An object-based image analysis for building seismic vulnerability assessment using high-resolution remote sensing imagery

Building seismic vulnerability assessment plays an important role in formulating pre-disaster mitigation strategies for developing countries. The occurrence of high-resolution satellite sensors has greatly motivated it by providing a promising approach to obtain building information. However, this also brings a big challenge to the accurate building extraction and its coherent integration with the assessment model. The main objective of this paper is to investigate how to extract building attributes from high-resolution remote sensing imagery using the object-based image analysis (OBIA) method, so as to accurately and conveniently assess building seismic vulnerability by the combination of in situ field data. A general framework for the assessment of building seismic vulnerability is presented, including (1) the extraction of building information using OBIA, (2) building height estimation, and (3) the support vector machine (SVM)-based building seismic vulnerability assessment. Particularly, an integrated solution is proposed that merges the strengths of multiple spatial contextual relationships and some typical image object measures, under the unified framework to improve building information extraction at different scale levels as well as for different interest objects. With the aid of 35 building samples from two powerful earthquakes in China, the cloud-free WorldView-2 images and some building structure parameters from field survey were used to quantity the grades of building seismic vulnerability in Wuhan Optics Valley, China. The results show that all 48 buildings among the study area have been well detected with an overall accuracy of 80.67 % and the mean error of heights estimated from building shadow is less than 2 m. This indicates that the integrated analysis strategy based on OBIA is suitable for extracting the building information from high-resolution remote sensing imagery. Additionally, the assessment results using SVM show that the building seismic vulnerability is statistically significantly related to structure types and building heights. Both the proposed OBIA method and its integration strategy with SVM are easily implemented and provide readily interpretable assessment results for building seismic vulnerability. This reveals that the proposed method has a great potential to assist urban planners for making local disaster mitigation planning through the prioritization of intervention measures, such as the reinforcement of walls and the dismantlement of endangered houses.     

Selection of shelters after earthquake using probabilistic seismic aftershock hazard analysis and remote sensing

Natural Hazards - After a major earthquake, one of the main tasks is to identify temporary shelters. In this study, we utilized probabilistic aftershock hazard analysis based on land use...     

Seismic vulnerability assessment of earthquake-prone mega-city Shillong,India using geophysical mapping and remote sensing

ABSTRACT

The concept of seismic vulnerability is a yard-stick of damage estimation from a probable earthquake considering physical cum social dimension and enables a basis for decision-makers to develop preparedness and mitigation strategies. We aim at vulnerability assessment of the typical urban system of capital city Shillong situated on hilly terrain. High-resolution satellite imagery of Shillong facilitates analysis of building footprints, communication network, and open ground. Different building typologies are identified taking into account the building’s structural configuration assessed through a rapid visual survey of more than 15% of total residential households. Slope map demarcates the landslide-prone area through discrete elevation modelling. A methodology incorporating several parameters e.g. building typology, slope angle, shear wave velocity characteristics, geomorphology, and the number of occupants in correlation with a physical measurement of vulnerability is presented and is applied to estimate the dimension of vulnerability. Additionally, MASW survey indicates lithology up to 30?m deep along with the existence of stiff soil and rocks at different depths whereas resonant frequency is identified to be in the range of 6–8?Hz through H/V ratio. Integrating all, it is observed that more than 60% of Shillong city falls under moderate to higher vulnerability and the rest is less vulnerable.     

遥感与GIS技术在生态环境脆弱性评价中的作用

为探讨生态环境脆弱性评价与遥感、GIS之间的关系, 在解读生态环境脆弱性评价的基础上, 从理论与应用两个方面展开分析。研究表明: 遥感、GIS技术可在模型建立、技术支持、数据源提供和展示平台构建等方面为生态环境脆弱性评价提供强有力的技术支撑。     

Scenario-based quantitative human vulnerability assessment of site-specific landslides using a probabilistic model

Landslides - Ensuring the safety of personnel and providing practical escape routes for potential victims play essential roles in reducing the human vulnerability to site-specific landslides....     

