This PDF file contains the front matter associated with SPIE Proceedings Volume 7454, including the Title Page, Copyright information, Table of Contents, Introduction (if any), and the Conference Committee listing.

The National Ecological Observatory Network (NEON), being funded by the National Science Foundation, is a continental-scale research platform for discovering, understanding and forecasting the impacts of climate change, land-use change, and invasive species on ecology. Local site-based flux tower and field measurements will be coordinated with high resolution, regional airborne remote sensing observations. The NEON Airborne Observation Platform (AOP) consists of an aircraft platform carrying remote sensing instrumentation designed to achieve sub-meter to meter scale ground resolution to bridge scales from organism and stand scales to the scale of satellite based remote sensing. Data from the AOP will be openly available to the science community and will provide quantitative information on land use change, and changes in ecological structure and chemistry including the presence and effects of invasive species. Remote sensing instrumentation consists of an imaging spectrometer measuring surface reflectance over the continuous wavelength range from 400 to 2500 nm with 10 nm resolution, a scanning, small footprint waveform LiDAR for 3-D canopy structure measurements and a high resolution airborne digital camera. The AOP science objectives, key mission requirements, the conceptual design and development status are presented.

Patterns of change in vegetation growth and condition are one of the primary indicators of the present and future ecological status of the globe. Nitrogen (N) is involved in photochemical processes and is one of the primary resources regulating plant growth. As a result, biological carbon (C) sequestration is driven by N availability. Large scale monitoring of photosynthetic processes are currently possible only with remote sensing systems that rely heavily on passive reflectance (R) information. Unlike R, fluorescence (F) emitted from chlorophyll is directly related to photochemical reactions and has been extensively used for the elucidation of the photosynthetic pathways. Recent advances in passive fluorescence instrumentation have made the remote acquisition of solar-induced fluorescence possible. The goal of this effort is to evaluate existing reflectance and emerging fluorescence methodologies for determining vegetation parameters related to photosynthetic function and carbon sequestration dynamics in plants. Field corn N treatment levels of 280, 140, 70, and 0 kg N / ha were sampled from an intensive test site for a multi-disciplinary project, Optimizing Production Inputs for Economic and Environmental Enhancement (OPE). Aircraft, near-ground, and leaf-level measurements were used to compare and contrast treatment effects within this experiment site assessed with both reflectance and fluorescence approaches. A number of spectral indices including the R derivative index D₇₃₀/D₇₀₅, the normalized difference of R₇₅₀ vs. R₇₀₅, and simple ratio R₈₀₀/R₇₅₀ differentiated three of the four N fertilization rates and yielded high correlations to three important carbon parameters: C:N, light use efficiency, and grain yield. These results advocate the application of hyperspectral sensors for remotely monitoring carbon cycle dynamics in terrestrial ecosystems.

Global climate change has attracted increasing attentions in recent years as a challenge facing human life. Accurately mapping, quantifying and monitoring changes in the physical characteristics of vegetation cover is a key element in the study of global climate change. The normalized difference vegetation index (NDVI) has been used extensively in ecosystem and climate monitoring. This paper examined vegetation change over the last 27 years (1981-2007) over Continental US. Using history of the values of the normalized difference vegetation index (NDVI) which is extracted from satellite sensor data acquired by the National Oceanic & Atmospheric Administration - Advanced Very High Resolution Radiometer (NOAA-AVHRR), long time series of satellite-derived vegetation index has been studied showing the increasing trend of vegetation index over Continental US from 1981 to 2007. The results demonstrated that the change of NDVI shows an increasing trend which might be induced by the global warming. The comparison of the land cover data in 1981 and 2001 validated the uptrend of NDVI.

A recent study established the theoretical basis for a new type of index based on passive microwave vegetation indices (MVIs). The approach was then calibrated for use with data from the Advanced Microwave Scanning Radiometer (AMSR-E) on the Aqua satellite under the assumption that there is no significant polarization dependence of the vegetation emission and attenuation properties. To demonstrate the potential of the new microwave vegetation indices, these were compared with the Normalized Difference of Vegetation Index (NDVI) derived using MODIS at continental and global scales. These results verified that the microwave vegetation indices can provide new and complementary information on vegetation to NDVI for the global monitoring of vegetation and ecosystem properties from space. The next phase of analysis has focused on quantifiable vegetation parameters, specifically vegetation water content that is a valuable parameter in soil moisture retrievals using microwave data. Data sets collected in several recent large scale field campaigns included vegetation water content over domains in addition to conventional indices. Comparisons to date indicate that the MVI does provide vegetation water content information, however, further analysis of vegetation type effects are needed.

