A novel approach to leveraging social media for rapid flood mapping: a case study of the 2015 South Carolina floods

Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the study case, this paper introduces a novel approach to mapping the flood in near real time by leveraging Twitter data in geospatial processes. Specifically, in this study, we first analyzed the spatiotemporal patterns of flood-related tweets using quantitative methods to better understand how Twitter activity is related to flood phenomena. Then, a kernel-based flood mapping model was developed to map the flooding possibility for the study area based on the water height points derived from tweets and stream gauges. The identified patterns of Twitter activity were used to assign the weights of flood model parameters. The feasibility and accuracy of the model was evaluated by comparing the model output with official inundation maps. Results show that the proposed approach could provide a consistent and comparable estimation of the flood situation in near real time, which is essential for improving the situational awareness during a flooding event to support decision-making.     

基于DEM的洪涝灾害信息提取与损失估算

数字高程模型(DEM)作为洪涝灾害遥感研究的辅助信息源可以提供两类信息,一是地面点的高程和所处地形部位以及与邻域的相互关系等方面的背景数据,二是研究区高程-面积关系、高程-容积关系及面积-容积关系等基本关系信息。利用这些背景数据和基本关系信息,结合洪水期遥感图像的解译,可以获取洪水淹没范围、淹没区积水量、水深、淹没历时以及作物受灾程度等灾情信息。本文阐述了这种研究的原理和方法。     

Deriving Bathymetric Maps of the Shallow Coastal Water of the Gaza Strip Coastal Zone Using Passive Remotely Sensed Imagery

Bathymetry, the mapping of the shape of the surface of the seafloor, is a necessary science for coastal populations that rely heavily on the marine ecosystem for their survival and prosperity. Bathymetric maps are typically derived through a sound or light remote sensing system that is mounted on a boat or airplane that sweeps the designated study area. However, in regions with political constraints or logistical difficulties, reaching the study area and conducting in situ measurements can be difficult or impossible. Thus, using passive satellite imaging can be an alternative approach to traditional hydrographic surveying methods. As bathymetric maps are influenced by the local sea water conditions, the bottom type, and the water constituents, choosing a derivation algorithm for the satellite images which results in a robust and accurate map is very important. In this study, QuickBird imagery was selected to investigate the functionality and the accuracy of two different bathymetric derivation algorithms to obtain robust and reliable maps of the Gaza Strip coastal zone. Despite the high pollution level in the seawater of the investigated area, the findings confirmed the feasibility of obtaining reasonable accurate bathymetric maps.     

闪电河流域水循环和能量平衡遥感综合试验

遥感试验是进行遥感原理的验证、遥感模型与反演方法的发展、遥感产品的真实性检验,推动卫星计划的论证实施及其观测在地球系统科学中应用的重要途径。闪电河流域水循环和能量平衡遥感综合试验以滦河上游闪电河流域为核心试验区,以地球表层系统的水循环过程和能量平衡为研究对象,旨在通过天—空—地一体化的观测手段,针对不同典型地表类型开展全波段主被动协同遥感观测,研究异质地表和山地条件下像元尺度遥感关键参量的观测方案,研究重要水热参量的遥感方法及其同陆面/水文过程模型的结合,支撑国家民用空间基础设施和空间科学先导专项相关卫星计划的论证实施。其中,航空飞行遥感试验搭载L波段主被动一体化微波载荷、双角度热红外相机、四波段多光谱相机和高光谱成像仪进行协同观测,实现了土壤水分、组分温度、植被含水量、叶面积指数等地表参数以及湖泊、水库、湿地等的遥感监测;地面同步观测试验利用车载微波辐射计、地基雷达和光谱仪进行了典型地物如裸土、植被、水体、人工目标等的遥感观测,并按照样区—样方—样点的多尺度嵌套方案进行了地表参数的同步采样,获取了该地区关键地表参数的短时期时空变化特征;同时配合卫星和机载观测,在闪电河流域完成了土壤温湿度、地表水热通量、地表辐射四分量、降水等气象要素的地面观测网络的建设,为验证地表辐射/散射遥感模型,发展、优化和验证水热参量遥感反演算法,研究地表水热参量尺度效应与尺度转化问题提供了重要平台,将促进陆表能量与水分交换过程的理解及其对全球变化的作用和反馈机制的研究。     

