Urban Sustainability Evaluation Based on Remote Sensing and Network Data Support: Progress and Prospect

The sustainable development of the city is the key to the realization of the global sustainable development goals. Urban sustainability evaluation is a measure to the sustainable development of cities, and basis of sustainable urban development. The current evaluation method is based on statistical data which is low spatial resolution, long period and high cost. In recent years, remote sensing data, network data and the multivariate data have been used for the evaluation for the sustainable development of cities, and there have been many related research cases, which provides a new idea and method to carry out the high resolution evaluation of urban sustainable development rapidly, accurately and cheaply. This article reviewed the remote sensing data and network data in the progress of the application in the evaluation to the sustainable development of cities, and discussed the advantages of remote sensing and network big data in the objectivity, accuracy, and timeliness of evaluation compared with traditional data. Based on the sustainable urban development indicators of the United Nations Sustainable Development Goals (SDG), a basic framework for the evaluation of sustainable development of cities with high temporal and spatial resolution of big data such as remote sensing data and network big data was proposed. The introduction of remote sensing and network big data will change the inherent paradigm of sustainability assessment, make high-resolution real-time evaluation possible, further innovate analytical techniques, improve data accuracy, and make clear the alternative relationship with traditional data being the focus and the only way to realize the replacement of traditional data by remote sensing and network big data.     

地质大数据分析的若干工具与应用

大数据科学研究范式是大数据时代的必然结果。在大数据时代,地质学研究正面临着前所未有的挑战与机遇,亟需地质大数据分析的基础支撑。本文介绍若干种有价值的地质大数据分析工具及其应用。知识图谱以其强大的语义处理能力和开放组织能力,为大数据时代信息的知识化组织和智能应用提供了有效工具。它旨在描述真实世界中存在的各种实体或概念及其关系,构成一张巨大的语义网络图,以节点表示实体或概念,边则由属性或关系构成。机器学习与卷积神经网络模型仍然是当前地质大数据研究的热点。演化算法借鉴了自然界中生物进化与自适应过程的思想,是一种基于种群的元启发式最优化算法。它具有无需先验知识、能在全局范围内进行隐并行搜索的优点,可以用来精确地获取大数据中隐含的演化趋势与时空特征。图形社区发现技术将网络划分为若干个内部节点相似社区,为分析和理解网络提供有力的技术支持。随着空间分辨率、时间分辨率和辐射分辨率不断提高,遥感技术已广泛成为地质数据获得的主要技术手段。遥感大数据的数据存取和智能处理是最重要的发展方向。这些地质大数据分析方法已有成功的应用案例,并将广泛用于各种地质研究,如城市土壤污染智能监测、模拟、管控与预警研究,得益于地质大数据研究支撑系统的恰当选择以及地质大数据技术的强力支持,建立了可解释的多源多层城市土壤污染知识图谱,源于多源异构大数据有效融合的主要障碍正在去除。     

遥感地质解译路线在西藏羌塘地区1∶5万区域地质调查中的应用

区域地质遥感调查是近几年来一直采用的一种新的地质调查方法,最大特点是充分利用遥感图像的空间宏观优势,结合地面调查工作进行多层次的影像地质解译,在整体上提高对工作区区域地质特征的全面认识,解决突出的基础地质问题和与成矿有关的关键问题,加快填图速度,提高成图质量。目前,可应用的遥感数据种类多、波段丰富、分辨率高,遥感数据处理的技术和方法越来越先进,为高质量成图和深入解译奠定了基础。本文在总结了工作中遥感数据的采集、处理、解译、应用的基础上,提出了遥感地质解译路线的必要性和方法,进一步规范了遥感地质解译路线的内容和样式,为区域地质调查遥感地质解译路线编制提供参考。     

Application of Remote Sensing in Flood Management with Special Reference to Monsoon Asia: A Review

