Monitoring global land surface drought based on a hybrid evapotranspiration model     

Yunjun Yao  Shunlin Liang  Qiming Qin  Kaicun Wang  Shaohua Zhao 《International Journal of Applied Earth Observation and Geoinformation》2011

The latent heat of evapotranspiration (ET) plays an important role in the assessment of drought severity as one sensitive indicator of land drought status. A simple and accurate method of estimating global ET for the monitoring of global land surface droughts from remote sensing data is essential. The objective of this research is to develop a hybrid ET model by introducing empirical coefficients based on a simple linear two-source land ET model, and to then use this model to calculate the Evaporative Drought Index (EDI) based on the actual estimated ET and the potential ET in order to characterize global surface drought conditions. This is done using the Global Energy and Water Cycle Experiment (GEWEX) Surface Radiation Budget (SRB) products, AVHRR-NDVI products from the Global Inventory Modeling and Mapping Studies (GIMMS) group, and National Centers for Environmental Prediction Reanalysis-2 (NCEP-2) datasets. We randomly divided 22 flux towers into two groups and performed a series of cross-validations using ground measurements collected from the corresponding flux towers. The validation results from the second group of flux towers using the data from the first group for calibration show that the daily bias varies from −6.72 W/m² to 12.95 W/m² and the average monthly bias is −1.73 W/m². Similarly, the validation results of the first group of flux towers using data from second group for calibration show that the daily bias varies from −12.91 W/m² to 10.26 W/m² and the average monthly bias is −3.59 W/m². To evaluate the reliability of the hybrid ET model on a global scale, we compared the estimated ET from the GEWEX, AVHRR-GIMMS-NDVI, and NECP-2 datasets with the latent heat flux from the Global Soil Wetness Project-2 (GSWP-2) datasets. We found both of them to be in good agreement, which further supports the validity of our model's global ET estimation. Significantly, the patterns of monthly EDI anomalies have a good spatial and temporal correlation with the Palmer Drought Severity Index (PDSI) anomalies from January 1984 to December 2002, which indicates that the method can be used to accurately monitor long-term global land surface drought.  相似文献   

Evaluating a thermal image sharpening model over a mixed agricultural landscape in India     

C. Jeganathan  N.A.S. Hamm  S. Mukherjee  P.M. Atkinson  P.L.N. Raju  V.K. Dadhwal 《International Journal of Applied Earth Observation and Geoinformation》2011

Fine spatial resolution (e.g., <300 m) thermal data are needed regularly to characterise the temporal pattern of surface moisture status, water stress, and to forecast agriculture drought and famine. However, current optical sensors do not provide frequent thermal data at a fine spatial resolution. The TsHARP model provides a possibility to generate fine spatial resolution thermal data from coarse spatial resolution (≥1 km) data on the basis of an anticipated inverse linear relationship between the normalised difference vegetation index (NDVI) at fine spatial resolution and land surface temperature at coarse spatial resolution. The current study utilised the TsHARP model over a mixed agricultural landscape in the northern part of India. Five variants of the model were analysed, including the original model, for their efficiency. Those five variants were the global model (original); the resolution-adjusted global model; the piecewise regression model; the stratified model; and the local model. The models were first evaluated using Advanced Space-borne Thermal Emission Reflection Radiometer (ASTER) thermal data (90 m) aggregated to the following spatial resolutions: 180 m, 270 m, 450 m, 630 m, 810 m and 990 m. Although sharpening was undertaken for spatial resolutions from 990 m to 90 m, root mean square error (RMSE) of <2 K could, on average, be achieved only for 990–270 m in the ASTER data. The RMSE of the sharpened images at 270 m, using ASTER data, from the global, resolution-adjusted global, piecewise regression, stratification and local models were 1.91, 1.89, 1.96, 1.91, 1.70 K, respectively. The global model, resolution-adjusted global model and local model yielded higher accuracy, and were applied to sharpen MODIS thermal data (1 km) to the target spatial resolutions. Aggregated ASTER thermal data were considered as a reference at the respective target spatial resolutions to assess the prediction results from MODIS data. The RMSE of the predicted sharpened image from MODIS using the global, resolution-adjusted global and local models at 250 m were 3.08, 2.92 and 1.98 K, respectively. The local model consistently led to more accurate sharpened predictions by comparison to other variants.  相似文献   

Improving the assessment of ICESat water altimetry accuracy accounting for autocorrelation     

Hani Abdallah  Jean-Stéphane Bailly  Nicolas Baghdadi  Nicolas Lemarquand 《ISPRS Journal of Photogrammetry and Remote Sensing》2011,66(6):833-844

