Geo-correction of high-resolution imagery using fast template matching on a GPU in emergency mapping contexts

The increasing availability of satellite imagery acquired from existing and new sensors allow a wide variety of new applications that depend on the use of diverse spectral and spatial resolution data sets. One of the pre-conditions for the use of hybrid image data sets is a consistent geo-correction capacity. We demonstrate how a novel fast template matching approach implemented on a Graphics Processing Unit (GPU) allows us to accurately and rapidly geo-correct imagery in an automated way. The key difference with existing geo-correction approaches, which do not use a GPU, is the possibility to match large source image segments (8192 by 8192 pixels) with relatively large templates (512 by 512 pixels). Our approach is sufficiently robust to allow for the use of various reference data sources. The need for accelerated processing is relevant in our application context, which relates to mapping activities in the European Copernicus emergency management service. Our new method is demonstrated over an area North-West of Valencia (Spain) for a large forest fire event in July 2012. We use DEIMOS-1 and RapidEye imagery for the delineation of burnt fire scar extent. Automated geo-correction of each full resolution image sets takes approximately 1 minute. The reference templates are taken from the TerraColor data set and the Spanish national ortho-imagery data base, through the use of dedicate web map services (WMS). Geo-correction results are compared to the vector sets derived in the related Copernicus emergency service activation request.JRC.G.2-Global security and crisis managemen

Copernicus-EMS mapping guidelines and best practice

This document contains the mapping guidelines for Copernicus Emergency Management Service (EMS) mapping production. It summarizes the JRC experience developed in the frame of Copernicus with respect to the challenging task of providing maps in support of the disaster risk management cycle. The main focus is on the rush mode mapping service, however the guidelines are applicable to the non-rush service as well. The document approaches the map per part component: title, cartographic information, overview maps, legend, and map frame, etc. Some specific and innovative elements are introduced, e.g. the summary table and the standard use of vector files. Particular attention is devoted to the consistency across the components that constitute the product. The structure and the schematic organization of the guidelines allow considering this document as a kind of practical handbook.JRC.G.2-Global security and crisis managemen

Discussion document on the introduction of monitoring to substitute OTSC - Supporting non-paper DS/CDP/2017/03 revising R2017/809

This discussion document builds upon the non-paper DS/CDP/2017/03 to introduce the possibility for substituting the OTSC by a system of monitoring for checking the fulfilment of land use/ land cover related CAP requirements. It describes the main concepts and components that need to be considered and developed for substituting the sampled on the spot checks of aid applications with a monitoring system on all of the applications. The goal is simplification and reduction of the burden of controls and especially for what concerns number of field visits. Such substitution requires a shift in thinking, procedures as well as technology and these are topics elaborated in some detail. An annex provides illustrations, examples, field cases and elaborations of the key topics. This document constitutes the Commission’s interpretation of common standards.JRC.D.5-Food Securit

Validation Protocol for Emergency Response Geo-information Products

Europe is making a significant effort to develop (geo)information services for crisis management as part of the Global Monitoring for Environment and Security GMES) programme. Recognising the importance of coordinated European response to crises and the potential contribution of GMES, the Commission launched a number of preparatory activities in coordination with relevant stakeholders for the establishment of an Emergency Response GMES Core Service (ERCS). GMES Emergency Response Services will rely on information provided by advanced technical and operational capabilities making full use of space earth observation and supporting their integration with other sources of data and information. Data and information generated by these services can be used to enhance emergency preparedness and early reaction to foreseeable or imminent crises and disasters. From a technical point of view, the use of geo-information for emergency response poses significant challenges for spatial data collection, data management, information extraction and communication. The need for an independent formal assessment of crisis products to provide operational services with homogeneous and reliable standards has recently become recognized as an integral component of service development. Validation is intended to help end-users decide how much to trust geo-information products (maps, spatial dataset). The focus, in this document, is on geo-information products, in particular those derived from Earth Observation data. Validation principles have been implemented into a protocol, as a tool to check whether the products meet standards and user needs. The validation principles, methods, rules and guidelines provided in this document aim to give a structure that guarantees an overall documented and continuous quality of ERCS products.JRC.DG.G.2-Global security and crisis managemen

The warning classification scheme of ASAP – Anomaly hot Spots of Agricultural Production

Agriculture monitoring, and in particular food security, requires near real time information on crop growing conditions for early detection of possible production deficits. Anomaly maps and time profiles of remote sensing derived indicators related to crop and vegetation conditions can be accessed online thanks to a rapidly growing number of web based portals. However, timely and systematic global analysis and coherent interpretation of such information, as it is needed for example for the United Nation Sustainable Development Goal 2 related monitoring, remains challenging. With the ASAP system (Anomaly hot Spots of Agricultural Production) we propose a two-step analysis to provide timely warning of production deficits in water-limited agricultural systems worldwide every month. The first step is fully automated and aims at classifying each sub-national administrative unit (Gaul 1 level, i.e. first sub-national level) into a number of possible warning levels, ranging from “none” to level 4++. Warnings are triggered only during the crop growing season, as derived from a remote sensing based phenology. The classification system takes into consideration the fraction of the agricultural area for each Gaul 1 unit that is affected by a severe anomaly of two rainfall-based indicators (the Standardized Precipitation Index computed at 1 and 3-month scale), one biophysical indicator (the anomaly of the cumulative Normalized Difference Vegetation Index from the start of the growing season), and the timing during the growing cycle at which the anomaly occurs. The level (i.e. severity) of the warning thus depends on: the timing, the nature and number of indicators for which an anomaly is detected, and the agricultural area affected. Maps and summary information are published on a web GIS. The second step, not described in detail in this manuscript, involves the verification of the automatic warnings by agricultural analysts to identify the countries (national level) with potentially critical conditions that are marked as “hot spots”. This report focusses on the technical description of the automatic warning classification scheme version 1.0.JRC.D.5 - Food Securit

Standard Operating Procedure - Collaborative Spatial Assessment CoSA - Release 1.0

The purpose of this Standard Operating Procedure (SOP) is to establish uniform procedures pertaining to the preparation for, the performance of, and the reporting of COllaborative (geo) Spatial Assessment (CoSA). CoSA provides a synoptic, unbiased assessment over the impact area of a disaster, which feeds the two main recovery perspectives of the Post-Disaster Needs Assessment (PDNA): i) the valuation of damages and losses carried out through the Damage and Loss Assessment (DaLA) methodology; and ii) the identification of human impacts and recovery needs carried out though the Human Recovery Needs Assessment (HRNA). CoSA is distinct from other geospatial and remote sensing based assessments because it i) draws on the collaborative efforts of distributed capacities in remote sensing and geospatial analysis, ii) aims to achieve the highest possible accuracy in line with the requirements of the PDNA and iii) tries to do so under stringent timing constraints set by the PDNA schedule. The current SOP will aid in ensuring credibility, consistency, transparency, accuracy and completeness of the CoSA. It is a living document, however, that will be enriched with new practical experiences and regularly updated to incorporate state-of-the-art procedures and new technical developments.JRC.DG.G.2-Global security and crisis managemen

The warning classification scheme of ASAP – Anomaly hot Spots of Agricultural Production, v1.1

Agriculture monitoring, and in particular food security, requires near real time information on crop growing conditions for early detection of possible production deficits. Anomaly maps and time profiles of remote sensing derived indicators related to crop and vegetation conditions can be accessed online thanks to a rapidly growing number of web based portals. However, timely and systematic global analysis and coherent interpretation of such information, as it is needed for example for the United Nation Sustainable Development Goal 2 related monitoring, remains challenging. With the ASAP system (Anomaly hot Spots of Agricultural Production) we propose a two-step analysis to provide timely warning of production deficits in water-limited agricultural systems worldwide every month. The first step is fully automated and aims at classifying each sub-national administrative unit (Gaul 1 level, i.e. first sub-national level) into a set of possible warning levels, ranging from “none” to level 4. Warnings are triggered only during the crop growing season, as derived from a remote sensing based phenology. The classification system takes into consideration the fraction of the agricultural area for each Gaul 1 unit that is affected by a severe anomaly of two rainfall-based indicators (the Standardized Precipitation Index computed at 1 and 3-month scale), one biophysical indicator (the anomaly of the cumulative Normalized Difference Vegetation Index from the start of the growing season), and the timing during the growing cycle at which the anomaly occurs. The level (i.e. severity) of the warning thus depends on: the timing, the nature and number of indicators for which an anomaly is detected, and the agricultural area affected. Maps and summary information are published in the Warning Explorer available at http://mars.jrc.ec.europa.eu/asap. The second step, not described in this manuscript, involves the verification of the automatic warnings by agricultural analysts to identify the countries with potentially critical conditions at the national level that are marked as “hot spots”. This report focuses on the technical description of the automatic warning classification scheme version 1.1.JRC.D.5 - Food Securit

Second discussion document on the introduction of monitoring to substitute OTSC: rules for processing application in 2018-2019

This document describes the main concepts and components of the 'checks by monitoring’. It elaborates and details the discussion document on monitoring as a substitute of the current sample approach (on the spot checks) of aid applications or payment claims. This 2nd discussion document elaborates on the rationale, concepts and procedures that form the heart of the monitoring approach, a move from a sequential compliance control followed by penalties towards a continuous monitoring that informs proactively when lodging claims and sends out warning alerts to prevent unintended non-compliances. This agricultural parcel (AP) monitoring takes advantage of the substantial modification of the control framework, most notably the timing of changes to the application and content of the control file.JRC.D.5 - Food Securit