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97 resultados encontrados para: TEMA: Sensores remotos
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1.
Libro
Nimbus-7 CZCS: coastal zone color scanner imagery for selected coastal regions. North America - Europe, South America - Africa - Antarctica / Warren A. Hovis; Edmund F. Szajna ...[et al.]
Hovis, Warren A. (dir.) ; Szajna, Edmund F. (dir.) ; Bohan, Walter A. (dir.) ;
Illinois : The Walter A. Bohan , s. f
Clasificación: 621.3678 / N5
Bibliotecas: Chetumal
Cerrar
SIBE Chetumal
ECO030003759 (Disponible)
Disponibles para prestamo: 1

2.
Artículo
*Solicítelo con su bibliotecario/a
A parallel path-following phase unwrapping algorithm based on a top-down breadth-first search approach
López García, Lourdes (autora) ; García Arellano, Anmi (autora) ; Cruz Santos, William (autor) ;
Contenido en: Optics and Lasers in Engineering Vol. 124, 105827 (January 2020) ISSN: 0143-8166
Nota: Solicítelo con su bibliotecario/a
Resumen en: Inglés |
Resumen en inglés

Path-following methods for two-dimensional phase unwrapping such as the Goldstein algorithm are the most efficient and robust methods in remote sensing, digital phase shifting, and nuclear magnetic resonance imaging, among others. Several authors have attempted to sketch parallel versions of path-following methods. However, only the first stages of the algorithm such as residue identification and branch-cut placement have been improved using parallel architectures, with limitations such as phase maps with a single continuous region and without isolated regions owing to the cuts. In this article, a systematic parallel Goldstein algorithm that can handle phase data with multi-regions and isolated regions is proposed. Our proposal can improve the three steps of the serial Goldstein algorithm, residue identification, branch cut, and integration. In particular, the integration step is formulated as a top-down breadth-first search problem on a graph for which a parallel algorithm was developed. Synthetic and real phase maps were used to validate the performance and robustness of the proposed parallel algorithm on a multicore architecture. For simulated and real phase maps, we obtained a speedup of 3.3 and 1.98, respectively, on a laptop computer with modest hardware resources.


3.
Artículo
Combining LiDAR data and airborne imagery of very high resolution to improve aboveground biomass estimates in tropical dry forests
Reyes Palomeque, Gabriela (autora) ; Manuel Dupuy, Juan (autor) ; Johnson, Kristofer D. (autor) ; Castillo Santiago, Miguel Ángel (autor) ; Hernández Stefanoni, José Luis (autor) ;
Disponible en línea
Contenido en: Forestry An International Journal of Forest Research Volume 92, número 5 (October 2019), p. 599–615 ISSN: 1464-3626
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Resumen en: Inglés |
Resumen en inglés

Knowledge of the spatial distribution of aboveground biomass (AGB) is crucial to guide forest conservation and management to maintain carbon stocks. LiDAR has been highly successful for this purpose, but has limited availability. Very-high resolution (<1 m) orthophotos can also be used to estimate AGB because they allow a fine distinction of forest canopy grain. We evaluated the separate and joint performance of orthophotos and LiDAR data to estimate AGB in two types of tropical dry forests in the Yucatan Peninsula. Woody plants were surveyed in twenty 0.1 ha plots in a semideciduous forest at Kaxil Kiuic Biocultural Reserve (RBKK) and 28 plots in a semievergreen forest at Felipe Carrillo Puerto (FCP). We fitted three regression models: one based on LiDAR data, another based on orthophoto variables calculated for forest canopy and canopy opening fractions, and a third model that combined both sets of variables. Variation in AGB was decomposed into LiDAR, orthophotos and joint components using variation-partitioning analyses. In FCP, regression models using LiDAR data only showed higher fit (R2 = 0.82) than orthophoto variables only (R² = 0.70). In contrast, orthophotos had a slightly higher fit (R² = 0.91) than LiDAR (R2 = 0.88) in RBKK, because orthophoto variables characterize very well the horizontal structure of canopies on this site. The model that combined both data sets showed a better fit (R2 = 0.85) only in FCP, which has a more complex forest structure. The largest percentage of AGB variation (88 per cent in RBKK and 67 per cent in FCP) was explained by the joint contribution of LiDAR and orthophotos. We conclude that both LiDAR and orthophotos provide accurate estimation of AGB, but their relative performance varies with forest type and structural complexity. Combining the two sets of variables can further improve the accuracy of AGB estimation, particularly in forests with complex vegeta


