Remote sensing is a technology which acquires the physical information of a measuring object indirectly based on the radiation acquired by a remote sensor. Therefore, to systematize the technology of converting the radiation to physical quantity is an important subject for remote sensing to spread in all the natural science fields. We have been developed a portable line spectrum radiometer, which are constructed entirely from commercially available components. Developed radiometer has steadiness and lightness with the commercial digital camera as a measurement unit. These two features are important in field use. And, developed radiometer was proven to be effective by actually measuring the sample color chart in the relative comparison of a spectral pattern. In this paper, we describe the instrument design of developed radiometer. Especially, we discusses it through the examination of the signal-noise characteristics based on the emphasis on the measuring a spectral pattern with the high signal-noise characteristics.
This paper reports a methodology to estimate soil moisture of non-inundated paddy fields on conditions that the field data synchronously measured is not available. Two L-band synthetic aperture radar (SAR) sensor data, i.e. Japanese Earth Resources Satellite-1 (JERS-1) /SAR, and Advanced Land Observing Satellite (ALOS) /Phased Array type L-band Synthetic Aperture Radar (PALSAR), were used. First, parameters of a model used for the soil moisture estimation were calibrated. Integral Equation Method (IEM) model, theoretical model to represent surface scattering in the microwave region, has several parameters. Among those parameters, two parameters, standard deviation of surface height, and autocorrelation length, were calibrated with actual volumetric soil moisture measured in 2007, and PALSAR backscatter coefficients. Then, the calibrated IEM model was applied to estimate volumetric soil moisture in 1990s using JERS-1/SAR. Finally, the volumetric soil moisture distribution maps in different years of 1990s were produced. While it is impossible to validate the estimated volumetric soil moisture because of the absence of field measurement data, it was found that the trend of the estimated volumetric soil moisture is similar to the trend of the actual volumetric soil moisture. It is concluded that the proposed methodology is quite effective to estimate soil moisture of non-inundated paddy fields on conditions that the field data synchronously measured is not available.
A method for calibration of the measuring instrument of solar direct, diffuse and aureole for estimation of refractive index and size distribution of aerosol is proposed. The method is based on Improved Langley Method : ILM that allows a calibration of the instrument without stable atmospheric conditions. ILM estimates size distribution, volume spectrum of aerosol by using measured solar direct (optical depth), diffuse and aureole (volume spectrum) together with extraterrestrial solar radiant flux for the reference wavelength. Then calibrate the instrument with optical depth, air mass and extraterrestrial solar radiant flux through extrapolate by plotting logarithmic function of extraterrestrial solar radiant flux subtracted by air mass multiplied by optical depth to air mass multiplied by optical depth is equal to 0 (at the top of the atmosphere) . By adjusting air mass, reconstructed volume spectrum and phase function using extraterrestrial solar radiant flux, solar direct, diffuse and aureole, the volume spectrum is reanalyzed thus accurate volume spectrum, phase function optical depth and solar diffuse and aureole can be re-estimated. The method proposed here allows estimation of extraterrestrial solar radiant flux at any wavelength by using recalibrated solar direct, diffuse and aureole, optical depth, air mass by ILM. It can be done by extrapolate by plotting logarithmic function of extraterrestrial solar radiant flux subtracted by air mass multiplied by optical depth to air mass multiplied by optical depth is equal to 0 at the reference wavelength then extrapolate by plotting that at the different wavelength based on Rate Langley Method : RLM. The numerical simulation based on measured data of solar direct, diffuse and aureole with ±3% and ±5% additive measurement noise shows that the proposed method is superior to the existing ILM method. Also the actual experimental data of the different 15 days of fine weather condition shows approximately 47.7% of improvement of the calibration accuracy can be achieved by the proposed method in comparison to the existing ILM method in terms of Root Mean Square error of the linear regression analysis of the relation between days and estimated extraterrestrial solar radiant flux.
This paper proposes a method to estimate precipitable water (PW) distribution over land using NOAA Advanced Very High Resolution Radiometer (AVHRR) thermal data, and mapping of daily PW over Japan from 1984 to 2001 were carried out using this method. The method adopts the split-window algorithm which utilizes the differential atmospheric effect in the two thermal wavebands. The brightness temperature difference between AVHRR channel 4 and 5 (denoted as T4-T5) increases along with atmospheric water vapor abundance, scan angle and land surface temperature (LST) . The effect caused by scan angle and LST was simulated using radiative transfer model and the correction formulas to eliminate theses effects from (T4-T5) were developed. The PW estimation formula was derived from the regression analysis between the (T4-T5) and GPS-derived PW. The root-mean-square error of the PW estimation is approximately 6 mm, and our AVHRR-based estimation has a fairly good result compared with that of radiosondes.
Least squares matching requires appropriate interpolation of the gray values in the search window corresponding to a template. Since there are few reports on comparison of image interpolation methods on matching accuracy, we decided to investigate performance of image interpolation methods applied to least squares matching. This paper reports an experiment conducted to evaluate image interpolation methods on matching accuracy by using 54 diverse images. Three popular methods in remote sensing and digital photogrammetry : bi-linear interpolation (BL), bi-cubic interpolation (BC), and cubic convolution (CC) were investigated. The results do not necessarily indicate that the matching accuracy of all methods depends on the interpolation accuracy. The results demonstrate that BC can produce better matching results than BL and CC in most cases when an image has no noise or smaller noises. Meanwhile, the results demonstrate that there is nothing to choose among three interpolation methods when an image has larger noises. Since the differences of the matching accuracy among three methods were small to be neglected, we conclude that BL would be the best interpolation method applied to least squares matching considering its inexpensive computational cost.
There are several kinds of laser scanners available for two-dimensional and three-dimensional measurement of object shapes, and there are some methods for setting the measurement devices in those laser scanners. Among those methods, calibration techniques are important for their practical use. I propose, in this technical report, some calibration methods of a laser scanner by measuring a target object with simple geometric shapes without using special machineries.