巴州植被盖度的变化和状况评价

利用2004和2005年4￣9月250×250m分辨率Modis资料,计算了巴州绿洲区域的植被盖度。巴州2005年植被盖度与2004年同期相比,低盖度植被面积变化较大,中、高盖度植被面积相对较稳定。在低盖度植被变化中,1级负变化比较明显,说明低植被覆盖地区生态环境脆弱,植被的生长不稳定,需要加大保护力度。     

MODIS影像条带噪声去除邻域插值法研究

条带噪声是影响Modis影像质量和反演精度的重要因子,有些在频率域表现为高频信息和低频信息相混合。针对条带噪声形成的原因和规律性,以及对影像进行傅立叶变换频谱分析,比较了几种常用条带噪声去除方法及其局限性。提出了邻域插值法,编程实现自动定位噪声行,进行插值处理,取得了较好的去噪效果,并保留了影像的细部特征。     

Generation and evaluation of gross primary productivity using Landsat data through blending with MODIS data

Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) has been used for the blending of Landsat and MODIS data. Specifically, the 30 m Landsat-7 ETM+ (Enhanced Thematic Mapper plus) surface reflectance was predicted for a period of 10 years (2000–2009) as the product of observed ETM+ and MODIS surface reflectance (MOD09A1) on the predicted and observed ETM+ dates. A pixel based analysis for six observed ETM+ dates covering winter and summer crops showed that the prediction method was more accurate for NIR band (mean r² = 0.71, p ≤ 0.01) compared to green band (mean r² = 0.53; p ≤ 0.01). A recently proposed chlorophyll index (CI), which involves NIR and green spectral bands, was used to retrieve gross primary productivity (GPP) as the product of CI and photosynthetic active radiation (PAR). The regression analysis of GPP derived from closet observed and synthetic ETM+ showed a good agreement (r² = 0.85, p ≤ 0.01 and r² = 0.86, p ≤ 0.01) for wheat and sugarcane crops, respectively. The difference between the GPP derived from synthetic and observed ETM+ (prediction residual) was compared with the difference in GPP values from observed ETM+ on the two dates (temporal residual). The prediction residuals (mean value of 1.97 g C/m² in 8 days) was found to be significantly lower than the temporal residuals (mean value of 4.46 g C/m² in 8 days) that correspondence to 12% and 27%, respectively, of GPP values (mean value of 16.53 g C/m² in 8 days) from observed ETM+ data, implying that the prediction method was better than temporal pixel substitution. Investigating the trend in synthetic ETM+ GPP values over a growing season revealed that phenological patterns were well captured for wheat and sugarcane crops. A direct comparison between the GPP values derived from MODIS and synthetic ETM+ data showed a good consistency of the temporal dynamics but a systematic error that can be read as bias (MODIS GPP over estimation). Further, the regression analysis between observed evapotranspiration and synthetic ETM+ GPP showed good agreement (r² = 0.66, p ≤ 0.01).     

利用MODIS气溶胶产品研究亚洲季风对气溶胶传输及其分布的影响

利用NASA Terra和Aqua卫星MODIS气溶胶卫星产品,统计了亚洲地区气溶胶光学厚度的空间和季节变化特点,发现东亚与南亚两气溶胶光学厚度高值区年际变化类似,季节变化有所不同。同时结合季风区气候条件,分析亚洲季风对气溶胶分布传输的影响,认为南亚气溶胶光学厚度大值区主要是由于南亚季风和高原地形综合作用形成,东亚地区主要是以当地人类活动产生的气溶胶为主,夏季会受到南亚地区气溶胶输送的影响。光学厚度大值区会随着强季风移动。     

