This PDF file contains the front matter associated with SPIE Proceedings Volume 8869, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and Conference Committee listing.

Ecological and crop condition monitoring requires high temporal and spatial resolution remote sensing data. However remote sensing instruments trade spatial resolution for swath width and it’s difficult to acquire remotely sensed data with both high spatial resolution and frequent coverage. A synthesized approach fusing multiple types of remote sensing imagery provides a feasible and economical solution. In this paper, we demonstrate an operational data fusion framework based on Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) for integrating existing MODIS data products (daily, 500m) and freely available Landsat data (16-day, 30m). Phenological metrics are extracted from the fused Landsat and MODIS data. Our case study focuses on an agricultural region in central Iowa. Initial results show that the detailed spatial and temporal variability of the landscapes can be identified from the fused remote sensing data. The derived phenology metrics show distinct features for crops and forest at the field scales and can be explained by the USDA’s reports on the crop progress. The data fusion and time-series analysis approaches provide a feasible solution to for ecological and crop condition monitoring at the field scales.

In desert cities, securing sufficient water supply to meet the needs of both existing population and future growth is a complex problem with few easy solutions. Grass lawns are a major driver of water consumption and accurate measurements of vegetation area are necessary to understand drivers of changes in household water consumption. Measuring vegetation change in a heterogeneous urban environment requires sub-pixel estimation of vegetation area. Mixture Tuned Match Filtering has been successfully applied to target detection for materials that only cover small portions of a satellite image pixel. There have been few successful applications of MTMF to fractional area estimation, despite theory that suggests feasibility. We use a ground truth dataset over ten times larger than that available for any previous MTMF application to estimate the bias between ground truth data and matched filter results. We find that the MTMF algorithm underestimates the fractional area of vegetation by 5-10%, and calculate that averaging over 20 to 30 pixels is necessary to correct this bias. We conclude that with a large ground truth dataset, using MTMF for fractional area estimation is possible when results can be estimated at a lower spatial resolution than the base image. When this method is applied to estimating vegetation area in Las Vegas, NV spatial and temporal trends are consistent with expectations from known population growth and policy goals.

Differences in spectral response function among sensors have known to be a source of bias error in derived data products such as spectral vegetation indices (VIs). Numerous studies have been conducted to identify such bias errors by comparing VI data acquired simultaneously by two different sensors. Those attempts clearly indicted two facts: 1) When one tries to model a relationship of two VIs from different sensors by a polynomial function, the coefficients of polynomial depends heavily on region to be studied: 2) Although increase of the degree of polynomial improves the translation accuracies, this improvement is very limited. Those facts imply that a better functional form than a simple polynomial may exist to model the VI relationships, and also that the coefficients of such a relationship can be written as a function of variables other than vegetation biophysical parameters. This study tries to address those issues by deriving an inter-sensor VI relationship analytically. The derivation has been performed based on a relationship of two reflectances at different wavelengths (bands), called soil isoline equation. The derived VI relationship becomes a form of rational function with the coefficients that depend purely on the soil reflectance spectra. The derived relationship has been demonstrated numerically by a radiative transfer model of canopy, PROSAIL. It is concluded that a rational function is a good candidate to model inter-sensor VI relationship. This study also shows the mechanism of how the coefficients of such a relationship could vary with the soil reflectance underneath the canopy.

A remote sensing regional evapotranspiration (ET) model was built on the basis of topography correction (slope, aspect and elevation), herein. A variety of satellite data which have visible, near-infrared and thermal infrared remote sensing data can be used by this improved model. Combined with conventional ground meteorological information, it can estimate regional distribution of ET under different climate and terrain conditions, expanding the scope of application. Taking into account the terrain factors, we modified the algorithm of SEBAL model. Results showed that, the modified inversion method of evapotranspiration can better reflect actual evapotranspiration condition. Evapotranspiration changes were consistent with land use types. This research indicates that application of medium or high resolution satellite data to calculate regional ET under undulating landform should consider the impact of terrain. It improves the accuracy of ET estimates and has important reference value for the work of the regional water balance and regional agricultural climate research.

