Google Scholar: cites
Protected areas from space map browser with fast visualization and analytical operations on the fly. Characterizing statistical uncertainties and balancing them with visual perception
Maso, Joan (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Zabala Torres, Alaitz (Universitat Autònoma de Barcelona. Departament de Geografia)
Pons, Xavier (Universitat Autònoma de Barcelona. Departament de Geografia)

Data: 2020
Resum: Despite huge progress in applying Earth Observation (EO) satellite data to protected areas, managers still lack the right tools or skills to analyze the data and extract the necessary knowledge. In this paper a set of EO products are organized in a visualization and analysis map browser that lowers usage barriers and provides functionalities comparable to raster-based GIS. Normally, web map servers provide maps as pictorial representations at screen resolution. The proposal is to use binary arrays with actual values, empowering the JavaScript web client to operate with the data in many ways. Thanks to this approach, the user can analyze big data by performing queries and spatial filters, changing image contrast or color palettes or creating histograms, time series profiles and complex calculations. Since the analysis is made at screen resolution, it minimizes bandwidth while maintaining visual quality. The paper explores the limitations of the approach and quantifies the statistical validity of some resampling methods that provide different visual perceptions. The results demonstrate that the methods known for having good visual perception, the mode for categorical values and the median for continuous values, have admissible statistical uncertainties.
Ajuts: European Commission 641762-2
European Commission 730329
European Commission 820852
Agència de Gestió d'Ajuts Universitaris i de Recerca 2017/SGR-1690
Nota: Altres ajuts: Xavier Pons is a recipient of an ICREA Academia Excellence in Research Grant (2016-2020).
Drets: This is an article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Creative Commons
Llengua: Anglès
Document: Article ; recerca ; Versió publicada
Matèria: Web mapping ; GIS analytics ; Statistics ; Generalization ; Remote sensing ; Protected areas
Publicat a: ISPRS international journal of geo-information, Vol. 9, issue 5 (May 2020) , art. 300, ISSN 2220-9964

DOI: 10.3390/ijgi9050300

27 p, 9.0 MB

El registre apareix a les col·leccions:
Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Ciències > Grup de Recerca Mètodes i Aplicacions en Teledetecció i Sistemes d'Informació Geogràfica (GRUMETS)
Documents de recerca > Documents dels grups de recerca de la UAB > Centres i grups de recerca (producció científica) > Ciències > CREAF (Centre de Recerca Ecològica i d'Aplicacions Forestals)
Articles > Articles de recerca
Articles > Articles publicats

 Registre creat el 2021-06-01, darrera modificació el 2021-09-29

   Favorit i Compartir