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This PDF file contains the front matter associated with SPIE Proceedings Volume 8203, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and the Conference Committee listing.
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This paper introduces the design and development of the field investigation system anddiscusses its application.
The system can gather multiple messages simultaneously and transfer to the servers in time. Moreover, it can customize
the investigation form with the technology of dynamic form that makes it be easily applied in various industries.
Compared with the common embedded geographic information system, this system has fully considered the actual
operation flow, thus is suitable for application in the field investigation.
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The obvious vertical strip and chromatic aberration exist in the raw images obtained from the linear push-broom CCD,
due to the different response among CCD detectors, the odd/even effect raised in signal transfer and the inconsistency of
electronic link outside CCD array. In this paper, one relative radiometric correction method based on dark target image
to calculate the bias coefficient and stable light target image to calculate the gain coefficient is discussed, taking the
Beijing-1 small satellite panchromatic image as an example. This method is independent of the statistic characteristics of
the corrected image, not only can remove the strip noise and the eliminate chromatic aberration, but also can make the
color balance of the image, and is suitable for the relative radiometric calibration of linear push-broom CCD remote
sensing image without calibration device onboard.
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Orbital image mapping is a key technology to achieve scientific and engineering goals in deep space exploration
missions. It provides topographic and morphological information for various scientific researches and also supports
follow-up landing missions. This paper presents rigorous photogrammetric models for Chang'E-1 and MRO HiRISE
images based on the pushbroom imaging principle. A multi-level stereo image matching method is developed in order to
generate high precision DEMs of lunar and Mars surfaces.
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This paper proposes a rover localization method from long stereo image sequences by using visual odometry based on
bundle adjustment. Firstly, a progressive stereo image network is built by feature tracking in multiple frames of the
stereo image sequence. Then exterior orientation parameters of all images in the network are solved by using bundle
adjustment technique to get the rover position. Field experimental results demonstrate that the developed method can
localize the rover in real time (2fps) with an accuracy of between than 1.5%.
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The first 20 channel images of Hyper Spectral Image (HSI) have obvious stripe noise, which seriously affects the
application of the HSI data. This paper summarized and analyzed the existed destriping methods. Based on the image
characteristics of HSI, a new stripe noise removal method was proposed by using spline interpolation function to resample.
Taking the HSI image of Guangzhou area as an example, the Fourier transform method, moment matching
method and the new method proposed in this paper were used to remove the stripe noise. The results showed that the
Fourier transform method couldn't remove the image stripe noise effectively; the moment matching method could
remove the image stripe noise, but it also forced the image mean column value to 1, which would destroy the differences
of image features information; The new method proposed in this paper was able to retain the differences of image
surface features while removing the image stripe noise. The destriping efficiency of the new method was better than the
other methods.
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This paper focuses on the analysis and selection of space-borne hyperspectral sensor parameters, through the simulation
of the entire data acquisition process and the applications using simulated hyperspectral data. Aiming at the alteration
mineral identification and mapping, we used the simulated space-borne hyperspectral data with different payload
parameters including the spatial resolution, spectral resolution and Signal-to-Noise-Rate (SNR) from HyMAP air-borne
hyperspectral data in Dongtianshan area in Xinjiang Province of China to identify and map the alteration minerals, so
that we could analyze and compare these results to find the optimal combination of payload parameters. A combination
of the parameters of 30m spatial resolution, 10 - 20nm spectral resolution and 200:1 (VNIR) / 150:1 (SWIR) SNR was
evaluated to possess the strongest ability for the mineral identification and mapping. This technology can also be
promoted by the other payload parameter analysis and selection.
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There has been a common method to study land use changes based on series of remote sensing data. However, data on
time nodes in the time series are almost the historical data, which is difficult in acquiring sample mark data for
classification and result verification. Thus, the classification accuracy is severely limited. Taking a series of 4 remote
sensing imageries of Xihe watershed, Gansu Province, Northwestern China as an example, the authors proposed a new
method to jointly rectify image series classification results based on trajectory analysis. The object-oriented classification
method was used to classify the remote sensing images, and results were output as vector data, which were then utilized
to take trajectory analysis on the change process of every specific point in the study area. The olassification results were
rectified by further investigation or expert querying on those patches with unreasonable trajectories. After joint
rectification, compared with those with no joint rectification, the classification accuracy for the former three time node
improved about 3%-8%, especially for the middle two periods of historical data, the classification accuracy improved up
to 7% -8%.
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We systematically analyzed the accuracy of Precise Point Positioning (PPP) combined with the investigation of the
IMU/GPS-supported aerial area, and compared the PPP with the differential global position system (DGPS). The
precision of PPP in mapping was checked by sampling areas. Our data illustrates that the accuracy of PPP in medium or
small scale of IMU/GPS-supported aerial photography is almost same as DGPS, which satisfies the requirements of
specifications.
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Bi-directional Reflectance Distribution Function (BRDF) of water is one of the most important factors to describe the
optical characteristics of ocean using Lidar. It also plays important roles in the research on remote sensing modelling and
inversion. This research was based on certain assumptions, by using Monte Carlo method to track a large number of
photon collisions in the water, and study on the influence of the laser beam incident zenith angle and Inherent Optical
Properties of water (i.e. scattering phase function, single scattering albedo) on the water BRDF. The simulation result
showed that both incident zenith angle of laser beam and IOP of water have an impact on shape and quantity of BRDF.