A MODIS-based automated flood monitoring system for southeast asia

Flood disasters in Southeast Asia result in significant loss of life and economic damage. Remote sensing information systems designed to spatially and temporally monitor floods can help governments and international agencies formulate effective disaster response strategies during a flood and ultimately alleviate impacts to population, infrastructure, and agriculture. Recent destructive flood events in the Lower Mekong River Basin occurred in 2000, 2011, 2013, and 2016 (http://ffw.mrcmekong.org/historical_rec.htm, April 24, 2017).The large spatial distribution of flooded areas and lack of proper gauge data in the region makes accurate monitoring and assessment of impacts of floods difficult. Here, we discuss the utility of applying satellite-based Earth observations for improving flood inundation monitoring over the flood-prone Lower Mekong River Basin. We present a methodology for determining near real-time surface water extent associated with current and historic flood events by training surface water classifiers from 8-day, 250-m Moderate-resolution Imaging Spectroradiometer (MODIS) data spanning the length of the MODIS satellite record. The Normalized Difference Vegetation Index (NDVI) signature of permanent water bodies (MOD44W; Carroll et al., 2009) is used to train surface water classifiers which are applied to a time period of interest. From this, an operational nowcast flood detection component is produced using twice daily imagery acquired at 3-h latency which performs image compositing routines to minimize cloud cover. Case studies and accuracy assessments against radar-based observations for historic flood events are presented. The customizable system has been transferred to regional organizations and near real-time derived surface water products are made available through a web interface platform. Results highlight the potential of near real-time observation and impact assessment systems to serve as effective decision support tools for governments, international agencies, and disaster responders.     

Monitoring water turbidity and surface suspended sediment concentration of the Bagre Reservoir (Burkina Faso) using MODIS and field reflectance data

Monitoring turbidity and Surface Suspended Sediment Concentration (SSSC) of inland waters is essential to address several important issues: erosion, sediment transport and deposition throughout watersheds, reservoir siltation, water pollution, human health risks, etc. This is especially important in regions with limited conventional monitoring capacities such as West Africa. In this study, we explore the use of Moderate Resolution Imaging Spectroradiometer data (MODIS, MOD09Q1 and MYD09Q1 products, red (R) and near infrared (NIR) bands) to monitor turbidity and SSSC for the Bagre Reservoir in Burkina Faso. High values ​​of these parameters associated with high spatial and temporal variability potentially challenge the methodologies developed so far for less turbid waters. Field measurements (turbidity, SSSC, radiometry) are used to evaluate different radiometric indices. The NIR/R ratio is found to be the most suited to retrieve SSSC and turbidity for both in-situ spectoradiometer measurements and satellite reflectance from MODIS.The spatio temporal variability of MODIS NIR/R together with rainfall estimated by the Tropical Rainforest Measuring Mission (TRMM) and altimetry data from Jason-2 is analyzed over the Bagre Reservoir for the 2000–2015 period. It is found that rain events of the early rainy season (February-March) through mid-rainy season (August) are decisive in triggering turbidity increase. Sediment transport is observed in the reservoir from upstream to downstream between June and September. Furthermore, a significant increase of 19% in turbidity values is observed between 2000 and 2015, mainly for the July to December period. It is especially well marked for August, with the central and downstream areas showing the largest increase. The most probable hypothesis to explain this evolution is a change in land use, and particularly an increase in the amount of bare soils, which enhances particle transport by runoff.     

使用MODIS数据对云顶高的反演研究

在地球大气能量收支平衡过程中,云具有特别显著的调节作用,是影响气候变化的一个非常重要因子,云的辐射特性和它的高度影响到辐射的收支可以导致地球的变暖或变冷。云顶气压是一个非常重要的云参数。目前有很多方法被用来估计云参数,而CO2薄片算法则是使用被动遥感资料反演云顶性质的重要方法之一。这项技术应用于HIRS资料上已经有20年的历史,而EOS系列地球环境卫星的升空,使EOS上搭载的MODIS探测器成为第一个拥有CO2薄片波段的高空间分辨率探测器。本文描述CO2薄片算法的理论模型和应用中的问题,结合实例进行分析,并讨论误差,以及对未来的展望。