The aim of this study was to analyze the urbanization in Shanghai from 1990 to 2005. For this purpose, a time series in 1990, 2000 and 2005 of remote sensing images were collected and interpreted.Land Use/ Cover Change information (i.e. speed and direction and spatial variations) were extracted and the main driving factors were analyzed. Results showed that (1) Urbanization in Shanghai increased from 10.77% in 1990 to 32.96% in 2005 with a total increment value of 22.19%. Land use for city construction, industry and traffic contribute mostly to the change in Land Use/Cover Change, and the average growth rate was 0.43% during 1990-2005 and 1.99% during 2000-2005; (2) The direction in urbanization were different during 1990-2005, mainly expanding in Northeast, Southeast and Southwest. (3) Spatial variations were observed in the urbanization during 1990-2005, and were mainly distributed in the city center (i.e. 0-12 km) in 1990, and then extended to 20 km in 2000 and 40 km in 2005. (4) Economic development and population growth were the main driving factors accounting for the urbanization in Shanghai during 1990-2005.

Many environmental factors, such as stratospheric ozone, aerosols, and clouds, may affect ultraviolet (UV) irradiance. The aim of this study was to investigate the possible association between ultraviolet B (UVB) radiation and total cloud amount, ozone, and aerosols simultaneously, leading to the assessment of possible impacts of climate change on UVB flux variations in the Continental United States (US). Findings indicate that in the past 22 years, while ozone decreased and aerosols increased across the US, the UVB decrease in the northern states was consistent with the increase in aerosols and total cloud amount. Climate change impact resulting in higher total cloud amount in the northern states might result in lower UVB in the future.

This paper provides a coherent pattern identification analysis of coastal land use and land cover (LULC) under the impact of seawater intrusion. This study analysis applied the 4-, 3-, and 2-band false color composite Landsat satellite data to characterize the LULC in the study area. The evapotranspiration (ET) and heat fluxes were estimated by using the SEBAL model with two-time phase thermal infrared band images and regional surface parameters. Our findings are as follows: 1) Due to its distance from the sea, the vegetation index gradually increases as the level of land use gradually increased. 2) The different influences of seawater intrusion in the study area resulted in significantly different influences of land surface parameters (LST, G_n, MSAVI, and Uindex) on ET. There are a variety of types of relational patterns between parameters (LST, G_n, MSAVI and Uindex) and ET (positive, negative, and no relationship). 3) Seawater intrusion significantly affected the spatial pattern of LUCC, which evidently affected the spatial distribution of ET. The spatial distribution pattern and change characteristics of ET were formed by double driving forces of seawater intrusion and LUCC under the background effects of regional climate.

Air quality has become a social issue that is causing great concern to humankind across the globe, but particularly in developing countries. Even though the Weather Research and Forecasting with Chemistry (WRF-Chem) model has been applied in many regions, the resolution for inputting meteorology field analysis still impacts the accuracy of forecast. This article describes the application of the CIMSS Regional Assimilation System (CRAS) in East China, and its capability to assimilate the direct broadcast (DB) satellite data for obtaining more detailed meteorological information, including cloud top pressure (CTP) and total precipitation water (TPW) from MODIS. Performance evaluation of CRAS is based on qualitative and quantitative analyses. Compared with data collected from ERA-Interim, Radiosonde, and the Tropical Rainfall Measuring Mission (TRMM) precipitation measurements using bias and Root Mean Square Error (RMSE), CRAS has a systematic error due to the impact of topography and other factors; however, the forecast accuracy of all elements in the model center area is higher at various levels. The bias computed with Radiosonde reveals that the temperature and geopotential height of CRAS are better than ERA-Interim at first guess. Moreover, the location of the 24 h accumulated precipitation forecast are highly consistent with the TRMM retrieval precipitation, which means that the performance of CRAS is excellent. In summation, the newly built Vtable can realize the function of inputting the meteorology field from CRAS output into WRF, which couples the CRAS with WRF-Chem. Therefore, this study not only provides for forecast accuracy of CRAS, but also increases the capability of running the WRF-Chem model at higher resolutions in the future.

