Recently, survey engineering requires knowledge and techniques that reflect its widely expanded field of application. Modern surveying now covers such areas as environmental pollution investigation, disaster prevention using satellite image information, the newest surveying instruments, and construction planning and design. This paper deals with an investigation of future survey engineering education. Information for this paper was gathered from 149 private survey companies, 168 education establishments (in response to questionnaires), personal interviews with specialists and many other sources. The findings of the investigation are presented together with an outline of survey education curricula.
The authors tested the applicability of category decomposition method based on the linear mixture model for the fusion of multipleresolution satellite data such as Landsat-TM and NOAA-AVHRR. The goal of the application of this method is to estimate the mixing ratio of different categories within one pixel of the lower-resolution data using the classification result of the higher-resolution data, which is considered to be useful for the extrapolation of the information from the higher-resolution data over the wider coverage of the lower-resolution data. The authors tested the estimation accuracy by two kinds of decomposition methods, the maximum likelihood estimation and the minimum distance estimation and also by the multiple regression method. The experimental results showed that the most adequate estimation was obtained by the category decomposition based on the minimum distance estimation.
The change in photogrammetry from analog to digital means a change from film to CCD sensor and real-time imaging became possible. It can be said that the most remarkable point of this change in photogrammetry is acceleration of real-time imaging. There are many kinds of digital still cameras on the market and these have became useful instruments in real-time imaging for stationary objects. For moving objects, a video camera is utilized since 30 frames are acquired per second. Video camera means 8mm camera; however, an 8mm camera is an analog camera in spite of the fact that a CCD sensor is used. Thus, a change in video camera from analog to digital means a change from analog tape to digital tape and direct transmission of digital image to a computer. This paper presents the concept of a digital video camera developed by the authors and shows examples obtained through tests.
Multivariate normal distribution for Maximum Likelihood classification (MLH) is widely used for image classification because it is adequate for multispectral imagery data as well as Synthetic Aperture Radar (SAR) data, and is easy to manupulate and is based on theoretical background mathematically. Spectral variability of the multispectral imagery data and textural feature of the SAR, however, are distributed as Chi-square like Probability Density function (PDF) and are ranged from non-zero value to finite value. So that if the MLH is applied to such that features, then classification performance is not good enough due to a mismatching between the real and assumed PDF or Likelihood Function. In order to overcome such this situation, a Maximum Likelihood classification with a simplified beta distribution is proposed in this paper. A difference between classification performances for the Maximum Likelihood classifications with multivariate normal and the simplified beta distributions is clarified with real satellite remote sensing data.
The change in photogrammetry from analog to digital means a change from film to CCD sensor and real-time imaging became possible. In these circumstances, digital photogrammetry is expected to become a useful tool in various fields, e. g. industry metrology, machine and robot vision, medical and sports science, archaeology, construction management and so on. However, CMOS image sensor has recently received more attention from the points of view of cheap cost and low power consumption. This paper investigate on the application of CMOS image sensor for digital photogrammetry.