RSS 1.0Departamento de Cartografia
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Recent Submissions
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Mapping nutrients content in a nematode-infected coffee plantation by empirical models derived from rapideye image
; Galo, Maria de Lourdes Bueno Trindade
; ; ; (Anuario do Instituto de Geociencias, 2019) [Artigo]
Nematodes are among the most important coffee pathogens, causing significant losses of productivity. The infection of the coffee plant by nematodes can compromise the root system inducing the manifestation of reflex symptoms ... -
Assessment of UAV-based digital surface model and the effects of quantity and distribution of ground control points
Gomes Pessoa, Guilherme; Caceres Carrilho, André ; Takahashi Miyoshi, Gabriela ; Amorim, Amilton ; Galo, Mauricio (International Journal of Remote Sensing, 2020) [Artigo]
The development of unmanned aerial vehicles (UAVs) along with that of positioning and imaging sensors has promoted the use of photogrammetric techniques for applications other than the conventional acquisition of the Earth’s ... -
Mass appraisal of apartment through geographically weighted regression
Fontoura Júnior, Caio Flávio Martinez; ; Tachibana, Vilma Mayumi (Boletim de Ciencias Geodesicas, 2020) [Artigo]
Housing Market appraisal studies generally apply classic regression models, whose parameters are globally estimated. However, the use of the Geographically Weighted Regression (GWR) model, allows the parameters to be locally ... -
Assessment of gps/glonass point positioning in Brazilian regions with distinct ionospheric behavior
Jerez, Gabriel Oliveira; Alves, Daniele Barroca Marra (Boletim de Ciencias Geodesicas, 2020) [Artigo]
Nowadays GPS (Global Positioning System) and GLONASS (GLObal NAvigation Satellite System) are the main systems of GNSS (Global Navigation Satellite Systems), also composed by Galileo and BeiDou. After a long period of ... -
Aquopts: A multisource processing system for multidimensional bio-optical data integration and correction
Coelho do Carmo, Alisson Fernando; Shimabukuro, Milton Hirokazu ; Imai, Nilton Nobuhiro ; Ribeiro Bernardo, Nariane Marselhe ; Yoshino Watanabe, Fernanda Sayuri ; Herênio de Alcântara, Enner (Computers and Geosciences, 2020) [Artigo]
Field surveys are an important source of data for several scientific studies. Hydrological optics investigations require a large amount of optical data acquired using sensors from distinct manufacturers built with specific ... -
Inland water's trophic status classification based on machine learning and remote sensing data
Watanabe, Fernanda S.Y.; Miyoshi, Gabriela T. ; ; Bernardo, Nariane M.R. ; Rotta, Luiz H.S. ; Alcântara, Enner ; Imai, Nilton N. (Remote Sensing Applications: Society and Environment, 2020) [Artigo]
In this work, we tested machine learning algorithms in classifying waters in a reservoir cascade with basis in trophic state. The classification was done through remote sensing reflectance (Rrs) measurements collected in ... -
Assessment of neutral atmospheric delay predictions based on the temporal resolution of an atmospheric model
Gouveia, Tayná Aparecida Ferreira; ; Monico, João Francisco Galera ; Alves, Daniele Barroca Marra (Boletim de Ciencias Geodesicas, 2020) [Artigo]
In Global Navigation Satellite Systems (GNSS), the effects of neutral atmosphere in electromagnetic signal propagation impacts directly on the quality of the final estimated position, leading to errors in the metric order. ... -
A novel deep learning method to identify single tree species in UAV-based hyperspectral images
Miyoshi, Gabriela Takahashi; ; ; ; ; Imai, Nilton Nobuhiro ; Tommaselli, Antonio Maria Garcia ; ; (Remote Sensing, 2020) [Artigo]
Deep neural networks are currently the focus of many remote sensing approaches related to forest management. Although they return satisfactory results in most tasks, some challenges related to hyperspectral data remain, ... -
The Impact of Atmospheric Correction on Brazilian Earth Tide Models
Arana, Daniel; Camargo, Paulo de Oliveira ; ; ; ; (Pure and Applied Geophysics, 2020) [Artigo]
Terrestrial gravity stations have been in operation for several years throughout Brazil. Minimizing geophysical effects on gravimetric observations is a major challenge in the generation of solid Earth tide models. The ... -
A machine learning framework to predict nutrient content in valencia-orange leaf hyperspectral measurements
; ; ; Moriya, Érika Akemi Saito; Imai, Nilton Nobuhiro ; ; ; ; ; et al. (Remote Sensing, 2020) [Artigo]
This paper presents a framework based on machine learning algorithms to predict nutrient content in leaf hyperspectral measurements. This is the first approach to evaluate macro-and micronutrient content with both machine ... -
