Simulation of scattered wave from tropical forest tree trunk was conducted in order to estimate the relationship between tree trunk diameters and backscattering coefficients. This simulation used Finite Difference Time Domain (FDTD) method. Mode expansion method was employed to analyze backscattering coefficients on tree trunk as absorber media to confirm the simulation result. Both simulation and analysis results are in good agreement. These results were applied successfully to estimate trunk diameters of tengkawang (Dipterocarpaceae) which dominantly distributed in tropical forest in central Borneo, Indonesia. This application results matched well with ground data.
It is important that understand BRF (Bi-directional Reflectance Factor) effect of ground reflectance for vegetation monitoring. BRF model proposed by Watanabe et al. (1996) has the characteristics of expression by ground based data and Sun-Target-Sensor geometry. Therefore, it may be able to estimate grass height by using multi-channel satellite sensor data, which has wide swath (ex. ADEOS OCTS (Ocean Color and Temperature Scanner), EOS-AM1 MODIS (Moderate Resolution Imaging Spectroradiometer) ) . The aim of this study is to develop the algorithm of estimation of grass height by using BRF model, which is expressed by polynomial equation. The results show that vegetation height estimated by BRF model has high accuracy, and also we confirmed that our proposed algorithm is useful for estimating vegetation height.
The earth environment is affected by changing vegetation biomass so, it is necessary to develop an algorithm based on the physical parameter of vegetation over a wide area by using satellite data with intermediate spatial resolution (1km2) . Our goals in this study are as follows. 1. To construct a biomass estimation model using the relationship between vegetation index (VI), vegetation cover ratio (VCR), and the biomass obtained by field data. 2. To apply the field data to satellite data. 3. To evaluate the estimated biomass derived from satellite data by using meteorological station data in Mongolia. Field measurement data obtained from 1995 to 1998 and NOAA-14 AVHRR LAC data are used. Field measurements are conducted by mobile measurement and biomass measurement (clipping grass) over a wide area. Reflectance, vegetation cover ratio, and weight of dry biomass are measured. The methodology has already succeeded in developing a method for constructing a satellite vegetation index and biomass model, that has vegetation cover as a parameter. Satellite data are processed with highly accurate geometric correction, atmospheric correction using 6S code, and composite. Biomass maps are then generated by satellite data, and field measurement data are validated using biomass data from 15 Mongolian meteorological stations. As a result, we can estimate vegetation biomass without influence of cloud contamination and vegetation growth for a composite of NOAA AVHRR LAC data exceeding five days. The error of estimated biomass in the Ulaanbaatar-Mandalgovi area is less than 10%.
Adjacency effects from layered box shaped clouds are clarified by means of Monte Carlo Simulation taking into account a phase function of cloud particles and multi-layered plane parallel atmosphere. Effects on adjacency effects of phase function of the clouds in concern and the number of layers of the plane parallel atmosphere are also found together with the effects from the top and the bottom clouds.
Weights for to the combined adjustment of GPS and terrestrial observations were investigated. The derived weights of terrestrial observations are shown as follows: Distance σS=2.5mm+ (15.9×S) mm PS=1/σS2 Direction σD=1.8″+ (0.218/S) ″ PD=1/σD2 Vertical angle σV=3.6″+ (0.589/S) ″PV=1/σV2 Leveling σL= (σLO√S) m PL=1/σL2 σLO=0.6 (1st order), 1.7 (2nd order), 3.2 (3rd order), unit in mm/km where σ: standard error, P: weight, S: approximate observed distance in km.
Recently, number of pixels for amateur camera are amazingly increasing by modern semiconductor and digital technology, and transmission techniques of image to PC had been received attention. In the 2001, there are 41 kinds of high resolution amateur cameras on the market which have more than 3 million pixels in Japan. The functionary for transmission of image to PC is standardized, and the price is less than 1000 US$. In these circumstances, it is expected that 3 mega amateur digital cameras will become useful tool in various photogrammetric fields, e.g. industry, machine and robot vision, archeology, architecture, construction management, and so on. With this objective, rapid acceleration of resolution for amateur camera was investigated in this paper.