Development of Trained Algorithm Detection of Fires for Multispectral Systems Remote Monitoring
نویسندگان
چکیده
The paper describes research of a trained threshold algorithm for analysis of the fire situation using multispectral remote sensing data. The algorithm is based on application of sub-satellite information about the fire on the territory covered by a satellite image. Thresholds are selected for each of the spectral bands for the determination of known fire threshold and then are used to select all thermal anomalies in the picture. According to study of the algorithm the informative spectral channels are defined for detecting fires. Combination of the results from the multiple channels spectroradiometer MODIS for increasing the probability of correct detection is demonstrated.
منابع مشابه
Localization Boyan algorithm to detect forest fires from MODIS sensor images
Of phenomena which much damage and irreparable import to forests and natural resources is the fire that each year, more than 100 fires occur in Iran and thousands of hectares of trees and plants eliminates. Given that fire risk is high in most parts of the world, full and continuous monitoring on this natural phenomenon, is essential. Use remote sensing is a way to identify and manage fire. Ahe...
متن کاملAn Automatic Detection of the Fire Smoke Through Multispectral Images
One of the consequences of a fire is smoke. Occasionally, monitoring and detection of this smoke can be a solution to prevent occurrence or spreading a fire. On the other hand, due to the destructive effects of the smoke spreading on human health, measures can be taken to improve the level of health services by zoning and monitoring its expansion process. In this paper, an automated method is p...
متن کاملCombining of Magnitude and Direction of Change Indices to Unsupervised Change Detection in Multitemporal Multispectral Remote Sensing Images
In remote sensing, image-based change detection techniques, analyze two images acquired over the same area at different times t1 and t2 to identify the changes occurred on the Earth's surface. Change detection approaches are mainly categorized as supervised and unsupervised. Generating the change index is a key step for change detection in multi-temporal remote sensing images. Unsupervised chan...
متن کاملSelf-Adaptive Gradient-Based Thresholding Method for Coal Fire Detection Based on ASTER Data - Part 2, Validation and Sensitivity Analysis
The self-adaptive gradient-based thresholding (SAGBT) method is a simple non-interactive coal fire detection approach involving segmentation and a threshold identification algorithm that adapts to the spatial distribution of thermal features over a landscape. SAGBT detects coal fire using multispectral thermal images acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer...
متن کاملتجزیه و تحلیل آتشسوزی جنگل با منشأ آبوهوایی با دادههای ماهوارهای در منطقهی البرز
Forest fire is one of the important problems in Iran which is caused by different factors such as human and natural factors. One of these factors is climate conditions that can be created by heat wave and special circulation of atmospheric phenomena. Occurrence of forest fire in north of Iran have different impacts on environment such as destruction of natural. According to the position of Iran...
متن کامل