Estimating Mediterranean stand fuel characteristics using handheld mobile laser scanning technology


COŞKUNER K. A., Vatandaslar C., ÖZTÜRK M., HARMAN İ., BİLGİLİ E., KARAHALİL U., ...Daha Fazla

INTERNATIONAL JOURNAL OF WILDLAND FIRE, sa.9, ss.1347-1363, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1071/wf23005
  • Dergi Adı: INTERNATIONAL JOURNAL OF WILDLAND FIRE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, CAB Abstracts, Environment Index
  • Sayfa Sayıları: ss.1347-1363
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

Background Accurate, timely and easily obtainable information on stand fuel is of great importance in the prediction of fire behaviour.Aims The objective of this study is to measure several stand fuel characteristics with handheld mobile laser scanning (HMLS) in six fuel types for Mediterranean region, and compare the results with traditional field fuel measurements (FFM) in 35 different sampling plots.Methods The measurements involved overstorey (the number of trees, diameter at breast height, crown base height, tree height, maximum tree height, stand crown closure) and understorey (understorey closure, understorey height) fuel characteristics, and ground slope. Correlation analysis and t-test were performed to examine the relationship between FFM and HMLS datasets. In addition, cross-validation statistics (RMSE, rRMSE and R-2) were employed to evaluate the accuracy of the HMLS method.Key results The results indicated strong correlations among all fuel characteristics. However, overstorey fuel characteristics were more favourable (r-values between 0.804 and 0.996, P < 0.01) than understorey (r-values between 0.483 and 0.612, P < 0.01). There was no significant difference between FFM and HMLS datasets in all fuel characteristics (P > 0.05).Conclusions The results indicated that the HMLS was practical, cost-effective, time-efficient and required less labour as compared to traditional FFM in plot-level (i.e. 0.1 ha) inventories.