Given that water resources are scarce and are strained by competing demands, it has become crucial to develop and improve techniques to observe the temporal and spatial variations in the inland water volume. Due to the lack of data and the heterogeneity of water level stations, remote sensing, and especially altimetry from space, appear as complementary techniques for water level monitoring. In addition to spatial resolution and sampling rates in space or time, one of the most relevant criteria for satellite altimetry on inland water is the accuracy of the elevation data. Here, the accuracy of ICESat LIDAR altimetry product is assessed over the Great Lakes in North America. The accuracy assessment method used in this paper emphasizes on autocorrelation in high temporal frequency ICESat measurements. It also considers uncertainties resulting from both in situ lake level reference data. A probabilistic upscaling process was developed. This process is based on several successive ICESat shots averaged in a spatial transect accounting for autocorrelation between successive shots. The method also applies pre-processing of the ICESat data with saturation correction of ICESat waveforms, spatial filtering to avoid measurement disturbance from the land–water transition effects on waveform saturation and data selection to avoid trends in water elevations across space. Initially this paper analyzes 237 collected ICESat transects, consistent with the available hydrometric ground stations for four of the Great Lakes. By adapting a geostatistical framework, a high frequency autocorrelation between successive shot elevation values was observed and then modeled for 45% of the 237 transects. The modeled autocorrelation was therefore used to estimate water elevations at the transect scale and the resulting uncertainty for the 117 transects without trend. This uncertainty was 8 times greater than the usual computed uncertainty, when no temporal correlation is taken into account. This temporal correlation, corresponding to approximately 11 consecutive ICESat shots, could be linked to low transmitted ICESat GLAS energy and to poor weather conditions. Assuming Gaussian uncertainties for both reference data and ICESat data upscaled at the transect scale, we derived GLAS deviations statistics by averaging the results at station and lake scales. An overall bias of −4.6 cm (underestimation) and an overall standard deviation of 11.6 cm were computed for all lakes. Results demonstrated the relevance of taking autocorrelation into account in satellite data uncertainty assesment.  相似文献   

Evaluation of a three-band model for estimating chlorophyll-a concentration in tidal reaches of the Pearl River Estuary, China   总被引：1，自引：0，他引：1  

Shuisen Chen  Ligang Fang  Hongli Li  Weiqi Chen  Wenrui Huang   《ISPRS Journal of Photogrammetry and Remote Sensing》2011,66(3):356-364

Accurate assessment of phytoplankton chlorophyll-a (Chla) concentration in turbid waters by means of remote sensing was challenging due to the optical complexity of turbid waters. Recently, a conceptual model containing reflectance in three spectral bands in the red and near-infrared range of the spectrum was suggested for retrieving Chla concentrations in turbid productive waters. The objective of this paper was to evaluate the performance of this three-band model to estimate Chla concentration in the Pearl River Estuary (PRE), China. Reflectance spectra of surface water and water samples were collected concurrently. The samples contained variable Chla (4.80-92.60 mg/m³) and total suspended solids (0.4-55.2 mg/L dry wt). Colored dissolved organic matter (CDOM) absorption at 400 nm was 0.40-1.41 m⁻¹; turbidity ranged from 4 to 25 NTU (Nephelometric Turbidity Units). The three-band model was spectrally calibrated by iterative and least-square linear regression methods to select the optimal spectral bands for the most accurate Chla estimation. Strong linear relationships (R²=0.81, RMSE=1.4 mg/m³, N=32) were established between measured Chla and the levels obtained from the calibrated three-band model [R⁻¹(684)-R⁻¹(690)]×R(718), where R(λ) was the reflectance at wavelength λ. The calibrated three-band model was independently validated (R²=0.9521, RMSE=6.44 mg/m³, N=16) and applied to retrieve Chla concentrations from the calibrated EO-1 Hyperion reflectance data in the PRE on December 21, 2006. The EO-1 Hyperion-derived Chla concentrations were further validated using synchronous in situ data collected on the same day (R²=0.64, RMSE=2 mg/m³, N=9). The spatial tendency of Chla distribution mapping by Hyperion showed gradually increased concentrations of Chla farther from the river mouths (although decreasing from east to west), which were disturbed by the combination of river outlets and tidal current in Lingding Bay of the PRE. This observation conformed to previous observations and studies, and could reasonably be explained by geographical changes. Also, results indicated that the slope of the three-band regression line decreased as the Chla concentration increased, resulting in the first sensitive band of the three-band model to move towards short wavelengths. These findings validated the rationale behind the conceptual model and demonstrated the robustness of this algorithm for Chla retrieval from in situ data and the Hyperion satellite sensor in turbid estuarine waters of the PRE, China.  相似文献   

