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1.
The information content of flood extent maps can be increased considerably by including information on the uncertainty of the flood area delineation. This additional information can be of benefit in flood forecasting and monitoring. Furthermore, flood probability maps can be converted to binary maps showing flooded and non-flooded areas by applying a threshold probability value pF = 0.5. In this study, a probabilistic change detection approach for flood mapping based on synthetic aperture radar (SAR) time series is proposed. For this purpose, conditional probability density functions (PDFs) for land and open water surfaces were estimated from ENVISAT ASAR Wide Swath (WS) time series containing >600 images using a reference mask of permanent water bodies. A pixel-wise harmonic model was used to account for seasonality in backscatter from land areas caused by soil moisture and vegetation dynamics. The approach was evaluated for a large-scale flood event along the River Severn, United Kingdom. The retrieved flood probability maps were compared to a reference flood mask derived from high-resolution aerial imagery by means of reliability diagrams. The obtained performance measures indicate both high reliability and confidence although there was a slight under-estimation of the flood extent, which may in part be attributed to topographically induced radar shadows along the edges of the floodplain. Furthermore, the results highlight the importance of local incidence angle for the separability between flooded and non-flooded areas as specular reflection properties of open water surfaces increase with a more oblique viewing geometry. 相似文献
2.
洪涝灾害会造成农田淹没、居民住宅损毁等危害,因此对洪水淹没范围进行实时、准确监测可有效进行灾后治理。利用光学传感器提取洪水淹没范围时,不能穿透云层,因此无法获取有效地面信息;而SAR使用微波波段,不受天气影响,在夜间也能成像。因此,SAR成为洪水灾害灾情评估的有力工具。本文利用2021年9月23日、10月5日、10月17日3景SAR雷达影像Sentinel-1A数据,计算相干性系数,设置阈值为0.2,提取水体淹没范围,分析其扩张范围及变化趋势,并根据生成的形变图分析水位抬升变化,验证了基于雷达数据的相干系数阈值提取方法监测洪水淹没范围,以及采用InSAR技术准确提取水体边界与分析水位上升趋势的可行性。 相似文献
3.
Satellite remote sensing is an effective method for extracting water bodies on a large scale. Radar imagery, such as synthetic aperture radar (SAR) imagery, can penetrate clouds and provide opportunities for water body identification when in situ observations are difficult to obtain because of severe weather conditions. However, when using SAR images in urban areas to extract water bodies, the radar’s double-bounce effect results in complicated backscatter patterns of water near urban features such as buildings due to the side-looking properties of SAR sensors and the vertical urban structures. Therefore, the objective of this study is to propose a reliable urban water extraction framework for SAR images that integrates urban surface morphological features for controlling radar’s multiple bounces. Statistical (logistic regression) and machine-learning (random forest) models were used to explore how radar’s double-bounce effect influences the prediction performance of urban water extraction. Our findings indicate that when extracting urban water bodies, urban water’s backscatter values could be significantly interfered by the neighboring building density above a threshold height that contributes to radar’s multiple bounces. Without model calibration, our framework incorporating urban surface morphology demonstrates high prediction ability with an Area Under the Curve (AUC) of 0.914 and with 97.0% of urban water cells correctly identified by testing in another city sharing similar urban forms. In summary, our study provides a better understanding of the role of the urban surface morphology in the double-bounce effect in SAR images, specifically for differentiating urban water and land, thereby improving the accuracy of urban water extraction and enhancing the feasibility of further applications of SAR imagery under complex urban landscapes. 相似文献
4.
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。 相似文献
5.
《International Journal of Digital Earth》2013,6(4):309-326
Abstract The paper discusses the potential of very high resolution (VHR) satellite imagery for post-earthquake damage assessment in comparison with the role of aerial photographs. Post-disaster optical and radar satellite data are assessed for their ability to resolve collapsed buildings, destroyed transportation infrastructure, and specific land cover changes. Optical VHR imagery has shown to be effective in quantifying building stock and for assessing damage at the building level. High-resolution synthetic aperture radar (SAR) imagery requires further research to identify optimum information extraction procedures for rapid assessment of affected buildings. Based on current technical and operational capabilities increasing efforts should be devoted to the generation of spatial datasets for disaster preparedness. 相似文献
6.
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. 相似文献
7.