Midwestern lakes and reservoirs are commonly exposed to anthropogenic eutrophication. Cyanobacteria thrive in these nutrient rich-waters and some species pose three threats: 1) taste & odor (drinking), 2) toxins (drinking + recreational) and 3) water treatment process disturbance. Managers for drinking water production are interested in the rapid identification of cyanobacterial blooms to minimize effects caused by harmful cyanobacteria. There is potential to monitor cyanobacteria through the remote sensing of two algal pigments: chlorophyll a (CHL) and phycocyanin (PC). Several empirical methods that develop spectral parameters (e.g., simple band ratio) sensitive to these two pigments and map reflectance to the pigment concentration have been used in a number of investigations using field-based spectroradiometers. This study tests a multivariate analysis approach, partial least squares (PLS) regression, for the estimation of CHL and PC. PLS models were trained with 35 spectra collected from three central Indiana reservoirs during a 2007 field campaign with dual-headed Ocean Optics USB4000 field spectroradiometers (355 - 802 nm, nominal 1.0 nm intervals), and CHL and PC concentrations of the corresponding water samples analyzed at Indiana University-Purdue University at Indianapolis. Validation of these models with 19 remaining spectra show that PLS (CHL R²=0.90, slope=0.91, RMSE=20.61 μg/L; PC R²=0.65, slope=1.15, RMSE=23.04. μg/L) performed equally well to the band tuning model based on Gitelson et al. 2005 (CHL: R²=0.75, slope=0.84, RMSE=40.16 μg/L; PC: R²=0.59, slope=1.14, RMSE=20.24 μg/L).

The water in green vegetation is detectable using reflectances in the near infrared and shortwave infrared. Canopy water content is estimated from the product of leaf water content and leaf area index (LAI). The Normalized Difference Infrared Index [NDII = (R₈₅₀ - R₁₆₅₀)/(R₈₅₀ + R₁₆₅₀)] was found to be strongly related to canopy water content using various moderate resolution sensors (Landsat TM, ASTER, AWiFS) during the SMEX02, SMEX04, SMEX05, and OTTER experiments. With the high temporal resolution of MODIS, changes in canopy water content may perhaps be used to estimate plant water stress and wild-fire potential. However, the low spatial resolution of MODIS does not allow the relationship between NDII and canopy water content to be determined experimentally. The objective of this study is to validate the expected relationship of canopy water content with NDII by the standard LAI data product from MODIS; the quotient is the expected leaf water content which will vary by land-cover type. Maximum NDII for 2000-2007 was calculated from the MODIS standard surface reflectance data products and compared to maximum MODIS LAI for the same years. Mean leaf water content from MODIS was not significantly different from leaf data for most land cover types. However the large standard deviations indicated that canopy water content from NDII is not currently accurate for monitoring the incipient stages of plant water stress.

The light absorbed by water in soil and plants is readily determined using hyperspectral full-range imagery and field spectrometers. The full absorption of light can be accounted for by fitting the shape of water absorptions at the same time as other diagnostic bands using multiple Gaussian functions. This research is particularly important in soils due to the loss of mineral band depth with the spread of the fundamental water just beyond the SWIR. The relationship of the albedo lost to band depth, for the same mineral media, is nonlinear. By including water and mineral absorptions in the same fitting, the accuracy of the mineral abundance estimates are shown substantially improved. In addition, measurements of absorption change within the soil surface are so sensitive to water content that these bands as indexes and absorption fitting are excellent predictors of the amount of organic matter. Spectral model is shown for determining water content based water indexes and the fitted SWIR band as a good predictors of soil biological crust, such as lichen and cyanobacteria, in hyperarid soils of the Mojave Desert.

Urban environmental conditions are strongly dependent on the land use and land cover properties and radiant thermal field of the land cover elements in the urban mosaic. Observations of urban reflectance and surface temperature provide valuable constraints on the physical properties that might be the determinants of urban storm formation. It is assume that consistencies in the covariation of land surface temperature with convective rainfall distribution can be identified to represent characteristics of the surface energy flux associated with different meteorological conditions. We retrieved the temperature from MODIS/Aqua (PM satellite) MYD11A1 temperature product (8-day composite and 1 km spatial resolution). Time period used is from June 1 to September 30 of year 2002 to 2008. MODIS reflectivity data and rainfall data corresponding to those dates were also used to verify the hypothesis. However, partial correlations may be seen in the time series analysis accounting for some convective storm events. Yet the San Antonio urban heat island (UHI) over the sea-breeze convergence zone along the coastal bend might affect the storm events too. Obviously, the other of the storm events were triggered by frontal cyclone at the continental scale that might not be directly related to the local UHI effects at all. Nevertheless, spatial analyses in relation to the NEXRAD images confirm spatial correlation between precipitation and UHI within at least 2 storm episodes.

