Skip to main content

Advertisement

SpringerLink
Log in

Carbon emissions in the field of land use, land use change, and forestry in the Vietnam mainland

  • Original Paper
  • Published:
Wetlands Ecology and Management Aims and scope Submit manuscript

Abstract

The biennial report of Vietnam includes updated information on the greenhouse gas emissions for the base years which are specified by the United Nations Framework Convention on Climate Change for reporting on greenhouse gas emissions by member nations of the Intergovernmental Panel on Climate Change. The estimation of greenhouse gas emissions in general and carbon emissions in particular in the field of land use, land use change, and forestry using advanced technology to provide the input data was recommended. Remote sensing technology with transparency, multi-time characteristics, and wide coverage is useful in this area. An experiment on carbon emission estimation was carried out based on land cover change over ten years between 2002 and 2012. The results obtained by remote sensing data classification for the land cover categories achieved a reliability of 68% for the year 2002 and 67% for the year 2012. Data in relation to the land cover change, soil zoning, and ecological/climate zoning in the Vietnamese mainland, through the process of integrating, processing, and synthesizing data, and using the reported activity data and carbon emission coefficients, were input into the Agriculture and Land Use Greenhouse Gas Inventory Software for carbon emission estimations based on the quality control and quality assurance work.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • The United States Geological Survey (USGS). Landsat Satellite Missions. https://earthexplorer.usgs.gov/

  • Alvarez R, Bonifaz R, Lunetta RS, Garcia C, Gomez G, Castro R, Bernal A, Cabrera AL (2003) Multitemporal landcover classification of Mexico using Landsat MSS imagery. Int J Remote Sens 24:2501–2514. https://doi.org/10.1080/01431160210153066

    Article  Google Scholar 

  • Buchwitz M, Reuter M, Schnesing O, Boesch H, Guerlet S, Dils B, Aben I, Armante R, Bergamaschi P, Bovensmann H et al (2015) The greenhouse gas climate change initiative (GHG-CCI): comparison and quality assessment of near-surface-sensitive satellite-derived CO2 and CH4 global data sets. Remote Sens Environ 162:344–362. https://doi.org/10.1016/j.rse.2013.04.024

    Article  Google Scholar 

  • Cairns MA, Brown S, Helmer EH, Baumgardner GA (1997) Root biomass allocation in the world’s upland forests. Oecologia 111:1

    Article  Google Scholar 

  • Chen W, Bo D, Xiaohui C, Liangpei Z (2017) A post-classification change detection method based on iterative slow feature analysis and Bayesian soft fusion. Remote Sens Environ 199:241–255. https://doi.org/10.1016/j.rse.2017.07.009

    Article  Google Scholar 

  • Congalton RG (1991) A review of assessing the accuracy of classification of remotely sensed data. Remote Sens Environ 37:35–46. https://doi.org/10.1016/0034-4257(91)90048-B

    Article  Google Scholar 

  • Crisp D, Atlas RM, Breon FM, Brown LR, Burrows JP, Ciais P, Connor BJ, Doney SC, Fung LY, Jacob DJ, Miller CE, Brien DO, Pawson S, Randerson JT, Rayner P, Salawitch RJ, Sande SP et al (2004) The orbiting carbon observatory (OCO) mission. Adv Space Res 34(4):700–709. https://doi.org/10.1016/j.asr.2003.08.062

    Article  CAS  Google Scholar 

  • Cristina G, Joanne CW, Michael AW (2016) Optical remotely sensed time series data for land cover classification: a review. ISPRS J Photogrammetry Remote Sens 116:55–72. https://doi.org/10.1016/j.isprsjprs.2016.03.008

    Article  Google Scholar 

  • Circular No. 10/2015/TT-BTNMT about Technical regulations for producing remote sensing imagery with high and super high resolution to be supplied to users. (2015) Ministry of Natural Resorces and Environment of Vietnam (MONRE).

  • Circular No. 27/2018/TT-BTNMT on Land statistics, inventory and land use status mapping (2018) Ministry of Natural Resorces and Environment of Vietnam (MONRE).

  • Decision No. 83/2000/QD-TTg on The use of the Vietnam national reference and coordinate system (2000) Vietnamese Prime Minister (VNPM).