黄河防洪遥感应用试验简介

本文详细地介绍了1988年黄河防汛遥感试验的情况,着重介绍了遥感图像、水位数据实时传 输系统的建立及试验的结果,介绍了黄河试验区防洪数据库的建立及试验取得的成果以及利用极 轨气象卫星进行洪水监测的结果。     

时序Sentinel-1A数据支持的长江中下游汛情动态监测

合成孔径雷达（SAR）因其对地观测全天候、全天时优势,成为多云多雨天气限制下洪水动态监测中不可或缺的数据来源之一。由于GEE（Google Earth Engine）云计算平台的兴起和短重访Sentinel-1数据的可获取性,洪水监测与灾害评估目前正面向动态化、广域化快速发展。顾及洪水淹没区土地覆盖变化的复杂性和发生时间的不确定性,基于时序Sentinel-1A卫星数据提出了针对大尺度范围、连续长期的汛情自动检测及动态监测方法。该方法首先,利用图像二值化分割时序SAR数据实现水体时空分布粗制图,逐像素计算时间序列中被识别为水体候选点的频率。然后,利用Sentinel-2光学影像对精度较粗的初期SAR水体提取结果进行校正,得到精细的水体分布图。最后,针对不同频率区间的淹没特点,采用差异化的时序异常检测策略识别淹没范围：对低频覆水区利用欧氏距离检测时序断点,以提取扰动强度大、淹没时间短的洪涝灾害区;对高频覆水区利用标准分数（Z-Score）检测时序断点,以提取季节性水体覆盖区。在GEE平台上利用该方法,实现了2020-05—10长江中下游地区全域洪水淹没范围时空信息的自动、快速、有效监测,揭示了不同区域汛情发展模式的差异性。本文提出的洪水快速监测方法对大尺度下的汛情动态监测、灾害定量评估和快速预警响应具有重要的现实意义。     

运用社交网络分析淹水空间信息之关联性

随着社交网络的普遍发展,大量的讯息透过智能手机发布在个人的微博或其他社交网站。台湾地区的社交网站以脸书(Facebook)的使用量最大,平均每天有近千万笔的讯息量,大多数的讯息多以食衣住行或个人讯息为主,但从本研究所撷取自2010年至2015年的数据中显示,公众在社交网站所分享的信息中具有降雨、淹水或相关灾情的讯息,而这些讯息具有极高比例的正确性。由于社交网站无法提供私人讯息,故本研究将从社交信息中,以地点为单位撷取大量的数据信息再辅以语意关键词萃取出有关可作为淹水预判的讯息数据。为检核资料的可性度,本研究透过历史台风数据FLO-2D仿真重建淹水之空间信息进行检核。从研究比对分析中发现,经萃取后的公众信息其与灾害的关联性及正确性相当显着,故透过社交网站中大量的非结构讯息,透过语意及空间的转换,可萃取转化为防灾信息,对广域的都市治理而言,此一讯息将可作为预判区域淹水或防救灾情报之有效参考。     

SZ-4飞船多模态传感器辐射模态数据处理与质量评价研究

研究了飞船多模态传感器中辐射模态1B产品数据的处理以及生成全球亮温图的方法,对辐射模态数据与SSM/I和AMSR-E星载微波辐射计对应通道进行了星星比对分析,建立了对应通道之间的线性关系。结果表明,飞船辐射模态亮温与SSM/I及AMSR-E的测量值在绝对幅度上相差较大,但却高度的线性相关,这在一定程度上说明了SZ-4辐射模态各通道亮温对地表微波辐射响应的能力。     

Deducing Rice Crop Dynamics and Cultural Types of Bangladesh Using Geospatial Techniques

