Study On Monitoring Method Of Forest Biomass And Carton Storage Based On Remote Sensing

Forest,as the major component of the terrestrial ecological system,and the change of forest biomass and carbon storage reflects the influences of forest succession,human activities,natural interference,climate change and man made pollution,and it has significant meaningful to the study of carbon cycle and climate change in global terrestrial ecological system.The paper uses 3 northeast provinces as the trial area,studies on the technological methods of extracting forest information and generating biomass model based on CBERS-WFI and MODIS data.Two methods used in the study are Multiple Linear Regression and BP neural network which are based on the plot data of national forest inventory,geographic and climate factors.And forest biomass and carbon storage in 3 northeast provinces are estimated.Furthermore,the change of forest biomass and carbon storage in the trial area is estimated with the comprehensive approach by comparing the two estimated result with the 2 different models.The study results are shown as below:(1) The technical method of extracting forest is based on RGB composite image of CBERS-WFI data,and is an effective method for macro extracting forest information rapidly.The forest extracting precision is can reach 80%.The forest extracting method of year NDVI slicing based on CBERS-WFI and MODIS,should define different threshold value for different area,and it can improve the precision of forest extracting efficiently,its precision can reach 84%.(2) Forest biomass estimation model based on CBERS-WFI and MODIS data is studied and generated with multiple linear regression and neural network modeling.The test result with test samples shows the forest biomass estimated precision is reached 85%,but different area has different estimated precision because there are distributed different forest types.(3) There is a positive correlation between Forest biomass and NDVI,Annual Average Precipitation,Annual Average Evapotranspiration,Annual Average Wettability,and their correlation coefficient is relative high.There is also positive correlation between Forest biomass and Annual Average accumulated temperature,longitude,and their correlation coefficient is a little low.There is a negative correlation between Forest biomass and latitude,the biomass per hectare will be decreased with the increasing of latitude.(4) In forest biomass estimation,MODIS data is better than WFI data,and BP neural network model gets better estimated result than Multiple Linear Regression.Using neural network model,the total forest biomass and carbon storage in 3 northeast provinces are estimated based on MODIS in 2004 and based on WFI in 2008.In 2004,the total forest biomass is 2404.58×10~6t,the carbon storage is 1202.29×10~6t.In 2008,the total forest biomass is 2368.20×10~6t,the carbon storage is 1184.10×10~6t.(5)The change area of Forest biomass and carbon storage is extracted by comprehensive comparing based on two estimated model and two different data which including CBERS-WFI and MODIS data.The obvious increasing area of forest biomass and carbon storage is 4.62 million hectares, is occupied 15.5%of the forest area in 3 northeast provinces.And the decreasing area of forest biomass and carbon storage is 1.45 million hectares,is occupied 4.87%of the forest area in 3 northeast provinces.The paper is firstly studied on forest biomass and carbon storage estimation model based on CBERS-WFI data,developed remote sensing resources that can be selected for forest macro monitoring. In the process of generating forest biomass estimation model,plot data of national forest inventory is firstly be used in 3 northeast provinces,and the amount of samples is larger than before studies,and the area grade factor of plot is first time be used to improve the matching degree between plots and remote sensing image pixels,all these improve the estimated precision of forest biomass and carbon storage greatly.In the analysis process of forest biomass and carbon storage change,it is the first time to use two types of low resolution RS data and two type of estimation model together to extract the change area of forest biomass and carbon storage.The change area is extracted more exactly and more scientifically.