From Satellite Imagery to Disaster Insights

12/17/2018
by   Jigar Doshi, et al.
0

The use of satellite imagery has become increasingly popular for disaster monitoring and response. After a disaster, it is important to prioritize rescue operations, disaster response and coordinate relief efforts. These have to be carried out in a fast and efficient manner since resources are often limited in disaster-affected areas and it's extremely important to identify the areas of maximum damage. However, most of the existing disaster mapping efforts are manual which is time-consuming and often leads to erroneous results. In order to address these issues, we propose a framework for change detection using Convolutional Neural Networks (CNN) on satellite images which can then be thresholded and clustered together into grids to find areas which have been most severely affected by a disaster. We also present a novel metric called Disaster Impact Index (DII) and use it to quantify the impact of two natural disasters - the Hurricane Harvey flood and the Santa Rosa fire. Our framework achieves a top F1 score of 81.2 gridded fire dataset.

READ FULL TEXT

page 2

page 4

research
06/10/2020

CNN-Based Semantic Change Detection in Satellite Imagery

Timely disaster risk management requires accurate road maps and prompt d...
research
10/14/2019

Building Damage Detection in Satellite Imagery Using Convolutional Neural Networks

In all types of disasters, from earthquakes to armed conflicts, aid work...
research
09/05/2022

Utilizing Post-Hurricane Satellite Imagery to Identify Flooding Damage with Convolutional Neural Networks

Post-hurricane damage assessment is crucial towards managing resource al...
research
06/10/2019

Landslide Geohazard Assessment With Convolutional Neural Networks Using Sentinel-2 Imagery Data

In this paper, the authors aim to combine the latest state of the art mo...
research
04/26/2020

Climate Adaptation: Reliably Predicting from Imbalanced Satellite Data

The utility of aerial imagery (Satellite, Drones) has become an invaluab...
research
11/16/2017

Poverty Mapping Using Convolutional Neural Networks Trained on High and Medium Resolution Satellite Images, With an Application in Mexico

Mapping the spatial distribution of poverty in developing countries rema...
research
03/09/2022

Autonomous Mosquito Habitat Detection Using Satellite Imagery and Convolutional Neural Networks for Disease Risk Mapping

Mosquitoes are known vectors for disease transmission that cause over on...

Please sign up or login with your details

Forgot password? Click here to reset