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Signal to noise ratio (SNR) is of great significance to the satellite remote sensing system dedicated to the monitoring of
lake water color. The technical requisites were set in this paper taking reference to the Sea-viewing Wide Field-of-View
Sensor (SeaWiFS), which was aboard on the SeaStar. We simulated radiative transfer process from water-leaving
radiance to apparent radiance on the top of atmosphere using 6S model, and calculated SNR based on the Equivalent
Electron Theory. Our results showed that SNR in bands less than 500 nm was too low to meet the demand. Time Delay
Integration (TDI) was essential in these bands. However, in bands greater than 500 nm, the SNR was higher enough
(greater than 400), indicating there was still much potential to improve the spatial or spectral resolution in these bands.
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Using the coupled ocean and atmosphere radiative transfer code (COART), the downward radiance distributions above
the sea surface and at 1 m depth in the water are calculated. Combined with the discrete angle numerical model, the
investigation of effect of instrument tilts on Ed, Es and Lu is provided. It is found that the average of the time series Esdata will be to eliminate the effect of the tilt of surface incident irradiance instrument caused by the rocked boat. And
different high tilt thresholds should be set respectively for Ed and Lu to flag invalid data records.
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In this paper, methods to locate the sunglints from geostationary meteorological satellite images are discussed, and then
an algorithm for moving the sunglints from the satellite images is described. Based on the correlation between different
channels of the sensor, data from the IR channel which is seldom affected by solar specular reflection is used to correct
the grayscale value of the sunglint area in the visible band images. The algorithm for moving the sunglints is tested by
using regression method upon the MODIS remote sensing images and proved to be effectual.
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This paper proposes a status monitoring and exception handling mechanism for geospatial information services. After
introducing a two-level collaborative model and information exchange center, definition and monitoring methods of
service status are provided. On this basis, multi-geospatial agents based collaborative monitoring process and exception
handling activities are used to enhance the quality and reliability of geospatial information services.
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The intercalibration of the two thermal infrared channels of SVISSR/FY-2 with AIRS/Aqua is developed by using an
improved HSC (High Spectral Convolution) method. The improvement of HSC includes two aspects: sub-pixel spatial
matching and automatic removing coarse errors of the measurement pairs. According to the viewing geometries of
SVISSR/FY-2 and AIRS/Aqua, a study area with the longitude from 41.5°E to 149.5°E and the latitude from 10°S to
10°N is especially selected. To transfer the calibration coefficients from AIRS/Aqua to SVISSR/FY-2, the SVISSR/FY-2
Normalized (NOM) 1B dataset and the AIRS/Aqua 1B infrared data in the months of December 2006, September 2007,
December 2007, September 2009 and May 2010 covering the study area are employed and are aggregated into the study
area with the spatial resolution of 0.5°×0.5°. The measurement pairs are extracted from the aggregated SVISSR/FY-2 and
AIRS/Aqua images under the following conditions: co-location, absolute solar zenith angle difference in the same day
less than 2° (|▵SZA|<2°), absolute viewing zenith angle differences less than 3° (|ΔVZA|<3°), and absolute relative
azimuth angle differences less than 6° (|▵RAA|<6°). The intercalibration results show that the SVISSR/FY-2
measurements are well linearly correlated with the convolved AIRS/Aqua data. On contrast to AIRS/Aqua channels, the
calibration biases exist in two SVISSR/FY-2 thermal infrared channels, and the re-calibration coefficients are presented.
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Terrain undulations have significant influence on the geometric and radiometric quality of high-resolution airborne
synthetic aperture radar images. The correction of these effects becomes indispensable before image analyzing. The
paper presents a new approach to the geometric correction under unknown parameters of the SAR imaging geometry.
Using a three-dimensional (3D) polynomial model, the image of the testing area is geo-corrected. The selection of
polynomial order is emphasized. The best appropriate polynomial order for testing area is selected after testing nine
different polynomial orders which are 1-1-0, 1-1-1, 2-2-0, 2-2-1, 2-2-2, 3-3-0, 3-3-1, 3-3-2, 3-3-3. The resulting image is
a fully terrain corrected one and could be used for real-time monitoring and evaluating emergencies (e.g., hurricanes or
earthquakes).
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Searching for a seamline kept away from area with great differece between overlapping orthoimages is significant for
orthoimage mosaic, which is an important step in Digital Orthoimage Map(DOM) production.A method combine
Minimizing Local Maximum Algotirhm and Greedy Select Algorithm for seamline searching is introduced. In process of
searching, maximum differece along the seam-line is limited. Results show that this method is self-adaptable and is able
to accomplish high quality seam-line searching.
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Radar altimeter is playing an important and irreplaceable role in ocean remote sensing. The Delay/Doppler Radar
Altimeter (DDA) is a new type of radar altimeter and has high spatial resolution, low power consumption and small size.
