This paper reports the calibration of model parameters to estimate soil moisture of non-inundated paddy fields using SAR (Synthetic Aperture Radar) data. The IEM (Integral Equation Method) model, theoretical model to represent surface scattering in the microwave region, was examined. Surface roughness parameters (standard deviation of surface height, autocorrelation function of the surface height, and autocorrelation length) are important parameters for microwave backscattering. However, the surface roughness of the paddy fields was found to change, and the autocorrelation length is quite difficult to accurately measure on the surface. Therefore, the two parameters, standard deviation of surface height, and autocorrleation length, were calibrated with actual soil moisture. As a result, it was found that the objective function to minimize the sum of residuals between estimated soil moisture and actual soil moisture produced the most optimal estimation results. In this case, The root mean square of errors between the estimated volumetric soil moisture and the actual soil moisture used for the calibration was 9.4%. This can be acceptable to consider the fluctuation of the surface roughness parameters during the noninundated season.
As some of ecological functions, plant physiological activities are known. Most of sunshine is receiving at forest canopy layer which consist of leaves and branches. The leaves are using it as energy source for forest activities such as photosynthesis. When we consider the plant physiological activities, light environment is the most important. That is why we investigated forest light environment through vertical light environment measurements such as Leaf Area Index (LAI) and Photosynthetic Active Radiation (PAR ; 400-700nm) . The light distribution in forest is defined by vertical radiation distribution. The leaf component of canopy is quantified by its structural LAI. The LAI is how many leaves area is projected and accumulated on the unit of ground area. This important parameter regulates a number of ecological processes. Tree leaves normally absorb PAR and vertical radiation distribution is accumulations of radiation, absorption, defuse transmission and interception. This phenomenon is generally defined by the Lambert-Beer low. In order to know the vertical forest light distribution, LAI and PAR measurements were executed in Tropical Rainforest. Trough our LAI and PAR measurements results show the same tendency as high dense forest LAI. The LAI value is increasing from tree top to the bottom. It is the theoretical knowledge of nature that leaves area accumulates from top to the bottom. According to this result, LAI is recognized to be correlative relationship with canopy height.
The urban heat island effect has become a concern. Toward measures against this phenomenon, it is important to quantify the heat energy exchanged between green areas and urbanized areas. LAI is used to estimate the quantity of heat energy exchanged between vegetation and the air, and it is onsite-measured directly by leaf sampling or indirectly by fish-eye image, which makes it difficult to perform in wide areas. Light detection and ranging (LiDAR), a laser-based remote sensing tool, is the most convenient way of measuring the horizontal and vertical distribution of leaf volume. The authors used LiDAR to map forest LAI in Shinjyuku Gyoen Park (0.8 km2), Tokyo, on a 5-m grid. Before mapping, the penetration efficiencies (percent of laser beams reflected by the ground) were determined from LiDAR data. From the calculated penetration efficiencies, a correlation equation (R2=0.75) was obtained between indirectly measured LAI (LAI=0.2-2.9 in forest) and the penetration efficiency for the park. Next, using the correlation equation, the penetration efficiency for the park was converted to LAI, and finally forest LAI was mapped. If forest LAI can be mapped for multiple areas in Tokyo, the currently available models can be used with greater accuracy for estimating the quantity of heat energy exchange of green areas.
Principles of Afforestation, Reforestation, and Deforestation (ARD) provided in Article 3.3 of the Kyoto Protocol should be monitored as land-uses change relative to the base year of 1990. Although the use of remote sensing technology is effective for this purpose, it is difficult to detect land-use changes by digital image analysis. Therefore, the Japanese Government adopted a photo-interpretation method which uses aerial photographs and SPOT-5/HRV-P images for ARD monitoring. In this study, verification of this method was conducted. Kumamoto Prefecture was adopted as study area. Lattice points at 500 m intervals were sampled for photointerpretation. A field survey was performed to evaluate the accuracy of the results obtained by photo-interpretation. The survey indicated values of 68.8 % for AR, and 90.9 % for D. Moreover, the ARD assessment in Akita and Ishikawa Prefectures was interpreted using the same method and the data were compared with the statistical material. The numerical values of both methods corresponded approximately. As a result, the photo-interpretation method enabled monitoring of ARD with a high degree of certainty for the Kyoto Protocol report.