4.
Capítulo de libro
Methodology to create geospatial MODIS dataset
Álvarez Carranza, Geraldine (autora) ; Lazcano Hernández, Hugo Enrique (autor) ;
Contenido en: Communications in computer and information science 1053 Mérida, Yucatán, México : Telematics and Computing, 2019 p. 25-33 ISBN:978-3-030-33228-0, 978-3-030-33229-7
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Resumen en: Inglés |
Resumen en inglés

Training and testing of algorithms used in computing for application in several studies, require datasets previously validated and labeled. In the case of satellite remote sensing, there are several platforms with large volumes of open source data. Aqua and Terra satellite platforms have available the sensor MODIS (Moderate-Resolution Imaging Spectroradiometer) which has available open access data forearth observation. Despite the facilities offered by the MODIS data platform, extracting data from a particular region for the construction of useful dataset requires an arduous work that includes manual, semiautomatic and automatic stages. The present study proposes a methodology for the construction of a geospatial dataset using MODIS sensordata. This methodology has been successfully implemented in the construction of dataset for the analysis of physical and biological variables in the Caribbean Sea, highlighting its application in the monitoring of Sargasso along the coastline of the state of Quintana Roo. Its application can be extended to any of the data and products offered by the MODIS sensor.


5.
Capítulo de libro - Ponencia
Moderate resolution imaging spectroradiometer products classification using deep learning
Arellano Verdejo, Javier ;
Contenido en: Communications in computer and information science 1053 Mérida, Yucatán, México : Telematics and Computing, 2019 p. 61-70 ISBN:978-3-030-33228-0, 978-3-030-33229-7
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Resumen en: Inglés |
Resumen en inglés

During the last years, the algorithms based on Artificial Intelligence have increased their popularity thanks to their application in multiple areas of knowledge. Nowadays with the increase of storage capacities and computing power, as well as the incorporation of new technologies for massively parallel processing (GPUs and TPUs) and Cloud Computing, it is increasingly common to incorporate this kind of algorithms and technology in tasks with a deep social and technological impact. In the present work a new Convolutional Neural Network specialized in the automatic classification of Moderate Resolution Imaging Spectroradiometer satellite products is proposed. The proposed architecture has shown a high-generalization by classifying more than 250,000 images with 99.99% accuracy. The methodology designed also can beextended, with other types of images, to make detection of Sargassum, oil spills, red tide, etc.


6.
- Artículo científico
*Solicítelo con su bibliotecario/a
A partition strategy to speedup Goldstein’s phase unwrapping algorithm on a multi-core architecture
López Ocaña, Abel ; Cruz Santos, William (coaut.) ; García Arellano, Anmi (coaut.) ; Rueda Paz, Juvenal (coaut.) ;
Contenido en: Programación Matemática y Software Vol. 10, no. 1 (2018), p. 1-7 ISSN: 2007-3283
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Resumen en: Español | Inglés |
Resumen en español

El desenvolvimiento de fase en dos dimensiones es una tarea importante y demandante en los métodos donde se obtienen mapas de fase envueltos tales como en aplicaciones de percepción remota y técnicas de interferometría. Entre las técnicas de desenvolvimiento de fase, el algoritmo de Goldstein es uno de los más robustos y eficientes. En este artículo, se propone una estrategia de partición para obtener una versión paralela del algoritmo de Goldstein sobre una arquitectura multinúcleo usando los lenguajes de programación C y OpenMP. Resultados experimentales obtenidos con datos simulados y reales muestran que nuestra propuesta se puede usar en aplicaciones en tiempo real.

Resumen en inglés

The two-dimensional phase unwrapping is an important and demanding task in measuring methods where a wrapped phase is retrieved such as in remote sensing applications and interferometry techniques. Among phase unwrapping tech-niques, Goldstein’s algorithm is one of the most robust and efficient. In this arti-cle, a partition strategy to parallelize Goldstein’s algorithm on a multi-core archi-tecture using the programming languages C and OpenMP is proposed. Experi-mental results, using simulated and real data, show that our proposal can be used for real time applications.


