Figure 1 - available via license: CC BY
Content may be subject to copyright.
Case I: ROI near the city Beira in the Province of Sofala, Mozambique (Spatial reference system EPSG:4326 [14]) .
Source publication
Insights into flood dynamics, rather than solely flood extent, are critical for effective flood disaster management, in particular in the context of emergency relief and damage assessment. Although flood dynamics provide insight in the spatio-temporal behaviour of a flood event, to date operational visualization tools are scarce or even non-existen...
Context in source publication
Context 1
... first case is a flood caused by a tropical cyclone, Idai, which made landfall during the night of 14 to 15 March 2019 near Beira City, Sofala Province, in central Mozambique (Figure 1). This is a coastal area with mostly cropland and grassland areas, yet also some built up area (city of Beira). ...
Similar publications
Keywords: SITS Land use land cover change BFAST MODIS NDVI LSLA A B S T R A C T In the context of Global Change Research, detection, monitoring and characterization of land use/land cover (LULC) changes are of prime importance. The increasing availability of dense satellite image time series (SITS) has led to a shift in the change detection paradig...
Citations
... By overlaying the above information, we achieved a detailed assessment of the inundation duration for different vulnerable entities. Generally, the duration of inundation is positively correlated with the severity of losses (Debusscher et al., 2020;Rättich et al., 2020). For instance, the length of time that crops are submerged directly determines their yield (Scott et al., 1989). ...
... By calculating river width at multiple segments for each time step, they estimate the discharge using a width-discharge relationship. Twenty-four percent of studies concentrating on the region focus on the anthroposphere [33,37,198,216,241]. As one major natural hazard in the area, floods are monitored by multiple studies [33,198,216]. ...
... Twenty-four percent of studies concentrating on the region focus on the anthroposphere [33,37,198,216,241]. As one major natural hazard in the area, floods are monitored by multiple studies [33,198,216]. As it is mostly insensitive to atmospheric influences, data from SAR sensors is preferred for this application. ...
... As it is mostly insensitive to atmospheric influences, data from SAR sensors is preferred for this application. Ref. [216] investigates the short-term dynamics of floods based on multi-temporal Sentinel-1 SAR with a roughly weekly temporal resolution. Focusing on a region in Kerala, India, Ref. [33] assesses the flood dynamics for an event that occurred in 2018. ...
Inland surface water is often the most accessible freshwater source. As opposed to groundwater, surface water is replenished in a comparatively quick cycle, which makes this vital resource—if not overexploited—sustainable. From a global perspective, freshwater is plentiful. Still, depending on the region, surface water availability is severely limited. Additionally, climate change and human interventions act as large-scale drivers and cause dramatic changes in established surface water dynamics. Actions have to be taken to secure sustainable water availability and usage. This requires informed decision making based on reliable environmental data. Monitoring inland surface water dynamics is therefore more important than ever. Remote sensing is able to delineate surface water in a number of ways by using optical as well as active and passive microwave sensors. In this review, we look at the proceedings within this discipline by reviewing 233 scientific works. We provide an extensive overview of used sensors, the spatial and temporal resolution of studies, their thematic foci, and their spatial distribution. We observe that a wide array of available sensors and datasets, along with increasing computing capacities, have shaped the field over the last years. Multiple global analysis-ready products are available for investigating surface water area dynamics, but so far none offer high spatial and temporal resolution.
... Flooding duration is an important parameter for flood damage assessment in agriculture (Debusscher et al., 2020;Rättich et al., 2020). This study tracked the dynamic changes in flooded cropland every 5-6 days using high-temporal-resolution Sentinel-1 SAR data (Amitrano et al., 2018). ...
Floods are causing massive losses of crops and agricultural infrastructures in many regions across the globe. During the 2018/2019 agricultural year, heavy rains from Cyclone Idai caused flooding in Central Mozambique and had the greatest impact on Sofala Province. The main objectives of this study are to map the flooding du-rations, evaluate how long crops survived the floods, and analyse the dynamics of the affected crops and their recovery following various flooding durations using multi-source satellite data. Our results indicate that Otsu method-based flooding mapping provides reliable flood extents and durations with an overall accuracy higher than 90%, which facilitates the assessment of how long crops can survive floods and their recovery progress. Croplands in both Buzi and Tica administrative units were the most severely impacted among all the regions in Sofala Province, with the largest flooded cropland extent at 23,101.1 ha in Buzi on 20 March 2019 and the most prolonged flooding duration of more than 42 days in Tica and Mafambisse. Major summer crops, including maize and rice, could survive when the fields were inundated for up to 12 days, while all crops died when the flooding duration was longer than 24 days. The recovery of surviving crops to pre-flooding status took a much longer time, from approximately 20 days to as long as one month after flooding. The findings presented herein can assist decision making in developing countries or remote regions for flood monitoring, mitigation and damage assessment.
... Sometimes, the infrastructures and environment are highly vulnerable to floods, causing considerable losses to society and property. (Wang et al. 2019, Debusscher et al. 2020. Floods have become one of the most frequent and cumulative losses among many natural hazards. ...
