基于Terra/MODIS的沙尘暴业务化遥感监测研究

探讨了以MODIS为数据源进行沙尘暴监测的业务化技术流程及方法。以2003年4月9~11日连续发生在我国西北部特大沙尘暴为例，进行了沙尘信息提取及等级划分的示例研究，并与已经业务化运行的气象卫星（NOAA-16、风云1C气象卫星）的结果进行了相关比较。结果表明，该研究为卫星遥感监测沙尘提供了新的数据源和监测途径。     

基于MODIS晴空数据的森林日净第一性生产力估算

基于光能利用率模型提出了一个基于MODIS数据参数反演的日净第一性生产力估算模型. 其中包括基于植被冠层叶面积指数和地表反照率的光合有效辐射比例能量平衡模型, 基于大气气溶胶光学厚度、水汽含量和Bird模型相结合的光合有效辐射计算模型. 日净第一性生产力模型所需的主要参数从MODIS数据反演获得. 为了验证净第一性生产力结果的估算精度, 用中国生态系统研究网络2003和2004年千烟洲和长白山观测站点的日净第一性生产力观测数据和模型估算结果对比, 结果表明两者具有较好的一致性. 同时也将同期NASA的净第一性生产力产品加以对比, 结果表明千烟洲站点上2004年的NASA产品低估了净第一性生产力值, 但长白山站则高估了净第一性生产力结果.     

MODIS与TM冬小麦种植面积遥感测量一致性研究——小区域实验研究

针对大范围冬小麦种植面积遥感测量业务化运行中所存在的不同空间分辨率遥感影像的获取能力、空间分辨率与测量精度之间相互制约的现实问题,选择典型实验区,采取全覆盖的多时相低分辨率MODIS数据与中高分辨率TM样区数据相结合的方法,以支持向量机（SVM）为主要技术手段,通过选取不同比例的TM样本量,对MODIS进行混合像元分解,并对MODIS冬小麦测量结果与TM测量结果进行一致性分析,进而提出了一套可用于大范围冬小麦种植面积遥感测量业务化推广的识别和精度检验方法。研究结果表明：当TM样本量大于5%时,相对于TM识别结果而言,MODIS像元精度可以稳定在82%以上;当TM样本量大于40%时,区域精度可以稳定在97%。因此,从理论上讲,在实际业务化运行中,只要能够获得监测区40%的中高分辨率的影像,采用本研究提出的多尺度冬小麦种植面积测量方法,基本上可以满足业务化运行的精度要求。     

Determining the source of dust storms with use of coupling WRF and HYSPLIT models: A case study of Yazd province in central desert of Iran

Dust storm, which has a significant impact on regional air quality, is one of the most hazardous meteorological phenomena in the arid areas. Yazd province is one of the arid areas in Iran that is exposed to dust storms. In this study, two cases of dust storms of Yazd province are studied with the use of coupling numerical models and aerosol optical depth (AOD) from MODIS data. We investigated synoptic condition of such dust storms that were formed downstream of upper level through in the area by focusing on two storms, on May 24 and 25, 2014. For this purpose, a dynamic coupling of this case is done using WRF output the HYSPLIT model. This model was implemented to investigate the sources of the dust storms by calculating the back trajectories from the receptor sites. The trajectories indicated that the first and the second case storms occurred in the northeast and the south of Yazd respectively. These results also showed a good agreement with MODIS aerosol optical depth data and HYSPLIT back trajectories paths.     

