大民屯凹陷沙四段一沙三段层序地层格架及岩性油气藏预测

利用高精度3D地震、测井和录井资料，建立了大民屯凹陷沙三段、沙四段高精度层序地层格架。沙三段、沙四段层序体系域构成特征属于受同沉积断裂坡折控制的层序，低位体系域主要发育低位三角洲，并分布在同沉积断裂坡折之下；高位体系域主要发育大型河流或扇三角洲沉积体系，并发育四级层序；湖扩展体系域在坡折带之下发育深湖泥岩和油页岩，在坡折之上发育滨浅湖沉积。SSq3-1，层序（沙三中下亚段）和SSq2-1，层序（沙四段）发育的受同沉积断裂坡折控制的低位域砂体分布在湖扩展域优质烃源岩之下。这些砂体正好处于沙三段、沙四段超压带内，对形成岩性油气藏十分有利。斜坡区SSq2-1。层序、荣胜堡洼陷SSq2-1和SSq3-1。层序发育的受同沉积断裂控制的低位域砂体最有利于形成岩性油气藏。     

Study on microscopic defects in Fe-Doped InP single crystals

Effect of crystal growth conditions on the density of microscopic defects, observed on polished Fe-doped InP LEC single crystal wafers, has been investigated by an interference contrast microscope and a laser scattering tomography (LST) system. It was found that microscopic defects have no correlation with dislocations. Crystal rotation speed affects the density of microscopic defects. In addition, the density depends on the time that the InP melt is held in the molten state before crystal growth. On the other hand, it was found that the H₂O concentration in B₂O₃ has no correlation with the generation of microscopic defects. The relationship between the microscopic defects and the stoichiometry of grown crystals was investigated by coulometric titration analysis. Since the density of microscopic defects is reduced as the indium concentration decreases, it is speculated that their origin is indium or indium oxide.     

Evaluating NDVI-based emissivities of MODIS bands 31 and 32 using emissivities derived by Day/Night LST algorithm

Surface emissivity estimation is a significant factor for the land surface temperature estimation from remotely sensed data. For fully vegetated surfaces, the emissivity estimation is performed in a simple manner since the emissivity is relatively uniform. However, for arid land with sparse vegetation, the estimation is more complicated since the emissivity of the exposed soil and rock is highly variable. In this study, mean and difference emissivity for bands 31 and 32 of MODIS sensor have been derived based on NDVI values. First, the NDVI thresholds have been determined to separate bare soil, partially vegetated soil and fully vegetated land. Then regression relations have been derived to estimate mean and difference emissivity of the bare soil samples and partially vegetated surfaces. A constant emissivity is also used for fully vegetated area. Along with the correlations, standard deviations of the regression relations have been examined for a set of representative soil types. Standard deviations smaller than 0.003 in mean emissivity and smaller than 0.004 in difference emissivity are resulted in regression linear relations. Evaluation of the NDVI derived regression relations has been performed using the results of MODIS Day/Night Land Surface Temperature (LST) algorithm on a pair of MODIS images. Using around 45,500 pixels with different soil and land cover types, emissivity of each pixel in bands 31 and 32 have been estimated. The calculated emissivities have been compared with emissivities calculated by MODIS Day/Night LST algorithm. Biases and standard deviations of NDVI-based relations show relatively high agreement for mean and difference emissivity relations with Day/Night method results. It may be concluded that the proposed algorithm can be used as a rather simple alternative to complex emissivity estimation algorithms.     

广州市地表温度反演与土地利用覆盖变化关系研究

利用环境星1A/1B遥感影像,运用Jiménez-Munoz & Sobrino's普适性单通道算法定量反演广州市的地表温度(Land Surface Temperature,LST) ,结合MNF主成分分析和支持向量机获取的不透水面分布格局,利用面向对象分类方法获得了土地利用覆盖情况,重点研究广州市不透水面、土地覆盖和植被指数与城市热环境的定量关系。研究结果显示:基于大气水汽含量实测数据的JM&S普适性单通道算法反演结果更精确;广州市2009~2011年的不透水面面积和土地覆盖与平均地表温度相关性分析表明:广州市连续3 a呈现城市扩张的现象,城市热效应显著加剧;城市平均地表温度与不透水面面积呈现正相关,与城市的植被指数和裸土指数呈现负相关。     

基于LST-EVI特征空间的土壤水分含量反演

干旱是人类历史上的重大自然灾害之一,而土壤水分是干旱监测最重要的指标。利用遥感手段反演地表土壤水分,可以充分反映土壤水分的时空变化特征,适合进行大范围动态监测。研究基于Landsat TM数据,运用普适性单通道算法得到地表温度(LST,Land Surface Temperature),然后选用增强型植被指数(EVI,Enhanced Vegetation Index),构建了LST\|EVI特征空间,计算出温度植被干旱指数(TVDI,Temperature\|Vegetation Dryness Index)。在对实测土壤含水量数据和对应TVDI值进行回归分析的基础上,反演出2010年6月14日黄骅市自然地表20 cm深度处的体积含水量。结果表明:TVDI方法在该研究区是完全可行的,拟合精度较高;研究区自然地表土壤体积含水量分布差异明显,中等含水量地区面积最大,西南和部分北部地区含水量较低,而含水量高的区域主要分布在苇洼和沿海地区。     

Predicting riparian evapotranspiration from MODIS vegetation indices and meteorological data

A vegetation index (VI) model for predicting evapotranspiration (ET) from data from the Moderate Resolution Imaging Spectrometer (MODIS) on the EOS-1 Terra satellite and ground meteorological data was developed for riparian vegetation along the Middle Rio Grande River in New Mexico. Ground ET measurements obtained from eddy covariance towers at four riparian sites were correlated with MODIS VIs, MODIS land surface temperatures (LSTs), and ground micrometeorological data over four years. Sites included two saltcedar (Tamarix ramosissima) and two Rio Grande cottonwood (Populus deltoides ssp. Wislizennii) dominated stands. The Enhanced Vegetation Index (EVI) was more closely correlated (r=0.76) with ET than the Normalized Difference Vegetation Index (NDVI; r=0.68) for ET data combined over sites and species. Air temperature (T_a) measured over the canopy from towers was the meteorological variable that was most closely correlated with ET (r=0.82). MODIS LST data at 1- and 5-km resolutions were too coarse to accurately measure the radiant surface temperature within the narrow riparian corridor; hence, energy balance methods for estimating ET using MODIS LSTs were not successful. On the other hand, a multivariate regression equation for predicting ET from EVI and T_a had an r²=0.82 across sites, species, and years. The equation was similar to VI-ET models developed for crop species. The finding that ET predictions did not require species-specific equations is significant, inasmuch as these are mixed vegetation zones that cannot be easily mapped at the species level.     

基于Landsat TM数据的延吉市地表温度的2种反演算法比较研究

基于Landsat TM影像中的热红外数据,利用单窗算法和单通道算法对延吉市的地表温度进行了反演,并对反演结果进行了统计.结果表明:2种反演算法所反演出来的地表温度总体趋势比较一致,其中单通道算法所反演出来的温度比单窗算法高一些,平均相差约1.03 K;2种算法的结果与亮度温度相比,单窗算法和单通道算法分别高出约3.32 K和4.35 K.