Drone Watch

GSTDTAP

项目编号	NE/N020316/1
	Drone Watch
	[unavailable]
主持机构	Cranfield University
项目开始年	2016
	2016
项目结束日期	2016-07-31
资助机构	UK-NERC
项目类别	Research Grant
国家	英国
语种	英语
英文摘要	Near real-time (48h) accurate mapping of flood extent, property and infrastructure damage in urban areas is required for the estimation of insurance loss and insurance claim validation. With flood damage estimated to be above £3billion/event (based on 2007 flooding events) and an average house claim of £40k, flood mitigation and damage assessment are a priority in the Governmental agenda. Current methodologies rely on the use of satellite data (SAR or optical) or aerial imagery collected from aircraft. However, several limitations within the underlying technology curtail the current effectiveness of the strategy: (i) optical imagery cannot provide information under low-cloud cover presence and (ii) satellite (SAR) data, which can penetrate cloud cover, is challenging in urban areas due to its oblique viewing angle and the difficulty of separating the water signature from other urban features. Hence, at present, we do not have sufficient data to robustly calculate flood impact in urban areas. Small-scale Vertical Take Off (VTO) Unmanned Aerial Vehicles (UAVs) are emerging as a key engineering tool for future environmental monitoring tasks. Within the context of flood extent mapping and damage estimation, UAV aerial imagery offers both timely (on-demand) and increasingly detailed (higher resolution) information than comparable satellite or aircraft imagery. Here, we contribute to address the gap in the provision of immediate post-event flood extent and visible damage information by coupling knowledge from four core research areas:- (i) emerging technologies (Dr. Rivas Casado), (ii) flood engineering (Dr. Butler and Dr. Yu), (iii) remote sensing (Dr. Johnson) and (iv) catastrophe modelling (Dr. Irvine). The objectives are achieved via six consecutive steps that integrate the four core disciplines mentioned. Step 1 (O1). UAV data will be collected to obtain a representation of the flooded area at fine resolution. This will require site selection, flight design andata acquisition. Independent frames will be mosaicked together to produce an accurate orthoimage of the area of interest (maximising resolution). Step 2. Satellite imagery will be collected for the area of interest to generate an additional layer of information (maximising coverage). The FloodMap model will be used to map flood extent using the digital elevation model generated from the UAV imagery. As far as possible, in limited time, existing damage data matching the selected event will be sought from Oasis or Ambiental partners. Step 3. The data sets from (1) and (2) will be integrated in a Geographical System Information (GIS) environment (maximising modelling efficiency). Step 4. Key parameters informing on flood extent will be extracted from (3) using established approaches. Outputs will be validated via ground truth data (if flooding occurs). In a flood constraint scenario, a comparison between flood derived parameters from UAV and satellite imagery will be provided (maximising modelling robustness). Step 5. Key to the overall success of the project is a strong focus on the correct understanding of the market requirements. For this purpose, a small-scale, exploratory market definition will be undertaken to gather the type of products different end user communities will require to visualise and successfully use the integrated product (maximising product uptake). Step 6. Step 6 will deliver the proof of concept through the integration of results from (4) and (5). A service definition will be provided to conceptualise the product the end user requires. At this stage, the service definition and integrated outcome should align to guarantee further allocation of funding resources on a cost-efficient tool for rapid assessment of damage from floods and storms that increases the accuracy in estimates of insurance loss and has the potential to enable the validation of insurance claims.
来源学科分类	Natural Environment Research
文献类型	项目
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/85921
专题	环境与发展全球科技态势
推荐引用方式 GB/T 7714	[unavailable].Drone Watch.2016.