Skip to main content

Advertisement

Log in

Global drought monitoring with big geospatial datasets using Google Earth Engine

  • Research Article
  • Published:
Environmental Science and Pollution Research Aims and scope Submit manuscript

Abstract

Drought or dryness occurs due to the accumulative effect of certain climatological and hydrological variables over a certain period. Droughts are studied through numerically computed simple or compound indices. Vegetation condition index (VCI) is used for observing the change in vegetation that causes agricultural drought. Since the land surface temperature has minimum influence from cloud contamination and humidity in the air, so the temperature condition index (TCI) is used for studying the temperature change. Dryness or wetness of soil is a major indicator for agriculture and hydrological drought and for that purpose, the index, soil moisture condition index (SMCI), is computed. The deviation of precipitation from normal is a major cause for meteorological droughts and for that purpose, precipitation condition index (PCI) is computed. The years when the indices escalated the dryness situation to severe and extreme are pointed out in this research. Furthermore, an interactive dashboard is generated in the Google Earth Engine (GEE) for users to compute the said indices using country boundary, time period, and ecological mask of their choice: Agriculture Drought Monitoring. Apart from global results, three case studies of droughts (2002 in Australia, 2013 in Brazil, and 2019 in Thailand) computed via the dashboard are discussed in detail in this research.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data availability

All the datasets are available in the repository of Google Earth Engine. The details and specifications of each dataset have already been mentioned in the datasets.

References

Download references

Author information

Authors and Affiliations

Authors

Contributions

Supervision, project administration, writing-review and editing, and validation were performed by Dr. Hammad Gilani. Data curation, formal analysis, investigation, methodology, software, visualization, and writing-original draft were the duty of Ramla Khan. The main idea of the research was the combined effort of both authors.

Corresponding author

Correspondence to Ramla Khan.

Ethics declarations

Ethical approval

Not applicable

Consent to participate

Not applicable

Consent to publish

Not applicable

Additional information

Responsible Editor: Philippe Garrigues

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

Khan, R., Gilani, H. Global drought monitoring with big geospatial datasets using Google Earth Engine. Environ Sci Pollut Res 28, 17244–17264 (2021). https://doi.org/10.1007/s11356-020-12023-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11356-020-12023-0

Keywords

Navigation