The amount of data that Sentinel fleet is generating over a territory such as Catalonia makes it virtually impossible to manually download and organize as files. The Open Data Cube (ODC) offers a solution for storing big data products in an efficient way with a modest hardware and avoiding cloud expenses. The approach will still be useful up to the next decade. Yet, ODC requires a level of expertise that most people who could benefit from the information do not have. This paper presents a web map browser that gives access to the data and goes beyond a simple visualization by combining the OGC WMS standard with modern web browser capabilities to incorporate time series analytics. This paper shows how we have applied this tool to analyze the spatial distribution of the availability of Sentinel 2 data over Catalonia and revealing differences in the number of useful scenes depending on the geographical area that ranges from one or two images per month to more than one image per week. The paper also demonstrates the usefulness of the same approach in giving access to remote sensing information to a set of protected areas around Europe participating in the H2020 ECOPotential project.
Abstract-Geographic Information Systems (GIS) and RemoteSensing (RS) applications are becoming an important issue for the territorial management, governmental and research projects, and for many fields of our society. A characteristic of such applications is the displaying of successive layers of information that, in some cases, may overlap areas of the displayed images that are eventually never showed to the final user of the application. Even though these overlapped areas are of null interest, the coding of these images considers the complete area of the image, and thus the coding performance of the compression system is penalized. This paper introduces a novel use of the Region Of Interest (ROI) coding techniques to overcome the drawbacks of the map overlapping in GIS and RS applications. The proposed approach is based on a ROI coding method defined for the JPEG2000 standard that efficiently improves the coding performance and keeps JPEG2000 compliance.
Given the circumstance that the process for the revision of the international standard ISO 19157 is currently open, this article presents a critical reflection on its content, application and some challenges posed by the new types of data (e.g. big data, BIM data, etc.), that also have a geospatial component and to which, therefore, this international standard can be applied as well. Proposals are put forward going along three lines of improvement, on the one hand the consideration of new data quality elements and on the other, the reinforcement of the interoperability of this international standard with other standards related to data quality, and finally various improvements (e.g. standardization of evaluation methods, clearly introducing the life cycle, improvement of the definition of metaquality, etc.) of the standard, which come from experience.
RESUMENLos estándares para la información geoespacial distribuida pueden ser de propósito general o particulares de un dominio. Algunos dominios han avanzado más que otros en la estandarización y en la interoperabilidad como por ejemplo el dominio Meteorológico-Climático o el Hidrológico. El colectivo de Hidrología detectó la necesidad del estándar WaterML, el cual ayuda a la óptima gestión de los recursos del agua. En términos generales, WaterML es un estándar que define un modelo de datos para la representación de las observaciones hidrológicas, con la intención de permitir el intercambio de este conjunto de datos a través de sistemas de información. Está basado en dos estándares: Geographic Markup Language (GML) y Observations and Measurements (O&M). WaterML en su versión 2.0 fue desarrollado por Open Geospatial Consortium (OGC), fue aprobado a mediados del 2012 y finalmente publicado a inicios del 2014. A pesar de ser un estándar emergente, diversas instituciones gubernamentales y no gubernamentales han considerado útil estandarizar la información sobre sus series temporales de datos hidrológicos y además publicarlas en la web. Este trabajo revisa y cuantifica el nivel de uso de WaterML en las aplicaciones hidrológicas actuales y sitúa a WaterML en la arquitectura del conjunto de los estándares OGC.
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