The conventional means to record hydrological parameters of aflood often fail to record an extreme event. Remote sensingtechnology along with geographic information system (GIS)has become the key tool for flood monitoring in recent years.Development in this field has evolved from optical to radarremote sensing, which has provided all weather capabilitycompared to the optical sensors for the purpose of flood mapping.The central focus in this field revolves around delineation of floodzones and preparation of flood hazard maps for the vulnerable areas.In this exercise flood depth is considered crucial for flood hazardmapping and a digital elevation model (DEM) is considered to bethe most effective means to estimate flood depth from remotelysensed or hydrological data. In a flat terrain accuracy of floodestimation depends primarily on the resolution of the DEM. Riverflooding in the developing countries of monsoon Asia is very acutebecause of their heavy dependence on agriculture but any floodestimation or hazard mapping attempt in this region is handicappedby poor availability of high resolution DEMs. This paper presents areview of application of remote sensing and GIS in flood managementwith particular focus on the developing countries of Asia.     

Wetland conservation: Change and fragmentation in Trinidad’s protected areas

Conservation efforts often neglect the importance of monitoring of protected areas, which is key to adaptively managing dynamic landscapes. In many developing countries, like Trinidad, protected areas are set aside as a result of an agreement with an international conservation organization, often resulting in inadequate planning and monitoring of the protected area. Monitoring of protected areas allows for an examination of the conservation scheme implemented and enables improved conservation decisions to be made. The research presented provides an example of the use of technology in monitoring conservation strategies in two protected wetlands, Caroni and Nariva, in Trinidad. Remote sensing and fragmentation analyses are used to quantify land cover change within these two protected wetlands. Results show that the classification of Caroni immediately identifies a shift towards anthropogenic land cover types, suggesting an increase in human activity within the park. This finding is further supported by the continuous measures used, such as decreases in mean NDVI and greenness values suggesting a decrease in the amount or health of the vegetation. While the classification of Nariva suggests a return to natural land covers, the continuous measures of land cover change indicate the opposite. Land cover change analyses are limited in Trinidad and in the Caribbean in general, partly due to satellite data availability, thus this research presents remote sensing and landscape fragmentation analyses as new tools for monitoring land cover change and conservation effectiveness in Trinidad.     

Analysis and characterization of the synergistic AIRS and MODIS cloud-cleared radiances

The Atmospheric Infrared Sounder (AIRS) and MODerate-Resolution Imaging Spectroradiometer (MODIS) on board NASA Earth Observing System (EOS) Aqua spacecraft measure the upwelling infrared radiance used for numerous remote-sensing- and climate-related applications. AIRS provides high spectral resolution infrared radiances, while MODIS provides collocated high spatial resolution radiances at 16 broad infrared bands. An optimal algorithm for cloud-clearing has been developed for AIRS cloudy soundings at the University of Wisconsin-Madison, where the spatially and spectrally collocated AIRS and MODIS data has been used to analyze the characteristic of this algorithm. An analysis and characterization of the global AIRS cloud-cleared radiances using the bias and the standard deviation between the cloud-cleared and the nearby clear measurements are studied. Scene inhomogeneity for both land- and water-surface types has been estimated to account for the assessed error. Both monthly and seasonal changes of global AIRS/MODIS cloud-clearing performance also have been analyzed.     

遥感技术在地质遗迹调查评价中的应用——以陕西华县莲花寺滑坡为例

针对地质遗迹资源调查依靠野外考察效率低、成本高及容易造成资源遗漏问题,将高空间分辨率卫星遥感技术引入地质灾害遗迹调查评价。基于IKONOS多光谱数据进行自然彩色变换,采用乘积法变换与全色数据进行融合,将遥感数据与DEM数据叠加生成三维遥感影像图,在遥感解译和野外调查的基础上,对莲花寺高速远程滑坡的形态特征、堆积体结构、成灾范围、成因机理及动力学过程进行研究,为陕西华县莲花寺滑坡地质遗迹评价提供直接的依据。研究结果表明:高空间分辨率卫星遥感技术应用于地质灾害遗迹调查评价,相对于传统野外考察等手段具有无比的优势。陕西华县莲花寺高速远程滑坡类型、特征、规模具有国际性对比意义,属国际罕见的滑坡灾害遗迹点,其稀有性对于研究高速远程滑坡这类特殊地质景观具有重要的现实意义,具有极高的科考研究和科普教育价值。     

