A Sharable and Efficient Metadata Model for Heterogeneous Earth Observation Data Retrieval in Multi-Scale Flood Mapping

Nengcheng Chen,Lianjie Zhou,Zeqiang Chen

doi:10.3390/rs70809610

Abstract

Remote sensing plays an important role in flood mapping and is helping advance flood monitoring and management. Multi-scale flood mapping is necessary for dividing floods into several stages for comprehensive management. However, existing data systems are typically heterogeneous owing to the use of different access protocols and archiving metadata models. In this paper, we proposed a sharable and efficient metadata model (APEOPM) for constructing an Earth observation (EO) data system to retrieve remote sensing data for flood mapping. The proposed model contains two sub-models, an access protocol model and an enhanced encoding model. The access protocol model helps unify heterogeneous access protocols and can achieve intelligent access via a semantic enhancement method. The enhanced encoding model helps unify a heterogeneous archiving metadata model. Wuhan city, one of the most important cities in the Yangtze River Economic Belt in China, is selected as a study area for testing the retrieval of heterogeneous EO data and flood mapping. The past torrential rain period from 25 March 2015 to 10 April 2015 is chosen as the temporal range in this study. To aid in comprehensive management, mapping is conducted at different spatial and temporal scales. In addition, the efficiency of data retrieval is analyzed, and validation between the flood maps and actual precipitation was conducted. The results show that the flood map coincided with the actual precipitation.

Highlights

Every year, floods cause numerous casualties [1]
This study proposes using a sharable and efficient model to retrieve Earth observation (EO) data for multi-scale flood mapping
We studied Wuhan city in China because Wuhan city contains hundreds of lakes

Summary

Introduction

Floods cause numerous casualties [1]. In the last decade of the 20th century, floods directly or indirectly affected approximately 1.4 billion people, and approximately 100,000 people lost their lives [2]. Floods can be mapped and monitored using remotely-sensed data acquired by aircrafts and satellites. This method has incomparable advantages over ground observations [3,4]. Analysis of flood loss assessments: First, validating the results of flood hazards is difficult because ground-based observation are generally expensive and time consuming, and standard equipment is difficult to find [5]. The use of remote sensing images is a proven method for successfully monitoring changes in flood hazards in time and space [6]. Available online: http://modis.gsfc.nasa.gov/data/dataprod/index.php (accessed on 6 January 2015). Available online: http://jena.apache.org/ (accessed on 6 August 2015). Available online: http://gcmd.nasa.gov/add/ancillaryguide/index.html (accessed on 6 January 2015).

Objectives

Findings

Discussion

Conclusion