It can be applied in open oceans, coastal zone and polar ice. In a fully developed linear ocean, the ocean model is
generated by sea wave spectrum model which consists of swell and wind spectrum. The sea surface is of random
character and can be described by random variables such as the ocean surface elevation probability density function
(OSE PDF) and the ocean surface wave height probability density function (OSWH PDF). In this paper different echoes
with the different OSWH PDFs and sea states are simulated. With spatial and temporal characteristics, the K-distribution
echo is closer to the ideal echo model. The results from this paper are helpful to the algorithmic method and performance
of the DDA. They also have directive to the DDA echo simulator.
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Most of China's rice production is located in the southern provinces of the country where frequent cloudy conditions
hinder the successful acquisition of optical imagery. Small field sizes and complex planting patterns pose additional
challenges to crop mapping using remote sensing approaches. High resolution radar data are most suitable for
operational monitoring of crops in this region of China. In this study, the suitability of high-resolution TerraSAR-X
StripMap data (6 m resolution) for identification of rice was investigated for a site in Xuwen, Guangdong Province,
China. An integrated decision tree and object-oriented classification approach was used. The results showed that higher
rice identification accuracies can be obtained using multi-temporal TerraSAR-X data at the tillering, jointing and
flowering periods. Both the VV and VH polarizations provided accurate rice identification.
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The quantitative relationship between the Normalised difference Vegetation Index (NDVI) data of Landsat and ASTER
sensors has not yet been examined though they have been frequently used in medium-scale vegetation observations. To
meet this need, this paper investigated the relationship of the NDVI measurements between Landsat-7 ETM+ and
ASTER. The study examined how well ASTER sensor vegetation observations replicate ETM+ vegetation observations,
and more importantly, the differences between the two sensors in the NDVI-based vegetation observations. Three
date-coincident image pairs of the two sensors were used in this comparison study. The digital numbers of the image
pairs were converted to at-satellite reflectance. The regression analysis of the scatterplots of ETM+ NDVI versus ASTER
NDVI was carried out to reveal their quantitative relationship. The model for the conversion of NDVI data between the
two sensors was also obtained by the regression. The results show that there are differences between the NDVI data of
the two sensors despite a very strong positive linear relationship between them. The ASTER sensor generally produces
lower NDVI measurements than ETM+.
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The accuracy of aerosol optical depth (AOD) products from polar-orbit satellites such as FengYun-3A (FY3A) is
limited, especially over land because it is hard to discriminate the contribution of the observed signal reflected by the
surface from the one scattered and absorbed by the aerosols over bright surface. In this paper, an approach by exploiting
the synergy of FengYun-3A (FY-3A) and Moderate Resolution Imaging Spectroradiometer (MODIS) data were
presented. The derived AOD compared to Aerosol Robotic Network (AERONET) observation and retrieval absolute
error around 0.1 is found, with R2 of 0.77. Moreover, a dust episode was presented in Mongolia on late March, 2010.; By
using HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) mode as well as the meteorological
parameters, we analyzed the advection and dispersion of this event, its transport effect for the episode and its influence.
Our data demonstrated that AOD increased up to 2.0 during the burning phase and then returned to normal values (0.2-
0.5), and the aerosol properties various, including both the AOD and aerosol type or source, which has a vertical
distribution difference, fully in line with transport process. This method should be wildly used on FY series satellite.
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The average vegetation height can be accurately extracted from ICESat GLAS data, however, a certain spatial interval
exist in laser strips and dots reduces the mapping accuracy of average canopy height after the interpolation of the GLAS
data. The MODIS-BRDF/albedo data consist of canopy structural data, such as LAI, canopy height etc. So the
combination of ICESat GLAS and MODIS data can be obtained more accurate distribution of average canopy height and
achieve the distribution of continuous canopy height. In this paper, the GLAS / MODIS data were collected in forest-rich
three provinces in northeastern China. We firstly filtered GLAS waveform data and get the average vegetation height,
and then selected the optional MODIS-BRDF / albedo bands to retrieve the average vegetation height. An artificial
neural networks model was esTablelished by training the MODIS BRDF data, and finally obtained the average
vegetation height over the whole three provinces. The fusion method between GLAS data and optical remote sensing
image was proposed to make up for their shortages and obtained a continuous distribution of average vegetation height.
It increases the analysis dimensions of forest ecosystem and produces more accurate data for forest biomass and carbon
storage estimates.
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Space-borne hyperspectral remote sensing imagery, supplying both spatial and spectral information for quantitative
remote sensing monitoring, is easily polluted by noises from atmosphere, terrain etc. Based on spectral continuum
removing and recovering, traditional fast Fourier Transform (FFT) was extended to Continuum Fast Fourier Transform
(CFFT) to separate noise from target information in frequency domain (FD). Thus, low-pass filter for reserving useful
information was designed for eliminating noise, with its cut-off frequency selected self-adaptively by optimal signal-tonoise
ratio (SNR). Hyperion hyperspectral imageries of Beijing and Xinjiang China were singled out for noise removing
to validate the filtering ability of the Continuum Fast Fourier Transform self-adapted by Optimal Signal-noise
Ratio(CFFTOSNR) method with qualitative description and quantificational indexs, including mean, variance, entropy,
definition and SNR etc. Experiment result shows that CFFTOSNR does well in reducing the gauss white noises in
spectral domain and stripe and band-subtracting noise in spatial domain respectively, while the quantificational indexs of
filtered imagery are all improved, with entropy of post-processed image obviously increased by 5 db.