Non-Poisson probabilistic seismic hazard assessment

The development of the new seismic hazard map of metropolitan Tehran is based on probabilistic seismic hazard computation using the non-Poisson recurrence time model. For this model, two maps have been prepared to indicate the earthquake hazard of the region in the form of iso-acceleration contour lines. They display the non-Poisson probabilistic estimates of peak ground accelerations over bedrock for 10 and 63 % probability of exceedance in 50 years. To carry out the non-Poisson seismic hazard analysis, appropriate distributions of interoccurrence times of earthquakes were used for the seismotectonic provinces which the study region is located and then the renewal process was applied. In order to calculate the seismic hazard for different return periods in the probabilistic procedure, the study area encompassed by the 49.5–54.5°E longitudes and 34–37°N latitudes was divided into 0.1° intervals generating 1,350 grid points. PGA values for this region are estimated to be 0.30–0.32 and 0.16–0.17 g for 10 and 63 % probability of exceedance, respectively, in 50 years for bedrock condition.     

Drought risk assessment using remote sensing and GIS techniques

Beginning with a discussion of drought definitions, this review paper attempts to provide a review of fundamental concepts of drought, classification of droughts, drought indices, and the role of remote sensing and geographic information systems for drought evaluation. Owing to the rise in water demand and looming climate change, recent years have witnessed much focus on global drought scenarios. As a natural hazard, drought is best characterized by multiple climatological and hydrological parameters. An understanding of the relationships between these two sets of parameters is necessary to develop measures for mitigating the impacts of droughts. Droughts are recognized as an environmental disaster and have attracted the attention of environmentalists, ecologists, hydrologists, meteorologists, geologists, and agricultural scientists. Temperatures; high winds; low relative humidity; and timing and characteristics of rains, including distribution of rainy days during crop growing seasons, intensity, and duration of rain, and onset and termination, play a significant role in the occurrence of droughts. In contrast to aridity, which is a permanent feature of climate and is restricted to low rainfall areas, a drought is a temporary aberration. Often, there is confusion between a heat wave and a drought, and the distinction is emphasized between heat wave and drought, noting that a typical time scale associated with a heat wave is on the order of a week, while a drought may persist for months or even years. The combination of a heat wave and a drought has dire socio-economic consequences. Drought risk is a product of a region’s exposure to the natural hazard and its vulnerability to extended periods of water shortage. If nations and regions are to make progress in reducing the serious consequences of drought, they must improve their understanding of the hazard and the factors that influence vulnerability. It is critical for drought-prone regions to better understand their drought climatology (i.e., the probability of drought at different levels of intensity and duration) and establish comprehensive and integrated drought information system that incorporates climate, soil, and water supply factors such as precipitation, temperature, soil moisture, snow pack, reservoir and lake levels, ground water levels, and stream flow. All drought-prone nations should develop national drought policies and preparedness plans that place emphasis on risk management rather than following the traditional approach of crisis management, where the emphasis is on reactive, emergency response measures. Crisis management decreases self-reliance and increases dependence on government and donors.     

Coastal erosion hazard and vulnerability assessment for southern coastal Tamil Nadu of India by using remote sensing and GIS

The measurement and recording of the height and spatial extent reached by coastal storm surges is fundamental to scientific progress in understanding these phenomena. Such information is required for better prediction and for risk assessment. Model-based evaluation of increasing delta vulnerability, for example, cannot be tested without long-term, consistent, and sustained observation of actual events. Also, storm surges occur within the temporal context of tidal variation, which must first be characterized through observation. Present standard approaches for measuring storm surges are not optimum. Thus, tidal gauges provide information at one point, whereas the heights reached by surges vary spatially. Also, post-surge ground surveys are expensive, laborious, and commonly lack comparison to similar data obtained for previous surges or for high tides. The advent of moderate spatial resolution, high temporal resolution remote sensing initiated by the launch of the two NASA MODIS sensors greatly reduces these constraints. For over a decade, daily coverage of most coastal land areas, though restricted by cloud cover, has systematically captured the maximum extents reached by both high tides and by storm surges. Automated water classification algorithms are now transforming the incoming image data into GIS water boundary files, again at daily or near-daily time steps. This paper provides a retrospective view of sample storm surges as mapped via these sensors and describes: (a) the present, MODIS-based surface water surveillance system, (b) the mapping enhancement to be provided by frequent-repeat, wide-swath satellite radar imaging, and (c) the emerging prospects for routine global surveillance of storm surge events. Such will be necessary if long-term trends are to be recognized, characterized, and understood, along coastal zones now being affected by both increasing subsidence and rising sea level.     

