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Spatio-temporal Dynamics of Forest Fuel Moisture Monitoring Using MODIS Data in Zhejiang Province

Author: YangGuoFu
Tutor: JiangHong;YuShuQuan
School: Zhejiang Forestry College
Course: Ecology
Keywords: Forest fires Fuel moisture Environmental Factors Regression Analysis Normalized Difference Vegetation Moisture Index
CLC: S762
Type: Master's thesis
Year: 2009
Downloads: 166
Quote: 6
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Abstract


Forest fires are natural ecosystem process is very important and inevitable confounding factors . It will change the plants and their community development and growth , control and regulate the interactions between plants , affecting forest succession , forest biomass and productivity , biogeochemical cycles , and atmospheric pollution. 1991-2006 , Zhejiang Province, the total burned area of ??forest fires 90310 hm ~ 2, accounting for the entire forest area of 1.63% , Zhejiang Province , the average annual burned area 5645hm ~ 2, along with the growing global change , the number of forest fires and area showed an increasing trend. Ecological studies in forest fire , forest fuel moisture content or humidity is forecast combustible forest fire forest fire behavior , energy release , the estimated size of the main indicators of fire , is to determine the real Shiying Lin planned fire with fire basis. Forest fuel moisture also directly affect the ease of ignition , fire intensity indirect impact , fire , forest fire spread rate, the effective radiation , has served as a forest fire warning a key parameter of concern for researchers . In this paper, Zhejiang common forest types evergreen broadleaf forest, pine , fir and bamboo forest for the study, investigation Rinnai Rinnai environmental factors and live and dead fuel back to the laboratory for determination of moisture content samples . The results showed that the highest temperature inside the pine forest , while the lowest air humidity and soil moisture , and its environment on the occurrence of forest fires is most favorable . Application of multivariate statistical analysis , to establish four kinds of forest types within the dead fuel moisture regression model to environmental factors , determine coefficient R ~ 2 are greater than 0.7 , the model examination showed that the model accuracy at 73 % or more. Establishment of forest fuel moisture live with MODIS normalized difference vegetation water index (NDWI) regression model, and in the province live on the scale of forest fuel moisture inversion results show that more than 60% accuracy , can be better reflection of forest fuel moisture conditions to be established for the forest fire warning system in Zhejiang Province has provided an important input parameters.

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CLC: > Agricultural Sciences > Forestry > Forest Protection > Forest fire
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