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.     

陀螺经纬仪的仪器常数随温度漂移规律的研究

对某型陀螺经纬仪的仪器常数受环境温度的影响进行实验,利用数理统计方法分析、处理了各温度下仪器常数的数据,发现其变化符合线性规律,从而可实现温度对仪器常数的漂移影响的自动补偿。     

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.     

Cartographic Symbol Design Considerations for the Space–Time Cube

The cartographic representation of geographic phenomena in the space–time cube comes with special challenges and opportunities when compared with two-dimensional maps. While the added dimension allows the display of attributes that vary with time, it is difficult to display rapidly varying temporal data given the limited display height. In this study, we adapt 2D cyclic point symbols to construct 3D surfaces designed along a helical path for the space–time cube. We demonstrate how these complex?3D helical surfaces can display detailed data, including data reported daily over 100 years and data reported in four-hour intervals over a year. To create the point symbols, each value is plotted along the curve of a helix, with each turn of the helix representing one year or week, respectively. The model is modified by varying the radii from the time axis to all points using the attribute value, in these cases maximum daily temperature and four-hourly ridership, and then creating a triangulated surface from the resulting points. Using techniques common to terrain representation, we apply hue and saturation to the surface based on attribute values, and lightness based on relief shading. Multiple surfaces can be displayed in a space–time cube with a consistent time interval facing the viewer, and the surfaces or viewer perspective can be rotated to display synchronized variations. We see this method as one example of how cartographic design can refine or enhance operations in the space–time cube.     

一种多因子加权平均温度模型的构建方法

针对在地基GNSS水汽反演的过程中,天顶湿延迟转换为大气可降水量时如何建立精确的大气加权平均温度(Tm)模型的问题,该文在建立Tm模型前全面考虑了对Tm有显著影响的变量并选择最优回归子集。但分析发现,最优回归子集中各变量之间存在较强的相关性,这将会导致变量之间存在多重共线性,从而影响模型的稳定性和可靠性。选择2013—2015年相关气象数据作为变量并应用岭回归的方法削弱变量之间的多重共线性,建立稳定的多因子Tm回归模型。并利用该模型分别预测2016年1—12月、2019年1—7月的Tm,均方根误差分别为2.3 K和2.0 K,预测精度较高,这将为高精度的水汽反演奠定较好的数据基础。     

基于城市地表温度与归一化植被指数对北京市建成区热环境分析

针对研究城市热环境的过程中,利用归一化植被指数(NDVI)进行地表温度(LST)反演,再将LST和NDVI结合说明地物变迁与城市热环境的影响的现状,利用Landsat-8多时相遥感影像、高分辨率影像、公开GIS等多源数据,通过人工交互判读和量化统计分析,实现了2013—2017年北京建成区NDVI变化及其对地表热环境影响分析,再对分析结果进行差值拟合评价。对NDVI阈值分割按照大小为LC1、LC2、LC3、LC4,对LST分为高温区(TH)、常温区(TR)和低温区(TL)。结果表明,2013年至2017年:1)建成区的平均NDVI增加0.03,其中LC1增加1.0%,LC2减少11.6%,LC3区域减少1.7%,LC4区域增加12.3%。2)建成区平均LST增加2.55 K,TH百分比增加0.6%;TR百分比减少1.1%,TL百分比增加0.5%。3)NDVI相对增加,地表温度相对下降以及NDVI相对减少,地表温度相对上升占60%,NDVI相对下降,地表温度相对下降以及NDVI相对增加,地表温度相对上升的占40%。     

温差对泉州四至井水氡测值的影响分析

温度变化是影响水氡观测值的主要因素之一.通过1986-2009年泉州台四至井观测数据资料的分析,说明:调整观测室室内温度使其超过采集水样的原始温度,在运输水样过程中对水样采取保温措施,减小取样水温和鼓泡后水温的温差,能够得到更真实、准确的观测值.     

The Geothermal Study of the Mid-Segment of the Tancheng-Lujiang Fault Zone and Its Neighboring Region

In this paper,25 new terrestrial heat flow values newly observed along the mid-segment of the Tancheng-Lujiang fault zone are listed.With these geothermal data and 37 other terrestrial heat flow values(previously published),we describe the distribution features of terrestrial heat flows in the area.In this research,the two-dimensional temperature structure from the surface to lithospheric bottom of the Huaibei-Sixian-Jinhu profile is inferred by using the finite-element method and the temperature and heat flow of sedimentary,granitic,and basaltic layers is calculated.     

人工侧向冻结条件下土的冻结试验

在人工侧向冻结、正弦和恒温2种冻结温度、开放和封闭条件下,对含水率为32 %的重塑粉质黏土进行了4组冻结试验。结果表明,补水条件相同时侧向正弦冻结试样的冻结速度比封闭正弦冻结试验的缓慢,当其冻结状态进入稳态之后,试样的整体温度场随着侧向冻结温度的正弦变化而出现相应的波动,但径向各段的温度梯度的相位滞后于正弦温度相位半个周期;正弦冻结试样与恒温冻结试样在同一条件下的冻胀量相近,封闭体系下自上而下轴向冻结试样的冻胀量高于同条件下侧向冻结试样的冻胀量;人工冻结工程中应考虑大气环境温度变化（如昼夜温差）及冷能侧向输入土体内时对冻土温度场的变化的影响。