This paper mainly focuses on the human settlement of livable city appraisal system to research the evaluation criteria, using Spatial Analyzing in Arcinfo, to unify the objective evaluation system, to conduct the analysis research from the spatial angle to Beijing residential environment healthy, by the subjective and objective aspects, there has conducted the spatial analysis research on the urban residential environment. The research indicated that:1) Beijing urban district residential environment healthy satisfaction degree level still permissible, has the obvious spatial autocorrelation characteristic. The satisfaction degree of the spatial difference research to indicate that, the satisfaction degree overall existence by take the urban center as the zero point to the periphery emission, the section presents "the saddle" characteristic, has the satisfaction degree nearby the transportation node "concave" region, simultaneously, some islet existence, also causes to the spatial distribution of the livable city satisfaction degree to be more complex; 2) uses the Beijing Environmental protection Bureau issue 2000-2006 year correlation data, carries on the objective evaluation using the factor analysis method to Beijing environment healthy in recent years, discovered atmospheric and the noise pollution does not present the rule change tendency; 3) the residential environment healthy system will divide into atmospheric, the water, the noise and the solid reject four sub-systems, will carry on the subjective and objective appraisal to Beijing the synthesis contrast analysis, north city is higher than western city regarding the air pollution appraisal. In the central city Xicheng District and Chongwen district's inhabitant has the enhancement regarding the air pollution appraisal, but Xuanwu district and Dongcheng district's air pollution condition still had certain disparity from the public satisfaction; The noise appraisal aspect, east city is higher than western city, the central city satisfaction degree has the rise except Xuanwu district. The plan and the construction provides the countermeasure suggestion through above conclusion for Beijing urban residential environment healthy. This will have the vital significance regarding the Beijing future development and the lives of the people residential environment quality enhancement.

Lake Okeechobee, Florida is the largest freshwater lake in the southeastern U.S. It is a key component in the hydrologic system of South Florida providing water supply for agriculture, the environment, and urban areas. Excessive phosphorus loads, from the Okeechobee watershed over the last few decades have led to increased eutrophication of this lake. Much of the excess phosphorus has been sequestered into the sediments. Sediment water interactions, including diffusive fluxes and sediment resuspension are a source of available phosphorus for phytoplankton. As a consequence, nutrient-enriched lake water has led to phytoplankton blooms from time to time. These blooms are often quantified by measurement of chlorophyll-a concentrations. While the in-situ water quality monitoring is time-consuming, sporadic, and costly, multispectral remote sensing sensors onboard satellites can detect chlorophyll-a contained in most phytoplankton efficiently. The objective of this study is to demonstrate the use of MODIS/Terra Surface Reflectance 1- Day images to capture the unique algal bloom event one week after the landfall of the hurricane Fay in mid-Sept. 2008. Use of the genetic programming model permits sound information retrieval for spatial mapping of chlorophyll-a concentrations, which help explain the mechanism as to why the algal bloom event occurred.

The strong relationships between vegetation phenology and global climate change have been found in recent years, especially with increasing popularity and availability of satellite data. Accurate estimates of canopy phenology are critical to quantify carbon and water exchange between forests and the atmosphere and its response to climate change. The objective of this study is to detect the spatial distribution of vegetation phenology with remote sensing and to quantitatively examine the linkage between forest phenology and forest type in contiguous United States. In particular, we focus on phenology variation between different forest types. To achieve this goal, we utilize LAI measurements from Moderate Resolution Imaging Spectroradiometer (MODIS) from 2000 to 2007 to identify phenological transition dates. The transition dates are then related to MODIS land cover type product to assess land cover type dependent phonological variation during 8 years. The results show that both evergreen forests and deciduous forests have an annual cycle of vegetation phenology. Greenup onset days vary diversely among different forest types. The phenology variation range of deciduous needle leaf forests is larger than that of deciduous broadleaf forests. Compared to greenup days, dormancy days have a little difference between different forest types. Grow length of different land cover varies obviously during 8 years.