Flood mapping from Synthetic Aperture Radar (SAR) data has attracted considerable attention in recent years. Most available algorithms typically focus on single-image techniques which do not take into account the backscatter signature of a land surface under non-flooded conditions. In this study, harmonic analysis of a multi-temporal time series of >500 ENVISAT Advanced SAR (ASAR) scenes with a spatial resolution of 150 m was used to characterise the seasonality in backscatter under non-flooded conditions. Pixels which were inundated during a large-scale flood event during the summer 2007 floods of the River Severn (United Kingdom) showed strong deviations from normal seasonal behaviour as inferred from the harmonic model. The residuals were classified by means of an automatic threshold optimisation algorithm after masking out areas which are unlikely to be flooded using a topography-derived index. The results were validated against a reference dataset derived from high-resolution airborne imagery. For the water class, accuracies > 80% were found for non-urban land uses. A slight underestimation of the reference flood extent can be seen, mostly due to the lower spatial resolution of the ASAR imagery. Finally, an outlook for the proposed algorithm is given in the light of the Sentinel-1 mission. 相似文献
8.
It is viable to differentiate the deep and shallow flood inundated regions through a new flood feature extraction techniques named as ‘Digital Elevation Model (DEM) and Synthetic Aperture Radar (SAR) image based flood feature extraction model’. The proposed model has been built mainly on the top of DEM of the disaster region without adopting standard multi-layer GIS techniques. To meet the time related factors of flood early warning system the image clustering operations has been automated at three different levels which bifurcates the input datasets and extracts the much required end results such as deep flooded regions, shallow flood inundated regions and non-flooded regions. The model has been tested with SAR flood images of known geographical region as well as remote geographical region. The proposed model can be automated against the input SAR sensor image and corresponding DEM of the respective SAR scene of any part of the world. 相似文献
9.
River boundaries extraction from SAR imagery is valuable for flood monitoring and damage assessment. Several rivers, parts of which include dammed lakes caused by landslides and rock avalanches triggered by the 2008 Wenchuan Earthquake, were taken as a case study for robust extraction. In this paper, a novel state-of-the-art approach for automated river boundaries extraction using high resolution synthetic aperture radar (SAR) intensity imagery is presented. The key of our approach lies in the combined usage of local connectivity feature of the river and a region-based active contours model (ACM) in a variational level set framework to differentiate between river and the background. First, sub-patched intensity thresholding segmentation is applied to SAR imagery. Pixels with intensities below the threshold are selected as potential river pixels while the others are potential background pixels. Second, potential river pixels are divided into several connected regions, considering that the river is a big connected region, only relatively bigger regions with similar contrast value are retained as the regions of interest (ROI) while others are noise due to pixel-level decision approach in the first step or shadows due to mountains terrain. Third, the ROI and their contours are regarded as local region and the initial contours to refine the river boundaries, which are used to reduce the scene complexity of ACM and its sensitivity to initial situation, respectively. A novel ACM driven by local image fitting (LIF) energy is presented and used for river boundaries extraction for the first time, which is not only robust against inhomogeneity widely spread in SAR imagery but also can work with efficiency without the need of re-initialization during iteration compared to traditional ACM. The proposed approach was tested on numerous high resolution airborne SAR images containing connected rivers or dammed lakes obtained by Chinese domestic radar system after Wenchuan Earthquake. For the overall dataset, the average commission error, omission error and root mean squared error were 6.5%, 3.3%, and 0.51, respectively. The average computational time for 4000 by 4000 image size was 21 min using a PC-based MATLAB platform. Our experimental results demonstrate that the proposed approach is robust and effective. 相似文献
10.
将卫星雷达遥感应用于滑坡灾害的探测与监测，不仅可以从空间尺度上大范围捕捉到滑坡信号，而且可以从时间尺度上以较长周期追踪滑坡的运动状态。但是，卫星雷达遥感本身的局限性和滑坡所处的复杂地形环境使这一应用面临一些挑战。对卫星雷达遥感技术的4个主要挑战进行了总结与分析，同时给出了相应的解决方案:①通过提高卫星雷达影像的空间、时间分辨率，使用较长波段雷达信号或采用增强型时间序列分析技术，可降低密集植被覆盖对相干性的影响。另外，采用像素点偏移量追踪或距离向分频干涉测量方法，可克服传统干涉测量中大梯度形变引起的相位失相干。②大气延迟对卫星遥感的影响较大，尤其是地处山区的滑坡探测和监测，利用通用型卫星雷达大气改正系统可显著减弱干涉影像的大气信号并进一步简化时间序列分析，提高缓慢运动滑坡的探测和监测质量。③对于中等分辨率的雷达影像而言，利用数字高程模型可提前量化分析雷达几何畸变（如叠掩、阴影等）引发的滑坡探测监测的适用性；而对于高分辨率的雷达影像而言，利用机器学习方法无需外部高分辨率数字高程模型即可精确识别雷达影像的阴影和叠掩区并进行掩膜，从而大幅度提高数据处理效率。④针对高坡度地区残余的地形相位引起的解缠误差，可通过基线线性组合的方法予以减弱。此外，提出了一个基于多源对地观测的滑坡探测/监测系统框架，综合卫星雷达遥感与其他对地观测数据（如地基雷达、激光雷达、全球导航定位系统），搭建了一个自动化滑坡探测与监测系统。该研究旨在阐明卫星雷达遥感的优缺点，进一步深化其在滑坡灾害监测方面的应用和推广，引出未来侧重发展方向的思考与探讨。 相似文献
11.
Satellite Remote Sensing, with both optical and SAR instruments, can provide distributed observations of snow cover over extended and inaccessible areas. Both instruments are complementary, but there have been limited attempts at combining their measurements. We describe a novel approach to produce monthly maps of dry and wet snow areas through application of data fusion techniques to MODIS fractional snow cover and Sentinel-1 wet snow mask, facilitated by Google Earth Engine. The method is demonstrated in a 55,000 km2 river basin in the Indian Himalayan region over a period of ∼2.5 years, although it can be applied to any areas of the world where Sentinel-1 data are routinely available. The typical underestimation of wet snow area by SAR is corrected using a digital elevation model to estimate the average melting altitude. We also present an empirical model to derive the fractional cover of wet snow from Sentinel-1. Finally, we demonstrate that Sentinel-1 effectively complements MODIS as it highlights a snowmelt phase which occurs with a decrease in snow depth but no/little decrease in snowpack area. Further developments are now needed to incorporate these high resolution observations of snow areas as inputs to hydrological models for better runoff analysis and improved management of water resources and flood risk. 相似文献
12.
This letter presents a new method for unsupervised urban area extraction from synthetic aperture radar (SAR) images based on the ffmax algorithm proposed by C. Gouinaud specially for acquiring urban areas in SPOT imagery. According to the statistical characteristics of urban areas, an adaptive and iterative method based on the low-level extraction given by the ffmax algorithm using a large window is proposed. Experimental results on real SAR images show that the proposed automatic method works quickly and can preserve the borders of urban areas as well as avoid the disturbance of other classes and the extractions of urban areas are reliable and precise 相似文献
13.
《International Journal of Digital Earth》2013,6(2):103-114
Abstract Due to spatial and temporal variability an effective monitoring system for water resources must consider the use of remote sensing to provide information. Synthetic Aperture Radar (SAR) is useful due to timely data acquisition and sensitivity to surface water and flooded vegetation. The ability to map flooded vegetation is attributed to the double bounce scattering mechanism, often dominant for this target. Dong Ting Lake in China is an ideal site for evaluating SAR data for this application due to annual flooding caused by mountain snow melt causing extensive changes in flooded vegetation. A curvelet-based approach for change detection in SAR imagery works well as it highlights the change and suppresses the speckle noise. This paper addresses the extension of this change detection technique to polarimetric SAR data for monitoring surface water and flooded vegetation. RADARSAT-2 images of Dong Ting Lake demonstrate this curvelet-based change detection technique applied to wetlands although it is applicable to other land covers and for post disaster impact assessment. These tools are important to Digital Earth for map updating and revision. 相似文献
14.
The Ramsar-listed wetlands of the Magela Creek floodplain, situated in the World Heritage Kakadu National Park, in northern Australia are recognised for their biodiversity and cultural values. The floodplain is also a downstream receiving environment for Ranger uranium mine, which is entering closure and rehabilitation phases. Vegetation on the floodplain is spatially and temporally variable which is related to the hydrology of the region, primarily the extent and level of inundation and available soil moisture. Time-series mapping of the floodplain vegetation will provide a contemporary baseline of annual vegetation dynamics to assist with determining whether change is natural or a result of the potential impacts of mine closure activities such as increased suspended sediment moving downstream. The research described here used geographic object-based image analysis (GEOBIA) to classify the upper Magela Creek floodplain vegetation from WorldView-2 imagery captured over four years (2010–2013) and ancillary data including a canopy height model. A step-wise rule set was used to implement a decision tree classification. The resulting maps showed the 12 major vegetation communities that exist on the Magela Creek floodplain and their distribution for May 2010, May 2011, June 2012 and June 2013 with overall accuracies of over 80% for each map. Most of the error appears to be associated with confusion between vegetation classes that are spectrally similar such as the classes dominated by grasses. Object-based change detection was then applied to the maps to analyse change between dates. Results indicate that change between dates was detected for large areas of the floodplain. Most of the change is associated with the amount of surface water present, indicating that although imagery was captured at the same time of year, the imagery represents different stages of the seasonal cycle of the floodplain. 相似文献
15.