7.
Artículo
Spatio-temporal assessment of chlorophyll a in Banco Chinchorro using remote sensing
Lazcano Hernández, Hugo Enrique (autor) ; Arellano Verdejo, Javier (autor) ; Hernández Arana, Héctor Abuid (autor) ; Alvarado Barrientos, María Susana (autora) ;
Contenido en: Research in Computing Science Vol. 147, no. 12 (December 2018), p. 213–223 ISSN: 1870-4069
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Resumen en: Inglés |
Resumen en inglés

Quantitative assessments of the temporal variances of physical and biological phenomena are very useful for the understanding of ecosystem functioning. Marine ecosystems are very complex, and regarding biodiversity and fishing resources, Banco Chinchorro (BCh) is one of the most important in the south of the Yucatan Peninsula. Additionally, BCh is an important hotspot of assimilation and release of carbon, for which hurricanes play a supporting role by mixing deep and superficial water masses affecting nutrient mixing and distribution. Here, the concentration of chlorophyll a (Chl a) was quantitatively linked to the occurrence of the four most recent hurricanes that affected BCh utilizing time-series analysis of satellite-derived (AQUA-MODIS) data-sets. Interestingly, different Chl aconcentrations between the south and north of BCh were confirmed quantitatively, which points to differential conservation efforts. The aim of this study was also to provide a proof-of-concept for the development of long-term monitoring methodology using remotely sensed data so that it may be replicated in other regions and with other satellite databases.


8.
Artículo
PDF PDF
Resumen en: Inglés |
Resumen en inglés

This paper presents new equations for estimating above-ground biomass (AGB) and biomass components of seventeen forest species in the temperate forests of northwestern Mexico. A data set corresponding to 1336 destructively sampled oak and pine trees was used to fit the models. The generalized method of moments was used to simultaneously fit systems of equations for biomass components and AGB, to ensure additivity. In addition, the carbon content of each tree component was calculated by the dry combustion method, in a TOC analyser. The results of crossvalidation indicated that the fitted equations accounted for on average 91%, 82%, 83% and 76% of the observed variance in stem wood and stem bark, branch and foliage biomass, respectively, whereas the total AGB equations explained on average 93% of the total observed variance in AGB. The inclusion of total height (h) or diameter at breast height² × total height (d²h) as a predictor in the d-only based equations systems slightly improved estimates for stem wood, stem bark and total above-ground biomass, and greatly improved the estimates produced by the branch and foliage biomass equations. The predictive power of the proposed equations is higher than that of existing models for the study area. The fitted equations were used to estimate stand level AGB stocks from data on growing stock in 429 permanent sampling plots. Three machine-learning techniques were used to model the estimated stand level AGB and carbon contents; the selected models were used to map the AGB and carbon distributions in the study area, for which mean values of respectively 129.84 Mg ha-¹ and 63.80 Mg ha-¹ were obtained.


9.
Libro
*En proceso técnico. Solicítelo con el bibliotecario de SIBE-Chetumal
Hyperspectral remote sensing: fundamentals and practices / Ruiliang Pu
Pu, Ruiliang ;
Boca Raton, Florida : CRC Press :: Taylor and Francis Group , c2017
Clasificación: 621.3678 / P8
Bibliotecas: Chetumal
Cerrar
SIBE Chetumal
ECO030008661 (Prestado)
Disponibles para prestamo: 0
Nota: En proceso técnico. Solicítelo con el bibliotecario de SIBE-Chetumal
Índice | Resumen en: Inglés |
Resumen en inglés