高分辨率遥感数据处理方法实验研究

近几年高分辨率遥感数据处理与应用研究越来越受到国内外学者的重视,已成为目前遥感应用研究领域的热点和难点之一。首先分析了基于像素的中分辨率卫星数据的遥感数据处理方法,包括:基于统计理论的分类方法和基于光谱信息的非参数理论方法的分类方法。在此基础上,针对高分辨率遥感图像的特点,分析了面向对象的高分辨率遥感数据处理方法。其中,图像分割是最关键的一步,即如何有效地提取出对象特征非常重要。最后,给出了高分辨率遥感数据处理方法相关算法实验,主要进行了几种图像分割算法实验,同时结合植被变化检测,进行了变化检测算法实验。     

被动微波遥感估算雪水当量研究进展与展望

被动微波遥感可以透过云层，全天候地提供地表一定深度的信息。星载被动微波遥感传感器的时间分辨率很高，在冰冻圈动态研究中有着重要的地位。在最近的二三十年中，大量被动微波遥感的应用都是在美国、加拿大、欧洲等地，而我国在这方面的研究相对较少。首先介绍了被动微波遥感数据在监测积雪方面的国内外研究进展，对现存的雪水当量（SWE）估算算法（和模型）的适用性进行讨论。然后，详细讨论了我国西部的青藏高原地区雪水当量的估算，阐明了利用SSM／I数据估算青藏高原地区雪水当量的复杂性，并指出了其复杂性产生的原因，提出了解决问题的方法，为该地区积雪动态的进一步研究提供了理论依据。     

草地植被盖度的多尺度遥感与实地测量方法综述

植被盖度作为一个重要的生态学参数被用在许多气候模型和生态模型中。地表实测和遥感测量是获取植被盖度的两种基本途径。以草地植被盖度的测量为研究对象,综合讨论了目前地表实测和遥感测量常用的方法,分析了它们的优缺点,并对如何提高草地植被盖度的测量精度做出展望。数码相机、高光谱遥感以及多尺度遥感数据的综合使用可能是未来草地植被盖度测量发展的趋势。     

机载InSAR数据自动生成DEM技术及其在内蒙古丰镇地区的应用

合成孔径雷达干涉测量(InSAR)技术是传统的合成孔径雷达技术和射电天文学中的干涉测量技术相结合而发展起来的一项新的遥感技术,这一新技术以其在大范围地表高程测量和地表变形测量方面所具有的独特优势和巨大潜力,而成为对地测量和地学科学研究的一个重要的工具。同星载InSAR相比,机载InSAR在高分辨率区域测图方面具有较大的优势,而且数据采集的时间安排及飞行方位选取方面相对较灵活。而且SAR是一种主动微波遥感技术,具有全天时全天候的工作特征,这一技术也正在成为中国西部困难地区测图的一个非常有效的工具。在详细分析应用机载InSAR数据测量地表高程的基本原理的基础上,提出了机载InSAR自动生成DEM的技术流程,并以内蒙古丰镇地区的机载InSAR数据为基础进行了试验研究,取得了较好的效果,为这一新技术的进一步实际应用奠定了基础。     

Landsat8卫星数据在安徽黄山汤口-寨西地热资源调查中的应用

遥感大数据分析与应用正成为地球信息科学领域重要的研究内容。利用热红外遥感技术进行地热异常信息的提取可以为地热资源勘查评价提供重要的依据。Landsat系列卫星数据拥有长时间的数据积累和较高的空间分辨率,是地表热环境时空序列大数据分析的重要数据。最新一代的Landsat8 卫星热红外数据在延续了较高分辨率的同时,敏感性更强,更加适合于对地表热环境空间分布进行精确分析。本文以安徽黄山汤口-寨西工作区为研究区,分别选用2016年12月9日Landsat8 的热红外遥感数据和2009年12月6日Landsat5 TM 数据,采用大气校正方法进行地表温度的反演和对比分析,通过密度分割分析提取地热异常信息,并综合遥感地质解译信息、气象、地形等数据,对工作区地热资源有利区进行了预测。结果表明：两个时相地表温度反演结果的空间分布基本一致,利用Landsat8 热红外数据的地表温度反演结果可以有效地获取地热异常信息,所圈定的地热异常较为合理,与工作区内主要的断裂构造分布一致,且和物探勘查和钻孔实验结果相对应,可以为地热资源勘查大数据分析提供重要的数据源。     

