Evaluation of Optical Remote Sensing Data in Burned Areas Mapping of Thasos Island, Greece


Elhag M., Yimaz N., Bahrawi J., Boteva S.

Earth Systems and Environment, cilt.4, sa.4, ss.813-826, 2020 (ESCI) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 4 Sayı: 4
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1007/s41748-020-00195-1
  • Dergi Adı: Earth Systems and Environment
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus
  • Sayfa Sayıları: ss.813-826
  • Anahtar Kelimeler: Forest fire, Mediterranean ecosystem, Normalized difference vegetation index, Principal components analysis, Temporal analysis, MAXIMUM-LIKELIHOOD CLASSIFICATION, PRINCIPAL COMPONENT ANALYSIS, DIFFERENCE VEGETATION INDEX, FIRE MANAGEMENT, FOREST-FIRES, LAND-USE, INFORMATION, ACCURACY, PATTERNS, CRETE
  • İstanbul Üniversitesi Adresli: Evet

Özet

© 2020, The Author(s).Forest fires are a common feature in the Mediterranean forests through the years, as a wide tract of forest fortune is lost because of the incendiary fires in the forests. The enormous damages caused by forest fires enhanced the efforts of scientists towards the attenuation of the negative effects of forest fire and consequently the minimization of biodiversity losses by searching more for the adequate distribution of attempts on forest fire prevention and, suppression. The multi-temporal Principal Components Analysis is applied to a pair of images of consecutive years obtained from Landsat-8 satellite to unconventional map and assess the spatial extent of the burned areas on the island of Thasos, Greece. First, the PCA was applied on the before fire image, and then a multi-temporal image is created from the 3rd, 4th, and 5th band of before and after images including Normalized Difference Vegetation Index to enhance the results. The results from the different steps of this analysis robustly mapped the burned areas by 82.28 ha confirmed by almost 85%. Are compared with data provided by the local forest service in order to assess their accuracy. The multi-temporal PCA outputs including NDVI (PC 4, PC %, and PC 6) give better accuracy due to its ability to distinguish the burned areas of older years and to the Normalized Difference Vegetation Index that gives better variance to the image.