Conference item
Improved flood mapping for efficient policy design by fusion of Sentinel-1, Sentinel-2 and Landsat-9 imagery to identify population and infrastructure exposed to floods
- Abstract:
- A reliable yet inexpensive tool for the estimation of flood water spread is conducive for efficient disaster management. The application of optical and SAR imagery in tandem provides a means of extended availability and enhanced reliability of flood mapping. We propose a methodology to merge these two types of imagery into a common data space and demonstrate its use in the identification of affected populations and infrastructure for the 2022 floods in Pakistan. The merging of optical and SAR data provides us with improved observations in cloud-prone regions; that is then used to gain additional insights into flood mapping applications. The use of open source datasets from WorldPop1 and OSM2 for population and roads respectively makes the exercise globally replicable. The integration of flood maps with spatial data on population and infrastructure facilitates informed policy design. We have shown that within the top five flood-affected districts in Sindh province, Pakistan, the affected population accounts for 31%, while the length of affected roads measures 1410.25 km out of a total of 7537.96 km.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 9.7MB, Terms of use)
-
- Publisher copy:
- 10.1109/igarss52108.2023.10282530
Authors
- Publisher:
- IEEE
- Host title:
- IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
- Pages:
- 1591-1594
- Publication date:
- 2023-10-20
- Event title:
- 2023 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2023)
- Event location:
- Pasadena, California, USA
- Event website:
- https://2023.ieeeigarss.org/
- Event start date:
- 2023-07-16
- Event end date:
- 2023-07-21
- DOI:
- EISSN:
-
2153-7003
- ISSN:
-
2153-6996
- EISBN:
- 9798350320107
- ISBN:
- 9798350331745
- Language:
-
English
- Keywords:
- Pubs id:
-
2279725
- Local pid:
-
pubs:2279725
- Deposit date:
-
2026-06-18
- ARK identifier:
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2023
- Rights statement:
- Copyright © 2023, IEEE
- Notes:
- This is the accepted manuscript version of the article. The final version is available online from IEEE at https://dx.doi.org/10.1109/igarss52108.2023.10282530
- Licence:
- CC Attribution (CC BY)
If you are the owner of this record, you can report an update to it here: Report update to this record