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991.
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   
992.
There is an urgent necessity to monitor changes in the natural surface features of earth. Compared to broadband multispectral data, hyperspectral data provides a better option with high spectral resolution. Classification of vegetation with the use of hyperspectral remote sensing generates a classical problem of high dimensional inputs. Complexity gets compounded as we move from airborne hyperspectral to Spaceborne technology. It is unclear how different classification algorithms will perform on a complex scene of tropical forests collected by spaceborne hyperspectral sensor. The present study was carried out to evaluate the performance of three different classifiers (Artificial Neural Network, Spectral Angle Mapper, Support Vector Machine) over highly diverse tropical forest vegetation utilizing hyperspectral (EO-1) data. Appropriate band selection was done by Stepwise Discriminant Analysis. The Stepwise Discriminant Analysis resulted in identifying 22 best bands to discriminate the eight identified tropical vegetation classes. Maximum numbers of bands came from SWIR region. ANN classifier gave highest OAA values of 81% with the help of 22 selected bands from SDA. The image classified with the help SVM showed OAA of 71%, whereas the SAM showed the lowest OAA of 66%. All the three classifiers were also tested to check their efficiency in classifying spectra coming from 165 processed bands. SVM showed highest OAA of 80%. Classified subset images coming from ANN (from 22 bands) and SVM (from 165 bands) are quite similar in showing the distribution of eight vegetation classes. Both the images appeared close to the actual distribution of vegetation seen in the study area. OAA levels obtained in this study by ANN and SVM classifiers identify the suitability of these classifiers for tropical vegetation discrimination.  相似文献   
993.
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   
994.
针对商业GIS软件缺乏对自定义空间数据格式的支持能力,提出了利用OGR自定义数据源来实现GIS软件对自定义空间数据格式支持。并以ArcGIS平台为例,将OGR数据模型在数据组织、几何模型、属性信息和空间参考信息等方面转换为ArcGIS软件空间数据模型,使ArcGIS具备了访问OGR自定义空间数据格式的能力,实现了自定义空间数据格式的扩展与应用,体现了开源GIS软件和商业GIS软件协同工作能力。  相似文献   
995.
提出一种新的基于梯形面片的空间运算方法,该方法将多边形要素预先分解成一系列的梯形面片,后续的空间运算将不再基于原始多边形要素进行操作,而是对分解产生的梯形面片进行更为简便的计算处理。梯形面片模型结合了常见矢量数据模型数据精度高、栅格数据模型运算简单等优点,在执行相关空间运算中与常见矢量和栅格模型相比具有优势。详述了该数据模型,并以点面包含分析和多边形叠置分析等实例探讨了其在空间运算中的应用,测试与分析表明该方法兼具数据精度高、算法实现简单等优点,能较有效地提高空间运算的执行效率。  相似文献   
996.
研究了利用时间序列分析方法进行变形预报。首先叙述了变形观测数据预处理、时间序列平稳性检验、模型的选用和检验;然后针对一组实测数据,利用多项式提取趋势项,分析回归残差,建立了AR(2)预报模型,并利用模型进行了预报;最后将预报结果与实测数据比较,证明了预报模型的有效性。  相似文献   
997.
UKF在基于地磁场的自主导航中的应用   总被引:1,自引:0,他引:1  
王向磊  丁硕  苏牡丹 《测绘科学》2011,36(6):103-105
本文研究了基于地磁场的自王导航,建立了以卫星轨道动力学方程为基础的系统状态方程,并详细推导了以地磁场矢量为观测量时的观测方程;为了解决系统的非线性问题把常用来解决非线性问题的UKF引入到基于地磁场的自主导航系统中;最后,用Matlab对基于地磁场的自主导航系统进行了仿真,仿真结果表明UKF有很好的收敛性和稳定性.  相似文献   
998.
基于偏差原则和正则化方法反演晴空地表BRDF和反照率   总被引:1,自引:1,他引:0  
提出一种反演晴空地表反照率快速稳健的新算法——混合算法。该方法首先利用双参数模型函数确定正则参数的初始值,然后由基于Morozov偏差原则的高阶收敛算法确定正则参数,继而通过Tikhonov正则化手段来反演BRDF模型。从POLDER-3/PARASOL BRDF数据库中任意挑选不同覆盖的地表像元测量数据,与MODIS全反演法结果作比较,对比较结果给予了讨论;最后选择天津市地区的卫星图像进行反演实验,并就反演结果给出了误差分析和算法模型的评价。  相似文献   
999.
简要介绍了利用高分辨率卫星影像GeoEye-1的特点针对新疆边境不能实施航空摄影的特殊地带,提出一套利用最少控制点可满足基础测绘要求的技术实施方案.  相似文献   
1000.
GIS系统中实现规模化建筑物的三维建模方法   总被引:1,自引:1,他引:0  
分析、总结了GIS技术与三维建模技术的特点,在此基础上提出了一种高效的基于地理信息系统开展建筑物三维建模的技术方法。即采用草图大师三维建模模块实现建筑物3D建模,并利用其与ArcGIS软件的接口,将其植入ArcGIS系统中,构建规模化的城市建筑的三维数字化应用模块,实现3D浏览和应用;同时重点探讨了建立应用模块的三维模型结构化方法,3D文件的组织与管理以及三维数据高效缓存技术处理细节。  相似文献   
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