Spatial analysis of fire potential in Iran using RS and GIS
Ardakani, Ali ; Valadan Zoje, Mohammad Javad and Mansourian, Ali LU
(2010)
In Journal of Environmental Studies
35(52).
p.25-34
- Abstract
- According to reports of forest range and watershed management organization of Iran, hundreds of forest fires take place in our country every year. Due to destroying forest and grass land in different parts of Iran, especially in Zagross and Alborz Mountain, it is necessary to develop new methods to reduce fire effects in these places. There are many parameters that increase probability of fire occurrence. Without considering these parameters, environmental and biomass impacts are very critical problems. As fire could be occur in many grass lands and forests, fire monitoring of fire in vegetation regions is impossible. Using Remote Sensing technology and geographic information system (GIS) modeling is a basic way to monitor and prevent from... (More)
- According to reports of forest range and watershed management organization of Iran, hundreds of forest fires take place in our country every year. Due to destroying forest and grass land in different parts of Iran, especially in Zagross and Alborz Mountain, it is necessary to develop new methods to reduce fire effects in these places. There are many parameters that increase probability of fire occurrence. Without considering these parameters, environmental and biomass impacts are very critical problems. As fire could be occur in many grass lands and forests, fire monitoring of fire in vegetation regions is impossible. Using Remote Sensing technology and geographic information system (GIS) modeling is a basic way to monitor and prevent from this national disaster. In this study, spatial distribution of fires which occurred in the last 8 years in Iran and were detected by Moderate Resolution Imaging Spectro-radiometer (MODIS) satellite images was used. Then, by using NDVI index and considering repetitive fires, permanent fires were distinguished from random fires. Finally, density function and spatial autocorrelation in GIS were employed as statistical parameters to detect potential regions to fire. The results show a correlation coefficient of 0.9 between the fires and NDVI mean. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4779721
- author
- Ardakani, Ali
; Valadan Zoje, Mohammad Javad
and Mansourian, Ali
LU
- publishing date
- 2010
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- fire regime, NDVI, satellite images, spatial autocorrelation
- in
- Journal of Environmental Studies
- volume
- 35
- issue
- 52
- pages
- 25 - 34
- publisher
- Dānishgāh-i Tihrān, mu̓assisah-i muṭāli’āt-i muḥīṭ-i zīst
- external identifiers
-
- scopus:77952175380
- ISSN
- 1025-8620
- language
- English
- LU publication?
- no
- id
- 3dfb9b3a-e0e7-4094-a63c-626643742df4 (old id 4779721)
- date added to LUP
- 2016-04-01 14:17:46
- date last changed
- 2025-01-03 22:24:11
@article{3dfb9b3a-e0e7-4094-a63c-626643742df4,
abstract = {{According to reports of forest range and watershed management organization of Iran, hundreds of forest fires take place in our country every year. Due to destroying forest and grass land in different parts of Iran, especially in Zagross and Alborz Mountain, it is necessary to develop new methods to reduce fire effects in these places. There are many parameters that increase probability of fire occurrence. Without considering these parameters, environmental and biomass impacts are very critical problems. As fire could be occur in many grass lands and forests, fire monitoring of fire in vegetation regions is impossible. Using Remote Sensing technology and geographic information system (GIS) modeling is a basic way to monitor and prevent from this national disaster. In this study, spatial distribution of fires which occurred in the last 8 years in Iran and were detected by Moderate Resolution Imaging Spectro-radiometer (MODIS) satellite images was used. Then, by using NDVI index and considering repetitive fires, permanent fires were distinguished from random fires. Finally, density function and spatial autocorrelation in GIS were employed as statistical parameters to detect potential regions to fire. The results show a correlation coefficient of 0.9 between the fires and NDVI mean.}},
author = {{Ardakani, Ali and Valadan Zoje, Mohammad Javad and Mansourian, Ali}},
issn = {{1025-8620}},
keywords = {{fire regime; NDVI; satellite images; spatial autocorrelation}},
language = {{eng}},
number = {{52}},
pages = {{25--34}},
publisher = {{Dānishgāh-i Tihrān, mu̓assisah-i muṭāli’āt-i muḥīṭ-i zīst}},
series = {{Journal of Environmental Studies}},
title = {{Spatial analysis of fire potential in Iran using RS and GIS}},
volume = {{35}},
year = {{2010}},
}