The authors have developed a photosynthesis crop model for grain production under the background of climate change and Asian economic growth in developing countries. This paper presents an application of the model to grain fields of paddy rice, winter wheat, and maize in China and Southeast Asia. The carbon hydrate in grains has the same chemical formula as that of cellulose in grain vegetation. The partitioning of carbon in grain plants can validate fixation amounts of computed carbon using a satellite-based photosynthesis model. The model estimates the photosynthesis fixation of rice reasonably in Japan and China. Results were validated through examination of carbon in grains, but the model tends to underestimate results for winter wheat and maize. This study also provides daily distributions of the PSN, which is the CO₂ fixation in Asian areas combined with a land-cover distribution classified from MODIS data, NDVI from SPOT VEGETATION, and meteorological re-analysis data by European Centre for Medium-Range Forecasts (ECMWF). The mean CO₂ and carbon fixation rates in paddy areas were 25.92 (t CO₂/ha) and 5.28 (t/ha) in Japan, respectively. The method is based on routine observation data, enabling automated monitoring of crop yields.

The object of this paper is to investigate the relationship between polarimetric SAR information and LAI. RADARSAT- 2 Fine Quad-pol SLC data with shallower and steeper incidence angles were programmed throughout the 2008 growing season. Optical data were acquired using a hyperspectral CASI airborne sensor as well as the SPOT-4 multi-spectral satellite. The optical data were used to generate LAI map for the entire study site. Backscatter coefficients, ratios of backscatter intensity, three polarimeric variables and three Cloude-pottier Decomposition parameters were extracted from the polarimetric data set. Temporal variations of the backscatter coefficient were analyzed. The results show an increase in backscatter with corn and soybean growth. The statistical analysis quantified the relationship between the radar parameters and LAI revealing a strong sensitivity for some radar configurations. For both corn and soybean, RADARSAT-2 cross-polarization (HV) backscatter at either shallow or steep incidence angles was well correlated with LAI. To avoid sensitivity to sensor calibration and changing target moisture conditions, ratios of backscatter intensity, polarimetric variables and Cloude-pottier Decomposition parameters were investigated. For corn, the ratio of HV/HH and HV/VV as well as pedestal height, total power, correlation coefficient, Entropy and alpha angle were highly correlation with LAI at steeper incidence angle. For soybean, the higher correlations were found with the ratio of HV/HH as well as pedestal height, total power, Entropy and alpha angle at shallow incidence angle. In general, the best results were observed for corn using the FQ6 acquisition. For soybean, the FQ20 data provided the most promising results.

This paper investigated the capacity of Hyperion images coupled with Partial least squares analysis (PLS) for mapping agricultural soil properties. Soil samples were collected from Cicero Creek Watershed of central Indiana, and analyzed for soil moisture content (MC), soil organic matter (SOM), total carbon (C), total phosphorus (P), total nitrogen (N) and clay content. Two scenes of Hyperion images covering the watershed were acquired, calibrated and georeferenced, and image spectra were extracted from them. Two phases of PLS modeling was conducted: all samples were used and outliers were identified and removed in phase 1, and in phase 2, the outlier removed dataset were split into two subsets for calibration and validation. The PLS results for both phases indicate that PLS modeling of Hyperion spectra is effective to predict MC, SOM, total C, and total N, but resulted in low correlations for total P and clay content. The low correlation for total P is attributed to low correlation between SOM and total P. The worst correlation for clay content is due to the low signal-to-noise ratio of Hyperion images in the short wave infrared region. Future work is needed for improving the estimates of total P and clay content.

This study select coniferous forests site and organized field measurement and airborne data collection campaign in June of 2008. It compared the performances of LAI estimation using LiDAR and hyperspectral data. The preliminary result shows both LiDAR and hyperspectral data were strongly correlated to field measured LAI, and hence, both data types are suitable for large scale mapping of LAI in forests. For hyperspectral data, the mean value from 3 by 3 window gives better LAI estimation than single pixel value. And the simple ratio vegetation index produced higher correlation with LAI than single band. For Lidar data, different forest types (needleleaf and broadleaf) shows different relationships between Lidar return ratio and LAI. Lidar percentile heights improve the LAI estimation in mountainous boreal forests.

Leaf Area Index (LAI) is a key vegetation structural parameter in ecosystem. Our new approach is on forest LAI retrieval by GOMS model (Geometrical-Optical model considering the effect of crown shape and Mutual Shadowing) inversion using multi-sensor observations. The mountainous terrain forest area in Dayekou in Gansu province of China is selected as our study area. The model inversion method by integrating MODIS, MISR and LIDAR data for forest canopy LAI retrieval is proposed. In the MODIS sub-pixel scale, four scene components' spectrum (sunlit canopy, sunlit background, shaded canopy and shaded background) of GOMS model are extracted from SPOT data. And tree heights are extracted from airborne LIDAR data. The extracted four scene components and tree heights are taken as the a priori knowledge applied in GOMS model inversion for improving forest canopy structural parameters estimation accuracy. According to the field investigation, BRDF data set of needle forest pixels is collected by combining MODIS BRDF product and MISR BRF product. Then forest canopy parameters are retrieved based on GOMS. Finally, LAI of forest canopy is estimated by the retrieved structural parameters and it is compared with ground measurement. Results indicate that it is possible to improve the forest canopy structural parameters estimation accuracy by combining observations of passive and active remote sensors.

