O índice de dissecação do relevo é uma análise morfométrica que considera o grau de entalhamento do vale e dimensão interfluvial média. Ross (1992 e 1994) formalizou este índice o qual possui diversas aplicações, como segmentação do relevo, fornecer bases para o mapeamento geomorfológico, estudar a relação morfogênese - pedogênese e vulnerabilidade ambiental. O cálculo e mapeamento do índice de dissecação de forma analógica é extremamente dispendioso além de estar sujeito a erros humanos e a diferenças de interpretação. Atualmente não existe um método para realizar de forma totalmente automatizada o cálculo do índice de dissecação e que considere ambas as variáveis propostas por Ross (grau de entalhamento dos vales e dimensão interfluvial média). O objetivo deste artigo é apresentar uma rotina de automatização do cálculo do índice de dissecação para cada pixel a partir de um modelo digital de elevação. O método é dividido em quatro etapas principais, sendo elas o tratamento do modelo digital de elevação, o mapeamento do grau de entalhamento dos vales, o mapeamento da dimensão interfluvial média para cada bacia e a integração destes dois últimos produtos. De acordo com a proposta de Ross (1994), ao final do mapeamento deve-se classificar os valores de dissecação em função de uma escala que varia de muito fraca a muito forte. Ao comparar o mapa resultante da proposta de classificação de Ross a um modelo tridimensional, ao mapa de declividade da área e da rede de drenagem notou-se alguns problemas, como a classe de dissecação muito forte ocorrer em regiões planas e com grau de entalhamento da drenagem extremamente baixo. Então foram sugeridas e testadas mais três propostas de classificação dos valores de dissecação.

Dams are structures built for controlling the flow of water for many useful purposes such as water supply, power generation, retention of mining and industrial waste, as well as recreation and flood control. However, they bring together some risk of dam body collapse causing damage for the dam downstream areas. Therefore, hypothetical dam break studies which provide mapping of areas potentially attainable in the event of a rupture are especially important for planning actions aiming minimization of associated losses. The aim of this research is to assess the degree of adherence or similarity between flood maps obtained by simulation studies and those effectively obtained from the collapse itself occurred in Dam I owned by Vale SA on January 25, 2019. The study focuses mainly on comparing the effects over the simulated flood maps caused by use of different representation of dam downstream topography relief, namely Shuttle Radar Topography Mission (SRTM), Advanced Land Observing Satellite from Alaska Satellite Facility (ALOS_ASF) and Airborne Laser Scanning (ALS) models. The simulations were performed using the HEC-RAS software developed by the US Army Corps of Engineers considering hypothesis of strong influence of relief in flood mapping results. In this way, three simulation tests were carried out for evaluation and discussion. In the first simulation, the digital terrain model derived from ALS was used. The second simulation was carried out associating the digital surface model ALOS_ASF with a spatial resolution of 12.5 m. Finally, the SRTM digital elevation model with 30 m spatial resolution provided by the United States Geological Survey (USGS) was used in third simulation. Results showed better adherence to simulations using data from ALS. This was verified by visual analysis over high resolution orthorectified images and by calculating statistics indicators such as the (F) index. Conclusions pointed out that flood patches resulting from simulation are critical tools for taking actions involving areas and populations to be affected, so the best relief model technologies like ALS data should be used in simulation.

Experiments conducted at the School of Engineering of the University of São Paulo, Brazil, using GNSS/NTRIP technology are described and analyzed in terms of accuracy. The method consists in using the data of a reference station, the IBGE RBMC-IP stations, collected in a remote station, by means of the Internet and a mobile phone, to obtain more accurate real time coordinates than those of the navigation method. The experiments consist in surveying the known coordinate points and of the error analysis (accuracy). Firstly with short distances (in the USP Base for Equipment Calibration), and then over increasing distances up to about 30 km, in terms of the limits foreseen for the RTK method, and for other greater distances by using the DGPS method, up to 2,700 km. The following were tested and analyzed: the use of different reference stations, the variation in accuracy over distance, the use of a L1 receiver and a L1/L2 one, as well as the use of the RTK and DGPS techniques, in terms of accuracy reached, that is, the difference between these coordinates and others considered as standard, besides checking if the equipment reaches or not the accuracy stated in the manual.