The Greenhouse Gases Observing Satellite (GOSAT) can provide high accuracy column-averaged dry air mole fractions of carbon dioxide (XCO₂). However, the observations have large gaps due to the impact of the cloud and observational modes. Although kriging interpolation yields the best linear unbiased predictor, it would be computationally expensive for a large dataset. Fixed Rank Kriging (FRK) is based on the Spatial Random Effect (SRE) model and it assumes that the process of interest can be expressed as a linear combination of spatial basis functions, plus a fine-scale-variation component. The FRK predictors and standard errors can be computed rapidly. This paper analyzes the FRK prediction of GOSAT Level 2 XCO₂ data over China and shows that the FRK prediction is consistent with other kriging methods (e.g., ordinary kriging). In addition, the result agrees well with the CO₂ measurements from the stations at Mt. Waliguan and Shangdianzi.

Aerosol optical depth (AOD) is critically important for a better understanding of how Earth’s climate is radiatively forced. To compensate for the conventional satellite observations, several types of ground-based radiometers are operated by AOD measurement programs. This study compares the Bratts Lake climate station’s long-term AOD measurements from 1999 to 2012 which are derived from two ground-based programs with high accuracy: the United States Department of Agriculture (USDA) UV-B Monitoring and Research Program (UVMRP) and the AERONET (AErosol RObotic NETwork) program. The comparison shows that, in the 14-year period, the AOD values have an excellent agreement at six wavelengths (368, 415, 500, 610, 665, and 860 nm) with varying slopes (ranging from 0.95763 to 1.04089), intercepts (ranging from 0.0219 to 0.03945), correlation coefficients (R) (ranging from 0.82005 to 0.96155), and root mean square errors (RMSE) (ranging from 0.02639 to 0.03663). The correlations of both monthly and hourly averaged AOD measurements are highly consistent for each band. Specifically, the shorter (with larger AOD values) the wavelength is, the better the correlation is. Also, the results show that the peaks of relative errors generally occur in summer each year, and at noon each day. Our analyses suggest that AOD products derived from UVMRP are accurate and can serve as an alternative ground-based validation source for satellite AOD measurements.

With the fast urbanization process, how does the vegetation environment change in one of the most economically developed metropolis, Shanghai in East China? To answer this question, there is a pressing demand to explore the non-stationary relationship between socio-economic conditions and vegetation across Shanghai. In this study, environmental data on vegetation cover, the Normalized Difference Vegetation Index (NDVI) derived from MODIS imagery in 2003 were integrated with socio-economic data to reflect the city’s vegetative conditions at the census block group level. To explore regional variations in the relationship of vegetation and socio-economic conditions, Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models were applied to characterize mean NDVI against three independent socio-economic variables, an urban land use ratio, Gross Domestic Product (GDP) and population density. The study results show that a considerable distinctive spatial variation exists in the relationship for each model. The GWR model has superior effects and higher precision than the OLS model at the census block group scale. So, it is more suitable to account for local effects and geographical variations. This study also indicates that unreasonable excessive urbanization, together with non-sustainable economic development, has a negative influence of vegetation vigor for some neighborhoods in Shanghai.

This paper introduces the basic theory and method of carbon dioxide (CO2) retrieval. The key step is to search for the optimal solution and the random search algorithm Genetic Algorithm (GA) which can effectively avoid the local optimization. We first investigate the basic principles of GA in CO₂ retrieval and then design the corresponding encoding and decoding methods as well as the fitness function. This newly-developed GA is further applied to retrieve the atmospheric CO₂ concentration using Atmospheric Infrared Sounder (AIRS) observations from January 2006 to December 2008 centered at 20°N, 144°E. Compared to the aircraft measurements, the GA retrieval yields the small root mean square error of 1.13 ppmv and reproduces good results with the observed seasonal cycle.

This paper was based on the 2005 general weather information of 11 Shanghai meteorological stations four times per day, and the 2005 MODIS LST data of Shanghai region at the nearly same time, analyzed the difference on UHI around the meteorological stations, under an ideal meteorological condition. The analysis shows the air temperature and LST was spatially identical to those that were observed in the core zone of Shanghai, with only a small difference in scope and range, but the lowest temperatures exhibited regional variations.