Canopy water content is an important variable for forestry and agriculture management. This study was aimed at building calibration models to estimate vegetation canopy (VC) equivalent water thickness (EWT) from high temporal resolution and large areal coverage MODIS images. The models were developed for a semi-arid area in Arizona (SMEX04) and the best one was applied to MODIS images covering a forest area in Southern Indiana. EWT derived from hyperspectral data in the process of atmospheric correction was used for calibrating MODIS spectral indices. Tested in this study were four vegetation indices: Normalized Difference Water Index (NDWI), Shortwave Infrared Water Stress Index (SIWSI), Normalized Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI), which were designed based on either water (NDWI and SIWSI) or chlorophyll absorptions (NDVI and EVI). Validating these indices on field measured EWT for the SMEX04 site resulted in R² correlations of 0.7547, 0.7509, 0.7299 and 0.7547, respectively. According to regression equations, however, EWT estimated using NDWI and SIWSI shows a slope more close to 1 than those using NDVI and EVI when validated with ground measured EWT, thus showing a better prediction ability than the two chlorophyll indices. The SIWSI-EWT model was chosen to apply to a time series of MODIS images covering the Southern Indiana areas and the relationship of EWT derived from these images to precipitation was examined.

We present preliminary design studies and modeling results for a new system for the assessment of vegetation photosynthetic function, especially carbon uptake. Plant health and carbon uptake efficiency are of key consideration in assessing global productivity, biomass, changes in land cover and carbon dioxide flux. Chlorophyll fluorescence (ChlF) measurements are critical for understanding photosynthetic functioning, plant environmental stress responses and direct assessments of plant health. Plant ChlF occurs predominately in two broad emission bands in the red and infrared regions of the spectrum. Unfortunately, the fluorescence signal from vegetation is much weaker than, and obscured by, the reflected signal. This limitation can be overcome by acquiring ChlF measurements in atmospheric absorption lines. The Interferometric Sensor for Plant Fluorescence (ISPF) will measure plant ChlF using the Fraunhofer Line Discrimination approach. Fabry-Perot (FP) etalons will be used to restrict the measurement to radiation in the Solar Fraunhofer lines (SFL). An advantage of the proposed sensor design is that it will collect measurements using two sets of SFL at the same time. This technique increases the optical throughput producing a larger signal to noise ratio (SNR). The instrument is designed to have two channels for two different spectral regions. Each channel will have two sub-channels, one defined by a prefilter (Reference, Ref) and the other having a tunable FP etalon. The first subchannel (the Ref) will cover a relatively broad spectral range to include at least two Fraunhofer lines but for which the fluorescence signal will represent only a small fraction of total reflected light. The second subchannel will use a FP interferometer to restrict the detected light to include only the selected SFL where the ChlF in-filling is significant. A small change in the fluorescence will then produce an insignificant change in the Ref subchannel but a relatively large change in signal from the FP subchannel. Changes in albedo or clouds will affect both subchannels proportionally so that the ratio of FP/Ref will be sensitive only to ChlF and almost insensitive to other parameters. The ISPF sensor will measure the fluorescence energy emitted by vegetation under natural sunlight. Advantages of the sensor over other designs are that it is passive (i.e., does not require an external illumination source), has simple structure and can be manufactured in a rugged, monolithic form that has no moving parts.

In terms of NCEP/NCAR daily reanalysis data and some remote sensing data, effects of diabatic heating on the short-term position variation of the west Pacific subtropical high (WPSH) during persistent heavy rain event in June 2005 in South China are analyzed based on the complete vertical vorticity equation. The results show that the position variation of WPSH is associated with the diabatic heating. In comparison with the climatology, there is strong heating on the north side of WPSH and relatively weak ITCZ convection on the south.. Each of westward extension of WPSH corresponds to a significantly enhanced heating to the west of WPSH. In mid-troposphere, the vertical variation of heating on the north (south) of WPSH during 12~24 June, 2005 is basically greater(less) than the climatology, which is unfavorable for the northward movement of WPSH. In the mid and late of June 2005, the vertical variation of heating over the eastern coast of the Arabian Sea and the Bay of Bengal (to the west of WPSH) is largely higher than the climatology, which is in favor of the increase of anti-cyclonic vorticity on the west of WPSH, inducing westward extension of WPSH. As a result, the heating on the north and south, and to the west of WPSH work together to make WPSH extend more southward and westward in June 2005, which is in favorable for rainbelts maintaining in South China.

