scholarly journals Aplicação de filtros passa-baixa em modelos digitais de elevação para avaliação da diferença altimétrica entre os Pantanais do Negro e Nhecolândia

2020 ◽  
Vol 9 (11) ◽  
pp. e1729119519
Author(s):  
Alesandro Copatti ◽  
Deborah Mendes ◽  
Ana Paula Garcia Oliveira ◽  
Fabricio Bau Dalmas ◽  
Antonio Conceição Paranhos Filho
Keyword(s):  

Os dados do radar interferométrico de abertura sintética SRTM apresentam grande potencialidade para estudos que envolvam a altimetria, uma vez que, além de estarem disponíveis gratuitamente na internet, também estão geocodificados, facilitando seu tratamento em Sistema de informações geográficas. Entretanto os dados SRTM apresentam algumas limitações de uso, entre elas o Efeito Dossel, consequência do modelo considerar o topo da vegetação como feição de relevo. Outra limitação, não menos importante, especialmente para a utilização desses dados em áreas planas, refere-se à precisão vertical desses dados, já que na área deste estudo, situada no Pantanal, uma diferença de apenas um metro tem um significado importante. O presente trabalho possui os objetivos de avaliar os dados de altimetria oriundos dos dados de SRTM, TOPODATA e do GLS; analisar a acurácia vertical, através da comparação dos dados destes sensores com os dados de altitude dos marcos geodésicos do Instituto Brasileiro de Geografia e Estatística; e aplicar Filtro Passa-Baixa de Média Móvel para a correção do "Efeito Dossel" dos dados SRTM. A área de estudo escolhida para realizar todas essas análises está englobada entre os Pantanais do Negro e Nhecolância. A metodologia aplicada foi desenvolvida em ambiente SIG de plataformas gratuitas: GRASS-GIS, Quantum GIS e SPRING. Os dados SRTM utilizados permitiram avaliar a diferença altimétrica entre o Pantanal do Negro e a Nhecolândia. Já os filtros aplicados sobre os dados SRTM diminuíram substancialmente as principais feições associadas ao efeito dossel da vegetação.

1995 ◽  
Vol 9 (4) ◽  
pp. 433-446 ◽  
Author(s):  
HELENA MITASOVA ◽  
LUBOS MITAS ◽  
WILLIAM M. BROWN ◽  
DAVID P. GERDES ◽  
IRINA KOSINOVSKY ◽  
...  
Keyword(s):  

2011 ◽  
Vol 59 (11-12) ◽  
pp. 1265-1272 ◽  
Author(s):  
Alessandro Frigeri ◽  
Trent Hare ◽  
Markus Neteler ◽  
Angioletta Coradini ◽  
Costanzo Federico ◽  
...  

Author(s):  
M. A. Brovelli ◽  
M. Minghini ◽  
M. E. Molinari

OpenStreetMap (OSM) is the largest spatial database of the world. One of the most frequently occurring geospatial elements within this database is the road network, whose quality is crucial for applications such as routing and navigation. Several methods have been proposed for the assessment of OSM road network quality, however they are often tightly coupled to the characteristics of the authoritative dataset involved in the comparison. This makes it hard to replicate and extend these methods. This study relies on an automated procedure which was recently developed for comparing OSM with any road network dataset. It is based on three Python modules for the open source GRASS GIS software and provides measures of OSM road network spatial accuracy and completeness. Provided that the user is familiar with the authoritative dataset used, he can adjust the values of the parameters involved thanks to the flexibility of the procedure. The method is applied to assess the quality of the Paris OSM road network dataset through a comparison against the French official dataset provided by the French National Institute of Geographic and Forest Information (IGN). The results show that the Paris OSM road network has both a high completeness and spatial accuracy. It has a greater length than the IGN road network, and is found to be suitable for applications requiring spatial accuracies up to 5-6 m. Also, the results confirm the flexibility of the procedure for supporting users in carrying out their own comparisons between OSM and reference road datasets.


Author(s):  
A. Petrasova ◽  
V. Petras ◽  
D. Van Berkel ◽  
B. A. Harmon ◽  
H. Mitasova ◽  
...  

Spatial patterns of land use change due to urbanization and its impact on the landscape are the subject of ongoing research. Urban growth scenario simulation is a powerful tool for exploring these impacts and empowering planners to make informed decisions. We present FUTURES (FUTure Urban – Regional Environment Simulation) – a patch-based, stochastic, multi-level land change modeling framework as a case showing how what was once a closed and inaccessible model benefited from integration with open source GIS.We will describe our motivation for releasing this project as open source and the advantages of integrating it with GRASS GIS, a free, libre and open source GIS and research platform for the geospatial domain. GRASS GIS provides efficient libraries for FUTURES model development as well as standard GIS tools and graphical user interface for model users. Releasing FUTURES as a GRASS GIS add-on simplifies the distribution of FUTURES across all main operating systems and ensures the maintainability of our project in the future. We will describe FUTURES integration into GRASS GIS and demonstrate its usage on a case study in Asheville, North Carolina. The developed dataset and tutorial for this case study enable researchers to experiment with the model, explore its potential or even modify the model for their applications.


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