Rice crop occupies an important aspect of food security and also contributes to global warming via GHGs emission. Characterizing rice crop using spatial technologies holds the key for addressing issues of global warming and food security as different rice ecosystems respond differently to the changed climatic conditions. Remote sensing has become an important tool for assessing seasonal vegetation dynamics at regional and global scale. Bangladesh is one of the major rice growing countries in South Asia. In present study we have used remote sensing data along with GIS and ancillary map inputs in combination to derive seasonal rice maps, rice phenology and rice cultural types of Bangladesh. The SPOT VGT S10 NDVI data spanning Aus, Aman and Boro crop season (1^st May 2008 to 30^th April 2009) were used, first for generating the non-agriculture mask through ISODATA clustering and then to generate seasonal rice maps during second classification. The spectral rice profiles were modelled and phenological parameters were derived. NDVI growth profiles were modelled and crop calendar was derived. To segregate the rice cultural types of Bangladesh into IPCC rice categories, we used elevation, irrigated area, interpolated rainfall maps and flood map through logical modelling in GIS. The results indicated that the remote sensing derived rice area was 9.99 million ha as against the reported area of 11.28 million ha. The wet and dry seasons accounted for 64% and 36 % of the rice area, respectively. The flood prone, drought prone and deep water categories account for 7.5%, 5.56% and 2.03%, respectively. The novelty of current findings lies in the spatial outcome in form of seasonal and rice cultural type maps of Bangladesh which are helpful for variety of applications.     

Development of S-NPP VIIRS global surface type classification map using support vector machines

With the launch of the Joint Polar Satellite System (JPSS)/Suomi National Polar-orbiting Partnership (S-NPP) satellite in October 2011, many of the terrestrial remote sensing products generated from Moderate Resolution Imaging Spectroradiometer (MODIS), such as the global land cover map, have been inherited and expanded into the JPSS/S-NPP mission using the new Visible Infrared Imaging Radiometer Suite (VIIRS) data. In this study, an improved algorithm including the use of a new classifier support vector machines (SVM) classifier was proposed to produce VIIRS surface type maps. In addition to the new classification algorithm, a new post-processing strategy involving the use of new ancillary data to refine the classification output is implemented. As a result, the new global International Geosphere-Biosphere Programme (IGBP) map based on the 2014 VIIRS surface reflectance data was generated with a 78.5 ± 0.6% overall classification accuracy. The new map was compared to a previously delivered VIIRS surface type map, and to the MODIS land cover product. Validation results including the error matrix, overall accuracy, and the user’s and producer’s accuracy suggest the new global surface type map provides similar classification accuracy compared to the old VIIRS surface type map, with higher accuracy achieved in agricultural types.     

Investigating flash floods potential areas using ASCAT and TRMM satellites in the Western Cape Province,South Africa

The aim of the study was to evaluate flash flood potential areas in the Western Cape Province of South Africa, by integrating remote sensing products of high rainfall intensity, antecedent soil moisture and topographic wetness index (TWI). Rainfall has high spatial and temporal variability, thus needs to be quantified at an area in real time from remote sensing techniques unlike from sparsely distributed, point gauge network measurements. Western Cape Province has high spatial variation in topography which results in major differences in received rainfall within areas not far from each other. Although high rainfall was considered as the major cause of flash flood, also other contributing factors such as topography and antecedent soil moisture were considered. Areas of high flash flood potential were found to be associated with high rainfall, antecedent precipitation and TWI. Although TRMM 3B42 was found to have better rainfall intensity accuracy, the product is not available in near real time but rather at a rolling archive of three months; therefore, Multi- sensor precipitation estimate rainfall estimates available in near real time are opted for flash flood events. Advanced Scatterometer (ASCAT) soil moisture observations were found to have a reasonable r value of 0.58 and relatively low MAE of 3.8 when validated with in situ soil moisture measurements. The results of this study underscore the importance of ASCAT and TRMM satellite datasets in mapping areas at risk of flooding.     

