A European Framework for Recording and Sharing Disaster Damage and Loss Data

The recently adopted ‘Sendai Framework for Action on Disaster Risk Reduction 2015-2030’ sets the goals to reduce loss of life, livelihood and critical infrastructure through enhanced national planning and international cooperation. The new Framework is expected to enhance global, regional and national efforts for building resilience to disasters, across the entire disaster management cycle (prevention, preparedness, response and early recovery). Improved monitoring and accountability frameworks, relying on harmonized disaster loss data will be required for meeting the targets and for capturing the levels of progress across different scales of governance. To overcome the problems of heterogeneous disaster data and terminologies, guidelines for reporting disaster damage and losses in a structured manner will be necessary to help national and regional bodies compile this information. In the European Union, the Member States and the European Commission worked together on the establishment of guidelines for recording and sharing disaster damage and loss data as a first step towards the development of operational indicators to translate the Sendai Framework into action. This paper describes the progress to date in setting a common framework for recording disaster damage and loss data in the European Union and identifies the challenges ahead.JRC.G.2-Global security and crisis managemen

A crowdsourced global data set for validating built-up surface layers

Several global high-resolution built-up surface products have emerged over the last five years, taking full advantage of open sources of satellite data such as Landsat and Sentinel. However, these data sets require validation that is independent of the producers of these products. To fill this gap, we designed a validation sample set of 50 K locations using a stratified sampling approach independent of any existing global built-up surface products. We launched a crowdsourcing campaign using Geo-Wiki (https://www.geo-wiki.org/) to visually interpret this sample set for built-up surfaces using very high-resolution satellite images as a source of reference data for labelling the samples, with a minimum of five validations per sample location. Data were collected for 10 m sub-pixels in an 80 × 80 m grid to allow for geo-registration errors as well as the application of different validation modes including exact pixel matching to majority or percentage agreement. The data set presented in this paper is suitable for the validation and inter-comparison of multiple products of built-up areas

Mapping Natural Habitats Using Remote Sensing and Sparse Partial Least Square Discriminant Analysis. GI_Forum 2013 – Creating the GISociety|

In this paper, we tested a relatively new version of the Partial Least Square (PLS) method called the Sparse Partial Least Square Discriminant Analysis (SPLSDA). This improved method performs variable selection and classification in a one-step procedure and has been successfully applied in the field of bioinformatics (LÊ CAO et al. 2011). We are applying the method on remote sensing data for the classification of natural and semi-natural habitats in a Natura 2000 site located in Southern France. The work has been performed in the framework of the MS.MONINA FP7 project which is using the potential of GMES for the development of a multi-scale mapping service aimed at monitoring European protected habitats and species at the local, regional and continental scales

Using SPOT-5 HRG Data in Panchromatic Mode for Operational Detection of Small Ships in Tropical Area

Nowadays, there is a growing interest in applications of space remote sensing systems for maritime surveillance which includes among others traffic surveillance, maritime security, illegal fisheries survey, oil discharge and sea pollution monitoring. Within the framework of several French and European projects, an algorithm for automatic ship detection from SPOT-5 HRG data was developed to complement existing fishery control measures, in particular the Vessel Monitoring System. The algorithm focused on feature-based analysis of satellite imagery. Genetic algorithms and Neural Networks were used to deal with the feature-borne information. Based on the described approach, a first prototype was designed to classify small targets such as shrimp boats and tested on panchromatic SPOT-5, 5-m resolution product taking into account the environmental and fishing context. The ability to detect shrimp boats with satisfactory detection rates is an indicator of the robustness of the algorithm. Still, the benchmark revealed problems related to increased false alarm rates on particular types of images with a high percentage of cloud cover and a sea cluttered background

Mapping Natural Habitats Using Remote Sensing and Sparse Partial Least Square Discriminant Analysis. GI_Forum 2013 – Creating the GISociety|

In this paper, we tested a relatively new version of the Partial Least Square (PLS) method called the Sparse Partial Least Square Discriminant Analysis (SPLSDA). This improved method performs variable selection and classification in a one-step procedure and has been successfully applied in the field of bioinformatics (LÊ CAO et al. 2011). We are applying the method on remote sensing data for the classification of natural and semi-natural habitats in a Natura 2000 site located in Southern France. The work has been performed in the framework of the MS.MONINA FP7 project which is using the potential of GMES for the development of a multi-scale mapping service aimed at monitoring European protected habitats and species at the local, regional and continental scales

Earth Observation for Habitat and Biodiversity Monitoring. GI_Forum 2013 – Creating the GISociety|

The special workshop “Earth observation for ecosystem and biodiversity monitoring – best practices in Europe and globally, at GI_Forum 2013, focused on the outcomes of the EUfunded projects MS.MONINA and BIO_SOS and related activities that highlight the potential of Earth observation data and technologies in support of biodiversity and ecosystem monitoring. In Europe, nature conservation rests upon a strong, yet ambitious policy framework with legally binding directives. Thus, geospatial information products are required at all levels of implementation. With advances in Earth observation data availability and the forthcoming of powerful data analysis tools we enter a new dimension of satellitebased services. Recent achievements of such endeavours were showcased and challenges discussed, using best practice examples from both inside and outside Europe. This article summarizes the state-of-the-art of satellite-based habitat mapping and accommodates the paper contributions in the current scientific discourse

Using SPOT-5 HRG Data in Panchromatic Mode for Operational Detection of Small Ships in Tropical Area

Nowadays, there is a growing interest in applications of space remote sensing systems for maritime surveillance which includes among others traffic surveillance, maritime security, illegal fisheries survey, oil discharge and sea pollution monitoring. Within the framework of several French and European projects, an algorithm for automatic ship detection from SPOT-5 HRG data was developed to complement existing fishery control measures, in particular the Vessel Monitoring System. The algorithm focused on feature-based analysis of satellite imagery. Genetic algorithms and Neural Networks were used to deal with the feature-borne information. Based on the described approach, a first prototype was designed to classify small targets such as shrimp boats and tested on panchromatic SPOT-5, 5-m resolution product taking into account the environmental and fishing context. The ability to detect shrimp boats with satisfactory detection rates is an indicator of the robustness of the algorithm. Still, the benchmark revealed problems related to increased false alarm rates on particular types of images with a high percentage of cloud cover and a sea cluttered background

Guidance for Recording and Sharing Disaster Damage and Loss Data: Towards the development of operational indicators to translate the Sendai Framework into action actionreduction translate the Sendai Framework into action

This report provides guidance to Member States in improving the coherence and completeness of the national disaster damage and loss data recording process, necessary for supporting evidence-based disaster risk management policies and actions. It proposes essential elements of an assessment methodology for recording damage and loss data and recommends simplified aggregate figures for sharing the data following a common data exchange format. The proposed common framework for damage and loss data recording directly supports reporting on indicators for global disaster risk reduction targets, envisaged as part of the EU commitment to the post-2015 Sustainable Development Goals and to the Sendai Framework for Disaster Risk Reduction. The guidance provided herein is a first iteration and is expected to evolve with further consultation and experience from the multiple stakeholders from Member States.JRC.G.2-Global security and crisis managemen