Urban heat island monitoring and analysis using a non-parametric model: A case study of Indianapolis

A procedure for the monitoring an urban heat island (UHI) was developed and tested over a selected location in the Midwestern United States. Nine counties in central Indiana were selected and their UHI patterns were modeled. Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) images taken in 2005 were used for the research. The images were sorted based on cloud cover over the study area. The resulting 94 day and night images were used for the modeling. The technique of process convolution was then applied to the images in order to characterize the UHIs. This process helped to characterize the LST data into a continuous surface and the UHI data into a series of Gaussian functions. The diurnal temperature profiles and UHI intensity attributes (minimum, maximum and magnitude) of the characterized images were analyzed for variations. Skin temperatures within any given image varied between 2–15 ^°C and 2–8 ^°C for the day and night images, respectively. The magnitude of the UHI varied from 1–5 ^°C and 1–3 ^°C over the daytime and nighttime images, respectively. Three dimensional (3-D) models of the day and night images were generated and visually explored for patterns through animation. A strong and clearly evident UHI was identified extending north of Marion County well into Hamilton County. This information coincides with the development and expansion of northern Marion County during the past few years in contrast to the southern part. To further explore these results, an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 2004 land use land cover (LULC) dataset was analyzed with respect to the characterized UHI. The areas with maximum heat signatures were found to have a strong correlation with impervious surfaces. The entire process of information extraction was automated in order to facilitate the mining of UHI patterns at a global scale. This research has proved to be promising approach for the modeling and mining of UHIs from large amount of remote sensing images. Furthermore, this research also aids in 3-D diachronic analysis.     

基于典型事例推理的路径规划方法研究(英文)

Case-based reasoning is an AI technique in which the previous solutions are stored for future use. People are used to guiding themselves according to those routes that are stored in their memories and have been used by them before. It is just based on people’s preference to familiar routes, which are gained through the study of the cognitive activities. We propose to apply the intelligent method based on the case reasoning to path planning. It is impossible for a case base to store all the solutions to all the shortest paths; therefore, part of them should be stored. However, which routes should be stored and which should not be? How do we adapt the cases that have already been stored and how do we acquire the shortest route based on them? All these issues need to be explained by integrating knowledge of the network on account of case-based reasoning techniques. This paper suggests the case-based reasoning in another point. This means finding some irreplaceable links on the basis of the complete analysis of the problems space, which are called the must_be_passed link between the source and destination. Merely compute the shortest path case from those best exit/entry nodes of the grids to the irreplaceable links, and then add them into the case base storing for future use. This method is based on case-based reasoning technique and completely considers the properties of the problem space. In addition to the use of knowledge of the natural grid in the route network, this method is more efficient than existing algorithms on computing efficiency.     

重金属对日本对虾仔虾存活及代谢酶活力的影响

本研究测定了铜、锌、镉对不同盐度下日本对虾仔虾的24hLC50、48hLC50、96hLC50,三种金属毒性大小依次为Cd2＋＞Cu2＋＞Zn2＋。对次致死浓度下仔虾的碱性磷酸酶（AKP）、酸性磷酸酶（ACP）、谷丙转氨酶（GPT）、及谷草转氨酶（GOT）的活性的测定结果表明：重金属对AKP、GPT、GOT活性有不同程度的抑制作用;且随着浓度的增高,抑制作用越明显。但对ACP活性有激活作用,且随着浓度的增高,激活作用越明显。     

热带西太平洋暖池及其与南方涛动和副热带高压关系

热带西太平洋暖池是全球大洋表面温度最高的区域,也是全球海-气能量交换年总量最大的海域。它的维持和变化不仅对El Nifio的发生、发展起着重要作用,而且对中高纬度大气环流的变化也有重要影响。近年来国内外对热带西太平洋暖池进行了许多实验和研究,取得了一些有意义的结果(王世平,1989; Wyrtki,1989;黄荣辉,1994;董敏,1994;Wajsowicz,1994)。但是这些研究多偏重于暖池对大气环流和东亚气候的影响方面,对暖池本身的主要特征及其变异方面的研究相对较少,而后者却是进一步了解发生在暖池区的海-气相互作用的过程,研究暖池在全球气候变化中的作用所不可缺少的。本文在分析1951-1990年间的SST资料和137°E,155°E,165°E断面观测结果的基础上,结合有关研究成果(符淙斌,1990),对暖池的形态、高温中心和热含量这三个主要特征及其变异特点进行了研究,并初步找出了暖池表面面积与南方涛动指数和副热带高压面积指数间的关系。     

Bias-corrected rational polynomial coefficients for high accuracy geo-positioning of QuickBird stereo imagery