The MODIS data has high temporal resolution but rather coarse spatial resolution, therefore, the MODIS-EVI data, which was more sensitive towards the phonological information than the MODIS-NDVI data, was chosen to build up the time series of studying area, in order to monitor and depict the original phonological characteristics of land cover. Moreover, the DEM, SLOPE, Homogeneity data, which all represent the differences of geographical distribution, and LST data, which represents the differences of earth-atmosphere interaction, were combined as ancillary data together with MODIS-EVI to build a decision tree. After the classification validation, the overall accuracy attainted to 71.9% and Kappa coefficient is 0.66. Therefore, it is proved that the land cover classification with high accuracy but low cost in regional scale is possible.

The temporal and spatial characteristics of climate change in China during the recent 100 years were analyzed using CRU05 climate data. We studied the impacts of climate change during the recent 100 years on vegetation ecological zones in China by using Holdridge Life Zone Classification Model and Center-of-Gravity Model. It is concluded that the precipitation and temperature increased and climate became wetter and warmer in most areas of China during the study period with an exception in the subtropical area to the south of Qinhuai River where climate changed toward more precipitation and lower temperature (wetter and colder). The climate change during recent 100 years had strong impacts on vegetation ecological zones in China. It was shown by the variations of spatial distributions of vegetation ecological zoning in three time periods in China and the space displacements of the centers of the gravity that the boreal type and cool temperate zone type in the vegetation ecological zone in China had expanded toward south; wet, moist, and rain forest types had moved forward to the west; the climate change in China during the recent 100 years had improved environmental quality and made the environment in China more suitable for plants to live and grow.

An operational atmosphere correction algorithm based on dark object method and the look up table which founded by MODTRAN4 model was introduced for Landsat images herein. The information of the satellite remote sensing images was used to support the atmosphere correction. The algorithm was applied to the Landsat ETM+ imagery and the comparison results of before and after atmospheric correction show that the impact of Landsat imagery caused by molecules, water vapor, ozone, and aerosol particles in the atmosphere was reduced effectively after the correction. This new atmospheric correction algorithm is effective and capable of retrieving surface reflectance accurately. The surface reflectivity was retrieved exactly to help remote sensing information extraction and thematic interpretation.

In this paper, we develop a method of estimating high temporal-spatial resolution LUE based on the relationship between LUE obtained from Changbai site eddy covariance flux tower and MODIS-derived values of scaled Photochemical Reflectance Index (sPRI). Using MODIS ocean band 11 at 531nm, we tried to detect variations in canopy reflectance related to the xanthophyll cycle. After test MODIS bands 12 and 13 as the reference band because the 570 nm reference band that had been determined to be optimum for calculating PRI in earlier studies is not available on MODIS, strong correlation between MODIS-sPRI and LUE were found only for backscatter reflectance scenes when band 13 (667nm) was used as the reference band with the relationship coefficient is 0.86. Accoring to the method, the retrieved regional LUE can reflect the spatial distribution variation.

Tibetan Plateau has a crucial impact on the atmospheric circulation changes of Asia and even the northern hemisphere and southern hemisphere, directly affecting the formation and evolution of weather and climate of China, and therefore the studying on weather, climate and their evolving mechanism over Qinghai-Tibet Plateau is of great significance, and this studying is helpful for improving accuracy of forecast disaster weather. Tibetan Plateau is the magnifying glass of global climate change too. The system of ecology and the environment in Tibetan Plateau is very fragile and very sensitive to global climate change, so Tibetan Plateau is a window of studying global climate change. Due to the special geographical conditions of the Tibetan Plateau, the weather stations are scarce over the plateau region, especially in its western region. The introduction and application of satellite remote sensing data on studying on the Tibetan Plateau, in particular, is very important and very necessary. Using satellite remote sensing data, some areas of the Tibetan Plateau is classified into several surface types, regional distributions of the Surface parameters are calculated and discussed according to each type. Further more, each distribution map and straight-bar figure of the Surface parameters is given out. The results indicate: All the regional distributions are characteristic by their terrain nature and the regional distributions are obvious and regular. It is seen that the derived regional distributions of land surface parameters for the whole mesoscale area are in good accordance with the land surface status.

