Assessment of human health impact from the exposure to PM10 air pollution is crucial for evaluating environmental damage. We established an empirical model to estimate ground PM10 mass concentration from satellite-derived aerosol optical depth and adopted the dose-response model to evaluate the annual average human health risks and losses related to PM10 exposure over China from 2010 to 2014. Unlike the traditional human health assessment methods, which relied on the in situPM10 concentration measurements and statistical population data issued by administrative district, the approach proposed in this study obtained the spatial distribution of human health risks in China by analyzing the distribution of PM10 concentration estimated from satellite observations and population distribution based on the relationship to the spatial distribution of land-use type. It was found that the long-term satellite observations have advantages over the ground-based observations in estimating human health impact from PM10 exposure.
The spatial data is important for researching atmospheric pollution by Geographic Information System and Remote
Sensing, and multi-grid shows important way on the global sharing, analysis and display. This paper reviews the recent
progress of monitoring atmospheric contamination, a new concept: spatial data based on multi-grid, using different size
grid in various scale research region in the same platform, and transform the conventional geo-spatial data into
multi-grid's geo-spatial data. As an application example, the authors construct of regional atmospheric pollution control
and decision support system with MODIS aerosol product and in-situ atmospheric pollution data in China as one of
social economic benefits in GEOSS.
Landscape pattern and eco-hydrological process had changed greatly after seven times emergency water transportation in
the lower reaches of Tarim River, Xinjiang, China. After analyzing the changes of eco-hydrological process, ground
water level, soil moisture and vegetation growth etc. of emergency water transportation, remote sensing images in 2000
and 2005 year which present the situation before and after the emergency water transportation were processed and
dynamic change characteristics of landscape pattern were analyzed. The changes of landscape pattern were described as
follows: The forest land, waters, farmland and construction landscape area increase, and forest land increases the biggest,
which increased by 23.03% during last 5 years. Waters landscape change is only inferior to forest land, which increased
by 16.04%. The lawn, sand and Gobi saline-alkali land landscape area reduced; lawn and farmland had made the biggest
contribution to the increase of forest land by 6.46% and 4.79% in the year 2005. Landscape diversity index, evenness
index, fractal dimension and general fragmentation increased, but dominance index reduced. The results indicate that RS
plays the vital role in the macroscopic dynamic change analysis of landscape pattern and seven times emergency water
transportation has greatly influenced eco-hydrology process and landscape pattern changes in the lower reaches of Tarim
River.
The devastating earthquake (Ms=8.0) of 12 May 2008 in Sichuan, China struck the whole world. To detect the large
damaged area in less time and identify seismogenic structure, remote sensing technology is strongly recommended. This
paper attempts to focus on seismic area to analyze the earthquake damage from different aspects. Firstly, pre- and
post-earthquake Landsat TM/ETM images, CBERS-02B CCD images, DEM and relating data is used to observe ground
changes. The analysis assumption is testified by the Tangjia Mountain dammed lake in Beichuan county and landslide in
Anxian county in relative news and reports. Furthermore, Radarsat data is used to complement the analysis, since it
could provide the seismic area surface deformation and a better 3-D vision. Also specific information of local fault,
landslide and sub-block features in seismic area could be observed and got, which helps to perfect the damage analysis.
All these analysis results could be useful for improving and revising the interpretations of geological, geodetic and
seismological data. Finally, the possibility of estimating and inducing earthquake damage using remote sensing data is
discussed.
The use of remote sensing technology to estimate regional evapotranspiration has been carried out for many years.
Recently, with the advancements in quantification of remote sensing and the access of MODIS data, more scientists have
been using MODIS data to monitoring regional evapotranspiration (ET) instead of the NOAA/AVHRR data. The surface
energy balance algorithm for land (SEBAL) model combined with NOAA/AVHRR and MODIS data separately is
applied to estimate the 24-hour regional evapotranspiration in a semi-arid agricultural area of northern China. And the
SEBAL regional evapotranspiration model calculated results from MODIS and NOAA/AVHRR data are compared with
the in-situ measured ground surface evaporation. The analysis shows that in estimating regional evapotranspiration of the
satellite based application, MODIS data is more appropriate than NOAA/AVHRR data.
Retrieving land-surface temperature with split-window algorithm was firstly applied to NOAA-AVHRR data.
With the application of MODIS sensor, its data has been used more and more widely. Since MODIS sensor is able
to observe vapor in the air, it can provide the parameters including vapor content and atmospheric transmissivity
for split-window algorithm which can thus be applied more conveniently. The article, adopting the split-window
algorithms of Becker-Li (1990), Sobrino (1991) and Qin Zhihao (2005), retrieves the surface temperature at
daytime and nighttime with MODIS1B data and compares with the surface temperature products of NASA. Finally,
the algorithm of Qin Zhihao is demonstrated to be the one with higher accuracy at daytime and nighttime and the
algorithm for surface temperature at nighttime is simple with acceptable accuracy.
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