Abstract
The wildland-urban interface (WUI)-the area where wildland vegetation and urban buildings intermix-is at a greater risk of fire occurrence because of extensive human activity in that area. Although satellite remote sensing has become a major tool for assessing fire damage in wildlands, it is unsuitable for WUI fire monitoring due to the low spatial resolution of the images from satellites that provide frequent information which is relevant for timely fire monitoring in WUI. Here, we take advantage of frequent (i.e., ca. daily), high-spatial-resolution (3 m) imagery acquired from a constellation of nano-satellites operated by Planet Labs ("Planet") to assess fire damage to urban trees in the WUI of a Mediterranean city in Israel (Haifa). The fire occurred at the end of 2016, consuming ca. 17,000 of the trees (152 trees ha-1) within the near-by wildland and urban parts of the city. Three vegetation indices (GNDVI, NDVI and GCC) from Planet satellite images were used to derive a burn severity map for the WUI area after applying a subpixel discrimination method to distinguish between woody and herbaceous vegetation. The produced burn severity map was successfully validated with information acquired from an extensive field survey in the WUI burnt area (overall accuracy and kappa: 87% and 0.75, respectively). Planet's vegetation indices were calibrated using in-field tree measurements to obtain high spatial resolution maps of burned trees and consumed woody biomass in the WUI. These were used in conjunction with an ecosystem services valuation model (i-Tree) to estimate spatially-distributed and total economic loss due to damage to urban trees caused by the fire. Results show that nearly half of the urban trees were moderately and severely burned (26% and 22%, respectively). The total damage to the urban forest was estimated at ca. 41 ± 10 M USD. We conclude that using the method developed in this study with high-spatial-resolution Planet images has a great potential for WUI fire economic assessment.
Original language | English |
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Article number | 1479 |
Journal | Remote Sensing |
Volume | 10 |
Issue number | 9 |
DOIs | |
State | Published - 1 Sep 2018 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2018 by the authors.
Keywords
- Economic model
- Ecosystem services
- Fire
- GCC
- GNDVI
- Haifa
- I-Tree
- Mt. Carmel
- NDVI
- Planet
- Satellite
- Urban forest
- Vegetation
- WUI