Based on analysis of the relation between various underlying surfaces intercepted from the different-radius circular buffer zones (the radius is respectively 1, 2, 3km, with 11 Shanghai meteorological stations as their center) and their corresponding air temperatures (four times per day, 2 a.m., 8 a.m., 2 p.m., and 8 p.m. (LST)). It is found that a positive correlation between urban land and UHI, and a strong negative correlation between vegetation and UHI. Urban land and vegetation within the range of 1 km around the station affected the observed air temperature from the station. The cooling effect of vegetation within the range of 2 km could not be ignored, whereas that within 3 km was not obvious. The effect of land use on air temperature was most remarkable at 8 p.m., followed by 2 a.m. The effect was not obvious at 8 a.m., and weak effect was observed at 2 p.m. At last, it is mainly discussed the possible reasons for how the correlation between different underlying surfaces and UHI can be formed.

Aerosol optical thickness (AOT) and atmospheric visibility are two important weather parameters. AOT reflects the state of the atmosphere,-and atmospheric visibility is widely used in various aspects of social life. Generally, it is reported in literatures that both of them are affected by Air Pollutants and other meteorological factors, such as surface pressure, ground temperature, wind speed, precipitation. In this paper, a statistic relationship expression is established between AOT and atmospheric visibility on the basis of the point-to-point meteorological observations. In the national region, the correlation between atmospheric visibility and weather factors indicates that the surface pressure has great influence on atmospheric visibility all the year round. And the influence based on precipitation is more obvious in spring and summer, mean-while wind speed and temperature play important roles in autumn and winter. A significant positive correlation was found between AOT and API. To express the relationship between atmospheric visibility and AOT, some computable models were utilized. According to the accuracy analysis, the cubic curve model and the power function model are more accurate. And both RMSE (root-mean-square error) of them is higher than 0.47. But the coefficient of cubic curve is more complex in practice. Finally, a simple estimation model of aerosol optical thickness based on meteorological station observed atmospheric visibility was conducted using power function. The Pearson coefficient between calculation of power function and observation is 0.73.

Chromophoric dissolved organic matter (CDOM) exists in all natural waters. Researches on optical properties of CDOM play an important role in ocean color remote sensing retrieval. The optical properties of CDOM in Zhejiang coastal waters were investigated from August 18, 2009 to June 9, 2011 covering four seasons. Based on the measured data, the distribution of the absorption coefficient of CDOM was analyzed. The results showed that absorption coefficient at 440 nm (a(440)) decreased with the offshore direction, and the relatively high value of a(440) was observed generally in the coastal waters and low value in the adjacent waters. The distribution reflected the terrigenous origin characteristics of CDOM. The relationship between salinity and a(440) of the four seasons was discussed. The results demonstrated that a(440) had a significant negative linear relationship with the salinity. That is to say, CDOM took on the conservative behavior in the research region.

Red tide not only destroys marine fishery production and deteriorates the marine environment, it also causes human health problems. In China, the East China Sea has a high incidence of red tide disasters. Remote sensing technology has been proven an effective means of monitoring red tides. Spectral information of red tide water is an important basis for establishing red tide remote sensing monitoring models. This paper analyzes and compares the differences between red tide event spectral curves and multiyear monthly averaged spectral curves of MODIS data from July 2002 to June 2012, and develops a red tide monitoring algorithm based on the background field, to extract red tide information of the East China Sea. With the application of the algorithm in the East China Sea, it reveals that it can effectively determine the location of red tide and extract red tide information.

HJ-1A/B were two small satellite constellations, that were launched for the environment and disaster monitoring and forecasting on September 6th, 2008. Based on the advantages of high temporal and spacial resolution of the HJ CCD data, this paper aims at evaluate four inversion algorithms of suspended sediments concentration by the remote sensing reflectance in the Hangzhou Bay. First, the atmospheric correction of HJ-1 A/B CCD imagery was carried out using fast line-of-sight atmospheric analysis of spectral hypercubes (FLAASH) model, in which aerosol optical depth was retrieved from synchronous Terra/MODIS data. Then, four classical band ratio algorithms were evaluated. Results show that He’s GOCI model was better than others with 12.75% relative error. At last, we compare the discrepancy between He’s GOCI algorithm and any other three model, results indicate that the other three empirical algorithms performance not very good because of the difference come from different satellite data, various study area, different research season, distinct correction result. This research has an important practical significance to improving the SSC inversion in the HZB.

