A sub-pixel analysis of urbanization effect on land surface temperature and its interplay with impervious surface and vegetation coverage in Indianapolis,United States

This study developed an analytical procedure based upon a spectral unmixing model for characterizing and quantifying urban landscape changes in Indianapolis, Indiana, the United States, and for examining the environmental impact of such changes on land surface temperatures (LST). Three dates of Landsat TM/ETM+ images, acquired in 1991, 1995, and 2000, respectively, were utilized to document the historical morphological changes in impervious surface and vegetation coverage and to analyze the relationship between these changes and those occurred in LST. Three fraction endmembers, i.e., impervious surface, green vegetation, and shade, were derived with an unconstrained least-squares solution. A hybrid classification procedure, which combined maximum-likelihood and decision-tree algorithms, was developed to classify the fraction images into land use and land cover classes. Correlation analyses were conducted to investigate the changing relationships of LST with impervious surface and vegetation coverage. Results indicate that multi-temporal fraction images were effective for quantifying the dynamics of urban morphology and for deriving a reliable measurement of environmental variables such as vegetation abundance and impervious surface coverage. Urbanization created an evolved inverse relationship between impervious and vegetation coverage, and brought about new LST patterns because of LST's correlations with both impervious and vegetation coverage. Further researches should be directed to refine spectral mixture modeling by stratification, and by the use of multiple endmembers and hyperspectral imagery.     

基于MODIS数据的雪面温度遥感反演(英文)

On the basis of simplification of the Planck function in a low temperature range, this paper revises the practical split-window algorithm and presents a method for retrieving snow surface temperature （Ts） based on MODIS data in the middle-latitude region. The application of this method in Qinghai Lake region reveals that it is feasible for the retrieval of Ts. Results of correlation analysis indicate that there was strong negative relationship between Ts and altitude. By analyzing three typical areas in which land cover was relatively homogenous, this paper discusses the relationship between Ts and normalized difference snow index （NDSI） and then presents a new concept named ＂NDSI-Ts space＂.     

Evaluation of change in subsurface thermal environment due to groundwater flow in the Tokyo Lowland,Japan

Information on the distribution of subsurface temperature and hydraulic heads at 24 observation wells in and around the Tokyo Lowland, the eastern part of the Tokyo Metropolitan area, were examined to make clear the relationship between groundwater and the subsurface thermal environment in the urban area. Minimums in temperature–depth logs due to subsurface temperature increasing at shallow parts were recognized in 21 wells. This fact shows subsurface temperature is affected by ground surface warming in almost all of this area. Deeper than minimums, where the effects of surface warming became relatively small, regional variation is observed as follows: high temperatures are shown in the central part to the southern part, and low temperatures shown in the inland to eastern part. The high temperature area corresponds to an area where the lower boundary of groundwater flow is relatively shallow. This area corresponds also to an area with severe land subsidence resulting from excessive groundwater pumping. It is considered that this high temperature area is formed by the effects of upward groundwater flow affected by hydrogeological conditions and pumping. On the other hand, a comparison between past data (1956–1967) and present data (2001–2003) revealed widespread decreasing temperature in the inland area. This is explained by downward groundwater flow based on an analysis of temperature–depth logs. This fact suggests that subsurface temperature is not only increasing from the effects of surface warming but also decreasing from the effects of groundwater environment change due to pumping.     

松辽盆地白垩纪湖泊水体温度与古气候温度估算

湖泊沉积物沉积的第一场所是湖底,湖底温度的高低影响沉积有机质的保存,也影响湖底下部地层的温度。了解古水体温度尤其是古水底温度情况成为评估松辽盆地白垩系生物气勘探前景的必要研究内容之一。根据已有的古气候研究成果与现今气候对比,得出白垩纪松辽盆地年平均气温约为14~24℃。再根据水库温度的计算方法和利用已有的古纬度及古水深的研究成果计算得出,白垩纪松辽盆地古湖盆水体表面温度为17~25℃;水深大于20 m的深湖区,水底温度为6.2~12.5℃;湖底最深处温度为4.0~11.3℃;青山口组和嫩江组沉积时期,湖水分层明显,湖底温度季节性变化很小且温度较低,约为8℃。湖底的低温对松辽盆地白垩纪生物气勘探是有利的。     

非均匀月壤介质的被动微波辐射传输模拟

基于非均匀月壤物理模型和辐射传输方程,模拟月壤介质中的微波辐射传输特性,探讨频率、月壤厚度等与月表亮温的关系。结果表明:在低频段,月壤微波辐射亮温的动态变化范围较大,可探测的月壤厚度大,3 GHz时的最大可探测月壤厚度达12.4 m;在高频段对应的可探测月壤厚度较小,特别是从50GHz往后的频率段内,最大可探测月壤厚度均小于2 m。不同频率的亮温-厚度变化曲线没有交叉点,且频率越高,所能探测的月壤厚度越小。根据模拟结果,建立了月壤厚度与亮温的查找表。基于查找表,利用单个波段的亮温数据即可得到月壤厚度信息。     