Aerosol pollution and its impact on regional climate during Holi festival inferred from ground-based and satellite remote sensing observations

In this paper, we report some salient features from a suit of special experiments that have been conducted over a coastal site (Mumbai) during February 23–March 03, 2010, encompassing an Indian festival, namely Holi, using solar radiometers and pyranometer. The results of the analysis of observations at the experimental site show higher (more than double) aerosol optical depth, water vapor, and lower down-welling short-wave radiative flux during the festival period. This is considered to be due to anthropogenic activities and associated meteorological conditions at the experimental location. To illustrate further, Angstrom parameters (alpha, denoting the aerosol size distribution, and beta, representing the loading) are examined. These parameters are found to be greater on Holi day as compared to those on the normal (control, pre-, and post-Holi) days, suggesting an increase in accumulation mode (smaller size) particle loading. The aerosol size spectra exhibited bimodal/power-law distribution with a dominant peak, modulated by anthropogenic activities, involving local and long-range transport of dust and smoke (emanated from biomass-burning) aerosols, which is consistent with MODIS satellite observations. The aerosol direct radiative forcing estimation indicated cooling at the bottom of the atmosphere.     

Reconstruction of cloud-contaminated satellite remote sensing images using kernel PCA-based image modelling

The presence of clouds can restrict the potential uses of remote sensing satellite imagery in extracting information and interpretation. Automatic detection and removal of clouds which hide significant information in the image is an important task in remote sensing. Hence, our aim is to detect clouds and restore the missing information in order to make the image ready for further analysis and applications. Due to the difference in nature and appearance, thick and thin clouds are dealt separately. Thick cloud is detected using an efficient Fuzzy C-Means (FCM) clustering algorithm, while thin cloud is detected using a simple region growing technique. In order to reconstruct the missing pixels, we utilize the prior knowledge about the statistics of the specific image class. Kernel principal component analysis (KPCA)-based image model is obtained using a set of training images. Missing area in the image is restored after an iterative projection operation and gradient descent algorithm. In short, an image lying out of the modelled image space is iteratively modified to obtain the restored image and that would be in the image space according to the obtained nonlinear low-dimensional and sparse KPCA image model. To illustrate the performance of the proposed method, a thorough experimental analysis on FORMOSAT multi-spectral images is done using MATLAB platform. When compared to the two recent existing techniques, our proposed method is superior and makes a promising tool for thick and thin cloud removal in multi-spectral satellite images.     

Groundwater potential zonation for basaltic watersheds using satellite remote sensing data and GIS techniques

This paper summarizes the findings of groundwater potential zonation mapping at the Bharangi River basin, Thane district, Maharastra, India, using Satty’s Analytical Hierarchal Process model with the aid of GIS tools and remote sensing data. To meet the objectives, remotely sensed data were used in extracting lineaments, faults and drainage pattern which influence the groundwater sources to the aquifer. The digitally processed satellite images were subsequently combined in a GIS with ancillary data such as topographical (slope, drainage), geological (litho types and lineaments), hydrogeomorphology and constructed into a spatial database using GIS and image processing tools. In this study, six thematic layers were used for groundwater potential analysis. Each thematic layer’s weight was determined, and groundwater potential indices were calculated using groundwater conditions. The present study has demonstrated the capabilities of remote sensing and GIS techniques in the demarcation of different groundwater potential zones for hard rock basaltic basin.     

Flow-based seismic risk assessment of a water transmission network employing probabilistic seismic hazard analysis

Natural Hazards - In this study, a seismic risk assessment model was proposed to evaluate the seismic reliability of a water transmission network. The proposed risk assessment model involves...     

