城市局部气候分区对地表温度的影响 ——以大连市区为例

以大连市区建筑数据、SPOT 5和Landsat 8遥感数据为基础,运用局部气候带分类、地表温度反演方法,研究大连市局部气候带分区类型和特征,进而分析不同局部气候带对城市地表温度的影响。研究结果表明：①大连市建筑类型高度主要为低层建筑、多层建筑和中高层建筑,建筑密度为中密度和较高密度,甘井子区分布大量森林绿地,中山区具有丰富的公园绿地;②地表温度整体偏高,空间上呈现东高西低的趋势,其中半数以上地区地表温度达到28℃~31℃,并且有超过1%的地区地表温度大于38℃,该区域出现极端高温;③同一建筑高度上,密度越大的建筑区域,地表温度越高;同一建筑密度,多层建筑高度覆盖区地表温度较高。森林绿地地表温度最低,公园绿地和社区绿地地表温度几乎一致,附属绿地地表温度最高。     

城市区域几何效应的辐射校正及其温度遥感反演

开展适用于城市地区热红外遥感图像几何效应的辐射校正物理模型研究,对提升城区下垫面温度反演精度具有重要作用。本文利用天空视域系数SVF（Sky View Factor,V）量化城区下垫面几何特征,并考虑几何特征对地物目标辐射传输的影响机理。将遥感传感器入瞳处的辐射亮度分解为地物目标发射辐射、地物目标反射辐射以及大气上行路径辐射3部分,并分析了各部分辐射在“城区—大气”界面的辐射传输过程,构建适用于城市下垫面的热辐射传输UTRT（Urban Thermal Radiation Transfer）模型,可应用于城区热红外遥感图像的几何效应辐射校正。基于Landsat 8 TIRS（Thermal Infrared Sensor）数据,将UTRT模型应用于北京市典型城区地表温度的反演,并对UTRT模型和不考虑下垫面几何特征反演结果进行对比分析,结果显示：（1）研究区内UTRT模型反演结果数值上整体低于不考虑下垫面几何特征的反演结果,差值范围为0—1.57 K,均值为0.44 K;（2）通过对不同地表覆被类型的分析对比,模型结果差值较大的区域为建筑和裸地,其空间分布明显受V值的影响,在一定范围内,V值越大反演结果数值越低;（3）对UTRT模型天空视域系数和环境温度两个参数进行敏感性分析,在地表发射率较小的场景中V参数敏感性较强,由于环境温度与目标地物温度较为接近,其参数的敏感性较低。结论为：UTRT模型可为城市下垫面遥感图像几何效应的辐射校正提供解决方案,对比不考虑下垫面几何特征的模型,前者可以更好地应用于城区地表温度遥感反演。该研究对推进城市高分辨率热红外定量遥感具有发展潜力和应用前景。     

基于辐射传导方程法的地表温度反演

随着城市的不断扩张导致城区存储较多的能量,研究地表温度反演变得越来越重要。本研究以典型的沿海城市烟台市牟平区作为温度反演的研究对象,运用辐射传导方程法,对Landsat 7ETM+数据,Landsat8TIRS遥感影像进行地表温度反演。结果表明2002年6月牟平区最高温度与最低温度差异为30℃,平均温度为33.5℃;2013年8月牟平区最高温度与最低温度差异为21℃,平均温度为30.2℃;高温区都集中在市区。研究结果对烟台市的城市规划和未来发展有一定的借鉴作用。     

采用ASTER影像进行地表温度反演与分析

基于ASTER遥感影像数据,运用劈窗算法对重庆市主城区进行了地表温度反演,得出重庆市主城区地表温度空间分布规律,结果表明重庆市主城区地表温度明显比郊区地表温度高,城区与近效温差达6.34℃,城市热岛效应明显。     

利用单窗算法反演Landsat 8 TIRS数据地表温度

以Landsat 8为数据源,并结合地表发射率、大气透过率等参数遥感估算方法,提出了针对TIRS 10数据的单窗算法TIRS10_SC,并开展了研究区的地表温度反演3种单窗算法的对比研究。结果表明,TIRS10_SC算法紧密结合Landsat8 TIRS传感器的特性,通过遥感估算城区下垫面的地表发射率、大气透过率等特征,可以较为准确地估算出地表不同覆被类型的温度;裸土与水泥下垫面等相对均质的下垫面的温度反演效果稍好,TIRS10_SC算法和Q_SC算法其平均误差为0.60℃,JM_SC算法其平均误差为1.01℃;对于植被下垫面,TIRS10_SC算法和Q_SC算法其平均误差为1.48℃,JM_SC算法其平均误差为1.26℃,为了提升城区植被下垫面温度反演精度,应该进一步准确地量化其发射率特性。     