Surface renewal analysis for sensible and latent heat flux density

High frequency temperature measurements were recorded at five heights and surface renewal (SR) analysis was used to estimate sensible heat flux density (H) over 0.1 m tall grass. Traces of the temperature data showed ramp-like structures, and the mean amplitude and duration of these ramps were used to calculate H using structure functions. Data were compared with H values measured with a sonic anemometer. Latent heat flux density (E) was calculated using an energy balance and the results were compared with E computed from the sonic anemometer data. SR analysis provided good estimates of H for data recorded at all heights but the canopy top and at the highest measurement level, which was above the fully adjusted boundary layer.     

Seismic hazard of Egypt

Earthquake hazard parameters such as maximum expected magnitude,M _max, annual activity rate,, andb value of the Gutenberg-Richter relation have been evaluated for two regions of Egypt. The applied maximum likelihood method permits the combination of both historical and instrumental data. The catalogue used covers earthquakes with magnitude 3 from the time interval 320–1987. The uncertainties in magnitude estimates and threshold of completeness were taken into account. The hazard parameter determination is performed for two study areas. The first area, Gulf of Suez, has higher seismicity level than the second, all other active zones in Egypt.b-values of 1.2 ± 0.1 and 1.0 ± 0.1 are obtained for the two areas, respectively. The number of annually expected earthquakes with magnitude 3 is much larger in the Gulf of Suez, 39 ± 2 than in the other areas, 6.1 ± 0.5. The maximum expected magnitude is calculated to be 6.5 ± 0.4 for a time span of 209 years for the Gulf of Suez and 6.1 ± 0.3 for a time span of 1667 years for the remaining active areas in Egypt. Respective periods of 10 and 20 years were reported for earthquakes of magnitude 5.0 for the two subareas.     

Estimation of covariance matrix from geochemical data with observations below detection limits

Multivariate statistical analyses have been extensively applied to geochemical measurements to analyze and aid interpretation of the data. Estimation of the covariance matrix of multivariate observations is the first task in multivariate analysis. However, geochemical data for the rare elements, especially Ag, Au, and platinum-group elements, usually contain observations the below detection limits. In particular, Instrumental Neutron Activation Analysis (INAA) for the rare elements produces multilevel and possibly extremely high detection limits depending on the sample weight. Traditionally, in applying multivariate analysis to such incomplete data, the observations below detection limits are first substituted, for example, each observation below the detection limit is replaced by a certain percentage of that limit, and then the standard statistical computer packages or techniques are used to obtain the analysis of the data. If a number of samples with observations below detection limits is small, or the detection limits are relatively near zero, the results may be reasonable and most geological interpretations or conclusions are probably valid. In this paper, a new method is proposed to estimate the covariance matrix from a dataset containing observations below multilevel detection limits by using the marginal maximum likelihood estimation (MMLE) method. For each pair of variables, sayY andZ whose observations containing below detection limits, the proposed method consists of three steps: (i) for each variable separately obtaining the marginal MLE for the means and the variances, , , , and forY andZ: (ii) defining new variables by and and lettingA=C+D andB=C–D, and obtaining MLE for variances, and forA andB; (iii) estimating the correlation coefficient _YZ by and the covariance _YZ by . The procedure is illustrated by using a precious metal geochemical data set from the Fox River Sill, Manitoba, Canada.     

EAR70、CLDAS和ERA Interim表层土壤温度在中国地区的评估

本文利用2010—2015年2400多国家气象站逐小时观测数据对覆盖中国的EAR70、CLDAS和ERA Interim 3种表层土壤温度进行了评估和对比。结果表明：空间上CLDAS表层土壤温度精度最高（平均误差为-0.5 ℃，均方根误差为3.0 ℃，相关系数为0.96），受益于CLDAS高精度的陆面初始场，EAR70平均误差得到了改善；时间上ERA Interim再分析表层土壤温度在6:00和夏、秋季精度会明显下降，再分析表层土壤温度在数值较高时段表现出冷偏差，原因是模拟的土壤温度数值上升速度慢，对应的参数化方案有待改进。再分析表层土壤温度在东北地区冬季存在冷偏差，可能和积雪覆盖有关，陆面参数化方案也有待提高。在地形复杂的青藏高原地区，融合地面观测的CLDAS提高了大气驱动的质量进而改进了土壤的模拟。ERA Interim分辨率较粗不适合在青藏高原或者沿海地区使用，结合了CLDAS的EAR70在青藏高原精度提高。土壤表层温度的精度随着高精度的土壤状态初始场进入模式中时间延长会显著下降。因此，CLDAS的实时同化方式，能够有效提高在分析数据的精度。