The main objective of this study was to retrieve rice yield and biomass fromRadarsat-2 SAR data with artificial neuralnetwork (ANN).For this purpose, a practical scheme for estimating rice yield from Radarsat-2 data is established, which demonstrates that Radarsat-2 data can serve asan important data source for monitoring rice system and estimating rice yield.The ANN was composed of the rice backscattering coefficients extracted from multi-temporal Radarsat-2 images and rice canopy parameters (i.e. height, moisture content and biomass) observed from the fields, and then it was applied to simulate the correlation betweenthese two parts. The rice yield and biomass onAugust 21 and September14 were retrieved based on the trained network, respectively. Compared with the measured data, the retrieved rice yield and biomassonAug.21 and Sept.14 were quite accurate.Our results suggested thatRadarsat-2SGX images can be usedto estimate rice yield regionally, and neural network method is feasible with respects to the estimation of rice yield and biomass.

This paper presents a new drought assessment method by modifying the NDVI-Ts space, which named NDVI-Ts general space. Based on this method, the general dry side and wet side equation were established for the period of 2000 and 2010 in the Mongolian Plateau. The results showed that: 1) the NDVI-Ts general space was more stable for monitoring drought than that for the single time Remote Sensing data; 2) Drought mainly distributed in the Mongolian Plateau, In Mongolian Plateau, there was about 75% area of drought; 3) Drought changed in the period of 2000 and 2010. In the year of 2003, the area of severe drought is the smallest. In 2001, the drought is the most serious. The results showed that, the distribution of drought was different in different year. There may be close correlation between the occurrence of drought and precipitation.

Fractional Vegetation Cover (FVC) is one of the most important variables in monitoring the changes of terrestrial ecosystems. Based on the Two-endmember model, FVC from 2000 to 2012 in Xinjiang was derived from MODIS Normalized Difference Vegetation Index (MODIS NDVI)) (16-Day). The spatio-temporal vegetation changes were analyzed, and the results showed that: Vegetation cover in Inner-Mongolia was higher than that in Mongolia. In the year of 2000, the FVC in Inner-Mongolia is 0.557, and 0.516 in Mongolia; while in the year of 2012, the FVC in Inner-Mongolia is 0.663, and 0.593 in Mongolia.

This article firstly calculated China's energy carbon emissions of 30 provinces in 2010 with the method of carbon emission inventories of 2006 IPCC based on the data of China energy statistical yearbook, and then calculated its carbon emission intensity with GDP data in China’s statistical yearbook. Next according to the formed formula the author calculated the EEI (Economic Efficiency Index) and ECI (Ecological Carrying Index) and made some corresponding figures with the help of GIS to analyze the fairness of the China’s energy CO₂ emissions in 2010.The results showed that the distribution of China’s CO₂ emissions for energy in 2010 become lower from the Bohai bay to the surroundings and the west circle provinces are with the lowest energy carbon emissions. The intensity distribution of China’s CO₂ emissions for energy in 2010 becomes higher from southeast China to north China. The distributions of EEI, ECI and for China’s energy CO₂ emissions are quite different from each other, and also with their comprehensive result. As to the fairness of China’s energy CO₂ emissions in 2010, we can say that the south provinces are better than those of Bohai bay areas (except Beijing and Tianjing).

Based on the quantitative calculation of 2000-2010 China's 30 provinces of carbon emissions by the method of 2006 IPCC with the data from China energy statistical yearbook and China cement Yearbook, a detailed analysis of the temporal and spatial variation characteristics of carbon emissions in both Chinese level and provinces’ level was made. The result showed that most of the provinces of China's carbon emissions presented an increasing trend in the past 11 years, especially in Shandong Province, Hebei Province, Shanxi Province, Liaoning Province, Jiangsu province which is located in the national top five. Then according to the current carbon emissions trend, the author put forward some countermeasures for China, such as speeding up the pace of industrial restructuring, searching for clean energy and other measures to reduce the carbon emissions of china to low the emission rate and contribute to the world.