基于RS、GIS的人口空间分布研究

人口的空间分布问题涉及人口学、经济学、地理学等多个学科,统计型人口数据的空间化是"数字地球"的重要研究内容。阐述了人口地域分布的基本理论,回顾了人口空间分布的研究进展,结合研究实践,提出了在遥感、GIS技术支持下,统计型人口数据空间化的研究思路和技术流程,并对该方法的特点和应用前景做了展望。     

地震活动性热红外异常提取方法研究

热红外遥感以其大视野、高精度和短周期等诸多优势以及对某些强震红外异常的良好反映,成为监测断裂活动性及地震短临前兆的很有前途的观测技术。热红外异常与地震关系的研究也受到国内外地震学者的广泛关注。但由于地表热红外辐射受云层、地形地貌、地物类型和气象等诸多非震因素的影响,因此,如何从复杂的红外遥感数据中提取出与地震活动有关的热异常一直是这项研究中的瓶颈问题。在对若干震例和地震活动区的热红外影像进行长期分析研究的基础上,对这一问题进行了探讨,同时提出了一些实用化的异常识别与提取方法,并对其可行性进行了分析。认为地震红外异常是地表亮温的相对变化,判别地震异常时,至少需利用两年以上的卫星资料,从不同的时空尺度上加以综合对比分析,仅靠震前震后一定时段的卫星资料不足以排除所有非震因素的影响。     

内蒙古朱拉扎嘎金矿ETM+数据提取蚀变异常方法研究

中国西北部大部分地区属于荒漠景观区,自然条件恶劣,常规的地质、物探、化探找矿工作难度大,如何借助遥感技术进行矿产资源勘查,是地质工作者积极探索的方向之一。本次工作选择内蒙古阿拉善盟朱拉扎嘎金矿作为实验区,利用卫星遥感ETM⁺数据进行蚀变异常提取方法研究。从蚀变矿物的波谱特征出发,对Crosta法则进行改造,建立了适合本区的异常提取模型：铁化蚀变异常提取以Band 2、 Band 3 、Band 4 、Band 5/Band 1主成分分析为核心技术;含羟基和碳酸盐化蚀变异常提取以Band 2、Band 4、 Band 5 、Band 7主成分分析为核心技术。运用该模型完成了矿区及其外围蚀变异常提取工作,经过地面光谱验证,检测到铁化、含羟基和碳酸盐化蚀变矿物,认为提取方法合理,提取结果可信。本次研究工作可以为矿区外围找矿提供新方法,为推广和应用遥感技术在荒漠景观区找矿提供参考。     

The application of remote sensing to environmental archaeology

An area in the Fenlands of Eastern England was used to assess the spectral, spatial, and seasonal requirements of airborne multispectral data for identifying wetland archaeological features by detecting crop and soil marks. Ordination of data from a scanner with 11 spectral channels was achieved using the Sheffield method, which calculates the wavebands that produce a 3 band composite image with optimum contrast using band variances and interband correlations. the spatial detail requirements for multispectral data were investigated by applying an edge enhancing filter to single waveband images. the loss of feature clarity with increased levels of spatial smoothing is visually apparent. Seasonal variation in crop mark visibility was quantified by cross tabulating feature visibility in fields known to contain features with time period and sensor type. If remote sensing is to be used for repeated operational archaeological survey then the quality and quantity of information which can be gained from the data must be evaluated. This study attempts to define some of the necessary operational requirements for the use of multispectral data for archaeology.     