  • Decision No. 05/2007/QD-BTNMT about the use of calculation and transfer parameters system between the international coordinate system WGS-84 and the national coordinate system VN-2000 (2007) Ministry of Natural Resorces and Environment of Vietnam (MONRE).

  • Datta D (2018) Assessment of mangrove management alternatives in village-fringe forests of Indian Sunderbans: resilient initiatives or short-term nature exploitations. Wetl Ecol Manag 26:399–413. https://doi.org/10.1007/s11273-017-9582-7

    Article  Google Scholar 

  • Douglas OF (2006) Tropical forest monitoring and remote sensing: A new era of transparency in forest governance? Singap J Trop Geogr 27(1):15–29. https://doi.org/10.1111/j.1467-9493.2006.00237.x

    Article  Google Scholar 

  • First Vietnam National report to the United Nations Framework Convention. on Climate Change (2003) Ministry of Natural Resources and Environment of Vietnam (MONRE).

  • Research Center for Forest Ecology and Environment (RCFEE) (2011) Forestry ecological zoning in Vietnam. UN-REDD Programme.

  • Franklin SE, Wulder MA (2002) Remote sensing methods in medium spatial resolution satellite data land cover classification of large areas. Prog Phys Geogr 26:173–205. https://doi.org/10.1191/0309133302pp332ra

    Article  Google Scholar 

  • Gandhi GM, Parthiban S, Thummalu N, Christy A (2015) Ndvi: Vegetation change detection using remote sensing and GIS—A case study of Vellore District. Pcocedia Computer Science 57:1199–1210

    Article  Google Scholar 

  • Intergovernmental Panel on Climate Change (IPCC) (2003) Good practice Guidance for land use, land-use change and forestry.

  • Intergovernmental Panel on Climate Change (IPCC) (1996) Guidelines for National Greenhouse Gas Inventories.

  • Intergovernmental Panel on Climate Change (IPCC) (2006) Guidelines for national greenhouse gas inventories 4.

  • Jensen JR (2005) Introductory digital image processing—a remote sensing perspective. Pearson Prentice Hall, USA

    Google Scholar 

  • Lawson IT, Kelly TJ, Aplin P, Boom A, Dargie G, Draper FCH, Hassan PNZBP, Hoyos-Santillan J, Kaduk J, Large D, Murphy W, Page SE, Roucoux KH, Sjögersten S, Tansey K, Waldram M, Wedeux BMM, Wheeler J (2015) Improving estimates of tropical peatland area, carbon storage, and greenhouse gas fluxes. Wetl Ecol Manag 23:327–346. https://doi.org/10.1007/s11273-014-9402-2

    Article  Google Scholar 

  • Lei LP, Guan XH, Zeng ZZ, Zhang B, Ru F, Bu R (2014) A comparison of atmospheric CO2 concentration GOSAT-based observations and model simulations. Sci China Earth Sci 57:1393–1402. https://doi.org/10.3390/s19051118

    Article  CAS  Google Scholar 

  • Lin C, Thomson G, Popescu SC (2016) An IPCC-Compliant technique for forest carbon stock assessment using airborne LiDAR-Derived Tree Metrics and Competition Index. Remote Sens 8(6):528. https://doi.org/10.3390/rs8060528

    Article  Google Scholar 

  • Li M, Zang S, Zhang B, Li S, Wu C (2014) A Review of remote sensing image classification techniques: the role of spatio-contextual information. Eur J Remote Sens 47:389–411. https://doi.org/10.5721/EuJRS20144723

    Article  Google Scholar 

  • Lu D, Weng Q (2007) A survey of image classification methods and techniques for improving classification performance. Int J Remote Sens 28(5):823–870. https://doi.org/10.1080/01431160600746456

    Article  Google Scholar 

  • Lu H, Liu G, Zhao J, Jiang I (2013) Current remote sensing options for monitoring carbon emissions. 21st International Conference on Geoinformatics.

  • Nam VN, Sasmito SD, Murdiyarso D, Purbopuspito J, MacKenzie RA (2016) Carbon stocks in artificially and naturally regenerated mangrove ecosystems in the Mekong Delta. Wetlands Ecol Manage 24:231–244. https://doi.org/10.1007/s11273-015-9479-2

    Article  CAS  Google Scholar 

  • Manual for the Agriculture and Land Use Software Program (2014) Version 4.5. Natural Resource Ecology Laboratory, Colorado University, CO, 80523 USA.