夏季黑河流域蒸散发量卫星遥感估算研究

依据空气动力学方法和蒸散发量时间尺度扩展方案,利用MODIS资料和气象资料,计算中国西北内陆河黑河流域复杂地形下,2004年夏季7月蒸散发量空间分布及总量。利用Landsat-5TM资料对比分析发现,估算地表水热传输过程时,采用高分辨率遥感资料的估算结果受下垫面非均匀性影响程度,明显小于采用中分辨率资料。通过"金塔实验"湍流观测资料验证表明,利用高分辨率资料估算日蒸散发量的相对误差在10%以内。对月蒸散发量计算分析表明,黑河流域海拔2000m以上祁连山区,7月平均蒸散发量是海拔2000m以下山前地区的2.2倍,而山前平原区绿洲(NDVI>0.10区域)平均蒸散发量又是荒漠戈壁地区的12.3倍。因此,流域中下游绿洲地区特别是农业灌溉区是夏季主要水资源消耗区。     

基于GF-1卫星遥感的冰川边界识别

高分一号（GF-1）卫星的成功发射开启了国产高分辨率对地观测的新时代, 为探讨国产高分卫星在冰川边界识别中的有效性, 在缺少短波红外和热红外波段的情况下, 将GF-1影像、 建立的波段比值Band1/Band4, 数字高程模型和坡度相结合, 采用面向对象的分析方法, 经过反复试验, 确定影像分割和合并尺度, 进而确定冰川边界的知识规则, 最终实现冰川边界的识别。以研究区第二次冰川编目数据集作为参考数据, 采用混淆矩阵的方法对识别结果进行验证, 总体精度和Kappa系数为90.05%和0.79。同时将识别结果与人工修订冰川边界进行对比, 可以发现除少量冰舌末端冰川外, 该方法可以有效地对冰川进行识别。建立的知识规则显示仅仅利用蓝色波段和DEM就可以有效地提取裸冰区, 波段比值、 坡度和纹理特征更有助于冰舌的提取。该研究表明GF-1卫星数据可以有效识别冰川范围, 为冰川研究提供可靠的数据和研究基础。     

Groundwater vulnerability and risk mapping in a geologically complex area by using stable isotopes, remote sensing and GIS techniques

Groundwater vulnerability and risk mapping is a relatively new scientific approach for facilitating planning and decision making processes in order to protect this valuable resource. Pan European methodology for aquifers vulnerability has recently been developed by assessing all the existing relevant techniques and emphasizing on karstic environments. In the particular study, state-of-the-art methods and tools have been implemented such as remote sensing, isotopic investigations and GIS to map the groundwater vulnerability and pollution risk in a geologically complex area of W. Greece. The updated land use map has been developed from a Landsat 7+TM image elaborated with image analysis software, while the detailed hydrogeologic properties of the area have been recorded with an intensive isotopic study. The local groundwater vulnerability map has been produced following the aforementioned Pan European method, in a GIS environment while the risk map, which was the final product of the study, has been developed after combining the vulnerability and the land use maps. The results indicated that the areas comprised of highly tectonized calcareous formations represented high vulnerability and risk zones while forested areas away from the karstic aquifer illustrated moderate to low vulnerability. Moreover, human activities increase the pollution risk in lowland areas consisting of sedimentary deposits that have been classified as moderate vulnerability. The particular methodology operated efficiently in this study and due to its accuracy and relatively easy implementation can be used as a decision support tool for local authorities.     

利用被动微波探测青海湖湖冰物候变化特征

湖冰物候是气候变化的敏感因子,不仅能反映区域气候变化特征,还可以反映区域气候与湖泊相互作用.利用长时间序列(1978—2018年)被动微波遥感18 GHz和19 GHz亮度温度数据、MODIS数据(2000—2018年)、实测湖冰厚度数据(1983—2018年)和气温、风速、降水(雪)数据(1961—2018年),分析...     

Urban flood vulnerability zoning of Cochin City,southwest coast of India,using remote sensing and GIS

Natural Hazards - The present study identified the various zones vulnerable to urban flood in Cochin City, one of the biggest metro cities on the southwest coast of peninsular India. The analysis...