کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8866736 1621194 2018 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Burn severity metrics in fire-prone pine ecosystems along a climatic gradient using Landsat imagery
ترجمه فارسی عنوان
معیارهای شدت سوختگی در اکوسیستم های کاج در معرض آتش سوزی در طول شیب آب و هوایی با استفاده از تصاویر لندست
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات کامپیوتر در علوم زمین
چکیده انگلیسی
Multispectral imagery is a widely used source of information to address post-fire ecosystem management. The aim of this study is to evaluate the ability of remotely sensed indices derived from Landsat 8 OLI/TIRS to assess initial burn severity (overall, on vegetation and on soil) in fire-prone pine forests along the Mediterranean-Transition-Oceanic climatic gradient in the Mediterranean Basin. We selected four large wildfires which affected pine forests in a climatic gradient within the Iberian Peninsula. In each wildfire we established CBI plots to obtain field values of three burn severity metrics: site, vegetation and soil burn severity. The ability of 13 spectral indices to match these three field burn severity metrics was compared and their transferability along the climatic gradient assessed using linear regression models. Specifically, we analysed the performance of 12 indices previously used for burn severity assessments (8 reflective, 2 thermal, 2 mixed) and a new reflective index (dNBR-EVI). The results showed that Landsat spectral indices have a greater ability to determine site and vegetation burn severity than soil burn severity. We found large differences in indices performances among the three different climatic regions, since most indices performed better in the Mediterranean and Transition regions than in the Oceanic one. In general, the dNBR-EVI showed the best fit to site, vegetation and soil burn severity in the three regions, demonstrating broad transferability along the entire climatic gradient.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Remote Sensing of Environment - Volume 206, 1 March 2018, Pages 205-217
نویسندگان
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