GPS/Doppler导航随机模型的移动窗口实时估计算法     

周泽波  沈云中  李博峰 《测绘学报》2011,40(2):220-225

引进时间遗忘因子和观测冗余度因子,有效地平衡移动窗口内不同时刻的观测数据及其冗余情况对单位权方差估值的贡献,改进单位权方差的移动开窗实时估计算法.采用载噪比模型确定观测权阵,等价权抗差估计方法处理粗差.实测车载GPS/Doppler数据的处理结果表明:采用本文算法显著提高GPS/Doppler的导航精度与可靠性.  相似文献   

一种导航卫星中长期轨道预报方法     

周建华  杨龙  徐波  谢廷峰 《测绘学报》2011,(Z1)

基于神经网络混合建模的思想提出一种针对导航卫星的中长期轨道预报方法,在原动力学模型的基础上引入神经网络模型作为补偿,从而获得新的预报模型。在训练过程中神经网络通过学习动力学模型轨道预报误差来掌握其变化规律,并在预报过程中为动力学模型预报提供补偿,以提高预报精度。对GPS卫星动力学模型中长期预报误差的特点进行分析,然后根据所得结论提出混合模型的中长期(15 d以上)预报方案,最后通过对GPS卫星的仿真试验证明混合模型的改进效果,结果表明新方法在15~40 d的预报上表现出很好的改进效果。  相似文献   

基于有理多项式系数模型的物方面元最小二乘匹配   总被引：2，自引：1，他引：1  

张过  陈钽  潘红播  江万寿 《测绘学报》2011,40(5):592-597

针对物方面元最小二乘匹配仅适用于单中心投影框幅式成像的匹配制作区域DSM问题,提出基于有理多项式系数（RPC）模型的物方面元最小二乘匹配算法,结合匹配窗口区域内多中心平行投影方式,构建RPC模型下的投影方程,将物方面元最小二乘匹配算法从适用于单中心投影框幅式成像扩展到适用于多中心投影推扫式成像的立体匹配,并用SPOT5-HRG、GeoEye、IKONOS立体影像进行试验验证。试验表明,RPC模型能用于物方面元最小二乘匹配且不损失匹配精度,增加了物方面元最小二乘匹配的应用范围和价值。  相似文献   

POS数据的上下视差误差源检测及误差补偿回归模型     

张永军  熊金鑫  熊小东  邓继伟 《测绘学报》2011,40(5):604-609

分析POS数据存在系统误差的主要原因,推导基于POS的立体像对相对定向模型,建立POS系统误差回归补偿模型。三个不同比例尺测区试验数据的结果表明：POS系统提供的外方位元素中角元素误差是引起模型上下视差的主要误差源;利用回归补偿模型对POS数据进行改正后模型上下视差明显减小;在无需区域网平差的情况下,直接通过相对定向消除POS系统误差,定位精度有较大提高,从而证明该补偿模型的正确性与可行性。  相似文献   

多普勒雷达降水反演及其与改进的区域气候模式RIEMS的同化研究     

吴明光  陈泰生  檀姗姗  骆骐  闾国年  盛业华 《测绘学报》2011,40(5):0-0

本博士论文在前人构建的陆面水文过程模型TOPX和区域气候模式RIEMS的耦合模式的框架基础上,针对耦合模式中RIEMS对降水和蒸散发的模拟精度较低,RIEMS和TOPX模式之间尺度不匹配等几个核心问题进行了深入细致的研究:对天气雷达资料的定量估测降水方面的研究获得了对沂沭河流域最佳的Z-R关系,并通过雷达雨量计联合校正法得到较高精度的面降雨量;采用集合卡尔曼滤波同化算法对雷达反演的面雨量及区域气候模式RIEMS的降水输出进行了数据同化方案研究,获得了更好的降水模拟效果;在RIEMS和水文模型TOPX构成的耦合模型中加入同化方案,实现了流域降水的实例模拟研究,结果表明使用同化方案明显改善了水文模拟效果。  相似文献   

基于切割环分解的三维建筑物细节层次模型构造   总被引：1，自引：0，他引：1  

杨必胜  姜少波 《测绘学报》2011,40(5)

提出一种基于切割环分解的建筑物LOD（细节层次）模型的自动生成方法,该方法首先通过二面角操作算子识别建筑模型中的切割环,然后通过切割环将建筑物模型迭代分割成建筑主体和一系列细部特征,并将分割的结果存储在一棵构造实体几何树（CSG tree）中,最后对特征部件按重要性进行等级划分,同时进行简化处理。试验结果表明该方法具有较高的计算效率,能有效减少模型表面的细节和较好保持模型的结构特征。  相似文献