This paper discusses the analysis of the severe dust storm that occurred over Beijing from 26th April to 3rd May in 2012 with the use of combined satellite observations and ground-based measurements. In this study, we analyze the pollution characteristics of particulate matters near ground, with the main focus on spatio-temporal and vertical distributions of aerosol during this event by using ground-based Aerosol Robotic Network (AERONET), MODerate resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data. Results show that the Aerosol Optical Depth (AOD) measured at 550 nm from the AERONET Beijing station has an ascending trend with a peak value of 2.5 on 1st May. Moreover, the AOD variation from the MODIS data agrees well with AERONET observations during the same time period. In addition, the vertical distribution of total attenuated backscatter coefficient (TABC), volume depolarization ratio (VDR) and color ratio (CR) of CALIPSO data are comprehensively analyzed. Results from these analyses show that the dust mainly accumulates in the layer at altitudes of 1.5 to 4.5 km on 1st May. In this dust layer, the values of TABC are generally around 0.002~0.0045 km^-1sr^-1 and VDR and CR are typically around 0.1~0.5 and 0.6~1.4 respectively. Thus, the combined satellite and ground-based observations are of great use for monitoring and analyzing air quality with high accuracy.

The Agro-Pastoral Transitional Zone in Northern China (hereafter APTZNC) is situated in an arid/semi-arid area, and is one of the most vulnerable areas in the world subject to climate change. Annual integrated the NASA Global Inventory Modeling and Mapping Studies (hereafter GIMMS) Normalized Difference Vegetation Index (hereafter ΣNDVI) and annual rainfall were used in this study. Meanwhile, the dynamics of ΣNDVI and rain-use efficiency (hereafter RUE) were predicted during the period, through the use of the Mann-Kendall nonparametric test and linear regression temporal trend analysis. The tendency of desertification under different precipitation scenarios was also analyzed. The results showed that annual ΣNDVI and rainfall were not significantly correlated in most sections of the study area, yet opposite results were observed for a smaller percentage of the study area (p<0.01). Changes in vegetation productivity may increase, whereas a significant decrease in a small pixel proportion was observed. The northeast and central sections of the study area are characterized by positive trends in RUE slope values, contrary to what was observed in the southwestern sections of the study area. The results fit well with the findings through ΣNDVI and RUE. Rainfall in the range of 200-500 mm can be seen as a threshold value as the desertification trend decreases and vegetation restoration capacity is enhanced with increasing rainfall.

This study compares the aerosol optical depth (AOD) at 0.55 um derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the National Aeronautics and Space Administration (NASA) Terra satellite with the Level 2.0 AOD (Quality Assured) from the Aerosol Robotic Network (AERONET) at four different locations over East China, including Hefei, Shouxian, Taihu, and Hangzhou-ZFU. The evaluation results indicate that most MODIS data from all sites fall into the expected error ranges (± 0.05 ± 0.15), with over a 66% probability that the NASA design requirements have been met. The Taihu station is an exception, accounting for only 41% of expected errors due to its lake area location and tendency to underestimate surface reflectance, thereby increasing the AOD values. Overall, the MODIS data show a good consistency and thus, are applicable for this analysis over the study area. The MODIS/Terra derived AOD at 0.55 um from 2000 to 2012 are used to analyze the spatio-temporal variation of AOD in East China. Results indicate that AODs are significantly affected by the topographic distribution. The AODs are relativity low over mountainous areas and high over plains and basins. Human activities also have a certain impact on the distribution of AOD. In addition, AODs exhibit clear seasonal variations; generally high in spring and summer, but low in autumn and winter. Combined with Angstrom exponent, aerosol particles are mainly coarse in spring and winter, but fine during summer and autumn.

Land surface heat and water fluxes are key components of water and energy cycles between land and atmosphere. Information about these surface fluxes can guide agricultural production and environmental preservation, and manage different ecosystems to mitigate climate change. The main objective of this work is to estimate the surface heat fluxes and evapotranspiration. For this purpose, the Community Land Model Version 3 was used, atmospheric forcing data and flux observation were extracted from AmeriFlux standardized Level 2 database, then surface heat fluxes under two different underlying surfaces were modeled. The results showed that the model works well regarding the simulation of daily surface fluxes and diurnal surface fluxes although these values were underestimated relative to the values observed from eddycovariance. After validation, evapotranspiration was chosen as the indicator for specific comparison. CLM3.0 showed a better performance in simulating the moisture and evapotranspiration.