Remote sensing and hydrological measurement based irrigation performance assessments in the upper Amu Darya Delta,Central Asia

In the Aral Sea Basin, where the Central Asian countries compete for limited water resources, reliable information on the actual water use for eight million ha of irrigated land are rare. In this study, spatially distributed land use data, seasonal actual evapotranspiration, and reference evapotranspiration derived from multitemporal MODIS data were combined with in situ water flow measurements for irrigation performance assessments in the upper Amu Darya Delta. The functioning of the major irrigation and drainage which supplies an agricultural area of 270,000 ha in the Uzbek province Khorezm was analysed using water balancing and adequacy indicators of irrigation water use.An average relative evapotranspiration of 95% indicated fulfilled water demands and partly over-irrigation, whereas values below 75% disclosed inadequate water supply in distant parts of the irrigation system. On the other hand, immense water withdrawals of approximately 24,000 m³ ha⁻¹ recorded at the system boundaries between April and September 2005 clearly exceeded the field water demands for cotton cultivation. Only 46% of the total irrigation amounts were consumed for crop production at field level. Throughout the vegetation period, approximately 58% of the total available water left the region as drainage water. Monthly observations of the depleted fraction and the drainage ratio highlighted drainage problems and rising groundwater levels at regional scale. In the most distant downstream subsystem, a high risk of groundwater and soil salinity during the main irrigation phase was found.A combination of high conveyance losses, hydraulic problems, direct linkages between irrigation and drainage, and low field application efficiencies were identified as major reasons for underperforming irrigation. The findings underlined the necessity of water saving and of reconsidering water distribution in Khorezm. The remote sensing approach was concluded as a reliable data basis for regular performance assessments for all irrigation systems in Central Asia.     

NDVI与气候因子关系在不同时间尺度上的结果差异

植被指数是反映地表植被覆盖状况的重要参数,分析气候因子与植被指数间的相互关系有助于揭示气候变化对植被的影响,然而当前研究有两种分析植被指数与气候因子关系的方法,分别为分析植被指数与生长季内和生长季间气候因子的关系,然而这两种法差异如何,何种方法更为合适需要进一步分析。利用2000年—2009年生长季的MODIS的归一化植被指数NDVI(Normalized Difference Vegetation Index)数据集和藏北那曲地区3个气象站逐月气象资料(月平均气温、≥0℃活动积温和月降水量),分析比较了生长季内和生长季间气候因子对植被生长影响的差异,并分析了两种方法的优劣。结果表明:(1)生长季内植被NDVI与同期气温和降水量均呈高度正相关,生长季内时滞时间尺度为1个月时,植被NDVI对月平均气温及降水响应均最为强烈。(2)生长季间NDVI与同期降水量相关性并不明显,气候因子的滞后效应在生长季间也较弱。(3)生长季内和生长季间植被NDVI与气候因子的关系所得出的结论有一定差异性,可能是因为两方面的原因:生长季内植被NDVI与水热因子的高相关性与中国季风季候造成的高温多雨出现在夏季有关,而生长季内高水热条件与高植被指数对应的多年重复必然造伪的高相关系数,但这种相关性不一定能真实反映植被与水热条件的关系,而生长季间水热等气候因子与植被指数年际变化相关性分析不存在水热与高植被指数同期问题,更能真实反映气候因子年际变化对植被的影响。     

A new MODIS daffy cloud free snow cover mapping algorithm on the Tibetan Plateau

Because of similar reflective characteristics of snow and cloud, the weather status seriously affects snow monitoring using optical remote sensing data. Cloud amount analysis during 2010 to 2011 snow seasons shows that cloud cover is the major limitation for snow cover monitoring using MOD10A1 and MYD10A1. By use of MODIS daily snow cover products and AMSR-E snow wa- ter equivalent products （SWE）, several cloud elimination methods were integrated to produce a new daily cloud flee snow cover product, and information of snow depth from 85 climate stations in Tibetan Plateau area （TP） were used to validate the accuracy of the new composite snow cover product. The results indicate that snow classification accuracy of the new daily snow cover product reaches 91.7% when snow depth is over 3 cm. This suggests that the new daily snow cover mapping algorithm is suitable for monitoring snow cover dynamic changes in TP.     