基于高分二号卫星数据的煤矿区地质灾害信息提取研究

随着遥感数据获取技术和能力的全面提高,遥感数据呈现出明显的大数据特征。发展适应于遥感大数据的智能分析和信息挖掘技术,成为当前遥感技术研究的前沿。高分二号（GF-2）卫星数据是我国首颗自主研发的亚米级高分辨率卫星数据,具有观测幅宽、重访周期短、高辐射精度、高定位精度等优势,为未来我国地质灾害的长期、动态地监测和研究提供了高精度、稳定可靠的数据源。本文选取安徽谢桥煤矿2015年1月8日的GF-2卫星影像为研究数据,在对煤矿区主要地质灾害遥感地学分析的基础上,采用面向对象的影像分析方法对研究区由采煤活动所诱发的地质灾害信息进行自动提取。结果表明：利用GF-2卫星数据能够有效地识别地质灾害体的位置、范围、形态等空间分布特征;面向对象的自动提取方法对于煤矿区大面积的积水塌陷盆地、小规模的塌陷坑和线性的地裂缝都有很高的提取精度,识别精度达90% 以上;基于逐层剔除的思路构建的提取规则,为GF-2数据在地质灾害调查和大数据分析中的应用提供了很好的技术支持,也为其它地物目标的提取提供了参考,但在特征的选择和阈值的设定上需要具体分析。     

Geophysical and hydrogeologic investigation of groundwater in the Karoo stratigraphic sequence at Sawmills in northern Matabeleland,Zimbabwe: a case history

Geophysical and hydrogeological investigations have been carried out around Sawmills in Zimbabwe, Africa. The investigations are components of a larger investigation to assess the groundwater potential of the Karoo sedimentary basin with regards to supplying water to Bulawayo City. The Sawmills area was selected due to the availability of borehole logs indicating favourable stratigraphy for groundwater availability and due to the high yields from the aquifers measured from these boreholes. Data collected using two geophysical methods are presented here: transient electromagnetic (TEM) and continuous vertical electrical sounding (CVES) data. The data have also been processed using laterally constrained inversion (LCI). Because the CVES provides greater detail in the shallow subsurface, whereas TEM is more effective at depth, a more accurate image of the entire subsurface profile is provided based on using both methods. The results suggest that LCI of CVES and TEM data, in the subsurface at the required depths at Sawmills, is able to provide a substantially more accurate image of the subsurface than either method alone. The hydrogeological interpretation of the geophysical data is valuable for determining the depth to and thickness of the potential aquifer horizon(s) and for identifying the position of potential recharge zones.     

遥感与GIS技术支持下的机场选址与工程地质分析

研究将“3S”技术（RS、GIS、GPS）应用到机场地址勘察中,主要是采用现代化遥感技术,以最新遥感图像LANDSATETM（最高空间分辨率15m）,SPOT图像（2．5m）和QUICKBIRD图像（0．61m）等作为信息源,通过遥感图像数据融合、数字镶嵌和影像增强等数字处理,制作不同类型、不同波段和不同分辨率的正射遥感影像及正射影像地图,为机场工程地质勘察提供最佳图像资料。通过遥感图像增强处理、信息提取及GIS空间分析等,对研究区的地质构造,地质灾害等进行解译。并借助GPS进行野外现场调研,查明研究区地质构造的特征,尤其是隐伏断裂、活动性断裂的分布,以及岩溶漏斗、洼地等水文地质现象,为小哨机场工程地质勘察工作提供了基础资料。     

甘肃华亭地区铀矿化信息遥感提取方法

从分析ETM各波段图像的信息特征入手,在黄土覆盖等环境因素干扰严重的地区,利用遥感技术对其铀矿化的信息进行了提取.在ERDAS软件的支持下,应用图像融合、波段比值、主成分分析、光谱指数等技术方法,对ETM遥感影像数据进行增强处理.其中,图像融合与传统的图像融合略有不同,是在进行图像融合前将原始图像（ETM1～5,7）进行低通滤波处理,使得融合后的图像既保留高分辨率数据的空间信息,又保留低分辨率数据的光谱信息.在对研究区的遥感数据进行增强处理后,选取有利波段组合,圈定了有利铀成矿的远景区.