基于时序MODIS NDVI的黑河流域土地覆盖分类研究

归一化植被指数(NDVI)是植被生长状态及植被覆盖度的最佳指示因子,其时序数据也已成为基于生物气候特征开展大区域植被和土地覆盖分类的基本手段。基于时序NDVI数据的土地覆盖分类,即通过提取NDVI时间信号所包含的植被生物学参数,构建起一个包含植被生物学信息的分类特征空间。利用2006年重建得到的MODIS NDVI 16天合成时间序列数据,并结合1 km分辨率的DEM数据、野外实地调查资料等辅助数据,综合分析了不同土地覆盖类型对应的时序NDVI谱线及其第一、二谐波的特征阈值,建立决策树对黑河流域的土地覆盖开展分类研究。结果表明,基于时序MODIS NDVI谱线特征的决策树分类精度为78%,Kappa系数为0.74。利用1 km时序MODIS NDVI时间序列获得较为准确的黑河流域土地覆盖类型是可行的。     

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.     

基于MODIS的春、夏季中国近海气溶胶对于云参数的影响差异研究

通过分析中国近海MODIS数据中气溶胶参数与云参数的相互关系,讨论了该区域气溶胶的间接效应及其对于云的可能影响.结果表明,在中国近海,气溶胶具有明显的间接效应,而且由于气溶胶种类和水汽的季节变化,使得气溶胶的间接作用具有很强的时间变化特征.在夏季,由于人为气溶胶占主导,它作为有效的云凝结核,使得气溶胶光学厚度（AOT）分别与云凝结核数（CCN）有正相关、与云滴有效半径（CER）有负相关性、与云光学厚度（COT）也存在着正相关,气溶胶的间接效应明显;在春季,由于沙尘气溶胶盛行,同时沙尘并不是很好的云凝结核,使得气溶胶光学厚度（AOT）分别与云凝结核数（CCN）的正相关减弱、与云滴有效半径（CER）则由夏季的负相关变为正相关、与云光学厚度（COT）存在弱的负相关,气溶胶的间接效应不明显.     

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.     

改善MODIS BRDF产品热点效应的方法研究

核驱动的Ross Thick-LiSparse Reciprocal(RTLSR)双向反射函数(BRDF)模型已广泛地应用于MODIS等星载传感器的业务化产品处理中。但是,对于多年MODIS二向反射产品历史数据,如何基于RTMLSR模型发展一种简单有效快速的方法,进行热点效应的校正是一个迫切需要解决的问题。本文提出了一种简单有效的方法,不需要对观测数据重新反演,直接在现有MODIS二向反射产品的基础上进行热点校正,方便用户对历史MODIS二向反射产品的使用。该方法应用POLDER-3/BRDF数据库和部分经MODIS业务化算法筛选的反射率数据进行验证,并与RTLSR模型和RTMLSR模型的结果进行比较,结果表明:(1)该方法比现有的MODIS业务化RTLSR算法,对热点反射率有明显改善,拟合相对误差平均降低了10.12%;(2)该方法相对于RTMLSR模型在热点反射率拟合效果上差别不大,相对误差相差2.10%;(3)该方法对热点和冷点归一化的植被指数(NDHD)的估算效果有一定程度的改善,相对于RTLSR模型降低了约4.99%,与RTMLSR模型的相对误差相差1.32%,该方法对直接应用现有MODIS BRDF产品,基于热点方向反射率反演植被结构参数(如植被聚集指数)的精度提高有现实应用价值。     

基于MODIS温度的青藏高原多年冻土活动层厚度变化研究

基于MODIS温度数据,采用TTOP模型和Stefan公式模拟了青藏高原地区的冻土分布并计算了活动层厚度,并与地面观测结果进行了对比。结果表明：2003—2019年青藏高原多年冻土面积为1.01×10⁶ km²;多年冻土活动层厚度区域平均值为1.79 m, 活动层厚度区域平均的变化率为3.67 cm/10a,且草甸地区的变化率明显大于草原地区,5100~5300 m高程带的活动层厚度变化速率最大。     

黄河宁夏段凌汛期气温变化特征

利用宁夏1991~2010年20 a凌汛期水文和气温序列资料,研究了宁夏凌汛期特征、凌汛灾害发生主要时段,黄河封河、开河集中期与日平均气温之间的关系。结果表明:宁夏凌汛特征为封开河时序相反,小流量、高水位行洪,受强冷空气影响较大;凌汛灾害主要发生在封河和开河期间;日平均气温正负转化日期与封、开河期有对应关系,宁夏封河集中期在12月20日至1月19日;开河集中日期在2月13~20日。在凌汛关键期结合MODIS遥感数据对凌汛灾害监测防范有一定指导意义。     

Mapping spatio-temporal flood inundation dynamics at large river basin scale using time-series flow data and MODIS imagery

Flood inundation is crucial to the survival and prosperity of flora and fauna communities in floodplain and wetland ecosystems. This study tried to map flood inundation characteristics in the Murray-Darling Basin, Australia, utilizing hydrological and remotely sensed data. It integrated river flow time series and Moderate Resolution Imaging Spectroradiometer (MODIS) images to map inundation dynamics over the study area on both temporal and spatial dimensions. Flow data were analyzed to derive flow peaks and Annual Exceedance Probabilities (AEPs) using the annual flood series method. The peaks were linked with MODIS images for inundation detection. Ten annual maximum inundation maps were generated for water years 2001–2010, which were then overlaid to derive an inundation frequency map. AEPs were also combined with the annual maximum inundation maps to derive an inundation probability map. The resultant maps revealed spatial and temporal patterns of flood inundation in the basin, which will benefit ecological and environmental studies when considering response of floodplain and wetland ecosystems to flood inundation.