Forest resources, a vital part of the earth’s terrestrial ecosystem, create the indispensable living conditions and environment for our human beings. Forest fires, nevertheless, is a prevalent and destructive natural disaster which is difficult to be disposed and relieved. It destroys forests, devastates forestry structures and environment, imbalances forest ecosystems and even threatens people’s lives and properties as well as social stability and national security.
According to the UN Food and Agricultural Organization’s statistics, there are nearly 220,000 forest fires each year on the globe, destroying 6.46 million hm2 of forests, which accounts for 0.13% of the worlds’ total forest areas. While figures show that the overall global forest coverage is currently 3.5 billion hm2, taking 26. 6% out of the land area, which is progressively decreasing at a rate of 1.04m hm2 each year. Meanwhile, environment deterioration, “greenhouse effect” and El Nino have also added to the situation and caused more frequent fires and loses.
The big challenges that we face are how to carry out effective fire prevention and how to properly evaluate risk classes of forest fires, so as to provide references for prevention plans and thereby alleviate disasters and protect the forest resources.
A New Solution
Satellite Remote sensing (RS) technology has the advantages of a grand sight, dynamic monitoring, efficient data acquisition, visible images and a wide coverage. The extensive employment of high-resolution satellite imagery in forestry fire prevention and investigation is gaining its social-economic benefits.
The high resolution of the Jilin-1 satellite imagery and its multi-spectral images can reflect the characteristics of vegetation. It is widely used by forestry workers in forest fire prevention and assessment.
Fire risk indexes are categorized based on five aspects: fire history, terrain, meteorological environment, vegetation and human factors. We’ve selected the following indexes considering their acquisition and representativeness.
1.Vegetation drying rate: referring to the vegetation’s growing characteristics, one of the factors that affect its maturity for fire.
2.Equivalent water thickness: referring to one of the indicators of the vegetation’s water content, manifested in three approaches of leaf water content, relative water content and equivalent water thickness. Here, we adopt the last one.
3.Land surface temperature: referring to the indexes reflecting the energy balance on the surface of the earth and the greenhouse effect, by which temperature will be calculated to generate the black body radiance image via the calculation of vegetation coverage index, vegetation coverage degree, and surface emissivity.
4.Gross weight of the inflammable: referring to the dry weight of the vegetation per unit area, which reflects the total amount of inflammable matters in the unit area. The potential energy distribution and fire behavior of different fuel types can be predicted according to the total weight of the inflammable matters.
5.Vegetation continuity: referring to the crushing degree of plants (inflammable matters) in the area, which reflects their distribution continuity, influencing the fire spreading speed and easiness.
The analytic hierarchy process is adopted to analyze and compare the above 5 fire risk assessment indexes during the fire risk index model building. Different weight information is confirmed to finish the fire risk index calculation. The calculated results are divided into 5 domain spaces which is correspondingly in line with the 5 fire risk classes.
Thematic Map of Forest Fire Danger Evaluation in Jilin City
(1) Yongji county and the jurisdiction of Jilin are at low risks;
(2) The majority of Panshi Countyare at medium risk with a minority of districts at low risk; while the northwest parts are at high risk.
（3）Jiaohe city is mostly at low risk, but there are a small number of moderately dangerous areas in the south and north; the southeast areas are of high dangers.
We assisted the Jilin City to create the first provincial forest fire-suppression strategy supporting system, based on geographic information, forest resources information, fire management information as well as tracking, monitoring, positioning, dispatching & commanding, making it more direct, accurate, efficient in fire extinguishing. The city has since then achieved a good performance in fire prevention with no fire disasters for 33 years.
WeCan Do More
Our forestry satellite project aims to build a customized satellite constellation for forestry remote sensing usage. It will provide images of spatial resolution less than 5m and up to 25 spectral channels. Forestry remote sensing data services will be supported and generally elevated in terms of forest resources investigation, disaster monitoring, eco-value assessment and other fields.
A four-star networking scheme consisted of sun-synchronous orbit, orbital plane and equiphase distribution is applied in the forestry satellite. The minimum interval between two adjacent satellites in networking takes 30 minutes or less to image the same object. Each star has the capability of large side-sway imaging, which can meet the real-time monitoring requests of natural disasters such as floods and fires.
19 visible near-infrared spectral bands, including 1 panchromatic band and 18 multi-spectral bands are configured in the forestry satellite; 4 short wave infrared spectral bands, 1 medium wave infrared spectral band and 1 long wave infrared spectral band, of a total of 25 spectral bands.
Application in Forest Resources Survey
25 spectral bands are configured in the forestry satellite to enable it to extract and distinguish the obtained images via varied reflection spectrums from different trees species, such as the evergreens, aquatic plants, ground flora, deciduous forest and shrub, offering basis for forestry resources investigation and protection.
Multi-spectral remote sensing imagery of forestry satellites is able to identify, extract, analyze the information of forest diseases and pests and offer pre-warning, evaluation, management and control for the forest diseases and pests, providing basis for the forest recourses conservation.
Forestry satellites are enabled to accurately estimate forest vegetation parameters such as chlorophyll content, leaf area index and biomass to foster forest resources management and a healthy and sustainable development of forestry.
Multi-spectral remote sensing data is applied to acquire the status quo, spatial distribution, coverage and dynamic changes information of forest resources, including its coverage changing and overall tendency based on the establishment and demonstration of a 3D model of the forest
Wetland RS monitoring and researching can be carried out by means of multi-phase remote sensing imagery. Accurate distribution and dynamic changes of various wetlands will serve to provide a foundation for the scientific decision for wetland conservation, management and ecological restoration of degraded wetlands to realize the sustainable development of wetland resources..
Land Desertification Monitoring
Forestry satellite RS images can also be used in the surveillance of land desertification. By analyzing the RS data of the same area during different phases, monitoring and statistical analyses of the evolution of the desertification progress can be realized, to provide data basis for desertification prevention.