Three regions, Huaibei, Jianghuai, Jiangnan, are divided based on the topography, climatic characteristics, as well as surface temperature from 1957 to 2006 of 16 stations in Anhui province. The change with the year, season and month is analyzed in Anhui province and three areas. Some conclusions are as follows. Anhui province had the lowest temperature in 1980s, but after that the temperature raised step by step. The warming fastest region is Jianghuai. The same pace of warming is in three areas: the greatest warming in spring, then that in autumn, the last in summer. It is warming remarkable in February and the cooling time occurs in July and December. But the fluctuation in three areas is different in some details. The heat island in Hefei is also researched. It suggests that the urban heat island intensity in 1990s in Hefei was the maximum, and then weakened. At the meanwhile, the summer is cooling and the winter is warming in Hefei.

Soil Moisture and Vegetation Growth are the most important and direct index in drought monitoring, and the spectrum interpretation of vegetation and soil are serious factors in the judgment of drought degree. To find a more real-time monitoring index of cropland soil moisture by remote sensing, a Cropland Soil Moisture Index (CSMI) was established in this paper based on the effective reflections of Normalized Difference Vegetation Index (NDVI) on deeper soil moisture and well expressions of Surface Water Content Index (SWCI) on surface soil moisture. By validation with different time-series MODIS data, the Cropland Soil Moisture Index (CSMI) not only overcome the limitation of hysteretic nature and saturated quickly of Normalized Difference Vegetation Index (NDVI), but also take the advantage of the Surface Water Content Index (SWCI) which effectively reduce the atmosphere disturbance and retrieval surface soil water content better. The index passed the significant F-tests with α = 0. 01, and is a true real-time drought monitoring index.

Based on the sea surface temperature (SST) and sea level pressure (SLP) data, the temporal and spatial variations of sea surface temperature anomaly (SSTA) in Kuroshio have been analyzed in this paper by means of the method of Rotated Empirical Orthogonal Function (REOF). The results show that there is a spatial change feature as a whole in addition to a remarkable interannual/interdecadal change of SSTA. After dividing the positive and negative SSTA years and analyzing a lot of meteorological elements in corresponding years, it is obtained that the SLP in Kuroshio current region and the height field at 700 hPa are negative anomaly with enhancement of winter monsoon in the negative years and vice versa, and that there is a close relation between SSTA of this region and distribution pattern of wind anomaly at 850 hPa.

Based on the 100-yr simulations from seasonal cycle global SST and sea ice driven by NCAR Cam3 atmospheric general circulation model, the natural variability of East Asian summer monsoon (EASM) in the internal atmosphere is investigated. Results suggest that the natural variability of EASM in the internal atmosphere displays 1) mainly distinct 3-7-yr interannual period and marked interdecadal variation; 2) in the year of weak EASM, sea level pressure (SLP) in Asian continent increases, with decreased SLP around Japan and in eastern Asian littorals; the 500 hPa height field exhibits negative anomalies over Europe, positive anomalies about the Caspian Sea and negative anomalies around Japan and in the Pacific area to the east, thus leading to an EU-like teleconnection wavetrain and almost v.v. for the year of strong EASM. It is also found that the simulated EASM has a close relation to the EU-like teleconnection wavetrain at 500 hPa on a synchronous basis.

Based on the relationship between yield of winter wheat at different growth stages and meteorological factors, the actual yield can be segregated step by step. Based on the yield data of reviving period to heading date without meteorological disasters, the ideal yield were calculated with Lagrange's Interpolation Polynomial and the yield loss rate affected by meteorological disasters have been assessed. By analyzing the degree of different meteorological disasters and their effect on yield from turning green period to heading date, the model of evaluation on late frost loss was defined. Take Shangqiu station as representative in Huanghuai Area, the yield loss caused by frost from 1980 to 2006 were simulated and analyzed. The results shows that the average rate of yield loss was 11.7% and the heavy disaster years of yield loss can be above 30%.

We studied the crop classification in North China using multi-bands MODIS data with time resolution of 8 days and spatial resolution of 500m in year 2007. Vegetation Index EVI was seen as a robust vegetation indicator and its layers were stacked in the time dimension to detect the phenology of various vegetation types including our targets crops. Before classification, a series of data processing steps were performed: first, a comprehensive use of time-frequency analysis methods such as iterated Savitzky-Golay filtering, multi-resolution analysis and energy threshold based algorithm was conducted to reduce noises in the EVI series data; second, crop/non-crop boundary was obtained from the noise reduced data using a binary encoding based algorithm, in which we introduced the concept of "effective width" as the threshold for crop/non-crop vegetation; third, we analyzed the wave structures including starting/ending/maximum curvature/minimum curvature/half wave height points and matched them to the typical crops' phenology in North China to form the training sample sets. The classification methods include ISODATA (unsupervised), SAM (Spectral Angle Mapper), Minimum Distance and SVM (Support Vector Machine). The results showed that the SVM method had the highest accuracy: 82.3% in the double-cropping area and 93.4% in the single-cropping area.

