Duchemin B.,CNRS Center for the Study of the Biosphere from Space |
Fieuzal R.,CNRS Center for the Study of the Biosphere from Space |
Rivera M.A.,ITSON |
Ezzahar J.,Cadi Ayyad University |
And 4 more authors.
Remote Sensing | Year: 2015
Regional analysis of water use efficiency (WUE) is a relevant method for diagnosing the performance of irrigation systems in water-limited environments. In this study, we investigated the potential of FORMOSAT-2 images to provide spatial estimates of WUE over irrigated wheat crops cultivated within the semi-arid Yaqui Valley, in the northwest of Mexico. FORMOSAT-2 provided us with a unique dataset of 36 images at a high resolution (8 m) encompassing the wheat growing season from November 2007 to May 2008. Time series of green leaf area index were derived from these satellite images and used to calibrate a simple crop/water balance model. The method was applied over an 8 × 8 km2 irrigated area on up to 530 wheat fields. It allowed us to accurately reproduce the time courses of Leaf Area Index and dry aboveground biomass, as well as evapotranspiration and soil moisture. In a second step, we analyzed the variations of WUE as the ratio of accumulated dry aboveground biomass to seasonal evapotranspiration. Despite the study area being rather small and homogeneous (soil, climate), we observed a large range in wheat biomass production, from 5 to 15 t·ha-1, which was primarily related to the timing of plant emergence. In contrast, the seasonal evapotranspiration only varied from 350 to 450 mm, with no evident link with sowing practices. A significant gain in crop water productivity was found for the fields sown the earliest (maximal WUE around 3.5 kg·m-3) compared to those sown the latest (minimal WUE around 1.5 kg·m-3). These results demonstrated the value of the FORMOSAT-2 images to provide spatial estimates of crop production and water consumption. The detailed information provided by such high space and time resolution imaging systems is highly valuable to identify agricultural practices that could enlarge crop water productivity. © 2015 by the authors.
Longoria-Gandara O.,Jesuit University |
Parra-Michel R.,CINVESTAV |
Carrasco-Alvarez R.,University of Guadalajara |
Mobile Information Systems | Year: 2016
This paper presents a novel iterative detection and channel estimation scheme that combines the effort of superimposed training (ST) and pilot-aided training (PAT) for multiple-input multiple-output (MIMO) flat fading channels. The proposed method, hereafter known as joint mean removal ST and PAT (MRST-PAT), implements an iterative detection and channel estimation that achieves the performance of data-dependent ST (DDST) algorithm, with the difference that the data arithmetic cyclic mean is estimated and removed from data at the receiver's end. It is demonstrated that this iterative and cooperative detection and channel estimator algorithm surpasses the effects of data detection identifiability condition that DDST has shown when higher orders of modulation are used. Theoretical performance of the MRST-PAT scheme is provided and corroborated by numerical simulations. In addition, the performance comparison between the proposed method and different MIMO channel estimation techniques is analyzed. The joint effort between ST and PAT shows that MRST-PAT is a solid candidate in communications systems for multiamplitude constellations in Rayleigh fading channels, while achieving high-throughput data rates with manageable complexity and bit-error rate (BER) as a figure of merit. © 2016 Omar Longoria-Gandara et al.
Castro L.A.,ITSON |
Beltran J.,CICESE |
Perez M.,CICESE |
Quintana E.,CICESE |
And 2 more authors.
UbiComp 2014 - Adjunct Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing | Year: 2014
Mobile phones include a variety of sensors that can be used to develop context-aware applications and gather data about the user's behavior, including the places he visits, his level of activity and how frequently and with whom he socializes. The collection and analysis of these data has been the focus of recent attention in ubiquitous computing, giving rise to the field known as mobile sensing. In this work, we present a collaborative extension to InCense, a toolkit to facilitate behavioral data gathering from populations of mobile phone users. InCense aims at providing people with little or no technical background with a tool that assists in the rapid design and implementation of mobile phone sensing campaigns. By extending the architecture of InCense to support distributed sensing campaigns we are able to incorporate several strategies aimed at optimizing battery, storage, and bandwidth. These issues represent significant challenges in sensing campaigns that generate considerable amounts of data (i.e., collecting audio) or quickly drain the battery in the device (i.e., GPS), given the limitations of mobile devices. In this work, collaborative sensing is used to decide which mobile phone should capture audio when two or more devices are potentially recording a similar audio signal. Copyright 2014 ACM.
Bazdresch M.,ITESO Periferico sur Manuel Gomez Morin |
Cortez J.,ITSON |
Longoria-Gandara O.,ITESO Periferico sur Manuel Gomez Morin |
Journal of Applied Research and Technology | Year: 2012
Hybrid MIMO space-time codes combine the benefits of spatial multiplexing with diversity gain to achieve both high spectral efficiency and link reliability. In this paper, we present a family of hybrid codes, known as LD STBC-VBLAST codes, along with a receiver architecture suitable for low-complexity hardware implementation. We show that, under Rayleigh fading, the performance of LD STBC-VBLAST codes is superior to other recently proposed hybrid codes. We also present a technique to derive, from a given propagation scenario, spatially correlated MIMO channel models adequate for space-time coding performance analysis. Using this technique, we evaluate the performance of LD STBC-VBLAST codes under several correlated channels.
Vargas-Rosales C.,ITESM |
Mass-Sanchez J.,CINVESTAV |
Ruiz-Ibarra E.,ITSON |
Torres-Roman D.,CINVESTAV |
International Journal of Distributed Sensor Networks | Year: 2015
In recent years, the use of wireless sensor networks has been increasing. Localization is a fundamental problem in wireless sensor networks (WSNs), since location information is essential for diverse applications such as tracking, quality network coverage, health, and energy efficiency. In this paper performance of localization algorithms such as range-free, range-based, and fuzzy-based decision is evaluated. We introduce a modification of an algorithm by providing weights to the correlation matrix to improve correctness. In all the cases the accuracy, precision, and computational complexity are evaluated as performance metrics. Location algorithms are evaluated using two scenarios, a first stage where all nodes are randomly distributed in a given area and a second scenario where four APs (access points) are placed on fixed positions and unknown nodes are randomly distributed within the sensing area. The received signal strength (RSS) is used to estimate the position of a node of interest. In the simulation results we show how our modified algorithm improves localization. On the other hand, we also have acceptable accuracy using distance-based algorithms, but they are more complex computationally. © 2015 C. Vargas-Rosales et al.