Next Article in Journal
Prospects for Imaging Terrestrial Water Storage in South America Using Daily GPS Observations
Previous Article in Journal
Remote Sensing Techniques for Soil Organic Carbon Estimation: A Review
Open AccessArticle

Improving an Extreme Rainfall Detection System with GPM IMERG data

ITHACA—Information Technology for Humanitarian Assistance, Cooperation and Action, 10138 Torino, Italy
Politecnico di Torino, Dipartimento di Ingegneria dell’Ambiente, del Territorio e delle Infrastrutture, 10129 Torino, Italy
Politecnico di Torino, Dipartimento Interateneo di Scienze, Progetto e Politiche del Territorio, 10125 Torino, Italy
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(6), 677;
Received: 11 January 2019 / Revised: 16 March 2019 / Accepted: 19 March 2019 / Published: 21 March 2019
(This article belongs to the Section Atmosphere Remote Sensing)
Many studies have shown a growing trend in terms of frequency and severity of extreme events. As never before, having tools capable to monitor the amount of rain that reaches the Earth’s surface has become a key point for the identification of areas potentially affected by floods. In order to guarantee an almost global spatial coverage, NASA Global Precipitation Measurement (GPM) IMERG products proved to be the most appropriate source of information for precipitation retrievement by satellite. This study is aimed at defining the IMERG accuracy in representing extreme rainfall events for varying time aggregation intervals. This is performed by comparing the IMERG data with the rain gauge ones. The outcomes demonstrate that precipitation satellite data guarantee good results when the rainfall aggregation interval is equal to or greater than 12 h. More specifically, a 24-h aggregation interval ensures a probability of detection (defined as the number of hits divided by the total number of observed events) greater than 80%. The outcomes of this analysis supported the development of the updated version of the ITHACA Extreme Rainfall Detection System (ERDS: This system is now able to provide near real-time alerts about extreme rainfall events using a threshold methodology based on the mean annual precipitation. View Full-Text
Keywords: early warning system; extreme events; flood monitoring; GPM; hydrology; rainfall early warning system; extreme events; flood monitoring; GPM; hydrology; rainfall
Show Figures

Graphical abstract

MDPI and ACS Style

Mazzoglio, P.; Laio, F.; Balbo, S.; Boccardo, P.; Disabato, F. Improving an Extreme Rainfall Detection System with GPM IMERG data. Remote Sens. 2019, 11, 677.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop