Archive | 2019

Alternativa para determinação de altitudes normais-ortométricas na Amazônia legal brasileira

 
 

Abstract


The present paper intends to develop an alternative methodology for prediction of normal-orthometric heights through Brazilian Legal Amazon Rain Forest, a region that imposes logistical-operational difficulties for fieldwork and in which there is considerable precariousness in the Brazilian Fundamental Altimetric Network (BFAN), evidencing the need to improve the network in question to fully align with the current recommendations for the achievement of the International Height Reference Frame. An alternative strategy is based on GNSS observations and the use of global geopotential models (GGMs); alternatively, it uses the national geoid model MAPGEO2015 to evaluate employability. To do so, an approach in three different variants is performed: a) use of absolute and relative approaches for altimetric determination; b) use of GGM extracts obtained in different degrees of development and MAPGEO2015; and c) the use of geoid height and height anomaly for normal-geoid height modeling. Data regarding GNSS observations are extracted from the stations of the SAT-GPS network, coinciding with BFAN stations, with information of both ellipsoidal and normal-orthometric heights; GGMs extracts are obtained pointwisely for the main current combined MGGs. Given the low mean accuracy of data in the study area and its low linkage with BFAN, it is chosen to adopt a test area —the state of Parana— best suited for elaboration and solidification of the strategy for a later application in the area of study. From the studies conducted in the test area, there is an unquestionable advantage of using the relative approach over the absolute one allied to GGMs, with an average of 72% better results for extracts developed up to\xa0 degrees 2190 and 720; MAPGEO2015 was an exception to such results, presenting no adequacy to the relative approach.

Volume None
Pages 179-199
DOI 10.35424/RCAR.V5I98.146
Language English
Journal None

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