The Hiroshima Institute of Technology (HIT) manages direct downlinks for microwave and optical earth observation satellite data in Japan. This study focuses on validating rice monitoring using ground truth data from ENIVISAT-1/ASAR, such as the height of rice crop, vegetation cover, and leaf area index in test sites in the Hiroshima district in Japan. ENVISAT-1/ASAR data can monitor the rice-crop growing cycle using alternating polarization (AP) mode images. However, ASAR data is influenced by several parameters, such as land-cover structure, and the direction and alignment of rice fields in the test sites. To investigate these parameters, in this study the validation was combined with microwave image data and ground truth data for rice-crop fields. Multitemporal, multidirection (descending and ascending), and multiangle ASAR AP-mode images were used to investigate the rice-crop growing cycle. Finally, the extraction of rice-planted areas was attempted using multitemporal ASAR AP mode data, such as VV/VH and HH/HV. This study clarifies that the estimated rice-planted area agrees with the existing statistical data for areas within the rice field. In addition, HH/HV is more effective than VV/VH in extracting the rice-planted area.
This study aims to establish a practical image analysis method for the use of middle-scale resolution images acquired by
the multi-spectral sensors such as Landsat-7/ETM+, Terra/ASTER and ALOS/AVNIR-2 as the complementary data
sources of higher resolution images such as Quickbird for the purpose of environmental monitoring of wide-range areas.
For this purpose, an image analysis based on mixture is investigated as one of the effective approaches. As the
information target, we selected vegetation cover rate (VCR) in urban area because it is one of the important
environmental factors to affect urban environment issue such as heat island phenomena.
In order to realize easy and efficient computation for estimating the mixture rate of vegetation categories, the linear
mixture model using two main categories including vegetation and non-vegetation, is applied in combination with the
least square estimation of multi-regressive coefficients for vegetation cover rate (VCR) and non-vegetation cover rate
(non-VCR) with several bands data by multi-spectral sensors. In addition, two sub-categories for both of vegetation and
non-vegetation categories are considered to specify representative pixel values as correct as possible, that is, trees and
grasses for vegetation, and buildings and bare-soils for non-vegetation respectively, and their optical mixture rates are
estimated as well as the mixture rate of vegetation and non-vegetation categories. For this purpose, an iterative procedure
is adopted, in which each mixture rate of two sub-categories for vegetation and non-vegetation is varied by ten percent
steps and the least square estimation is applied with all combinations of mixture rates of sub-categories for vegetation
The experiments for VCR extraction were conducted in the test site of Hiroshima-city and by using multi-spectral data
acquired by Landsat-7/ETM+, Terra/ASTER, and ALOS/AVNIR-2. The accuracy for VCR extraction was evaluated
based on the comparison with the VCRs obtained by means of pixel-wise vegetation/non-vegetation classification of a
Quickbird multi-spectral image. The result shows that the number of bands is one of the important parameters in general.
However, it was verified that the combination of wavelength regions is more important than the number of bands. The
result of this study suggests that the combination of wavelength regions is essential in middle-resolution multi-spectral
images for vegetation cover rate estimation based on mixture analyses.
Hiroshima Institute of Technology (HIT) is operating the direct down-links of microwave and optical earth observation
satellite data in Japan. This study focuses on the validation for rice crop monitoring using microwave remotely sensed
image data acquired by ENIVISAT-1 referring to ground truth data such as height of rice crop, vegetation cover rate and
leaf area index in the test sites of Hiroshima district, the western part of Japan.
ENVISAT-1/ASAR data has the capabilities for the monitoring of the rice crop growing cycle by using alternating cross
polarization mode images. However, ASAR data is influenced by several parameters such as land cover structure,
direction and alignment of rice crop fields in the test sites. In this study, the validation was carried out to be combined
with microwave image data and ground truth data regarding rice crop fields to investigate the above parameters. Multi-temporal,
multi-direction (descending and ascending) and multi-angle ASAR alternating cross polarization mode images
were used to investigate during the rice crop growing cycle. On the other hand, LANDSAT-7/ETM+ data were used to
detect land cover structure, direction and alignment of rice crop fields corresponding to the backscatter of ASAR.
Finally, the extraction of rice planted area was attempted by using multi-temporal ASAR AP mode data such as VV/VH
and HH/HV. As the result of this study, it is clear that the estimated rice planted area coincides with the existing
statistical data for area of the rice crop field. In addition, HH/HV is more effective than VV/VH in the rice planted area
With the objective of developing accurate global image data and to find the effects of difference of observation time, several reliable global cloud free data sets of Terra MODIS and Aqua MODIS will be developed utilizing personal computers. Out of 36 bands seven bands (Band 1 through 7) with similar spectral features to those of Landsat-7 ETM+ are selected, since these bands cover the most important spectra to derive land cover features. And then, some statistical information of the developed data sets and NDVI computed from the data sets were investigated. From the analysis, it was clarified that the means and standard deviations of band 2, 3, 4 and 6 of Aqua MODIS data are more slightly larger than those of Terra MODIS data although the values of band 5 and 7 of Aqua MODIS are more slightly smaller than those of Terra MODIS data. And it was also found that NDVI of Aqua MODIS data computed from band 2 (NIR) and band 1 (R) are also higher (approximately from 0.03 to 0.05 at the range of NDVI) than those of Terra NDVI because of the above mentioned reasons.
This study aims the development of a practical method for the extraction of vegetation cover rate (VCR) in urban areas
using Landsat TM/ETM+ data. The linear mixture model in which two main categories, vegetation and non-vegetation,
have two sub-categories respectively is employed combined with the least square estimation using six bands data of
TM/ETM+ data. The experimental results show fairly good coincidence between the VCRs from Landsat and the ground
surface conditions from ground survey, and high correlation between the VCRs from Landsat and from Quickbird. The
experiments also show the possibility to generate VCR distribution maps in urban areas, and to extract their yearly
changes. In addition the relationships between the VCRs estimated in this study and some vegetation indices are
investigated. Finally the algorithm is modified to extract VCR conditions in wider urban areas, Tokyo-metropolis and
Kinki-district, the biggest and the secondary biggest urban areas in Japan respectively.