Advances in understanding of the mechanism for generation of earthquake thermal precursors detected by satellites

Stresses building up during an earthquake preparation phase also manifest themselves in the form of a so called increased land surface temperature (LST) leading to a thermal precursor prior to the earthquake event. This phenomenon has now been validated by our observations of short-term thermal anomalies detected by infrared satellite sensors for several recent past earthquakes around the world. The rise in infrared radiance temperature was seen to vary between 5 and 12 °C for different earthquakes. We discuss in this paper different explanations for the generation of such anomalies that have been offered. Emission of gases due to the opening and closure of micropores upon induced stresses and also the participation of ground water have been propounded as a possible cause for generation of thermal anomalies. Seismo-ionosphere coupling, by which gases like radon move to the earth–atmosphere interface and cause air ionization thus bringing about a change in air temperature, relative humidity, etc., has been put forth by some workers. A mechanism of low frequency electromagnetic emission was tested and experimented by scientists with rock masses in stressed conditions as those that exist at tectonic locations. The workers proposed the positive hole pair theory, which received support from several scientific groups. Positive holes (sites of electron deficiency) are activated in stressed rocks from pre-existing yet dormant positive hole pairs (PHPs) and their recombination at rock–air interface leads to a LST rise. A combination of remote sensing detection of rock mechanics behavior with a perception of chemistry and geophysics has been applied to propose the remote sensing rock mechanics theory. Remote sensing detections of such anomalies confirm so far proposed lab theories for such a hotly debated field as earthquake precursor study by providing unbiased observations with consistency in time and space distribution.     

地壳垂直形变模型的研究

本文重点研究了建立整个形变区域的形变速率曲面和形变加速率曲面,同时也研究了求这两种曲面的方法(基于多元逐步回归分析的间接法和直接法),从而使我们对整个形变区域有一个形变的整体概念,也使我们能方便地得出形变区任何一个已知其平面位置的点在任一观测期内的形变量。     

基于人工神经网络面插值的方法研究

前人研究表明三层前向人工神经网络不仅能以任意精度逼近任意函数,还能以任何精度逼近其各阶导数。根据这一特性,本文将反向传播网络（Ｂａｃｋ－Ｐｒｏｐａｇａｔｉｏｎ,简称ＢＰ网络）应用于面插值。本文认定地理要素的空间分布可以用一复杂的非线性函数模拟,该函数是由多种因素综合作用的结果,即地理要素的值是这些因素的函数,如果以各因素的输入、对应地理要素值为期望输出,对网络进行训练可对地理要素的空间分布进行模拟     

联合机载LiDAR数据和潮汐数据自动提取潮位线

首先,联合机载激光雷达(LiDAR)数据提取的海岸带数字表面模型(DSM)与验潮站数据提取的高、低潮面进行相交运算,生成"水陆二值图像",然后对其以提取边缘的方式提取高、低潮潮位线;针对LiDAR光束无法穿透水体导致低潮线附近DSM为无效值的缺陷,采取移动趋势面拟合法外推概略低潮线附近DSM,在此基础上重新提取更精确的低潮潮位线。实验表明,该方法能在较少人工干预的情况下有效提取高、低潮潮位线。     

Automatic techniques for 3D reconstruction of critical workplace body postures from range imaging data

The paper shows techniques for the determination of structured motion parameters from range camera image sequences. The core contribution of the work presented here is the development of an integrated least squares 3D tracking approach based on amplitude and range image sequences to calculate dense 3D motion vector fields. Geometric primitives of a human body model are fitted to time series of range camera point clouds using these vector fields as additional information. Body poses and motion information for individual body parts are derived from the model fit. On the basis of these pose and motion parameters, critical body postures are detected. The primary aim of the study is to automate ergonomic studies for risk assessments regulated by law, identifying harmful movements and awkward body postures in a workplace.     

Analysis of urban built-up areas and surface urban heat island using downscaled MODIS derived land surface temperature data

Regional scale urban built-up areas and surface urban heat islands (SUHI) are important for urban planning and policy formation. Owing to coarse spatial resolution (1000 m), it is difficult to use Moderate Resolution Imaging Spectroradiometer (MODIS) Land surface temperature (LST) products for mapping urban areas and visualization, and SUHI-related studies. To overcome this problem, the present study downscaled MODIS (1000 m resolution)-derived LST to 250 m resolution to map and visualize the urban areas and identify the basic components of SUHI over 12 districts of Punjab, India. The results are compared through visual interpretation and statistical procedure based on similarity analysis. The increased entropy value in the downscaled LST signifies higher information content. The temperature variation within the built-up and its environs is due to difference in land use and is depicted better in the downscaled LST. The SUHI intensity analysis of four cities (Ludhiana, Patiala, Moga and Vatinda) indicates that mean temperature in urban built-up core is higher (38.87 °C) as compared to suburban (35.85 °C) and rural (32.41 °C) areas. The downscaling techniques demonstrated in this paper enhance the usage of open-source wide swath MODIS LST for continuous monitoring of SUHI and urban area mapping, visualisation and analysis at regional scale. Such initiatives are useful for the scientific community and the decision-makers.     

高灵敏度机载L波段微波辐射计探测海表盐度

海水盐度是研究大洋环流和全球气候变化的重要参数,L波段(1400-1427MHz)微波辐射计是进行海水盐度遥感的最有效工具.在该频段内,微波辐射亮度温度对海水盐度变化的灵敏度为0.5K/psu,而用于海洋研究的盐度分辨率为0.1-0.2psu,要求微波辐射计的灵敏度优于0.1K.高灵敏度机载L波段微波辐射计,应用数字增益波动自动补偿和温度补偿技术,保证了系统的稳定性,并采用高效的滤波技术有效地抑制了全球定位信号(GPS)对接收机的干扰,灵敏度达到0.08K.进行了多次航空和海上对比遥感试验,获得了分辨率优于0.2psu、误差精度0.42psu的测量结果.     

移动曲面拟合用于高程控制测量的探讨

多项式曲线拟合、三次样条曲线拟合、多项式曲面拟合、多面函数曲面拟合、移动法曲面拟合是全球定位测量水准拟合常用方法,本文结合实例,分析多种方法获得数据的精度,并通过工程实例比较和分析,认为移动法曲面拟合拟合法精度更高且稳定,具有较高的可靠性和实用价值。     

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

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.     

3D Zernike矩在三维地形匹配中应用

本文介绍了三维地形匹配工作原理,提出3DZernike矩在三维地形匹配中应用算法。该方法利用三维地形曲面与其3DZernike矩具有一一对应关系,计算实时恢复得到的三维地形与基准图中参考三维地形的3DZernike矩,比较这两个3DZernike矩之间欧式距离,并以欧式距离最小为最佳匹配原则实现三维地形的精确匹配。该方法充分利用3DZernike矩的性质,将三维地形匹配转换成3DZernike矩匹配。该算法对匹配地形无特殊要求,抗噪声能力强,能实现三维地形的精确匹配。