The rational function model (RFM) is widely used as an alternative to physical sensor models for 3D ground point determination with high-resolution satellite imagery (HRSI). However, owing to the sensor orientation bias inherent in the vendor-provided rational polynomial coefficients (RPCs), the geo-positioning accuracy obtained from these RPCs is limited. In this paper, the performances of two schemes for orientation bias correction (i.e., RPCs modification and RPCs regeneration) is presented based on one separate-orbit QuickBird stereo image pair in Shanghai, and four cases for bias correction, including shift bias correction, shift and drift bias correction, affine model bias correction and second-order polynomial bias correction, are examined. A 2-step least squares adjustment method is adopted for correction parameter estimation with a comparison with the RPC bundle adjustment method. The experiment results demonstrate that in general the accuracy of the 2-step least squares adjustment method is almost identical to that of the RPC bundle adjustment method. With the shift bias correction method and minimal 1 ground control point (GCP), the modified RPCs improve the accuracy from the original 23 m to 3 m in planimetry and 17 m to 4 m in height. With the shift and drift bias correction method, the regenerated RPCs achieve a further improved positioning accuracy of 0.6 m in planimetry and 1 m in height with minimal 2 well-distributed GCPs. The affine model bias correction yields a geo-positioning accuracy of better than 0.5 m in planimetry and 1 m in height with 3 well-positioned GCPs. Further tests with the second-order polynomial bias correction model indicate the existence of potential high-order error signals in the vendor-provided RPCs, and on condition that an adequate redundancy in GCP number is available, an accuracy of 0.4 m in planimetry and 0.8 m in height is attainable.     

Human-environment interactions in agricultural land use in a South China's wetland region: A study on the Zhujiang Delta in the Holocene

The formation and evolution of agricultural land uses in the Zhujiang Delta of South China are examined in the light of the dynamics of people and the environment and their interplay. The origin and propagation of agriculture are found to have a close relationship with the climate and sea level changes in the Holocene era. The development of rice cultivation, horticulture, and dike-pond system exemplifies human-environment interactions in a specified geographical and social context, which are manifested by the impact of environmental changes and population growth on agricultural innovations. The technologies of dike building and land reclamation, which represent local farmers effort to build a new and harmonious relationship with the changed environment, were critical to the agricultural success and sustainability. Imprudent use of a new agricultural technology could damage the environment, as evidenced by a frequent flooding that followed inappropriate dike building and premature reclamation. Diverse agricultural land uses are as a result of the adaptation of agricultural technology innovations to the environmental conditions.     

福建省物探化探遥感成果回顾（续）

福建物探、化探工作起步于20世纪50年代。近半个世纪以来,福建省地质工作者利用物探、化探、遥感等技术在区域地质,深部地质,矿产地质,水文地质、工程地质,环境地质,医学地质,农业地质等领域取得了丰硕成果,但还存在一定差距。为进一步提高福建省物探、化探、遥感等技术水平和扩大应用领域,对今后工作提出几点建议和对策。     

Multidimensional social trust and regional entrepreneurial activities: Based on data from the China Family Panel Studies (CFPS)北大核心CSCD

社会信任作为非正式制度环境的核心构成要素对区域创业活动有复杂而重要的影响。由于社会距离、交往对象的不同,社会信任在表现形式和作用机制方面差异明显,但现有研究鲜有关注社会信任不同维度对区域创业的影响。论文从普遍信任、亲缘信任、制度信任3个维度构建社会信任框架,利用中国家庭跟踪调查(CFPS)2012、2014、2016、2018年4期面板数据和企业工商注册信息微观数据进行实证分析,研究发现：(1)在全国尺度,亲缘信任显著提高了区域创业活跃度,而普遍信任、制度信任对区域创业活跃度的作用不明显。(2)交互效应结果显示,普遍信任、亲缘信任与经济发展之间存在替代效应;普遍信任与政府干预互为补充,政府干预越弱,普遍信任对区域创业的激励作用越强;而制度信任与政府干预表现为相互促进的互动关系,共同促进了区域创业活跃度。(3)分样本异质性检验表明,东部地区创业活跃度对社会信任的依赖度较弱;中西部地区创业活跃度受到普遍信任、亲缘信任的积极影响;政商关系良好城市的创业活跃度受到制度信任的促进作用,创业政策红利得到有效释放;在政商关系普通城市,普遍信任能够显著促进创业,激发创业活力。研究证实了不同维度社会信任...     

Use of earth observation data for applications in public health

The Earth Observation (EO) data with their advantages in spectral, spatial and temporal resolutions have demonstrated their great value in providing information about many of the components that comprise environmental systems and ecosystems for decades that are crucial to the understating of public health issues. This literature review shows that in conjunction with in situ data collection, EO data have been used to observe, monitor, measure and model many environmental variables that are associated with disease vectors. Furthermore, satellite derived aerosol optical depth has been increasingly employed to estimate ground-level PM_2.5 concentrations, which have been found to associate with various health outcomes such as cardiovascular and respiratory diseases. It is suggested that Landsat-like imagery data may provide important data sources to analyse and understand contagious and infectious diseases at the local and regional scales, which are tied to urbanisation and associated impacts on the environment. There is also a great need of data products from coarse resolution imagery, such as those from moderate resolution imaging spectrometer, multiangle imaging spectroradiometer and geostationary operational environmental satellite , to model and characterise infectious diseases at the continental and global scales. The infectious diseases at greater geographical scales have become unprecedentedly significant as global climate change and the process of globalisation intensify. The relationship between infectious diseases and environmental characteristic have been explored by using statistical, geostatistical and physical models, with recent emphasis on the use of machine-learning techniques such as artificial neural networks. Lastly, we suggest that the planned HyspIRI mission is crucial for observing, measuring and modelling environmental variables impacting various diseases as it will improve both spectral resolution and revisit time, thus contributing to better prediction of occurrence of infectious diseases, target intervention and tracking of epidemic events.