洪涝灾害给社会、经济造成巨大损失,及时、快速监测洪涝范围在抗灾救灾中具有重要意义。合成孔径雷达(SAR)由于其主动式微波成像的机理,可为全天时、全天候、大范围洪涝灾害监测提供支持。本文首先以高分三号(GF-3)卫星影像为数据源,基于灰度共生矩阵(GLCM)、局部二值模式(LBP)等6种纹理描述方法提取138个SAR影像纹理特征;然后利用随机森林(RF)指标重要性评估功能,筛选出重要性得分较高的纹理特征进行水体信息提取;最后结合数学形态学对初始水体提取结果进行后处理,评估安徽巢湖附近区域洪涝灾害。试验表明,本文方法的水体提取精度优于传统阈值法(Otsu)及分类算法(KNN和SVM),可有效提取洪涝灾害的影响范围,为选取合适的SAR影像纹理特征进行洪涝范围快速监测提供参考。 相似文献
16.
Mapping floods due to Hurricane Sandy using NPP VIIRS and ATMS data and geotagged Flickr imagery 总被引：1，自引：0，他引：1
Donglian Sun Sanmei Li Wei Zheng Arie Croitoru Anthony Stefanidis Mitchell Goldberg 《International Journal of Digital Earth》2016,9(5):427-441
In this study, we present an approach to estimate the extent of large-scale coastal floods caused by Hurricane Sandy using passive optical and microwave remote sensing data. The approach estimates the water fraction from coarse-resolution VIIRS and ATMS data through mixed-pixel linear decomposition. Based on the water fraction difference, using the physical characteristics of water inundation in a basin, the flood map derived from the coarse-resolution VIIRS and ATMS measurements was extrapolated to a higher spatial resolution of 30 m using topographic information. It is found that flood map derived from VIIRS shows less inundated area than the Federal Emergency Management Agency (FEMA) flood map and the ground observations. The bias was mainly caused by the time difference in observations. This is because VIIRS can only detect flood under clear conditions, while we can only find some clear-sky data around the New York area on 4 November 2012, when most flooding water already receded. Meanwhile, microwave measurements can penetrate through clouds and sense surface water bodies under clear-or-cloudy conditions. We therefore developed a new method to derive flood maps from passive microwave ATMS observations. To evaluate the flood mapping method, the corresponding ground observations and the FEMA storm surge flooding (SSF) products are used. The results show there was good agreement between our ATMS and the FEMA SSF flood areas, with a correlation of 0.95. Furthermore, we compared our results to geotagged Flickr contributions reporting flooding, and found that 95% of these Flickr reports were distributed within the ATMS-derived flood area, supporting the argument that such crowd-generated content can be valuable for remote sensing operations. Overall, the methodology presented in this paper was able to produce high-quality and high-resolution flood maps over large-scale coastal areas. 相似文献
17.
Plague is a zoonotic infectious disease present in great gerbil populations in Kazakhstan. Infectious disease dynamics are influenced by the spatial distribution of the carriers (hosts) of the disease. The great gerbil, the main host in our study area, lives in burrows, which can be recognized on high resolution satellite imagery. In this study, using earth observation data at various spatial scales, we map the spatial distribution of burrows in a semi-desert landscape.The study area consists of various landscape types. To evaluate whether identification of burrows by classification is possible in these landscape types, the study area was subdivided into eight landscape units, on the basis of Landsat 7 ETM+ derived Tasselled Cap Greenness and Brightness, and SRTM derived standard deviation in elevation.In the field, 904 burrows were mapped. Using two segmented 2.5 m resolution SPOT-5 XS satellite scenes, reference object sets were created. Random Forests were built for both SPOT scenes and used to classify the images. Additionally, a stratified classification was carried out, by building separate Random Forests per landscape unit.Burrows were successfully classified in all landscape units. In the ‘steppe on floodplain’ areas, classification worked best: producer's and user's accuracy in those areas reached 88% and 100%, respectively. In the ‘floodplain’ areas with a more heterogeneous vegetation cover, classification worked least well; there, accuracies were 86 and 58% respectively. Stratified classification improved the results in all landscape units where comparison was possible (four), increasing kappa coefficients by 13, 10, 9 and 1%, respectively.In this study, an innovative stratification method using high- and medium resolution imagery was applied in order to map host distribution on a large spatial scale. The burrow maps we developed will help to detect changes in the distribution of great gerbil populations and, moreover, serve as a unique empirical data set which can be used as input for epidemiological plague models. This is an important step in understanding the dynamics of plague. 相似文献
18.