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Earthquake is caused by collision and compression of lithosphere plates. It has been found that during rock failure under
lithosphere plate compression, some anomalies of thermal emission at certain frequencies, e.g. 300MHz, 2GHz and
22GHz, might be observed.
Satellite-borne AMSR-E (Advanced Microwave Scanning Radiometer-EOS) has dual-polarized 12 channels (6.925,
10.65, 18.7, 23.8, 36.5 and 89GHz), where two channels, 18.7 and 23.8GHz, are close to the sensitive frequency, i.e.
22GHz. In this paper, the brightness temperature (Tb) at the channel 18.7GHz is especially analyzed to see if the
emission anomaly is correlated with the earthquake in Yushu area, Qinghai province (32°N-34°N, 96°E-98°E), China on
April 14, 2010. An anomaly index (RAI, radiation anomaly index) is defined for monitoring the Tb change and RAI
during prior- and post-earthquake, and another channels, i.e. 23.8 and 10.6 GHz, as the assistance to exclude the
influences most likely from atmospheric water vapor and terrain surface temperature on RAI.
The AMSR-E Tb data during 2003-2010 were collected, and RAI of Yushu area indicated plausible anomaly on April 12,
2010, which is the date that two days before the Yushu earthquake. Thus, the analysis of RAI might provide a feasible
tool for earthquake forecast from multi-year observations of AMSR-E data.
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Land cover is a crucial product required to be calibrated, validated and used in various land surface models that provide
the boundary conditions for the simulation of climate, carbon cycle and ecosystem change. This paper presented a
method to map land cover from multitemporal landsat images using Dempster-Shafer theory of evidence. The method
firstly resolved in Gaussian probability density function calculate the basic probability assignment of each single satellite
image, then multitemporal landsat images were combined using Dempster's Rule of combination. Finally, a decision rule
based on ancillary information is used to make classification decisions. This method had 87.91% overall accuracy for the
land cover types compared with the result of the Aerial hyperspectral image classification. The results of this study
showed that Dempster-Shafer theory of evidence is an effective tool to map land cover using multitemporal landsat
image.
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Combined with traditional image information and spectral information, hyperspectral remote sensing could not only get
the space information about the surface of the earth, but also obtain continuous spectrum of single pixel. Spectral
matching technique is one of the key technologies of imaging spectroscopy remote sensing classification and target
detection. Spectral characteristics can be used to identify surface features category in hyperspectral remote sensing. The
traditional method of spectral matching includes the minimum Euclidean distance matching, spectral angle matching and
spectral similarity matching. SAM (spectral angle matching) is better than others, but the discrimination is not high, and
usually could not get a satisfactory result. This paper gives a proposal that introducing and using the hidden Markov
model to describe the pixel spectral characteristics, and then compare this method with several commonly used methods
by using the standard USGS spectral library data in the experiment.
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In remote sensing imagery, ground objects belonging to the same land cover category always have similar optimal
segmentation scales. The paper proposed a method using the land cover categories as a prior knowledge to guide the
synthesis of multi-scale image segmentation results. This method took into account the variety of scale characteristics of
different ground objects as well as the similarity of scale of objects belonging to the same land cover category. Firstly,
the image was coarsely divided into multiple regions, and each of them belonged to a land cover category. Then for each
category, we selected the optimal segmentation scale by the supervised accuracy assessment of segmentation results.
Finally, the optimal scales of segmentation results were synthesized to get the final segmentation result. To validate this
method, the Quickbird image was segmented and classified. Experimental results showed that this method could
generate accurate segmentation results for the latter classification.
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The coastal zone in Beibu Gulf is dominated by diurnal tide and there exists the largest mangrove community in China.
The frequently used mangrove extraction methods seldom took the tide influence into account which would lead to
extracted area loss on single instantaneous remote sensing image. The loss cannot be ignored when the mangrove
submerged time is long. This study took one portion of Beibu gulf coastline as research site. Four temporal HJ CCD
images with different tide levels were selected for inundation mangrove extraction and coastal terrain classification.
Based on the analysis of targets image-spectra, several decision factors were proposed, and subsequently a multi-layer
decision tree was constructed. After the classification, target distributions at research site including the submerged
mangrove were acquired. The overall classification precision was high up to 91.79%, and the Kappa coefficient was
0.9064. The obtained submerged mangrove area was 2.155 km2, which comprised 4.5% of total mangrove area and
would be lost if the extraction were only applied on single image.
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Jiangsu coastal area is abundant in wetland resources and possesses wetland reserve of global relevancy. However, the
wetland area has been shrinking with more and more human activities. In this paper, 5 ALOS AVNIR-2 images as well as
an additional TM image acquired at low tide level were selected to carry out a research of Yancheng coastal wetland.
Characteristics of subcategories and vegetation coverage were surveyed during filed work before a 2-tier decision tree
method was adopted to distinguish different wetland categories. At last, the total area was classified as 8 major wetland
categories with an overall accuracy of 97.16% as well as Kappa coefficient of 0.96. Only 2 sampling sites biased in the
classification when 28 field recorded samples were compared and the result was satisfying.
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The spatial and spectral resolution of ASTER data has been greatly improved much more than the common ETM data.