中国MODIS地表温度产品验证

分析了MODIS地表温度产品的误差来源，重点研究利用高分辨率遥感影像数据ASTER同步反演的验证方法。以2003年8月1日太 湖地区为例，用ASTER数据的反演结果与同时相的MODIS地表温度产品进行比较，分别在太湖水面、无锡城区及城郊农田3个典型地表 状况下选取感兴趣区域做线性拟合，取得了较好的结果，拟合的R2值可达0.966 6。     

基于劈窗算法从ASTER遥感数据反演地表温度

应用卫星热红外遥感影像反演地表温度对于研究城市生态环境、气象过程具有重要意义,ASTER 遥感数据为此提供了有效的信息源。针对从 ASTER 数据中反演地表温度(LST)的需要,首先利用 MODIS 数据反演大气水汽含量,并模拟出大气水汽含量与大气透过率的关系,求得大气透过率,然后通过决策树分类结果和地物光谱特征计算出地表反射率,最后采用劈窗算法反演出地表温度。通过某市2个季节的试验表明该方法具有较高的精度,能够有效应用于城市热环境分析,为城市物理环境综合分析评价提供支持。     

基于Landsat TM数据的北京城市热岛研究

利用Landsat TM热红外波段数据，根据辐射传输方程反演得到北京地区地表温度，讨论了北京城市热岛现象及其与土地覆盖类型和植被指数的关系。结果显示，北京城区地表温度明显比郊区地表温度高。通过地表温度对比分析发现，城区平均地表温度比近郊区和远郊区地表温度分别高出4．5℃和9℃，城市热岛效应明显。城区不同地表覆盖类型的地表温度也有显著差异，城市地表温度与NDVI具有明显的负相关关系，城市地表植被覆盖度低是城市热岛出现的主要原因。     

天山中段近地表气温的遥感反演及时空分布特征

为天山中段近地表气温研究提供可靠、空间分辨率较高的数据源,该文以气象站气温数据、再分析气温数据以及遥感数据为主要数据源,采用多元回归模型反演了近地表气温并进行精度验证。在此基础上,揭示天山中段近地表气温时空分布特征及其变化趋势。结果表明:①反演精度与实测值相近,且精度较好。②天山中段近地表气温呈四周高,中部低,平原区高,丘陵、山区低的空间分布格局;年际变化呈先升高后降低,年内呈周期性单峰变化的趋势。③2001—2016年天山中段近地表气温以不显著增加为主,占显著降低的区域甚少。研究结果证明用多元回归模型可以提高近地表气温的遥感反演精度,为今后近地表气温研究提供空间分辨率较高的数据及其获取方法。     

顾及地面传感器观测数据的遥感影像地面温度反演算法

针对遥感数据对地面温度反演精度低及地面温度传感器数据为点数据的特点,构建了融合地面温度传感器实时监测数据与遥感反演地面温度数据的协同反演方法体系。以HJ-1遥感影像的地表温度反演为例,提出了四种融合策略,通过分析比较得到四种结果。四种方案的融合结果的均方根误差分别从0.884 8℃下降为0.656 2℃、0.428 8℃、0.453 5℃、0.426 1℃;相关系数分别从初始的0.619 5提高到0.634 3、0.862 9、0.850 7、0.864 8。其中,方案4在增加地面点间隔的情况下,均方根误差能够保持在0.45℃以下,相关系数在0.85以上,并采用不同影像和实测数据进行相对验证。最后探讨了不同方案的特点,得出最优的融合方案,以达到对地表温度进行实时动态监测的目的。     

Evolution of the Earth's principal axes and moments of inertia: the canonical form of solution

 Harmonic coefficients of the 2nd degree are separated into the invariant quantitative (the 2nd-degree variance) and the qualitative (the standardized harmonic coefficients) characteristics of the behavior of the potential V ₂(t). On this basis the evolution of the Earth's dynamical figure is described as a solution of the time-dependent eigenvalues–eigenvectors problem in the canonical form. Such a canonical quadratic form is defined only by temporal variations of the harmonic coefficients and always remains finite, even within an infinite time interval. An additional condition for the correction or the determination of temporal variations of the 2nd degree is obtained. Temporal variations of the fully normalized sectorial harmonic coefficients are estimated in addition to ˙Cˉ ₂₀, ˙Cˉ ₂₁, and ˙Sˉ ₂₁ of the EGM96 gravity model. In addition, a non-linear hyperbolic model for Cˉ _2m (t), Sˉ _2m (t) is constructed. The trigonometric form of the hyperbolic model leads to the consideration of the potential V ₂(ψ) instead of V ₂(t) within the closed interval −π/2≤ψ≤+π/2. Thus, it is possible to evaluate the global trend of V ₂(t), the Earth's principal axes and the differences of the moments of inertia within the whole infinite time interval. Received: 25 September 1998 / Accepted: 28 June 2000     