Hyperspectral remote sensing has been a frontier of geospatial technology since the late 1980s, first with the launch of airborne sensors, and later, in the 1990s, with the addition of spaceborne sensors. Today, we can witness the maturity of hyperspectral remote sensing from its wide range of applications, readily available software for image processing, and large volume of pertinent publications. With the expectation of future satellite missions of hyperspectral imaging with global coverage and increasing improvement in image-processing efficiency and information extraction effectiveness, hyperspectral remote sensing will usher in an era of reinvention with the integrated use of high spatial and temporal resolution, LiDAR, and radar sensing. In this context, I am pleased that Dr. Ruiliang Pu has the vision and energy to have written a book on this important topic. The book provides an exhaustive review of the characteristics of airborne and spaceborne hyperspectral sensors, systems, and missions; it discusses in detail the algorithms, techniques, and methods for processing and analyzing hyperspectral data. Further, the author assesses the features and modules of operational tools and software for processing hyperspectral data, followed by a comprehensive investigation of hyperspectral remote sensing applications to geology, soils, vegetation, and environments. Dr. Pu instills his research of more than two decades and rich teaching experience across the Pacific Ocean into the writing of this book. It is a one-of-a-kind textbook, as well as research monograph. I plan to use this book for my multiple remote sensing classes. This book is the sixteenth volume in the Taylor & Francis Series in Remote Sensing Applications, and 2017 marks the tenth anniversary of this series.

As envisioned in 2007, the books in the series contribute to advancements in theories, methods, techniques, and applications of remote sensing in various fields. In fact, as seen today, many of the books in the series have served well as references for professionals, researchers, and scientists, and as textbooks for teachers and students throughout countries all over the world. I hope that the publication of this book will promote a wider and deeper appreciation and application of hyperspectral remote sensing technology. Finally, my hearty congratulations go to Dr. Pu for creating a new milestone in the history of remote sensing.

Índice

Foreword
Preface
Acknowledgments
Author
Introduction
Chapter 1 Overview of Hyperspectral Remote Sensing
Chapter 2 Field Spectrometers and Plant Biology Instruments for HRS
Chapter 3 Imaging Spectrometers, Sensors, Systems, and Missions
Chapter 4 Hyperspectral Image Radiometric Correction
Chapter 5 Hyperspectral Data Analysis Techniques
Chapter 6 Hyperspectral Data Processing Software
Chapter 7 Hyperspectral Applications in Geology and Soil Sciences
Chapter 8 Hyperspectral Applications to Vegetation
Chapter 9 Hyperspectral Applications to Environments
Index


10.
Libro
Reporte técnico sobre la estación para la recepción de información satelital: ERIS Chetumal / elaborado por: María Eugenia Guadarrama Mancilla ; dirigido por: Anmi García Arellano
Guadarrama Mancilla, María Eugenia ; García Arellano, Anmi (coaut.) ;
Chetumal, Quintana Roo, México : El Colegio de la Frontera Sur , 2017
Clasificación: EE/621.367809726 / G8
Bibliotecas: Chetumal
Cerrar
SIBE Chetumal
ECO030008656 (Disponible)
Disponibles para prestamo: 1
PDF
Resumen en: Español |
Resumen en español

En este trabajo se realizó una investigación y recopilación de información relacionada a la distribución de datos satelitales generados en la Estación de Recepción de Información Satelital (ERIS-Chetumal) con el fin de presentar un reporte técnico de esta área de la ERIS. Alguna información técnica importante de diferentes áreas de operación no estaba registrada ni disponible en ningún documento de las diferentes instituciones que han sido parte del proyecto de la ERIS, por tal motivo se realizaron diferentes entrevistas a los técnicos encargados de la operación de la estación para obtener dicha información y se realizaron búsquedas en diferentes páginas web de las instituciones y que han subido información relacionada al tema, también se incluye información de las ponencias del taller que se realizó en la Ciudad de Chetumal del 30 noviembre al 2 de diciembre del 2015 sobre este proyecto. Este trabajo, nos ha permitido conocer la información descargada por la ERIS en el periodo comprendido a los años 2007 a 2013; el proceso que se lleva a cabo desde la captación de las señales del satélite a la antena, hasta su procesamiento y conversión para llegar a obtener un archivo de distribución en la web de la ERIS, así como las características de acceso a la información y distribución y las aplicaciones en las cuales está involucrada o sirven de base para toma de decisiones, se ha apoyado en las pruebas piloto para la implementación del prototipo del "Servicio Federado de Cómputo en la nube para el Almacenamiento, Procesamiento y Distribución de Imágenes Satelitales" y poderlo comparar con la utilizada anteriormente por el servidor de la ERIS