The accuracy of Leaf Area Index (LAI) estimation from multi-angle optical remotely sensed data depends on the BRF sensitivity to LAI and BRF inversion methods. The objective of this study is to investigate the limitations of the BRF inversion method for LAI estimation. We explored the BRF sensitivity to LAI, leaf reflectance/transmittance, and soil reflectance which strongly influence the BRF changes. Sensitivity analyses using simulated BRF data showed that BRF in the near infrared has high sensitivity to LAI up to 2. However when LAI>4, BRF has no sensitivity to LAI. LAI estimation accuracy using the BRF inversion method also depends on the initial guesses. The BRF inversion experiments using several initial guess patterns suggest that estimated LAI is accurate when LAI initial guesses are lower than true LAI. However estimation accuracy deteriorates in all initial guess patterns when LAI>3. Finally we applied the BRF inversion method for the BRF data acquired by the ground measurement. The results were consistent with those of simulation experiments.
Circular structures on the ground are one of the characteristic features recognized on satellite images and aerial photographs. Many of the circular structures are comprised of arcuate topographic ridges, which represent the erosional remnants of caldera structures. Distinguishing circular structures is difficult and inconsistent on satellite images and aerial photographs because it is based on photogeological interpretation through human eyes. To overcome this inconvenience, we have used digital elevation models to detect circular structures, focusing especially on the topographic expression of volcanic calderas that have been extensively modified by erosion. The detection of topographic calderas was conducted by using a simple algorithm that we developed on the basis of topographic characteristics such as the topographic rim of the caldera, which shows a circular pattern, and the direction of maximum slope of the rim, which consists of steep cliffs sloping toward the center of the caldera. By using this procedure, the lines drawn from the cliff of the caldera along the direction of the maximum slope will concentrate in the center of the caldera. Based on this result, score maps are constructed by measuring the density of lines along the above mentioned maximum slope directions. By applying our algorithm to downward and upward directions along the maximum slope, we were able to automatically detect the central areas of low ground and areas of circular topographic form, including topographic calderas. This could be achieved without having to use photogeological interpretation and statistic analysis obtaining from satellite images and aerial photographs, even if the outline of a topographic circular feature was broken into separate segments by surface erosion. This algorithm presents the disadvantage that it also identifies as high scoring areas, those areas with topographic domes and flat planes formed by Quaternary lavas and pyroclastic flows which are characteristic topographic features of Quaternary volcanoes.
Airborne Multi-Spectral Scanner (AMSS) is an airborne whiskbroom sensor having 25 spectral channels similar to those of Global Imager (GLI) on ADEOS-II satellite. The radiometric calibration coefficients for the visible and near-infrared channels are determined by observing an integrating sphere on the ground just before the flight. The absolute input spectrum of the integrating sphere was precisely measured at Tsukuba Space Center. During the ground-based calibration experiments, we found the temperature dependence of the output digital number of AMSS possibly due to the detector sensitivity variations. In February 2001, we had a field campaign around Saroma Lake, Hokkaido. The surface albedo of icy surface of Saroma Lake and various atmospheric parameters were measured simultaneously with the overpass of AMSS. Based on the standard procedure of vicarious calibrations and careful monitor of the detector temperature, we checked the in-flight radiometric performance of AMSS. The errors in the radiometric calibration coefficients are estimated to be smaller than 5 percent except channel 1.
For better understanding of the land-surface situation, the multi-temporal analysis algorithm for evaluating the land-cover change are newly proposed, based on the "pair-wise comparative strategy" of the satellite multi-spectral data. The proposed procedure for the multi-temporal analysis consists of the following steps : (Step 1-2) Data preparation and Preprocessing of the geometric correction as well as radiometric normalization ; (Step 3) For all comparative pairs of the satellite data observed at the different time, the dissimilarity image are produced by calculating the dissimilarity-measures for the TM-Band 2, Band 3 and Band 4, respectively. The Land-cover Change Detection maps (termed LCD map) are also generated by assigning those dissimilarity images to the blue, green and red image planes, respectively. These LCD maps are arranged on the pair-wise comparative table ; (Step 4) Through the quantification method type-IV, the scatter-diagrams are also investigated with respect to the items corresponding to the observational time of the satellite data, and (Step 5) Interpretation of the pair-wise comparative table. By using those scatter-diagrams jointly with the pair-wise comparative table, the effective and efficient estimation on the land cover change could be achieved with respect to the monthly, yearly and the seasonal changes as well.
In satellite spectra, though the scale is affected by the intensity of sunstroke, the angle of land inclination, the observation angle of the sensors and so on, the shape is not severely deformed by those effects. Thus, we have developed a spectral shape-dependent analysis utilizing a normalization procedure. By normalizing the apparent reflectances which are estimated from Landsat/TM data using the sum of those between 6 or 4 bands, inevitable topographic and atmospheric effects can be suppressed. The correction algorithm is very simple and timesaving and the suppression of topographic effects is especially effective. Here we show the correction principle and preliminary results.
The triangular distribution of the data are found on a NIR-RED scatter plot by using the Landsat TM data in the urban area same as in large scales of vegetation areas. The PWV could be thus proposed as a water index in urban areas. The index could indicate location of small water bodies because it sensitively increases with water surfaces in the land. The water index could be thus effectively used for evaluating management of environmental water circulation in urban areas.