Enhancing the visualisation of floods is essential for users to understand disaster information. However, existing flood visualisation methods have some deficiencies like scarce scene content expression and difficulty obtaining disaster information quickly and lacked a semantic description of the disaster scenes. This study presents constraint rules of flood disaster scene modelling guided by disaster information to determine the disaster’s content and correlation. We created a disaster fusion expression model to obtain the complete flood disaster scene which integrated basic geography scene, flood space-time process and disaster object models. Finally, we proposed a dynamic suitability visualisation method for the flood scene to increase the readability of disaster information. We applied the proposed model in the Danba County flood in Sichuan Province, China, to validate the model’s performance effectiveness. The finding shows the variation range of flow velocity and flood depth at different monitoring points at a specific time, and also shows the disaster level of disaster objects in the study area. It indicates that the proposed method can effectively realise the fusion of 3D disaster scenes and the dynamic suitability visualisation of floods and help users understand floods quickly and get useful disaster information.
Hydro-numerical models are increasingly important to determine the adequacy and evaluate the effectiveness of potential flood protection measures. However, a significant obstacle in setting up hydro-numerical and associated flood damage models is the tedious and oftentimes prohibitively costly process of acquiring reliable input data, which particularly applies to coastal megacities in developing countries and emerging economies. To help alleviate this problem, this paper explores the usability and reliability of flood models built on open-access data in regions where highly resolved (geo)data are either unavailable or difficult to access yet where knowledge about elements at risk is crucial for mitigation planning. The example of Ho Chi Minh City, Vietnam, is taken to describe a comprehensive but generic methodology for obtaining, processing and applying the required open-access data. The overarching goal of this study is to produce preliminary flood hazard maps that provide first insights into potential flooding hotspots demanding closer attention in subsequent, more detailed risk analyses. As a key novelty, a normalized flood severity index (INFS), which combines flood depth and duration, is proposed to deliver key information in a preliminary flood hazard assessment. This index serves as an indicator that further narrows down the focus to areas where flood hazard is significant. Our approach is validated by a comparison with more than 300 flood samples locally observed during three heavy-rain events in 2010 and 2012 which correspond to INFS-based inundation hotspots in over 73 % of all cases. These findings corroborate the high potential of open-access data in hydro-numerical modeling and the robustness of the newly introduced flood severity index, which may significantly enhance the interpretation and trustworthiness of risk assessments in the future. The proposed approach and developed indicators are generic and may be replicated and adopted in other coastal megacities around the globe.
Hydro-numerical models offer an increasingly important tool to determine the adequacy and evaluate the effectiveness of potential flood protection measures. However, a significant obstacle in setting up hydro-numerical and associated flood damage models is the tedious and oftentimes prohibitively costly process of acquiring reliable input data, which particularly applies to coastal megacities in developing countries and emerging economies. To address this problem, this paper takes the example of Ho Chi Minh City, Vietnam, and proposes a new and comprehensive methodology for acquiring, processing, and applying the necessary open-access data (topography, bathymetry, tidal, river flow, and precipitation time series) to set up an urban surface run-off model. As a key novelty of the paper, a normalized flood severity index (NFSI) that combines flood depth and duration is proposed. The index serves as an indicator that helps uncover urban inundation hotspots with severe damage potential, drawing attention to specific districts or boroughs with special adaptation needs or emergency response measures. The approach is validated by comparison with more than 300 locally reported flood samples, which correspond to NFSI-processed inundation hotspots in over 73 % of all cases. These findings corroborate the robustness of the proposed index, which may significantly enhance the interpretation and trustworthiness of hydro-numerical assessments in the future. The proposed approach and developed indicators are generic and may be replicated and adopted in other coastal megacities.
Jadeja, MahipalMuthu, RahulInformation visualization is the study of visual representations of abstract data in order to strengthen the human understanding of the data. Graph visualization is one of the subfields of information visualization. It is used for the visualization of structured data, i.e. for inherently related data elements. In the traditional graph visualization techniques, nodes are used to represent data elements, whereas edges are used to represent relations. In this paper, our focus is on the representation of structured data. According to us, key challenges for any graph-based visualization technique are related to edges. Some of them are planar representation, minimization of edge crossing, minimizing the number of bends, distinguish between the vertices and the edges, etc. In this paper, we propose two methods that use the same underlying idea: Assignment of unique label to each vertex of the graph and remove all the edges. Nodes are adjacent if and only if their corresponding labels are disjoint. Our proposed representations do not have edges so we do not need to consider the challenges related to edges that is the biggest advantage. The algorithm for obtaining valid labelling as well as procedures related to dynamic changes (addition/removal of edges and/or vertices) is explained in detail. The space complexities of the proposed methods are O(n2) and O(n3) where n denotes the number of nodes. Application of our proposed methods in the analysis of a social network site is also demonstrated. Characteristics of these methods are highlighted along with possible future modifications.
