Análisis de la dinámica multitemporal del espejo de agua de dos lagos amazónicos durante 2014-2020, utilizando imágenes de SAR en GEE y técnicas de regresión

Amazonas es una de las regiones de montaña de Perú con elevada cobertura nubosa, por lo que utilizar datos ópticos en el análisis multitemporal de cuerpos de agua (como los lagos Pomacochas y Burlan) resulta dificultoso. Por tanto, en esta investigación utilizamos productos de Sentinel-1 A/B para analizar la dinámica multitemporal del espejo de agua de los lagos Burlán y Pomacochas desde 2014 a 2020. Para ello, en Google Earth Engine procesamos 517 imágenes SAR para cada lago mediante los algoritmos: Classification and Regression Trees (CART), Random Forest (RF) y Support Vector Machine (SVM). Posteriormente, con los valores de área y perímetro en Google Collaboratory (GC) se implementó un código para ejecutar regresión lineal simple, polinómica, de vectores de soporte, de árboles de decisión y random forest. Con el método de regresión de mayor R 2 se predijo el valor del área y perímetro de cada lago para el 2021-02-10, mismo valor que fue comparado con un vuelo fotogramétrico de un RPAS, utilizando puntos de control de un receptor GNSS Trimble R10. Durante los primeros meses del año se registraron aumentos del área y perímetro de cada lago, esto influenciado por el aumento de precipitaciones en la zona. RF funcionó mejor en clasificación y regresión, mostrando la forma de los polígonos de cada lago muy similares al ortomosaico obtenido por el RPAS. Finalmente, buscamos aportar con una metodología rápida para clasificar en dos categorías imágenes de SAR, además, realizar análisis de regresión en GC mediante cinco métodos que pueden ser replicadas en distintas áreas temáticas

Site Selection for a Network ofWeather Stations Using AHP and Near Analysis in a GIS Environment in Amazonas, NW Peru

Meteorological observations play a major role in land management; thus, it is vital to properly plan the monitoring network of weather stations (WS). This study, therefore, selected ‘highly suitable’ sites with the objective of replanning the WS network in Amazonas, NW Peru. A set of 11 selection criteria for WS sites were identified and mapped in a Geographic Information System, as well as their importance weights were determined using Analytic Hierarchy Process and experts. A map of the suitability of the territory for WS sites was constructed by weighted superimposition of the criteria maps. On this map, the suitability status of the 20 existing WS sites was then assessed and, if necessary, relocated. New ‘highly suitable’ sites were determined by the Near Analysis method using existing WS (some relocated). The territory suitability map for WS showed that 0.3% (108.55 km2) of Amazonas has ‘highly suitable’ characteristics to establish WS. This ‘highly suitable’ territory corresponds to 26,683 polygons (of ≥30 × 30 m each), from which 100 polygons were selected in 11 possible distributions of new WS networks in Amazonas, with different number and distance of new WS in each distribution. The implementation of this methodology will be a useful support tool for WS network planning

Spatiotemporal Dynamics of Grasslands Using Landsat Data in Livestock Micro-Watersheds in Amazonas (NW Peru)

In Peru, grasslands monitoring is essential to support public policies related to the identification, recovery and management of livestock systems. In this study, therefore, we evaluated the spatial dynamics of grasslands in Pomacochas and Ventilla micro-watersheds (Amazonas, NW Peru). To do this, we used Landsat 5, 7 and 8 images and vegetation indices (normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and soil adjusted vegetation index (SAVI). The data were processed in Google Earth Engine (GEE) platform for 1990, 2000, 2010 and 2020 through random forest (RF) classification reaching accuracies above 85%. The application of RF in GEE allowed surface mapping of grasslands with pressures higher than 85%. Interestingly, our results reported the increase of grasslands in both Pomacochas (from 2457.03 ha to 3659.37 ha) and Ventilla (from 1932.38 ha to 4056.26 ha) micro-watersheds during 1990–2020. Effectively, this study aims to provide useful information for territorial planning with potential replicability for other cattle-raising regions of the country. It could further be used to improve grassland management and promote semi-extensive livestock farming

Crowd computing as a cooperation problem: an evolutionary approach

Cooperation is one of the socio-economic issues that has received more attention from the physics community. The problem has been mostly considered by studying games such as the Prisoner's Dilemma or the Public Goods Game. Here, we take a step forward by studying cooperation in the context of crowd computing. We introduce a model loosely based on Principal-agent theory in which people (workers) contribute to the solution of a distributed problem by computing answers and reporting to the problem proposer (master). To go beyond classical approaches involving the concept of Nash equilibrium, we work on an evolutionary framework in which both the master and the workers update their behavior through reinforcement learning. Using a Markov chain approach, we show theoretically that under certain----not very restrictive-conditions, the master can ensure the reliability of the answer resulting of the process. Then, we study the model by numerical simulations, finding that convergence, meaning that the system reaches a point in which it always produces reliable answers, may in general be much faster than the upper bounds given by the theoretical calculation. We also discuss the effects of the master's level of tolerance to defectors, about which the theory does not provide information. The discussion shows that the system works even with very large tolerances. We conclude with a discussion of our results and possible directions to carry this research further.This work is supported by the Cyprus Research Promotion Foundation grant TE/HPO/0609(BE)/05, the National Science Foundation (CCF-0937829, CCF-1114930), Comunidad de Madrid grant S2009TIC-1692 and MODELICO-CM, Spanish MOSAICO, PRODIEVO and RESINEE grants and MICINN grant TEC2011-29688-C02-01, and National Natural Science Foundation of China grant 61020106002.Publicad

