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    Landsat derived percent vegetation cover of Israel (as of 2003) - Vdataset -...

    • service.tib.eu
    Updated Nov 29, 2024
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    (2024). Landsat derived percent vegetation cover of Israel (as of 2003) - Vdataset - LDM [Dataset]. https://service.tib.eu/ldmservice/dataset/png-doi-10-1594-pangaea-804209
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    Dataset updated
    Nov 29, 2024
    License

    Attribution-NonCommercial 3.0 (CC BY-NC 3.0)https://creativecommons.org/licenses/by-nc/3.0/
    License information was derived automatically

    Area covered
    Israel
    Description

    Wildfires are part of the Mediterranean ecosystem, however, in Israel all wildfires are human caused, either intentionally or un-intentionally. In this study we aimed to develop and test a new method for mapping fire scars from MODIS imagery, to examine the temporal and spatial patterns of wildfires in Israel in the 2000s and to examine the factors controlling Israel's wildfire regime. To map the fires we used two 'off-the-shelf' MODIS fire products as our basis—the 1 km MODIS Collection 5 fire hotspots, the 500 m MCD45A1 burnt areas—and we created a new set of fire scar maps from the 250 m MOD13Q1 product. We carried out a cross comparison of the three MODIS based wildfire scar maps and evaluated them independently against the wild fire scars mapped from 30 m Landsat TM imagery. To examine the factors controlling wildfires we used GIS layers of rainfall, land use, and a Landsat-based national vegetation map. Wildfires occurred in areas where annual rainfall was above 250 mm, mostly in areas with herbaceous vegetation. Wildfire frequency was especially high in the Golan Heights and in the foothills of the Judean mountains, and a high correspondence was found between military training zones and the spatial distribution of fire scars. The use of MODIS satellite images enabled us to map wildfires at a national scale due to the high temporal resolution of the sensor. Our MOD13Q1 based mapping of fire scars adequately mapped large (>1 km**2) fires with accuracies above 80%. Such large fires account for a large proportion of all fires, and pose the greatest threats. This database can aid managers in determining wildfire risks in space and in time.

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
(2024). Landsat derived percent vegetation cover of Israel (as of 2003) - Vdataset - LDM [Dataset]. https://service.tib.eu/ldmservice/dataset/png-doi-10-1594-pangaea-804209

Landsat derived percent vegetation cover of Israel (as of 2003) - Vdataset - LDM

Explore at:
Dataset updated
Nov 29, 2024
License

Attribution-NonCommercial 3.0 (CC BY-NC 3.0)https://creativecommons.org/licenses/by-nc/3.0/
License information was derived automatically

Area covered
Israel
Description

Wildfires are part of the Mediterranean ecosystem, however, in Israel all wildfires are human caused, either intentionally or un-intentionally. In this study we aimed to develop and test a new method for mapping fire scars from MODIS imagery, to examine the temporal and spatial patterns of wildfires in Israel in the 2000s and to examine the factors controlling Israel's wildfire regime. To map the fires we used two 'off-the-shelf' MODIS fire products as our basis—the 1 km MODIS Collection 5 fire hotspots, the 500 m MCD45A1 burnt areas—and we created a new set of fire scar maps from the 250 m MOD13Q1 product. We carried out a cross comparison of the three MODIS based wildfire scar maps and evaluated them independently against the wild fire scars mapped from 30 m Landsat TM imagery. To examine the factors controlling wildfires we used GIS layers of rainfall, land use, and a Landsat-based national vegetation map. Wildfires occurred in areas where annual rainfall was above 250 mm, mostly in areas with herbaceous vegetation. Wildfire frequency was especially high in the Golan Heights and in the foothills of the Judean mountains, and a high correspondence was found between military training zones and the spatial distribution of fire scars. The use of MODIS satellite images enabled us to map wildfires at a national scale due to the high temporal resolution of the sensor. Our MOD13Q1 based mapping of fire scars adequately mapped large (>1 km**2) fires with accuracies above 80%. Such large fires account for a large proportion of all fires, and pose the greatest threats. This database can aid managers in determining wildfire risks in space and in time.

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