Sagar S. Salunkhe S. S. Rao I. Prabu V. Raghu Venkataraman Y. V. N. Krishna Murthy Chintamani Sadolikar Supriya Deshpande 《Journal of the Indian Society of Remote Sensing》2018,46(6):915-925
In many flood prone river basins, water inundates vast areas of land causing loss of life and heavy damage to the dwellings in flood plains. It also impacts agricultural productivity and cause severe economic losses. One of the reasons for flooding in plains of Brahmaputra valley in north east India is embankment breaching. In this study, an attempt was made for probabilistic flood hazard modelling of July 2008 embankment breaching scenario of Brahmaputra river at Matmara village, Lakhimpur district in Assam, based on various numerical simulations with the help of Center for Computational Hydro science and Engineering hydro-dynamic model. The methodology was applied over 2146 km2 flood prone area. Data inputs in the study include: Advanced Spaceborne Thermal Emission and Reflection Radiometer Digital Elevation Model, Pre-flood and Post flood satellite images of Landsat Enhanced Thematic Mapper Plus (ETM+) and other ancillary data. The simulation was carried out for various discharge levels based on flood frequency analysis. The result of the model includes spatial variations of inundated water depth and water velocity. The results were validated by comparing it with the post-flood ETM+ data and flood situation status report of National Informatics Centre. Flood hazard maps were prepared by carrying out a spatial analysis of simulated inundation depth and velocity. It was seen that the majority of flooded area fell into the very high and high categories. This information can be used to plan appropriate cost effective flood mitigation schemes. 相似文献
19.
Operational flood mitigation and flood modeling activities benefit from a rapid and automated flood mapping procedure. A valuable information source for such a flood mapping procedure can be remote sensing synthetic aperture radar (SAR) data. In order to be reliable, an objective characterization of the uncertainty associated with the flood maps is required.This work focuses on speckle uncertainty associated with the SAR data and introduces the use of a non-parametric bootstrap method to take into account this uncertainty on the resulting flood maps. From several synthetic images, constructed through bootstrapping the original image, flood maps are delineated. The accuracy of these flood maps is also evaluated w.r.t. an independent validation data set, obtaining, in the two test cases analyzed in this paper, F-values (i.e. values of the Jaccard coefficient) comprised between 0.50 and 0.65. This method is further compared to an image segmentation method for speckle analysis, with which similar results are obtained. The uncertainty analysis of the ensemble of bootstrapped synthetic images was found to be representative of image speckle, with the advantage that no segmentation and speckle estimations are required.Furthermore, this work assesses to what extent the bootstrap ensemble size can be reduced while remaining representative of the original ensemble, as operational applications would clearly benefit from such reduced ensemble sizes. 相似文献
20.
Although wetlands in Tanzania and Kenya have great potentials for agricultural production and a multitude of uses, many of them are not even documented on official maps. Lack of official recognition has done little in preventing there over utilization. As the wetlands continue to play remarkable roles in the movement of people and terrestrial species in the region, it is important that they are monitored and properly managed. This study was undertaken in Usambara highlands and the Pangani floodplain in Tanzania, the Mount Kenya highlands and Laikipia floodplain in Kenya to map the different types of wetlands in terms of their size, density, spatial distribution and use patterns. Remote sensing techniques and field surveys were adopted, and 51 wetlands were identified in flood plains within the semi-arid and sub-humid lowlands, and inland valleys in the region. The detailed maps generated showed the intensity of wetland use, inland valleys being the most intensively used, and are useful in monitoring changes in wetlands for their effective management. The use of multispatial resolution imagery, combined with field survey and GIS produced satisfactory results for the delineation and mapping of small wetlands and their uses. 相似文献