Recently, the air quality has been continuing to deteriorate and threaten public health in the Pearl River Delta. China, the host country for the 2010 Asian Games, faced the great challenge of air quality issues, particularly in the Pearl River Delta, where the Asian Games were held. The major aim of this study is to reveal the spatial and temporal characteristics of NO₂ in the Pearl River Delta during October 2004 to December 2010. The long-term characteristics and variations of the NO₂ column concentration before and during the 2010 Asian Games were analyzed by using the NO₂ product OMNO2e from the Ozone Monitoring Instrument (OMI). Results show that the annual average of the NO₂ column concentration has a significant downward trend from 2005 to 2010 in the Pearl River Delta: the total column concentration of NO₂ (TotNO₂) in the atmosphere decreased from 9.207×10¹⁵ molec/cm² to 8.173×10¹⁵ molec/cm², with an average annual rate of -2.247%; the tropospheric column concentration of NO₂ (TropNO₂)decreased from 6.685×10¹⁵ molec/cm² to 5.646×10¹⁵ molec/cm², with an average annual rate of -3.109%. The ratio TropNO₂/TotNO₂ indicating the amount of NO₂ exhausted by human activities also decreased from 0.726 in 2005 to 0.691 in 2010. During the 2010 Asian Games, the weekly average of the TropNO₂ in Pearl River Delta was maintained at a low level. The NO₂ average distribution in the Pearl River Delta is characterized by the maximum in the geometric center, outwardly smaller, and the shrinking areas with high TropNO₂ concentration from 2005 to 2010. Foshan, Jiangmen and Kwangchowan were severely polluted cities during the Games. However, the air quality of the Pearl River Delta was improved compared to its historical periods due to governmental preventive/control measures during the 2010 Asian Games.

Accurate estimation of variability of the surface heat fluxes is very important in the hydrological, meteorological, and agricultural applications. Community land model (CLM) may be used to continuously predict the temporal and spatial sensible and latent heat flux, however, its output is contaminated by uncertainties of the model’s parameters, model structure and forcing data. The aim of this paper is to improve the sensible and latent heat flux prediction of CLM by using data assimilation schemes with Ensemble Kalman Filter (EnKF) algorithm. The data assimilation results are compared against eddy-covariance observations collected at three sites (Arou, Guantan and Yingke) in the northwest of China including grassland, forestland, and cropland cover types. The CLM usually overestimates the sensible heat flux while underestimates the latent heat flux at the three observation sites. The comparison results indicate that data assimilation method improves the estimation of surface sensible and latent heat fluxes from the model, with clear reduction in the resulting uncertainty of estimated fluxes. The average reductions in the RMSE and MAE values of all sites are 40.62 and 25.83 W/m² while the average decline of MAE values were 33.80 and 26.92 W/m² for sensible and latent heat fluxes, respectively, while the most significant reductions in the RMSE values are 67.70 and 30.40 W/m² for sensible and latent heat flux with EnKF algorithm, respectively. Although this study clearly implies that the assimilation of sensible and latent heat fluxes EnKF algorithm has the potential to improve the surface heat fluxes predictions of CLM, further research is required to make definitive conclusions when assimilation of sensible and latent heat fluxes derived from real remote sensing data into CLM. Furthermore, the good approximation of the model and measurement errors and the assimilation multi-source data simultaneously into the CLM may produce better results.

Aerosol optical depth (AOD), aerosol single scattering albedo (SSA), and asymmetry factor (g) at seven ultraviolet wavelengths along with total column ozone (TOC) were retrieved based on Bayesian optimal estimation (OE) from the measurements of the UltraViolet Multifilter Rotating Shadowband Radiometer (UV-MFRSR) deployed at the Southern Great Plains (SGP) site during March to November in 2009. To assess the accuracy of the OE technique, the AOD retrievals are compared to both the Beer’s law derived ones and the AErosol RObotic Network (AERONET) AOD product; and the TOC retrievals are compared to both the TOC product of the U.S. Department of Agriculture UV-B Monitoring and Research Program (USDA UVMRP) and the Ozone Monitoring Instrument (OMI) satellite data. The scatterplots of the AOD estimated by the OE method with the Beer’s law derived ones and the collocated AERONET AOD product both show a very good agreement: the correlation coefficients vary between 0.98 and 0.99; the slopes range from 0.95 to 1.0; and the offsets are less than 0.02 at 368 nm. The comparison of TOC also shows a promising accuracy of the OE method: the standard deviations of the difference between the OE derived TOC and other TOC products are about 5 to 6 Dobson Units (DU). The validation of the OE retrievals on the selected dates suggests the OE technique has its merits and is a supplemental tool in analyzing UVMRP data.

