Remote sensing in fighting wildfire
One of the most valuable land survey techniques is remote sensing, which involves obtaining data on places and objects from great distances. Physical features of an area can be measured using this technique using reflected as well as emitted radiations from a distance (Potić et al., 2017). Inland survey remote sensing can be used to reveal the growth of cities, track changes in farming land over time as well as mapping out the uneven nature of ocean floors. The technique may target a line, point, or a feature in a given area which needs to be distinguishable and contrasting with adjacent features.
Wildfires raging forests have been causes of losses of billions of dollars globally. This has necessitated the development of advanced wildfire management techniques. Satellite remote sensing is among the main primary sources of data utilized for predicting the danger rating of fires, fire mapping, monitoring, and fire ecology study. Different types of maps can be generated from remote sensing data at either special or temporal scales suitable for operational fire management use. The commonly used satellites utilized for global fire detection are the Moderate Resolution Imaging Spectroradiometer (MODIS) and the National Oceanic and Atmospheric Administration (NOAA) (Hua & Shao, 2017). The satellites have a high temporal resolution as well as the capability to detect fire outbreaks even in remote areas.
Data generated by the satellite remote sensors can then be channeled to specific websites to offer valuable information to fire-fighting agencies. The technique is both efficient and cost-effective hence increasing in popularity in many countries. Advancement of remote sensing of wildfires has made it possible to date scars from older fires and approximation of burn severity following fire outbreaks (Feng at al., 2017). It also estimates the amount of burning biomass, which is then used in working out carbon emissions when assessing the effects of wildfires on climate change.
References
Hua, L., & Shao, G. (2017). The progress of operational forest fire monitoring with infrared remote sensing. Journal of forestry research, 28(2), 215-229.
Potić, I. M., Ćurčić, N. B., Potić, M. M., Radovanović, M. M., & Tretiakova, T. N. (2017). Remote sensing role in environmental stress analysis: Eаst Serbia wildfires case study (2007-2017). Journal of the Geographical Institute” Jovan Cvijic”, SASA, 67(3), 249-264.
Feng, L. I., Handong, L. I. A. N. G., Xiaoping, Z. H. A. O., Jiangwei, B. A. I., & Yukun, C. U. I. (2017). Remote sensing monitoring and assessment of fire-fighting effects in Wuda coalfield, Inner Mongolia. Remote Sensing for Land & Resources, 29(3), 217-223.