ASTER Remote sensing data have a good prospect in the abnormal alteration mineral extraction. This paper studies the
ore prospect in Chengmenshan of the JiuJiang district, JiangXi Province. According to the spectral features of common
alteration mineral on metal deposits and the ASTER band characteristics, using ASTER Multi-spectrum data can
calculate the RBD of limonitization and hydroxide radical mineral. Extracting remote sensing anomaly in
Chengmenshan combine RBD with Principal component method, and contrasted with the geologic information, the
results show that extract and process data-processing techniques are more reliable.
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Using the inherent features of high resolution data, such as the shape and the texture, this paper proposed an object and
rule based fuzzy classification method. First, multi-scale segmentations were used to obtain homogeneous objects at
different scales. According to fuzzy classification ideas, these segmented objects were further classified by using the
corresponding spectral, shape, texture, topology and other object-related characteristics. This method not only overcomes
the limitations of pixel based classifications, but also takes advantage of the inherent features of high resolution data. To
fully compare and analyze the proposed classification method, an IKONOS image of urban areas was selected as test
data. According to four main classification steps, this data was classified as houses, roads, vegetation, and bare land. The
classification results showed that the proposed method enhances the accuracy of classification and is of great advantages
compared with the traditional pixel based classification methods.
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Coal fire generates a number of environmental problems and results in disorderly changes of landcover. Detecting the
change of Land-cover is an important scientific issue of the land evaluation and the eco-environmental change
forecasting. The temporal land cover maps with high accuracy make it possible to explore the eco-environmental
changes of coal fire area. In thispaper, the multi-layer segmentation-based classification approach, Markov Transition
Matrix methodology and Dynamic indexesby using Landsat TM data was carried out. The results reveal that coal mine
and resident change are mostly in recent decades among all land cover types. Private coal mining exploitation and
government administrative measures are the deriving factors.
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The urban development is usually accompanied with the re-planning and reconstruction of the old urban area, which is
one of the key issues of the urban development program. Over the past decade, Fuzhou City of Fujian province, SE
China, has speeded up its reconstruction progress. The Cangxia area, located in the southwestern of the city, was replaned
and reconstructed to improve people's living conditions because the area was full of intensively-built squatter
settlements. In order to study the thermal environmental changes of the Cangxia area before and after the reconstruction,
three Landsat TM images of 1986, 1996 and 2006 were utilized to perform feature extractions of the thermal-related
information of the area, such as the land surface temperature (LST), impervious surface area (ISA) and vegetation
coverage. The quantitative analysis on the relationship between ISA and LST suggested a positive exponential
relationship between the two factors. With the assistance of the Urban-Heat-Island Ratio Index (URI), the digital image
processing on the three multi-temporal images revealed the spatial and temporal variations of the urban heat island (UHI)
effect in the investigated area from 1986 to 2006. The results showed that after the launch of the reconstruction project of
this squatter settlement-dominated area, the UHI effect in the area had been greatly mitigated in the past 20 years, since
the URI value had been decreased from 0.648 in 1986 to 0.245 in 2006. This owes greatly to the significant decrease in
high-density ISAs and the notable increase in vegetation covers. The reconstruction is of benefit to the UHI mitigation of
the Cangxia area.
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The Northeast China is the largest distribution region of forests in China, thus its changes in forest undoubtedly have
great impact on the global carbon cycle. However, no comprehensive analyses of the changes in forest of this region over
the past 25 years have been conducted. In this paper, vegetation in Northeast China was first classified with an expert
classification method based on different vegetation types with different NDVI time profiles, then the 25-year changes in
forest attribution (i.e., area, growing stock and biomass) was examined based on models constructed, and the
comprehensive analysis by using the forest identity was also made.
The results showed that forest area, growing stock volume and biomass decreased 1.5 Mha (1 Mha = 106 ha), 187 Mm3(1 Mm3 = 106 m3) and 222.75 Mt (1 Mt = 106 ton), respectively, with the relative annual change rates of -0.18%, -0.32%
and -0.34% over the past 25 years. The comprehensive analysis showed that the forest carbon storage in Northeast China
was estimated 1.21 Pg C (1 Pg = 1015 g) in the period of 2004-2006, and forests of this region released 3.64 Tg C per
year (1 Tg = 1012 g), which means that it demonstrated as a carbon source over the past 25 years. However, such changes
in forest attribution showed a significant regional variation; for example, the attributes declined in Heilongjiang and Jilin,
while increased in Liaoning Province. The declines in forest growing stock volume are mainly due to the decrease in
area, which may be further caused by the coupling effects of frequent forest fires and deforestation.
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The vegetation, as the main component of the ecosystems, is the main receptor of acid rain pollution. Because of the
discrepancy of the vegetation characteristics and environment, the responses of the different types of vegetation to acid
rain in different regions are different. In this paper, we chose 9 eco-regions in southern China as study area, based on
the acid rain and NOAA/NDVI data from 1992 to 2006, and revealed the impact of acid rain on the vegetation by using
spatial interpolation, cluster analysis and curve fitting. The result shows that the most tropical and subtropical moist
broadleaf forests were positively correlated with the acidity of precipitation and the growth was inhibited obviously. On
the contrary, the growth of temperate coniferous forests was promoted by acid rain to some extent. In generally, the
vegetation in the condition of the weak acid rain grew better, especially the Qin Ling Mountains deciduous forests and
the Changjiang Plain evergreen forests. For South China-Vietnam subtropical evergreen forest, Yunnan Plateau
subtropical evergreen forests and Qionglai-Minshan conifer forests, the significant difference of NDVI between the
different gradients of acid rain lasted almost the whole year, while that of the other eco-regions only appeared most
obviously in Winter.