Analysis of inversion errors of ionospheric radio occultation

The retrieved electron density profile of ionospheric radio occultation (RO) simulation data can be compared with the background model value during the simulation and the inversion error can be obtained exactly. This paper studies the inversion error of ionospheric RO through simulation. The sources of the inversion errors are analyzed. The impacts of measurement errors, such as the errors in phase measurements and satellite orbits, are very small and can be neglected. The approximation of straight-line propagation introduces errors at the height of the F1 layer under solar maximum condition. The spherical symmetry approximation of the electron density distribution is found to be the main source of the inversion error. The statistical results reveal some characteristics of the inversion errors. (1) The relative error increases with enhanced solar activity. (2) It is larger in winter than in equinox season, and it is smallest in summer. (3) For all seasons, it is smaller at middle latitude than at other latitudes. (4) For all seasons and geomagnetic latitudes, it is smaller at daytime than at other times. The NmF2 of the ROs from COSMIC are compared with the measurements of ionosondes, and the relative differences show the same dependencies on season, geomagnetic latitude and local time, as the relative errors of the simulated ionospheric ROs.

Prioritisation of sub-watersheds based on earth observation data of agricultural dominated northern river basin of India

The Upper Tons River Basin of North India has been selected for prioritisation of sub-watersheds (SW) based on morphometric parameters with respect to groundwater derived from topographic sheets and CARTOSAT data. There are 10 SW have been delineated in the region, high stream frequency (F_s) values of SW (1–5) and SW-9 indicated the occurrence of steep slopes, less permeable rocks, greater runoff, less infiltration possibility. Further, these regions have been predicted as poor groundwater potentialities. SW-2 has been identified as poorest groundwater potential zone, whereas SW-4 and SW (6–8) regions possess good permeable bed rocks. The Drainage density (D_d) map demonstrated that the middle south-west region possesses higher D_d whereas northeastern regions contain lower D_d. Further, the areal parameters indicate elongated shape of the basin, hilly region has moderate to steeper ground slope. The outcomes of work have potential to manage groundwater and to ameliorate the flash flood and droughts.     

接收机天线相位中心改正对IGS/IGMAS站的影响

针对天线相位中心改正影响GPS数据解算以及处理软件不能识别接收机天线类型的问题,该文提出了利用近似型号的天线进行数据处理的方法。首先利用IGS站精确确定天线相位中心改正对数据解算造成的影响,再利用IGMAS站验证方法的可靠性。该文选取部分IGS、IGMAS站的数据,利用GAMIT软件进行试验并分析。结果表明,当不使用天线相位改正模型时,增大了单天基线解的NRM_S值,并增加15.5%的基线误差,对精密定位能带来平均2cm的影响;当将处理软件不识别的天线换成近似能识别的天线时,基线解效果要比不使用天线改正效果好,水平和垂向的定位精度均在3.9mm左右,比使用原装能识别天线的定位精度稍差。该方法既保证了精度,也较为简单快捷。     

Fractal characterization of the spatial distribution of geological point processes

Geological point processes can be used to model point patterns occurring frequently in a wide variety of geoscience fields, including the study of mineral deposits, oil producing wells, earthquakes, and landslides. Characterization of the spatial distribution of GPP has implications for understanding the properties of the underlying geological processes and events. Three examples of GPP dealing with (1) metallic mineral deposits, (2) oil producing wells, and (3) aftershocks of the Wenchuan earthquake (on 12 May 2008, magnitude 8.0) are presented to illustrate that (1) the spatial distribution of geological point processes generally shows clustering implying rejection of the Poisson model because L(r) > L_Pois(r); (2) the clustering statistics of the underlying geological processes are fractal; and (3) the size distribution of geological point processes is scale invariant. These results indicate existence of a fundamental law concerning the fractal nature of the point distributions generated by geological point processes.     

Accuracy of GPS-derived relative positions as a function of interstation distance and observing-session duration

 Ten days of GPS data from 1998 were processed to determine how the accuracy of a derived three-dimensional relative position vector between GPS antennas depends on the chord distance (denoted L) between these antennas and on the duration of the GPS observing session (denoted T). It was found that the dependence of accuracy on L is negligibly small when (a) using the `final' GPS satellite orbits disseminated by the International GPS Service, (b) fixing integer ambiguities, (c) estimating appropriate neutral-atmosphere-delay parameters, (d) 26 km ≤ L ≤ 300 km, and (e) 4 h ≤T ≤ 24 h. Under these same conditions, the standard error for the relative position in the north–south dimension (denoted S _n and expressed in mm) is adequately approximated by the equation S _n =k _n /T ^0.5 with k _n =9.5 ± 2.1 mm · h^0.5 and T expressed in hours. Similarly, the standard errors for the relative position in the east–west and in the up-down dimensions are adequately approximated by the equations S _e =k _e /T ^0.5 and S _u =k _u /T ^0.5, respectively, with k _e =9.9 ± 3.1 mm · h^0.5 and k _u =36.5 ± 9.1 mm · h^0.5. Received: 5 February 2001 / Accepted: 14 May 2001     