In many countries, the positional accuracy control by points in Cartography or Spatial data corresponds to the comparison between sets of coordinates of well-defined points in relation to the same set of points from a more accurate source. Usually, each country determines a maximum number of points which could present error values above a pre-established threshold. In many cases, the standards define the sample size as 20 points, with no more consideration, and fix this threshold in 10% of the sample. However, the sampling dimension (n), considering the statistical risk, especially when the percentages of outliers are around 10%, can lead to a producer risk (to reject a good map) and a user risk (to accept a bad map). This article analyzes this issue and allows defining the sampling dimension considering the risk of the producer and of the user. As a tool, a program developed by us allows defining the sample size according to the risk that the producer / user can or wants to assume. This analysis uses 600 control points, each of them with a known error. We performed the simulations with a sample size of 20 points (n) and calculate the associated risk. Then we changed the value of (n), using smaller and larger sizes, calculating for each situation the associated risk both for the user and for the producer. The computer program developed draws the operational curves or risk curves, which considers three parameters: the number of control points; the number of iterations to create the curves; and the percentage of control points above the threshold, that can be the Brazilian standard or other parameters from different countries. Several graphs and tables are presented which were created with different parameters, leading to a better decision both for the user and for the producer, as well as to open possibilities for other simulations and researches in the future.

Computer programs applied to disaster simulation are widely used and widespread today, taking as input various data, from specific to the application area to MDTs (Digital Terrain Models). This need for data input and, in particular, data related to relief is very relevant in prediction procedures for forecasting catastrophes, such as the failure of tailings mining deposit dams. Therefore, it is of fundamental importance to know and quantify the quality of this input data in question, in order to effectively serve this application. To this end, in this research, several tests were carried out, using as a reference for best results those obtained with the introduction of MDT from a LIDAR (Light Detection and Ranging) flight survey, this data being used as one of the primary and input into HEC-RAS (Hydrologic Engineering Center-River Analysis System). Subsequently, these same data had their spatial resolution degraded, that is, the pixel size increased, generating models with worse quality for new inputs and obtaining new simulation results of mining dam failures. As a laboratory, the test area of the B1 Dam, located in Brumadinho-MG, Brazil, was used as a laboratory, where one of the biggest mining disasters in the world recently occurred and, for which, there are real data from the area affected by the dam collapse. . The results obtained demonstrated that the use of an MDT with a spatial resolution of at least 2.5 meters or better, with MDT class A cartographic quality compatible with the most recent Brazilian standard, would guarantee reliable results.

This work is an altimetry evaluation study involving Digital Elevation Models ASTER GDEM version 2 and SRTM version 3. Both models are readily available free of charge, however as they are built from different remote sensing methods it is also expected that they present different data qualities. LIDAR data with 25 cm vertical accuracy were used as reference for assessment validation. The evaluation study, carried out in urbanized area, investigated the distribution of the residuals and the relationship between the observed errors with land slope classes. Remote sensing principles, quantitative statistical methods and the Cartographic Accuracy Standard of Digital Mapping Products (PEC-PCD) were considered. The results indicated strong positive linear correlation and the existence of a functional relationship between the evaluated models and the reference model. Residuals between -4.36 m and 3.11 m grouped 47.7% of samples corresponding to ASTER GDEM and 63.7% of samples corresponding to SRTM. In both evaluated models, Root Mean Square Error values increased with increasing of land slope. Considering 1: 50,000 mapping scale the PEC-PCD classification indicated class B standard for SRTM and class C for ASTER GDEM. In all analyzes, SRTM presented smaller altimetry errors compared to ASTER GDEM, except in areas with steep relief.