Evaluation of hyperspectral multitemporal information to improve tree species identification in the highly diverse atlantic forest
Miyoshi, Gabriela Takahashi; Imai, Nilton Nobuhiro ; Tommaselli, Antonio Maria Garcia ; de Moraes, Marcus Vinícius Antunes ; (Remote Sensing, 2020) [Artigo]
The monitoring of forest resources is crucial for their sustainable management, and tree species identification is one of the fundamental tasks in this process. Unmanned aerial vehicles (UAVs) and miniaturized lightweight ... -
An incongruence-based anomaly detection strategy for analyzing water pollution in images from remote sensing
Dias, Maurcio Arajo; da Silva, Erivaldo Antnio ; ; Casaca, Wallace ; ; Negri, Rogrio Galante (Remote Sensing, 2020) [Artigo]
The potential applications of computational tools, such as anomaly detection and incongruence, for analyzing data attract much attention from the scientific research community. However, there remains a need for more studies ... -
Comparative performance of convolutional neural network, weighted and conventional support vector machine and random forest for classifying tree species using hyperspectral and photogrammetric data
; ; ; ; ; ; ; ; ; Miyoshi, G. T. et al. (GIScience and Remote Sensing, 2020) [Artigo]
The classification of tree species can significantly benefit from high spatial and spectral information acquired by unmanned aerial vehicles (UAVs) associated with advanced classification methods. This study investigated ... -
A feasibility study on incremental bundle adjustment with fisheye images and low-cost sensors
Tommaselli, Antonio M.G.; Campos, Mariana B. ; Castanheiro, Letícia F. ; (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 2019) [Trabalho apresentado em evento]
Low cost imaging and positioning sensors are opening new frontiers for applications in near real-time Photogrammetry. Omnidirectional cameras acquiring images with 360° coverage, when combined with information coming from ... -
Accurate calibration scheme for a multi-camera mobile mapping system
; Campos, Mariana Batista; Tommaselli, Antonio Maria Garcia ; ; ; ; ; (Remote Sensing, 2019) [Artigo]
Mobile mapping systems (MMS) are increasingly used for many photogrammetric and computer vision applications, especially encouraged by the fast and accurate geospatial data generation. The accuracy of point position in an ... -
Improving the empirical line method applied to hyperspectral inland water images by combining reference targets and in situ water measurements
do Carmo, Alisson Fernando Coelho; Bernardo, Nariane Marselhe Ribeiro ; Imai, Nilton Nobuhiro ; Shimabukuro, Milton Hirokazu (Remote Sensing Letters, 2020) [Artigo]
Empirical line methods are frequently used to correct images from remote sensing. This method is performed in two steps: the first stage finds the calibration equation representing the data interval and the second step ... -
Klobuchar and nequick g ionospheric models comparison for multi-gnss single-frequency code point positioning in the Brazilian region
Setti Júnior, Paulo de Tarso; Alves, Daniele Barroca Marra ; da Silva, Crislaine Menezes (Boletim de Ciencias Geodesicas, 2019) [Artigo]
One of the main error sources in GNSS positioning comes from the ionosphere, an atmospheric layer that stays in the signal path between the satellite and the receiver. For single frequency positioning, the ionospheric ... -
Automatic object extraction from high resolution aerial imagery with simple linear iterative clustering and convolutional neural networks
Carrilho, A. C.; Galo, M. (International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 2019) [Trabalho apresentado em evento]
Recent advances in machine learning techniques for image classification have led to the development of robust approaches to both object detection and extraction. Traditional CNN architectures, such as LeNet, AlexNet and ... -
Bundle Adjustment of a Time-Sequential Spectral Camera Using Polynomial Models
Berveglieri, Adilson; Tommaselli, Antonio Maria Garcia ; Santos, Lucas Dias ; (IEEE Transactions on Geoscience and Remote Sensing, 2019) [Artigo]
Lightweight hyperspectral cameras based on frame geometry have been used for several applications in unmanned aerial vehicles (UAVs). The camera used in this investigation is based on a tunable Fabry-Pérot interferometer ... -
Postprocessing synchronization of a laser scanning system aboard a UAV
Machado, Marcela Do Valle; Tommaselli, Antonio Maria Garcia ; Torres, Fernanda Magri ; Campos, Mariana Batista (Photogrammetric Engineering and Remote Sensing, 2019) [Artigo]
Synchronization of airborne laser scanning devices is a critical process that directly affects data accuracy. This process can be more challenging with low-cost airborne laser scanning (ALS) systems because some device ...