Multi-source data fusion and modeling to assess and communicate complex flood dynamics to support decision-making for downstream areas of dams: The 2011 hurricane irene and schoharie creek floods,NY

In light of climate and land use change, stakeholders around the world are interested in assessing historic and likely future flood dynamics and flood extents for decision-making in watersheds with dams as well as limited availability of stream gages and costly technical resources. This research evaluates an assessment and communication approach of combining GIS, hydraulic modeling based on latest remote sensing and topographic imagery by comparing the results to an actual flood event and available stream gages. On August 28th 2011, floods caused by Hurricane Irene swept through a large rural area in New York State, leaving thousands of people homeless, devastating towns and cities. Damage was widespread though the estimated and actual floods inundation and associated return period were still unclear since the flooding was artificially increased by flood water release due to fear of a dam break. This research uses the stream section right below the dam between two stream gages North Blenheim and Breakabeen along Schoharie Creek as a case study site to validate the approach. The data fusion approach uses a GIS, commonly available data sources, the hydraulic model HEC-RAS as well as airborne LiDAR data that were collected two days after the flood event (Aug 30, 2011). The aerial imagery of the airborne survey depicts a low flow event as well as the evidence of the record flood such as debris and other signs of damage to validate the hydrologic simulation results with the available stream gauges. Model results were also compared to the official Federal Emergency Management Agency (FEMA) flood scenarios to determine the actual flood return period of the event. The dynamic of the flood levels was then used to visualize the flood and the actual loss of the Old Blenheim Bridge using Google Sketchup. Integration of multi-source data, cross-validation and visualization provides new ways to utilize pre- and post-event remote sensing imagery and hydrologic models to better understand and communicate the complex spatial-temporal dynamics, return periods and potential/actual consequences to decision-makers and the local population.     

Mapping spatio-temporal flood inundation dynamics at large river basin scale using time-series flow data and MODIS imagery

Flood inundation is crucial to the survival and prosperity of flora and fauna communities in floodplain and wetland ecosystems. This study tried to map flood inundation characteristics in the Murray-Darling Basin, Australia, utilizing hydrological and remotely sensed data. It integrated river flow time series and Moderate Resolution Imaging Spectroradiometer (MODIS) images to map inundation dynamics over the study area on both temporal and spatial dimensions. Flow data were analyzed to derive flow peaks and Annual Exceedance Probabilities (AEPs) using the annual flood series method. The peaks were linked with MODIS images for inundation detection. Ten annual maximum inundation maps were generated for water years 2001–2010, which were then overlaid to derive an inundation frequency map. AEPs were also combined with the annual maximum inundation maps to derive an inundation probability map. The resultant maps revealed spatial and temporal patterns of flood inundation in the basin, which will benefit ecological and environmental studies when considering response of floodplain and wetland ecosystems to flood inundation.     

Resource constraint mapping and management in arid tract of Punjab

The arid tract of Punjab experiences various problems like thick sand cover (sand dunes) in large area, poor retention of water and nutrients in coarse textured soils, soil salinity and/or alkalinity, water logging and poor ground water quality. In the present study multidate remotely sensed data both in the form of aerial photographs and satellite imagery on 1:50,000 scale were interpreted visually to map physiography and soils. The ground water samples from tubewells distributed all over the area were collected and analysed to prepare ground water quality map. The soil and ground water quality maps were integrated to produce a resource constraint map of the area showing physical, chemical and hydrological constraints. The study revealed that alluvial plain suffers from hydrological constraints due to marginal to.poor ground water in 86% of the total area. The sand dunes show both physical and hydrological constraints due to coarse textured (sandy) soils and brackish ground water. The basins having soil salinity and brackish ground water cover 0.10% of the area. Keeping in view the type of constraint, locale specific measures like levelling and stabilisation of sand dunes, reclamation of salt affected and water logged areas followed by plantation of tree species which act as biopumps are suggested. The conjuctive use of surface (canal) and ground water is essential to prevent secondary salinization and sodification. The study demonstrates the potential usefulness of remote sensing technology in mapping natural resources and assess the nature, magnitude and spatial distribution of resource constraints.     