Impact of land-cover layout on particulate matter 2.5 in urban areas of China

ABSTRACT

Urbanization in China is closely connected with ambient particulate matter 2.5 (PM_2.5). However, the potential for altering PM_2.5 through the urban landscape characteristics is uncertain. In this study, we analyzed the urban PM_2.5 pollution situation for 2014–2016 and investigated the impact of landscape factors on urban PM_2.5 in China at the city level. All the prefecture-level cities were stratified by urban population size into small (<500,000), medium (500,000–1,000,000), and large (>1,000,000), and the other second-level administrative cities were assigned as ‘other’ cities. The multivariate regression model including both urban landscape factors and social-economic variables explained 70.0%, 32.8%, 19.2%, and 12.4% of the arithmetic mean PM_2.5 concentration (AMC-PM_2.5) for the other, small, medium, and large cities, respectively. With regard to the configuration of land cover, agricultural activity is a major contributor of PM_2.5 pollution, for which the explanatory power ranged from 7.6% (for the large cities) to 64% (for the other cities). In addition, grassland aggregation also has a limited but negative effect on urban PM_2.5 pollution, despite the negligible effect on dry deposition. Overall, these findings likely reflect the interaction between urban air quality and urbanization, and will have implications for air quality control strategies.     

Simulation of peri-urban growth dynamics using weights of evidence approach

The study aims to simulate the peri-urban growth dynamics in a growing region of India using Weights of Evidence (WOE) based cellular automata model. The growth process was expressed as a function of four causative variables corresponding to which seven data layers were generated in a Geographic Information Systems environment. The model was calibrated for the period 2000–2005 using Kappa indices and fuzzy set theory based two way comparison method. The Kappa value was 0.7, while the value of K_location and K_histo were 0.81 and 0.93, respectively. The fuzzy similarity values increased for small to large neighbourhood sizes which showed that the model was able to simulate the contiguous and dense growth. However, for dispersed and isolated growth the model showed less accuracy. The model was validated for period 2005–2010 and revealed a Kappa value of 0.88, while value of K_location and K_histo were 0.91 and 0.96, respectively.     

印度洋及太平洋海表盐度时空特征分析

目前对印度洋和太平洋海表盐度变化的大尺度分析相对较少，Aquarius作为海表盐度的观测卫星，其观测数据在分析海表盐度时空特征时有着不可替代的优势。为了降低观测资料本身的误差对分析结果的影响，文本首先利用质量—距离双重加权方法生成新的高精度Aquarius网格化月均海表盐度场，并基于此盐度场和Argo资料对2011-09至2015-05印度洋及太平洋海表盐度的时空特征进行了分析。结果显示，盐度分布和纬度有明显的相关性，整体呈现低、高纬偏低，中纬偏高的态势，纬度极值随时间并没有很明显的变化，然而时间最大值随纬度的变化曲线呈现明显的以赤道为中心的近似中心对称分布特征。分析显示印度洋和太平洋盐度分布主要包括4个高盐区和4个低盐区，但每个盐度区的变化趋势与幅度不尽相同。     

Estimating the parameters of forest inventory using machine learning and the reduction of remote sensing features

Locally computed statistics of image texture and a case-based reasoning (CBR) system were evaluated for mapping of forest attributes. Cluster analysis was preferred to regression models, as a pre-selection method of features. The best stand-based accuracy using satellite sensor images was 74.64 m⁻³ ha⁻¹ (36%) RMSE for stand volume, 1.98 m⁻³ ha⁻¹ a⁻¹ (49%) for annual increase in stand volume, where κ = 0.23 for stand growth classes and κ = 0.41 for dominant tree species in stands. The top pixel-based accuracy using orthophotos was 76.54 m⁻³ ha⁻¹ (41%) RMSE for stand volume, 1.87 m⁻³ ha⁻¹ a⁻¹ (44%) for annual increase in stand volume, where κ = 0.24 for stand growth classes and κ = 0.38 for dominant tree species in stands. Mean saturation in 30 m radius was the most useful feature when orthophotos were used, and standard deviation of Landsat ETM 6.2 values in 80 m radius was the best when satellite sensor images were used. The most valuable feature components (radii, channels and local statistics) for orthophotos were: 30 m kernel radius, lightness and the mean of pixel values; for satellite sensor images: 80 m kernel radius, near-infrared channel (ETM 4) and the mean of pixel values. Locally computed statistics.