Abstract in English:

Abstract: The potential of intrinsic parameters to estimate geospatial data quality on Voluntary Geographic Information (VGI) platforms is a recurrent theme in Cartography. The spatial-temporal distribution in these platforms is very heterogeneous, depending on several factors such as input availability, number, and motivation of volunteers, especially in developing countries. The most recent approaches have been aiming to detail temporal patterns as an additional measure of quality in VGI. This research proposes a methodology to identify and analyze the behavior of the contribution parameters over time (2007-2022) of the OSM platform and differentiates the influences that affect its growth. Part of the Metropolitan region of Curitiba was the study area, subdivided into 1 x 1 km cells. The cumulative growth of contributions was calculated and later adjusted using a Logistic Regression. The obtained parameters made it possible to identify abruptly growing cells caused by external data import, mass contributions, or collective mapping activities. In addition, heterogeneity in the growth of the data available in OSM over time was evident. Furthermore, the proposed methodology promoted the investigation of a new indicator of intrinsic quality based on modelling the spatiotemporal evolution of OSM feature insertions.

Abstract in English:

Abstract: The mapping of rainfall is fundamental in the hydrological modeling process. In this sense, the importance of knowing the geographic and seasonal dynamics of average estimates of rainfall and associated uncertainties is evident. Thus, the present study aimed to predict the spatial and seasonal distribution of rainfall, with the estimation of related uncertainties, in the state of Rio Grande do Sul (RS). Average rainfall varies over the months of the year. In January, February, June, July, August, and September it rains more north and northeast. In March, April, May, October, November, and December it rains more northwest and north. In general, it rains a lot in October and little rain in August. From a geographical point of view, it is possible to highlight that greater volumes of rain occur in the northern part of the state of RS. The uncertainties associated with rainfall estimates show divergent temporal dynamics, with the greatest uncertainties tending to occur in January, February, September, and October and that the smallest uncertainties are observed in June, July, and August.