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This paper introduces the procedure of emergency remote sensing assessment for Haiti earthquake happened on Jan 12
2010. The procedure is divided into 4 steps: data preparation, data processing, information extraction and damage
assessment, and contains three key targets which are damage information extraction, quantitative assessment and
estimation of casualties and economic losses. In the first stage, the damage information of the buildings is the basis, and
the other information, including building type, damage grade, built-over area, would be extracted by visual interpretation
and automatically statistic with human-computer interaction from the high resolution disaster imageries. Then the remote
sensing damage index and equivalent ground damage index of building could be counted in the second stage. According
to this result, the specialists sketch a more exact intensity distribution in different regions of the metropolis. At last, the
number of casualties is estimated by an empirical model adapting to worldwide earthquake as the detailed construction
damage has been known. To assess the economic losses, we use a macro economic-based model which only needs
population, per capita GDP and statistical macro-economic fragility related to seismic intensity. In this case, it is the first
time to implement the methods of remote sensing assessment in foreign serious earthquake emergency, which is proven
of being applicable outside China.
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This paper is concerned with the construction of spatial data acquisition and application, and the communication and
service platforms. The techniques for managing multi-source spatial data used in disaster rescues are discussed,
including data- and meta-database construction and system development. An application example is also given. The
results of this study were proven to be effective. The data processing period was significantly reduced and the validity of
decision-making was similarly improved.
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In this study, the optical depth of vegetation is worked out with Microwave Polarization Difference Index (MPDI)
focusing on the drought that hit Yunnan in early 2010 and using AMSR-E data of the first three months of 2010 in
Yunnan Province. Inversion of soil moisture is conducted by using Microwave radiative transfer model and Dielectric
constant model, and thereupon drought grading is made, so that the drought grades of the first three months of 2010 in
most of the regions in Yunnan Province are obtained. By verifying the retrieval results by means of the soil moisture
data collected from ground-based measurements, the conclusion of this study is drawn: with the research method by
which soil moisture is retrieved from AMSR-E data, and thereupon the drought grading is made, the drought in
Yunnan Province can be effectively monitored.
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The Lop Nur region is located in the east of the Tarim Basin. It has served as the strategic passage and communication
hub of the Silk Road since Han Dynasty. During Wei-Jin period, the river system there was well developed and the
ancient city of Loulan was bred there. In this study, GIS is used to accomplish automatic extraction of the river course in
the Lop Nur region at first using ArcGIS. Then the RCI index is constituted to extract ancient river course from Landsat
ETM image with band 3 and band 4. It is concluded that the north river course of Peacock River conformed before the
end of the 4th century AD according to the distribution of the entire river course of the Lop Nur region. Later, the
Peacock River changed its way to south to Tarim River, and flowed into Lop Nur along the direction paralleling Altun
Mountain from west to east. It was the change of the river system that mainly caused the decrease in water supply around
ancient city of Loulan before the end of 4th century. The ancient city of Loulan has been gradually ruined in the sand
because of the absence of water supply since then.
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Chlorophyll-a concentration is one of the most important indexes of Lake Eutrophication. Fine temporal and spatial
resolution remote sensing images provide an effective way to monitor blue-green algae in Lake Taihu by studying the
spatial distribution regularities of chla concentration. However, both low spatial resolution remote sensing images (e.g.
MODIS) due to their heterogeneity and high or moderate spatial resolution remote sensing images (e.g. TM/ETM+) due
to their low temporal resolution give rise to unsatisfactory estimate of chla concentration. Therefore, in this study, an
effective method for estimating chla concentration using remote sensing images at different scales was developed. Chla
concentration was inferred from Hyperion images at 30m resolution and MODIS images at 250m resolution. The spatial
variability of Chla concentration was analyzed and Taihu Lake was divided into area with low variability and area with
high variability. The quadratic polynomial (R2=0.8709) and linear (R2=0.7387) correlation was established. Finally, the
obtained relationship between chla concentration estimate at different spatial scales were applied to correct the estimate
from MODIS data.
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This paper explores the optimal methods for processing CBERS-02B images and using them to classify the land uses of
karst mountain areas with 3S technologies, especially the RS digital image processing technology. Through multiple
experiments and analysis, the difficulty of CBERS-02B images in distinguishing water from mountain shades,
construction land from dry land and paddy field are satisfactorily removed. And the combination of band 421, based on
OIF method, is proved optimal for classifying the land uses of karst areas. After comparing and evaluating the effect of
HIS, PCA and HPC based image fusion methods, the HIS transformation based image fusion method is found best for
CBERS-02B HR and CCD data fusion in the case of karst highland mountains. Based on the experiments, this paper
proves that CBERS images are capable of large scale land use classification for karst areas, a competent substitute of TM
images for karst mountain area land use survey.
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The extraction of typical targets (such as water, road and damaged buildings) of nature disaster is important to the
emergency management, post-disaster damage assessment and disaster monitoring. This paper shows an objected
oriented method to extract water, road and building targets in the earthquake of Wenchuan(2008), Yushu(2010) and
Haiti(2010). We built the optimal feature sets with spectral features, shape features, texture features and context features.