鄱阳湖地区洪涝灾害遥感分析

鄱阳湖是一个吞吐型,季节性的浅淡水湖,高水湖相,低水河相。有“高水是湖,低水似河”,“洪水一片,枯水一线”的独特景观。洪涝灾害发生时,给周边地区造成巨大损失。利用TM遥感卫星图片,以特征最明显的1998年特大洪涝灾害为例,对鄱阳湖地区洪涝灾害症结和防洪策略提出几点见解。     

海冰微波辐射传输模式和实验研究

海冰是影响地球热循环的重要因素。以海冰和海水的微波热辐射为源,并通过位于海面遥感海冰的３层分层介质系统的分析,取得中间介质厚度与所接收到的辐射亮温有如下模式：ＴＢ＝Ａ＋Ｂｅ－ＣＤ。其中Ａ,Ｂ,Ｃ与遥感系统的极化,使用角度和角频率有关,可以通过实际地面的海冰测试试验获得。该模式符合电磁场在有损介质中的传播特性,反映出被动微波遥感所接收到的能量与传播距离的关系。近几年来,根据该模式,使用４个频段微波辐射计在地面进行实测（入射角为０°）,在飞行中使用３个频段,结果空中和地面基本符合。实践证明其模式是正确的可行的。文中给出在辽东湾测得航线上的冰厚度分布和亮度温度与冰厚度的统计曲线。最后指出影响测量并限制对厚度识别的几种因素。     

结合数据融合与特征选择的遥感影像尺度多样目标检测

基于深度神经网络模型的遥感影像地物检测取得了巨大成功,很大程度上得益于大规模数据集的支撑。但是,从现有遥感影像数据集本身来看,不同类别地物的数量分布不一致,同类地物对象以不同尺寸大小呈现,是导致地物样本的尺度不均衡问题的直接因素。对此,本文采用数据集内影像加权融合与地物多尺度特征选择的策略来缓解该问题。首先,将数据集内两张影像的像素值进行加权并得到融合后的影像,从而使不同类别地物样本更加均衡且具有较高的背景多样性;其次,通过选择合适尺度的特征图预测相应尺度的目标类别,且允许同一尺度目标在相邻特征图上进行预测,这样使模型能根据目标尺度进行训练;最后,基于目标中心区域的特征图预测目标边界框,预测的边界框更符合目标本身的尺度。通过在两个遥感数据集上分别进行实验,表明训练的模型在对复杂背景下的类别不均衡目标的识别更加准确,能够适应遥感影像下不同尺度目标的识别。     

中国海洋卫星及应用进展

中国十分重视海洋遥感及其监测技术的发展,初步形成了具有优势互补的海洋遥感观测体系,并发挥了显著的经济和社会效益。其中,海洋一号(HY-1A/B)卫星已经广泛应用于中国海温预报业务系统、冬季海冰业务监测、夏季赤潮和绿潮监测、海岸带动态变化监测、近岸海水水质监测和渔业遥感监测等方面。海洋二号(HY-2A)卫星不仅填补了中国海洋动力环境卫星遥感的空白,也是目前国际上唯一在轨运行的集主被动微波遥感器于一身的综合型海洋动力环境卫星,具备同时获取风场、有效波高、海面高度和海面温度的能力。通过卫星获得的数据提高了中国海洋环境监测与灾害性海况预报的水平,为国民经济建设和国防建设、海洋科学研究、全球变化研究等提供了可靠的遥感数据,同时还在国际对地观测体系中发挥了重要作用,受到国内外用户的高度认可。海洋一号和海洋二号卫星系列为中国建立完善的海洋环境立体监测体系奠定了坚实基础。根据国家发展和"一带一路"建设的实施,在加快建设海洋强国、维护海洋权益和加快发展海洋经济的进程中对海洋遥感的发展也进一步提出了更高的要求和更紧迫的需求。为此,紧紧围绕国家海洋强国战略需求,在《国家民用空间基础设施中长期发展规划(2015年—2025年)》中专门规划了海洋观测卫星系列,服务于中国的海洋资源开发、环境保护、防灾减灾、权益维护、海域使用管理、海岛海岸带调查和极地大洋考察等方面,同时兼顾陆地和大气观测领域的需求。在充分继承已有HY-1A/B、HY-2A、高分三号(GF-3)和中法海洋卫星(CFOSAT)成功研制经验和应用成果的基础上,发展多种光学和微波遥感技术,建设新一代的海洋水色卫星和海洋动力环境卫星,具备卫星组网观测能力;发展海洋监视监测卫星,构建优势互补的海洋卫星综合观测体系。通过空间基础设施的建设,海洋遥感卫星必将在建设海洋强国的进程中发挥出重要作用。     

多波段多极化被动微波遥感地震应用研究进展与前沿方向探索

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