Real-Time Multi-Scale Mapping for Emergency Management
ISBN 978-85-88783-11-9
Authors
1Fayne, J.V.; 2Fuhrmann, S.; 3Rice, M.T.; 4Bolten, J.D.
1GEORGE MASON UNIVERSITY Email: jessicavfayne@gmail.com
2GEORGE MASON UNIVERSITY Email: sfuhrman@gmu.edu
3GEORGE MASON UNIVERSITY Email: mrice4@gmu.edu
4NASA GODDARD SPACE FLIGHT CENTER Email: john.bolten@nasa.gov
Abstract
Earth-observing satellite data are widely used in the remote sensing community to create disaster prediction and analysis products for use by local managers and planners. In order for these products to serve their intended purpose, the end users must be able to interpret the scientific data presented for use as a basis of decision-making. However, data from varying resolutions can be difficult to integrate into a product that is easily readable. When real-time data updates are necessary for quick action from emergency management professionals, ‘real-time’ data usually means low spatial resolution and generalization of areas that require more detail. The cartographic remote sensing frame of reference compels remote sensing scientists to create cartographic products that satisfy the needs of end-users while maintaining scientific accuracy. This research seeks to demonstrate that satellite images can be combined to monitor changes over an area with a higher temporal resolution than individually, and seeks to show that the output of the combined datasets will be more useful and easier to understand from a planning perspective. The example for this study will compare existing flood area extent products with a new area extent product that will integrate reflectance and emissivity data from MODIS, VIIRS, and Landsat, along with the mean emissivity from ASTER. To accomplish this, images from these sensors are analyzed at a pixel level to scan and update throughout the region of study. Beginning with a coarse resolution then moving into a finer resolution dataset, the processing method will provide more detail in areas that are flooded, or alert areas, and less detail in areas that may be dry. The iterative area method can be used for combining datasets that have variable temporal and spatial resolution as well as for other purposes that may require high temporal resolution and variable spatial resolution. The results of this method can be hosted on a publicly accessible website for use by planners and engineers, with high resolution alert areas highlighted for ease of use and interpretation. Future research will incorporate other GIS data layers such as roads, buildings, and bridges to bring attention to areas that might be effected.