Experiment result shows that this method can extract flood area, road and damaged buildings effectively and achieve a
relatively high accuracy. These experimental studies are leading to the opportunity to integrate classical damage survey
and image oriented semi-automatic interpretation.
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Landslide is one of the serious geological disasters that bring serious impact on transportation construction and highway
traffics. It is critical to improve the level of warning and emergency response to the highway landslide. Based on the
application of unmanned aerial vehicles (UAV), the highway landslide warning and emergency response system is
developed in this paper. The system consists of two main components, including landslide warning sub-system and the
UAV emergency response sub-system. The establishment of this system will contribute to: 1) improving the warning and
monitoring of highway landslide; 2) quickly understanding the situation of landslide disaster, and therefore helping the
policy-makers with emergency rescue, disaster assessment, and reconstruction; and 3) using it as a research platform for
large-scale landslides, debris flow monitoring and warning, and other emergency relief work.
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Due to the indistinction of land boundary and the confusion of categories in wetland as well as the big spectral difference
of high-resolution remote sensing images, how to segment land boundaries exactly and maintain homogeneity in one
category as much as possible are the difficult points of wetland information extraction of remote sensing images. In this
paper, Xixi Wetland in Hangzhou is taken as research object and QuickBird high-resolution image as research data. Two
approaches for wetland information accurate extraction based on Markov random field (MRF) theory are explored. The
experimental results showed that this method has a good effect on exact segmentation of land boundaries and Inhibition
of classification noises, and has higher accuracy and speed compared with other MRF methods.
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This paper provides an analysis of main land types and image features of their change information by using
RADARSAT-2 satellite data of Chengdu, Yantai and Shantou. It also deals with the geometric rectification accuracy of
RADARSAT-2 data with a corner reflector. A method of fusing RADARSAT-2 data and optical image was used to
extract change in land use monitoring and to assess accuracy, in order to provide an effective supplement for the new
round investigation of the national resources.
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Detailed data of spatial and temporal distribution and radiative properties of aerosols are required for assessment on
aerosol direct radiative forcing. In recent years, with the development of remote sensing instruments as well as
corresponding sophisticated inversion algorithms, the global aerosol distribution can be acquired by satellite remote
sensing. The aerosol optical depth in the areas with high surface albedo can be inversed by the latest MODIS deep blue
algorithm with good complementarity to the applicable areas with traditional dark target inversion scheme. Based on
both algorithms, the distribution of aerosol optical depth over land areas of China in 2005 was provided, with an
averaged value 0.31. Moreover, the aerosol optical depths are high in spring and summer while low value in autumn and
winter, and greatly different in different areas. In addition, the surface albedo data inversed by MODIS and MISR were
coupled into the self-developed radiative model,called RAD01. The aerosol direct radiative forcing at the top of
atmosphere (TOA), on the surface and in the atmosphere over land areas of China were calculated as -7±2Wm-2, -21.9
±6.4Wm-2 and 4.9±4.3Wm-2 respectively. Due to the strong absorptivity of aerosols over land areas of China, the
aerosol radiative forcing on the surface was three times larger than that at TOA, with a strong heating effect on the
atmosphere.
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The surplus of phosphorus leads to water eutrophication. Huge input of fertilizers in agricultural activities enriches
nutrition in soil. The superfluous nutrient moves easily to riparian water by rainfall and surface runoff; leads to water
eutrophication of riparian wetlands and downstream water; and consequently affects ecological balance. Thus it is
significant to investigate the risk of phosphorus loss in agricultural land, to identify high concentration areas and guide
the management of nutrition loss. This study was implemented mainly in the area of agricultural use in southern Western
Australia, where a three-year period preliminary monitoring of water quality showed that the concentration of different
forms of phosphorus in water had far exceeded the standard. Due to the large scale surface runoff caused by occasional
storms in Western Australia, soil erosion was selected as the main driving factor for the loss of phosphorus. Remote
sensing and ground truth data were used to reflect the seasonal changes of plants. The spatial distribution of available
phosphorus was then predicted and combined with the evaluation matrix to evaluate the loss risk of phosphorus. This
evaluation was based on quantitative rather than qualitative data to make better precision. It could help making decision
support for monitoring water quality of rivers and riparian wetlands.
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Although influenza is a common disease with characteristics of seasonality, the determinants of each season's onset,
magnitude, and duration are poorly understood. This paper focuses on the role of environmental factors in spread and
epidemic of seasonal influenza and explores the environmental explanatory factors for different types of influenza in
mainland China. It also introduces satellite remote sensing as an important data obtaining approach, and highlights the
potential of using satellite images for monitoring dynamics of climate and landscapes related to the spread of seasonal
influenza. Applying Geographic Information System (GIS) technique combining with traditional statistical analysis, the
paper uses influenza virus isolation rate (VIR) as the measure of influenza activity and analyzed its association with
environmental factors. The results show that the spread and epidemic of influenza is influenced by various
environmental factors, among which the temperature and humidity are seemed to be the determinants. However, the
impacts of the environmental factors to different types of virus are varied. Low temperature and humidity conditions
arere associated with a higher activity of both influenza A and B. On the contrary, high temperature and humidity
conditions are associated with a higher activity of influenza A, but are associated with only a moderate or low, less
consistent increase in the activity of influenza B. Recognition of this association could lead to better understanding of the
mechanisms of emergence of influence epidemics and provide scientific evidence for controlling influenza.