Com o diabo no corpo: os terríveis papagaios do Brasil colônia

Desde a Antiguidade, papagaios, periquitos e afins (Psittacidae) fascinaram os europeus por seu vivo colorido e uma notável capacidade de interação com seres humanos. A descoberta do Novo Mundo nada faria além de acrescentar novos elementos ao tráfico de animais exóticos há muito estabelecido pelos europeus com a África e o Oriente. Sem possuir grandes mamíferos, a América tropical participaria desse comércio com o que tinha de mais atrativo, essencialmente felinos, primatas e aves - em particular os papagaios, os quais eram embarcados em bom número. Contudo, a julgar pelos documentos do Brasil colônia, esses voláteis podiam inspirar muito pouca simpatia, pois nenhum outro animal - exceto as formigas - foi tantas vezes mencionado como praga para a agricultura. Além disso, alguns psitácidas mostravam-se tão loquazes que inspiravam a séria desconfiança de serem animais demoníacos ou possessos, pois só três classes de entidades - anjos, homens e demônios - possuíam o dom da palavra. Nos dias de hoje, vários representantes dos Psittacidae ainda constituem uma ameaça para a agricultura, enquanto os indivíduos muito faladores continuam despertando a suspeita de estarem possuídos pelo demônio. Transcendendo a mera curiosidade, essa crença exemplifica o quão intrincadas podem ser as relações do homem com o chamado “mundo natural”, revelando um universo mais amplo e multifacetado do que se poderia supor a princípio. Nesse sentido, a existência de aves capazes de falar torna essa relação ainda mais complexa e evidencia que as dificuldades de estabelecer o limite entre o animal e o humano se estendem além dos primatas e envolvem as mais inusitadas espécies zoológicas.Since ancient times, parrots and their allies (Psittacidae) have fascinated Europeans by their striking colors and notable ability to interact with human beings. The discovery of the New World added new species to the international exotic animal trade, which for many centuries had brought beasts to Europe from Africa and the Orient. Lacking large mammals, tropical America participated in this trade with its most appealing species, essentially felines, primates and birds - especially parrots - which were shipped in large numbers. It should be noted, however, that at times these birds were not well liked. In fact, according to documents from colonial Brazil, only the ants rank higher than parrots as the animals most often mentioned as agricultural pests. On the other hand, some of these birds were so chatty that people suspected them to be demonic or possessed animals, since only three classes of beings - angels, men and demons - have the ability to speak. Nowadays, several Psittacidae still constitute a threat to agriculture, and the suspicion that extremely talkative birds were demon possessed has also survived. More than a joke or a mere curiosity, this belief exemplifies how intricate man’s relationships with the “natural world” may be. In this sense, the existence of birds that are able to speak adds a further twist to these relationships, demonstrating that the problem of establishing a boundary between the animal and the human does not only involve primates, but also includes some unusual zoological species

Gestión del conocimiento. Perspectiva multidisciplinaria. Volumen 17

El libro “Gestión del Conocimiento. Perspectiva Multidisciplinaria”, Volumen 17 de la Colección Unión Global, es resultado de investigaciones. Los capítulos del libro, son resultados de investigaciones desarrolladas por sus autores. El libro es una publicación internacional, seriada, continua, arbitrada, de acceso abierto a todas las áreas del conocimiento, orientada a contribuir con procesos de gestión del conocimiento científico, tecnológico y humanístico. Con esta colección, se aspira contribuir con el cultivo, la comprensión, la recopilación y la apropiación social del conocimiento en cuanto a patrimonio intangible de la humanidad, con el propósito de hacer aportes con la transformación de las relaciones socioculturales que sustentan la construcción social de los saberes y su reconocimiento como bien público

Dynamics of the Burlan and Pomacochas Lakes Using SAR Data in GEE, Machine Learning Classifiers, and Regression Methods

Amazonas is a mountain region in Peru with high cloud cover, so using optical data in the analysis of surface changes of water bodies (such as the Burlan and Pomacochas lakes in Peru) is difficult, on the other hand, SAR images are suitable for the extraction of water bodies and delineation of contours. Therefore, in this research, to determine the surface changes of Burlan and Pomacochas lakes, we used Sentinel-1 A/B products to analyse the dynamics from 2014 to 2020, in addition to evaluating the procedure we performed a photogrammetric flight and compared the shapes and geometric attributes from each lake. For this, in Google Earth Engine (GEE), we processed 517 SAR images for each lake using the following algorithms: a classification and regression tree (CART), Random Forest (RF) and support vector machine (SVM).) 2021-02-10, then; the same value was validated by comparing the area and perimeter values obtained from a photogrammetric flight, and the classification of a SAR image of the same date. During the first months of the year, there were slight increases in the area and perimeter of each lake, influenced by the increase in rainfall in the area. CART and Random Forest obtained better results for image classification, and for regression analysis, Support Vector Regression (SVR) and Random Forest Regression (RFR) were a better fit to the data (higher R2), for Burlan and Pomacochas lakes, respectively. The shape of the lakes obtained by classification was similar to that of the photogrammetric flight. For 2021-02-10, for Burlan Lake, all 3 classifiers had area values between 42.48 and 43.53, RFR 44.47 and RPAS 45.63 hectares. For Pomacohas Lake, the 3 classifiers had area values between 414.23 and 434.89, SVR 411.89 and RPAS 429.09 hectares. Ultimately, we seek to provide a rapid methodology to classify SAR images into two categories and thus obtain the shape of water bodies and analyze their changes over short periods. A methodological scheme is also provided to perform a regression analysis in GC using five methods that can be replicated in different thematic areas