A new indicator for enhancing fire fuel mapping in Marivan forests, west of Iran

Abstract

Hundreds of forest fires have been occurred, every year, in the oak forests of Zagros Mountain chains, especially in Marivan region, Kurdistan province, western Iran. Vegetation condition is considered as one of the critical dynamic factors in estimating fire susceptibility. Geographical Information System (GIS) integrated with Remote Sensing (RS) data provides significant geospatial information of environmental conditions before, during and after a fire occurrence, accurately, easy, not expensive, and with reduced risky fieldworks. This study aims to introduce a local method to differentiate between grass-covered surface and tree canopy in Marivan forests to recognize grass-covered area, as one of the most vulnerable fuel types to fire. The methodology uses Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) product, as an input, to develop a new indicator named Zagros Grass Indicator (ZGI). The ZGI intends to reduce the effect of tree canopy to reach the NDVI value which is created only by grass cover by employing the phenological characteristics of the forest trees and grass species. ZGI is supposed to be more efficient than NDVI for mapping grass-covered area which regarded as one of the most important factors in estimating fire susceptibility in the study area. The results revealed that the ZGI-based map is highly correlated with the distribution of fire occurrences recorded by official authorities.

Zagros Grass Index—A New Vegetation Index to Enhance Fire Fuel Mapping: A Case Study in the Zagros Mountains

“…In studying fuel types, grass species have not been looked at only as an ecological factor but as the most flammable fuel type [40,41]. Notably, the NDVI has been widely employed to estimate vegetation phenology as well as its quality and growth condition [43][44][45]. NDVI, serving as an index of vegetation growth and coverage, finds extensive use in describing spatio-temporal characteristics of land use and land cover (LULC), including percent vegetation coverage [44][45][46][47].…”

“…Notably, the NDVI has been widely employed to estimate vegetation phenology as well as its quality and growth condition [43][44][45]. NDVI, serving as an index of vegetation growth and coverage, finds extensive use in describing spatio-temporal characteristics of land use and land cover (LULC), including percent vegetation coverage [44][45][46][47]. However, the NDVI cannot differentiate between trees, shrubs, and grass because of their similar spectral characteristics [22,40].…”