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Water optical properties are important factors that affect phytoplankton biomass, carbon formation and carbon output of
the upper body. Water spectral absorption properties are among the most important inherent optical properties. This
paper was a preliminary analysis on spectral absorption properties of water suspended particle, de-pigmented particle,
pigment particle and chromophoric dissolved organic matter (CDOM) in main channel of Hangzhou Xixi Wetland
National Park phase I. The results indicate that the absorption spectrum of suspended particle is similar to the
de-pigmented particle, while the absorption spectrum of pigment particle is almost submerged in the de-pigmented
particle; The absorption spectrum of de-pigmented particle and CDOM follows the exponential decay law, the former
slope Sd average value of the exponential function in the range of 400-700nm is 9.56±0.86μm-1, the latter slope Sgaverage value of the exponential function in the range of 400-500nm is 14.28±1.23μm-1. The absorption peak of
chlorophyll a of pigment particle near 440nm is virtually not existent and also very weak at 675nm. According to the
absorption contribution rate of each component to the total absorption, de-pigmented particle is the greater contributor
than pigment particle and CDOM in this field campaign. In addition, according to water mass classification based on the
contribution rate of absorption coefficient at 440nm, vast majority of the water body in study area could be classified
into the most optical complex water mass type.
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Radiative forcing as an index of climate change can reflect the relative effect of climate factors. To understand climatic
implications of aerosols over the China Seas, the aerosol direct radiative forcing at the top of atmosphere (TOA) is
computed using three-year collocated Clouds and the Earth's Radiant Energy System (CERES) radiation fluxes and
Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness data on the platform Terra. The
upward radiation flux for clear skies is a key for the aerosol radiative forcing at the TOA. A linear relationship is found
between the solar radiation fluxes at the TOA from CERES and the aerosol optical thickness is at 550 nm from MODIS
over the China Seas. In a linear regression Eq., the intercept for zero aerosol optical thickness is the radiation flux at the
TOA for clear skies. Based on the definition of the aerosol direct radiative forcing at TOA and the diurnal correction
factor from a simulated radiative forcing using radiation transfer model, the daily averaged aerosol direct radiative
forcing at the TOA is estimated and its seasonal variations over the cloud-free China Seas are presented. In total, the
aerosol radiative forcing over the China Seas is negative. It implies that the aerosol over the China Seas is mainly a
cooling effect on climate change, which is opposite to the greenhouse effect. The largest aerosol radiative forcing is
found in spring, while the smallest is in summer. The aerosol radiative forcing over the coastal region is always more
than that in the open ocean in four seasons. The method in the study can be used for evaluation of the aerosols impact on
global or region climate from satellite measurements.
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Based on the relationship between the net reflectivity value of Aster data and geochemical index of trace elements, a
statistical model had been established in Jinchuan Nickel-copper Mining area, Gansu province, China. The remote
sensing geochemical anomalies over the areas extending towards south and northwest had been enclosed by analysing
the geochemical surface sampling, surveying spectrum at corresponding points in field, determing spectrum
characteristic spectral range and the threshold value of different element anomalies or different lithological section, as
well as making line No.55 of remote sensing ,geology exploration and geochemical section as a benchmark. The study
shows that the zones of remote sensing-geochemistry anomaly calculated by the statistical models consistent with the
known mining areas, and there are traditional geochemical anomaly within the remote sensing geochemical anomaly in
the parts of the unknown area, which is also validated by remote sensing geochemical anomalies distributed in periphery.
By analyzing both remote sensing geochemical anomaly and regional geological data, the predictions achieve better
effects than that by using the information of remote sensing and geochemical anomalies only.
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Based on ATOVS data and conventional sounding data, two assimilation experiments are performed to simulate a heavy
rainfall over the middle-lower reaches of Yangtze River and the east of southwest China from June 22 to 24 in 2004 by
using model MM5. In the NOATOVS experiment, only conventional sounding data are assimilated based on the
successive correction scheme, while in the ATOVS experiment, the ATOVS radiance data are assimilated by using the
GRAPES (Global and Regional Assimilation and Prediction System) 3D-Var system. The effect of the radiance data on
the background field is analyzed. It indicates that direct assimilation of ATOVS radiance data could improve the
temperature, humidity and wind fields within the troposphere. Moreover, the comparison between the results of the two
experiments shows that ATOVS experiment can not only simulate the circulation pattern well, but also describe the
intensity and the distribution of the rainfall better than the NOATOVS experiment.
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Residential mobility refers to the spatial movement of individuals and households between dwellings within an urban
area. This considerable amount of intra-urban movement affects the urban structure and has significant repercussions for
urban transportation. In order to understand and project related impacts, a considerable number of residential mobility
models has been developed and used in the regional planning process. Within this context, the history and state-of-art
residential mobility models are discussed and indicated. Meanwhile, a residential mobility Microsimulation model,
called URM-Microsim (Urban Residential Mobility Microsimulation), is introduced and discussed.
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