  • Olivier JGJ, Schure KM and Peters JAHW (2017) Trends in global CO2 and total greenhouse gas emissions. https://www.pbl.nl/sites/default/files/downloads/pbl-2017-trends-in-global-co2-and-total-greenhouse-gas-emissons-2017-report_2674.pdf

  • Richards JA (1993) Remote sensing digital image analysis—an introduction. Springer, Berlin

    Book  Google Scholar 

  • Second Vietnam National report to the United Nations Framework Convention. on Climate Change (2010) Ministry of Natural Resources and Environment of Vietnam (MONRE).

  • The second biennial updated report of Vietnam to the United Nations Framework Convention on Climate Change (2017) Vietnam Publishing House of Natural Resources, Environment and Cartography.

  • The United Nations Framework Convention on Climate Change (2012) Training Materials for National Greenhouse Gas Inventories: Quality Assurance/Quality Control Version 2.

  • Wang M, Cao W, Guan Q, Jiang C, Yan Y, Su X (2018) Potential of texture metrics derived from high-resolution PLEIADES satellite data for quantifying aboveground carbon of Kandelia candel mangrove forests in Southeast China. Wetlands Ecol Manage 26:789–803. https://doi.org/10.1007/s11273-018-9610-2

    Article  CAS  Google Scholar 

  • Yifan C, Long L, Longqian C, Yu Z, Liang C, Xisheng Z, Xiaoyan Y (2018) Settings open accessarticle land-use carbon emissions estimation for the Yangtze River Delta urban agglomeration using 1994–2016 Landsat Image Data. Remote Sens 10(9):1334. https://doi.org/10.3390/rs10091334

    Article  Google Scholar 

  • Yoshida Y, Ota Y, Eguchi N, Kikuchi N, Nobuta K, Tran H, Morino I, Yokota T (2011) Retrieval algorithm for CO2 and CH4 column abundances from short-wavelength infrared spectral observations by the greenhouse gases observing satellite. Atmos Meas Tech 4:717–734. https://doi.org/10.5194/amt-4-717-2011

    Article  CAS  Google Scholar 

  • Yu W, Xicun Z, Cheng L, Xiaoyan G, Xinyang Y, Chunyan C, Houxing S (2017) Applications of hyperspectral remote sensing in ground object identification and classification. Adv Remote Sens 6(3):201–211. https://doi.org/10.4236/ars.2017.63015

    Article  Google Scholar 

Download references

Acknowledgements

Many thanks must first go to the Program management board of the Vietnam National Science and Technology program on Space Technology (period 2016–2020, code CNVT/16-20) for financing us. This support is gratefully acknowledged. For materials, suggestions, and assistance, the authors would like to thank the research group of the project "Studying on carbon emission calculation using remote sensing data serving for greenhouse gas inventory. Case study by using image VNREDSat-1 and existing image sources in Vietnam”, code VT-UD.06/17-20 (belonging to the Vietnam National Science and Technology program on Space Technology, period 2016–2020). In particular, thanks are extended to our colleagues, Vu Thi Tuyet and Tran Thu Huyen, who spent their time helping us in numerous ways in order to bring our task to fruition.

Author information

Authors and Affiliations

  1. National Remote Sensing Department, Ministry of Natural Resources and Environment of Vietnam, 83 Nguyen Chí Thanh, Dong Da, Hanoi, 10057, Vietnam

    Le Quoc Hung

  2. Department of Environmental Science and Human Engineering, Saitama University, Japan, 255 Shimo-okubo, Sakura-ku, Saitama-shi, Saitama-ken, 338-8570, Japan

    Takashi Asaeda

  3. Hanoi University of Mining and Geology, Ministry of Education and Training of Vietnam, 18 Duc Thang, Bac Tu Liem, Hanoi, 10053, Vietnam

    Vu Thi Phuong Thao

Authors
  1. Le Quoc Hung
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Takashi Asaeda
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Vu Thi Phuong Thao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Le Quoc Hung.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hung, L.Q., Asaeda, T. & Thao, V.T.P. Carbon emissions in the field of land use, land use change, and forestry in the Vietnam mainland. Wetlands Ecol Manage 29, 315–329 (2021). https://doi.org/10.1007/s11273-021-09789-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11273-021-09789-6

Keywords

Search

Navigation