Study On NPP Estimation Using RADARSAT-SAR And TM Data In Rainy And Cloudy Area

Tropical forest NPP is one of the most important parameters for global carbon stock model yet can only be estimated with great uncertainties because of vegetation indices saturation and difficulty of obtaining optical remote sensing image in those rainy areas and tropical forest areas.Microwave remote sensing has the advantage in monitoring tropical forest but has not been used in estimating NPP yet. Can we using SAR to estimate NPP in those areas that optical remote sensing can not be get?Based on LANDSAT-TM data and RADARSAT-SAR data and the survey data of leizhou forest bureau, we present a way to replace optical remote sensing by Microwave remote sensing in NPP estimation model in our study.First we simulate forest crown reflectance using LAI estimated by RADARSAT-SAR image and then we use the simulate forest crown reflectance to estimate NPP in south china. In this study, a simplified logarithm model was build to estimate forest canopy LAI by RADARSAT-SAR. In the same time, taking the LAI estimated by backscatter coefficient of RADARSAT-SAR as input parameter of SAIL model to simulate forest canopy reflectance, then use the simulate canopy reflectance as remote sensing input data to estimate forest NPP based on CASA model. Using radarsat-sar to estimate NPP is first promoted in our study.The main result is listed as following:1. LAI extraction using LANDSAT-TM and RADARSAT-SAR data.LAI extraction using RADARSAT-SAR is the basement of this study in estimation NPP using RADARSAT-SAR. So the result is important for estimation...