Effects of soil water on crop growth and yield are performed on the changes of crop growing conditions and biomass growth. In this paper, long-term field experiment data at Zhengzhou Experiment Station were used to statistically analyze the relationships between crop growing conditions and biomass growth at current stage and soil water at previous stage. And the relationships between soil water and yield were also set up. Subsequently, optimum soil water and drought indexes were determined for different growth stages of winter wheat. All these results lay the foundation for dynamic evaluation of drought in winter wheat.

Using datasets of 1991-2004 meteorological and soil data as well as field management from 8 stations in the summer-sown maize zone over the Huang-Huai River Basin, North China, study is performed of the water deficit in various phases of growth of the crop impacting on the final yield by means of CERES-Maize of DSSAT Version 4.0, whose parameters are adjusted for local conditions. Results show that 1) in the jointing stage of vegetative growth and the filling stage (especially its earlier part) of the reproduction growth, field moisture acts as a key factor affecting the yield; 2) deficient moisture in the 7-leaf and jointing periods would cause maximum leaf area index to significantly drop, keeping dry matter from accumulation, leading to appreciable diminution of weight of dry stem and leaves; 3) water deficit in the earlier (middle) filling stage would result in reduced number of grains per cob (decrease substantially the weight of 100 grains). The findings in conjunction with measured moisture can be used to implement the "efficient irrigation with less water" practice in this vast region.

In this study, three scenes of Landsat TM/ETM+ images covering Beijing area were used to examine the relationship between the UHI and land use and land cover (LULC) changes, as well as between the UHI and vegetation greenness. The brightness temperatures, LULC, and NDVI were retrieved from the calibrated images. The results showed that the urban or built-up area in Beijing has increased by 4.07% from 1988 to 2005, with nearly 5.7% of vegetated land lost during the same period. The barren area was also increased in this period as large number of land was taken over for urban construction. Seasonal pattern of UHI was obvious with highest UHI intensity observed in summer and lowest in winter. Moreover, with the rapid urbanization, the extent of UHI expanded with newly hot spots emerged surrounding the central urban area. In addition, higher NDVI or vegetation coverage leads to higher land surface temperature (LST) in winter and lower LST in summer. This was due to the different thermal characteristic between vegetated area and non-vegetated area. Therefore, increasing vegetation coverage can be beneficial to the mitigation of UHI effect in urban area in hot season while to keep the land warmer in cold season.

Satellite remote sensing monitoring of forest fire-points is a routine operation of weather service. By taking advantage of remote sensing information's characteristics such as relatively fixed resolution, little geometric distortion and quite stable data quality, the thesis establishes Henan Satellite Remote Sensing Forest Fire-points Automatic Monitoring System in the way of automatic geography registration based on gray correlation and control point database, which can realize automation of the whole process including automatic monitoring,automatic geography registration,automatic fire-points monitoring,automatic production releasing and cell phone short-message notice of fire-points warning information. The system could greatly improve service efficiency. Automatic registration of remote sensing information based on gray correlation and control point database features simpleness and quickness. Through automatic geography registration testing of sunny EOS/MODIS data (at daytime and nightime) during 18 periods from February 2008 to May 2008 in Henan Province with average error of registration is 0.637 pixels at daytime and 0.319 at nighttime, it can fully meet ordinary operation requirements. Fire-point identification and fire-point area estimate method in the system can be applied to monitoring different fires at daytime and at nighttime. Besides, it can automatically screen effective fire-points according to background geographic information, and thus it can improve monitoring accuracy.

The objectives of this study are to explore the performance of MODIS remote sensing data in large scale ET and drought mapping based on physical consideration of land surface energy balance. It was revealed from the analysis results that ET derived from MODIS data was in very good agreement with the measured by lysimeter with the consistency index of 0.917, correlation coefficient of 0.872, and daily relative error of -11.34%. Further, regional water stress index (RWSI) was derived from ET by remote sensing demonstrated a strong correlation with field measured soil moisture and is more significantly correlative to mean 0-20cm soil moisture. The case study conducted for fall drought monitoring in North China during years 2005-2006 indicated that the spatial distribution of drought conditions evaluated from RWSI was in good agreement with actual precipitation and drought status. As the efficient method on the basis of relative soil moisture and ET by MODIS data only with Yucheng station measurements, yet more extensive validation with field measurements at regional scale is necessary to be done to discriminate the effects and the accuracy of the proposed RWSI method.