farming-pastoral ecotone over the countries along Belt and Road Initiative. Sustainability, 11(6): 1590
  18. 18.
    Liu Q H, Wu J J, Li L, Yu L, Li J, Xin X Z, Jia L, Zhong B, Niu Z, Xu X L, Meng Q Y, Zhao J, Zhang H L, Hu G C and Zheng C L. 2018. Ecological environment monitoring for sustainable development goals in the Belt and Road region. Journal of Remote Sensing, 22(4): 686-708
  19. 19.
    Liu Y, Zhou C X, Zheng L and Wang Z M. 2020. Surface freeze-thaw dataset development of the Antarctic ice sheet based on multisource data (1999-2019). Journal of Global Change Data and Discovery, 4(4): 325-331
  20. 20.
    Ma Y, Liu L Y, Chen R N, Du S S and Liu X J. 2020. Generation of a global spatially continuous TanSat solar-induced chlorophyll fluorescence product by considering the impact of the solar radiation intensity. Remote Sensing, 12(13): 2167
  21. 21.
    Niu Z, Li J H, Gao Z H, Gong E D, Zhang S M, Zhang J, Liu S, Ouyang X Y and Zhang R. 2018. Progress and future of China’s annual report on remote sensing monitoring of global ecosystem and environment. Journal of Remote Sensing, 22(4): 672-685
  22. 22.
    Niu Z G, Zhang H Y and Gong P. 2011. More protection for China’s wetlands. Nature, 471(7338): 305-305
  23. 23.
    Quan X W, He B B, Yebra M, Liu X Z, Liu X F, Zhang X D and Cao H. 2018. Retrieval of fuel moisture content from Himawari-8 product: towards real-time wildfire risk assessment//IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. Valencia: IEEE: 7660-7663
  24. 24.
    Tian H F, Niu Z, Liu Q H, Wu M Q, Fu D M, Li L, Wu J J, Pei J, Gong W, Cheng L and Zhong B. 2019. The vegetation coverage datasets covering ten interconnection projects of the Belt and Road Initiative (2017). Journal of Global Change Data and Discovery, 3(1): 27-33
  25. 25.
    UN (United Nations). 2015. Transforming our world: the 2030 agenda for sustainable development A/RES70/1[EB/OL].
  26. 26.
    Wu B F, Zhang M, Zeng H W, Zhang X, Yan N N and Meng J H. 2016. Agricultural monitoring and early warning in the era of big data. Journal of Remote Sensing, 20(5): 1027-1037
  27. 27.
    Xu G H. 2019. Based in China to the World: Earth Observations and Global Change. Beijing: Science Press
  28. 28.
    Yan J F, Wang M H, Su F Z, Xiao R M and Wang T. 2021. Analysis of the change in the ecological environment based on remote sensing in typical coastal zones of the Indian Ocean from 1990 to 2017. Arabian Journal of Geosciences, 14(12): 1092
  29. 29.
    Zhong B, Wu S L, Liu Q H, Shan X J, Yang A X and Peng J J. 2017. 1 km/5 day surface reflectance data product over China-ASEAN (2013). Journal of Global Change Data and Discovery, 1(3): 290-298

Lesen Sie die ganze Passage

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website