Abstract
Extreme weather events can have devastating impacts on agricultural systems, and the livelihoods that depend on them. Tools for rapid, comprehensive and cost-effective assessment of impacts, especially if carried out remotely, can be of great value in planning systematic recovery of production, as well as assessing risks from future events. Here, we use openly available remote sensing data to quantify the impacts of hurricanes Irma and Maria in 2017 on banana production area in the Dominican Republic — the world’s largest producer of organic bananas. Further, we assess the risk to current production area if a similar extreme event were to re-occur. Hurricane associated damage was mapped using a simple change detection algorithm applied to Synthetic Aperture Radar (SAR) data over the three main banana growing provinces of northern Dominican Republic, i.e. Monte Cristi, Valverde and Santiago. The map of hurricane affected area was overlaid with banana plantation distributions for 2017 and 2019 that were mapped (accuracy = 99.8%) using a random forest classifier, and a combination of SAR and multi-spectral satellite data. Our results show that 11.35% of banana plantation area was affected by hurricane damage in 2017. Between 2017 and 2019, there was a high turnover of plantation area, but with a net gain of 10.8%. However, over a quarter (26.9%) of new plantation area spatially overlapped with regions which had seen flooding or damage from hurricanes in 2017. Our results indicate that banana production systems in northern Dominican Republic saw extensive damage in the aftermath of hurricanes Irma and Maria. While production area has recovered since then, a substantial proportion of new plantations, and a greater fraction of production area in general, occur at locations at risk from future extreme events.
Competing Interest Statement
The authors have declared no competing interest.
Abbreviations used
- AS
- ‘After set’ of images; A three month collection of Sentinel-1 images (seven images) during and after hurricanes Irma and Maria affected the study area (6th September 2017 to 30th November 2017).
- ASmean
- A single band image of mean pixel values from AS.
- B
- Sentinel-1 image over the study region immediately before hurricane Irma.
- BS
- ‘Before set’ of images; A one year collection of Sentinel-1 images (26 images) before hurricane Irma affected the study area (1st September 2016 to 6th September 2017).
- BSmean
- A single band image of mean pixel values from BS.
- BSSD
- A single band image of pixel wise standard deviations from BS.
- D
- A single band image of the difference between ASmean and BSmean expressed in terms of BSSD
- DEM
- Digital Elevation Model
- ESA
- European Space Agency
- FB
- Flood-Buffer; regions upto 100m from pixels detected as open-water flooding (FO)
- FL
- Flood-Legacy; Pixels assessed to have experienced more protracted hurricane/flood damage. They are characterised by large deviations in pixel values in the three months following hurricanes Irma and Maria, relative to values observed for the same pixel over a one year period before the hurricanes.
- FO
- Flood-Open; regions which show characteristics of open-water flooding in Synthetic Aperture Radar satellite data
- I
- Sentinel-1 image over the study region immediately after hurricane Irma.
- M
- Sentinel-1 image over the study region immediately after hurricane Maria.
- NDVI
- Normalised Difference Vegetation Index
- SAR
- Synthetic Aperture Radar
- VH polarisation
- Vertical transmit - horizontal receive band of Sentinel-1 imagery
- VV polarisation
- Vertical transmit - vertical receive band of Sentinel-1 imagery