The coastal zone is very important in the world. China coastal zone was granted the first priority of developing economy in the late 1980s. Since then, high population density and rapid economic development hace caused intensive changes of LUCC in this zone. Those changes have lead to land degradation. Besides, China governments launched series of projects and policy to improve such problems. Those will inevitably cause to diverse spatial dynamics of land degradtion. However, the state of land degradation in certain time is still unknown. Soil erosion is an important indicator of land degradation.Therefore, we use RS images，RUSLE model to anlyze the spatial pattern of soil erosion for 2000. By spatial analysis, we found that soil erosion in China coastal zone is not serious. Widespread soil erosion is only occurred on coastal zones in Shandong, Hainan and werstern Guangdong Province. Although rainfall eosivity factor(R) is higher in southern coastal zone, erosion tends to occur on the slopes with lower LS values in northern coastal zone than southern coastal zone. Goevernments have enforced some policy to reduce the extent of soil erosion by conversion of farmland to woodland and barren mountains to woodland. But the difference between southern and northern coastal zone is still not realized. To improve soil eorosion in those areas, we should let governments put more funds to increase vegetation cover in north. Such study will provide helpful suggestions for governments to prevent soil erosion in coastal zone.

To extract information from high resolution images is a challenge work.Compared tothe traditional pixel-based approach, the advantages of object-oriented classification methods are well documented. However, the appropriate scale parametersofthese methods are difficult to be determined, andthe choices of scale parametersareof high importance, whichwill havea strong effect on the segmentation effectiveness. Whereas the evaluations of the quality of a segmentation method are still mainly based onsubjective judgment, which is a complicated process and lacksstability and reliability. Thus, an objective and unsupervised method needs to beestablished for selecting suitable parameters for a multi-scale segmentation to ensure the bestresults. In this work, a novicemethod is introduced to choose the optimal parameter for themulti-scale segmentation. For large information in band itself and weak relationship among multispectral bands, valuable bands should be selected from original data and weighed by the degreeofcorrelation. Then thresholds of all 3 selected bands ranging from 20 to 200 (intervals of 10)are created in Definiens Professional 8.7. It considers that a segmentation has two desirable properties: each of the resulting segments should be internally homogeneous and should be distinguishable from its neighborhood. Therefore, the global intra-segment and inter-segment heterogeneity indexes are taken into account to identify the optimal segmentation scale. Finally, cubic spline interpolation is applied to select the optimalsegmentation scale. As a result, the measure combining a spatial autocorrelation indicator and a variance indicator shows that the method can improve the precision in global segmentation.

China economy has been rapidly increased since 1978. Rapid economic growth led to fast growth of fertilizer and pesticide consumption. A significant portion of fertilizers and pesticides entered the water and caused water quality degradation. At the same time, rapid economic growth also caused more and more point source pollution discharge into the water. Eutrophication has become a major threat to the water bodies. Worsening environment problems forced governments to take measures to control water pollution. We extracted land cover from Landsat TM images; calculated point source pollution with export coefficient method; then SWAT model was run to simulate non-point source pollution. We found that the annual TP loads from industry pollution into rivers are 115.0 t in the entire watershed. Average annual TP loads from each sub-basin ranged from 0 to 189.4 ton. Higher TP loads of each basin from livestock and human living mainly occurs in the areas where they are far from large towns or cities and the TP loads from industry are relatively low. Mean annual TP loads that delivered to the streams was 246.4 tons and the highest TP loads occurred in north part of this area, and the lowest TP loads is mainly distributed in middle part. Therefore, point source pollution has much high proportion in this area and governments should take measures to control point source pollution.