Results of a CLM4 Land Surface Simulation over China Using a Multisource Integrated Land Cover Dataset

In this study, the high-accuracy multisource integrated Chinese land cover （MICLCover） dataset was used in version 4 of the Community Land Model （CLM4） to assess how the new land cover information affected land surface simulation over China. Compared to the default land cover dataset in CLM4, the MICL data indicated lower values for bare soil （14.6% reduction）, nee- dleleaf tree （3.6%）, and broadleaf tree （1.9%）; higher values for shrub cover （1.8% increase）, grassland （9.9%）, cropland （5.0%）, glaciers （0.5%）, lakes （1.6%）, and wetland （1.1%）; and unchanged for urban areas. Two comparative CLM4 simulations were conducted for the 33-yr period from 1972 to 2004, one using the MICL dataset and the other using the default dataset. The results revealed that the MICL data produced a 0.3% lower mean annual surface albedo over China than the original data. The largest contributor to the reduced value was semiarid regions （2.1% reduction）. The MICL-data albedo value agreed more closely with observations （MODIS broad- band black-sky albedo products） over arid and semiarid regions than for the original data to some extent. The simulated average sensible heat flux over China increased by only 0.1 W m 2 owing to the reduced values in arid and semiarid regions, as opposed to increases in humid and semihumid regions, while an increased latent heat flux of I W m-2 was reflected in almost identical changes over the whole region. In addition, the mean annual runoff simulated by CLM4 using MICL data decreased by 6.8 mm yr-1, primarily due to large simulated decreases in humid regions.     

Soil respiration mapped by exclusively use of MODIS data for forest landscapes of Saskatchewan,Canada

Soil respiration (R_s) is of great importance to the global carbon balance. Remote sensing of R_s is challenging because of (1) the lack of long-term R_s data for model development and (2) limited knowledge of using satellite-based products to estimate R_s. Using 8-years (2002–2009) of continuous R_s measurements with nonsteady-state automated chamber systems at a Canadian boreal black spruce stand (SK-OBS), we found that R_s was strongly correlated with the product of the normalized difference vegetation index (NDVI) and the nighttime land surface temperature (LSTn) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The coefficients of the linear regression equation of this correlation between R_s and NDVI × LSTn could be further calibrated using the MODIS leaf area index (LAI) product, resulting in an algorithm that is driven solely by remote sensing observations. Modeled R_s closely tracked the seasonal patterns of measured R_s and explained 74–92% of the variance in R_s with a root mean square error (RMSE) less than 1.0 g C/m²/d. Further validation of the model from SK-OBS site at another two independent sites (SK-OA and SK-OJP, old aspen and old jack pine, respectively) showed that the algorithm can produce good estimates of R_s with an overall R² of 0.78 (p < 0.001) for data of these two sites. Consequently, we mapped R_s of forest landscapes of Saskatchewan using entirely MODIS observations for 2003 and spatial and temporal patterns of R_s were well modeled. These results point to a strong relationship between the soil respiratory process and canopy photosynthesis as indicated from the greenness index (i.e., NDVI), thereby implying the potential of remote sensing data for detecting variations in R_s. A combination of both biological and environmental variables estimated from remote sensing in this analysis may be valuable in future investigations of spatial and temporal characteristics of R_s.     

An improved dark object method to retrieve 500 m-resolution AOT (Aerosol Optical Thickness) image from MODIS data: A case study in the Pearl River Delta area,China

This paper presents an improved Dark Dense Vegetation (DDV) method for retrieving 500 m-resolution aerosol optical depth (AOT) based on MOD04-C005 arithmetic with the Moderate Resolution Imaging Spectroradiometer (MODIS) from the National Aeronautics and Space Administration (NASA). The improvements include change of the movement pattern of retrieval window, selection of a more suitable aerosol type, and storage of the look-up table. The method is then applied to obtain the AOT over the Pearl River Delta region (PRD). By comparing the results with the co-temporal ground sunphotometer observations in 2010, the correlation coefficient is found to be 0.794 with RMSE 0.139 and their variations remain consistent. Contrasts between model values in 2008 and MODIS AOT products in the same date also reveal a high accuracy of the improved DDV method. We also performed sensitivity tests to analyze the impacts of several parameters on apparent reflectance at different bands, and the results show that apparent reflectance is much more sensitive to surface reflectance and AOT than to elevation.