New Paradigm in Geotechnical Performance Monitoring Using Remote Sensing

2018 ◽  
pp. 195-201
Author(s):  
Thomas Oommen ◽  
El Hachemi Bouali ◽  
Rudiger Escobar Wolf
Keyword(s):  
Remote Sensing ◽  
Performance Monitoring ◽  
New Paradigm

Programmable Integrated Photonics

2020 ◽  
Author(s):  
José Capmany ◽  
Daniel Pérez
Keyword(s):  
Integrated Circuit ◽  
Performance Monitoring ◽  
Low Cost ◽  
Limiting Factors ◽  
External Control ◽  
Integrated Photonics ◽  
New Paradigm ◽  
Photonic Integrated Circuit ◽  
And Performance ◽  
Application Fields

Programmable Integrated Photonics (PIP) is a new paradigm that aims at designing common integrated optical hardware configurations, which by suitable programming can implement a variety of functionalities that, in turn, can be exploited as basic operations in many application fields. Programmability enables by means of external control signals both chip reconfiguration for multifunction operation as well as chip stabilization against non-ideal operation due to fluctuations in environmental conditions and fabrication errors. Programming also allows activating parts of the chip, which are not essential for the implementation of a given functionality but can be of help in reducing noise levels through the diversion of undesired reflections. After some years where the Application Specific Photonic Integrated Circuit (ASPIC) paradigm has completely dominated the field of integrated optics, there is an increasing interest in PIP justified by the surge of a number of emerging applications that are and will be calling for true flexibility, reconfigurability as well as low-cost, compact and low-power consuming devices. This book aims to provide a comprehensive introduction to this emergent field covering aspects that range from the basic aspects of technologies and building photonic component blocks to the design alternatives and principles of complex programmable photonics circuits, their limiting factors, techniques for characterization and performance monitoring/control and their salient applications both in the classical as well as in the quantum information fields. The book concentrates and focuses mainly on the distinctive features of programmable photonics as compared to more traditional ASPIC approaches.

scholarly journals Ecosystem Performance Monitoring of Rangelands by Integrating Modeling and Remote Sensing

2012 ◽  
Vol 65 (3) ◽  
pp. 241-252 ◽  
Author(s):  
Bruce K. Wylie ◽  
Stephen P. Boyte ◽  
Donald J. Major
Keyword(s):  
Remote Sensing ◽  
Performance Monitoring

Towards a new paradigm for innovative training methods for capacity building in remote sensing

2006 ◽  
Vol 38 (10) ◽  
pp. 2290-2298
Author(s):  
R.K. Gupta ◽  
P.M. Bala Manikavelu ◽  
D. Vijayan ◽  
T.S. Prasad
Keyword(s):  
Remote Sensing ◽  
Capacity Building ◽  
Training Methods ◽  
New Paradigm

Crowdsourcing for Rapid Damage Assessment: The Global Earth Observation Catastrophe Assessment Network (GEO-CAN)

2011 ◽  
Vol 27 (1_suppl1) ◽  
pp. 179-198 ◽  
Author(s):  
Shubharoop Ghosh ◽  
Charles K. Huyck ◽  
Marjorie Greene ◽  
Stuart P. Gill ◽  
John Bevington ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Damage Assessment ◽  
Primary Source ◽  
Earth Observation ◽  
Research Centre ◽  
New Paradigm ◽  
Joint Research ◽  
Satellite Applications ◽  
Training And Research ◽  
Post Disaster

This paper provides an account of how the Global Earth Observation Catastrophe Assessment Network (GEO-CAN) was formed to facilitate a rapid damage assessment after the 12 January 2010 Haiti earthquake. GEO-CAN emerged from the theory of crowdsourcing and remote sensing-based damage interpretation and represents a new paradigm in post-disaster damage assessment. The GEO-CAN community, working with the World Bank (WB), the United Nation Institute for Training and Research (UNITAR) Operational Satellite Applications Programme (UNOSAT) and the European Commission's Joint Research Centre (JRC) led the way for a rapid Post Disaster Needs Assessment (PDNA) utilizing remote-sensing based analysis as the primary source of information for building damage. The results of the GEO-CAN damage assessment were incorporated into the final PDNA framework developed by the WB-UNOSAT-JRC and adopted by the Haitian government. The GEO-CAN initiative provides valuable lessons on multi-agency collaboration, rapid and implementable damage assessment protocols under extreme situations for the disaster management profession, developmental organizations, and society.

scholarly journals Spatial Analysis of Urban Residential Sensitivity to Heatwave Events: Case Studies in Five Megacities in China

2021 ◽  
Vol 13 (20) ◽  
pp. 4086
Author(s):  
Guoqing Zhi ◽  
Bin Meng ◽  
Juan Wang ◽  
Siyu Chen ◽  
Bin Tian ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Big Data ◽  
Spatial Analysis ◽  
Urban Planning ◽  
Language Processing ◽  
Temporal Trends ◽  
New Paradigm ◽  
Geographic Space ◽  
Low Sensitivity ◽  
The Relationship

Urban heatwaves increase residential health risks. Identifying urban residential sensitivity to heatwave risks is an important prerequisite for mitigating the risks through urban planning practices. This research proposes a new paradigm for urban residential sensitivity to heatwave risks based on social media Big Data, and describes empirical research in five megacities in China, namely, Beijing, Nanjing, Wuhan, Xi’an and Guangzhou, which explores the application of this paradigm to real-world environments. Specifically, a method to identify urban residential sensitive to heatwave risks was developed by using natural language processing (NLP) technology. Then, based on remote sensing images and Weibo data, from the perspective of the relationship between people (group perception) and the ground (meteorological temperature), the relationship between high temperature and crowd sensitivity in geographic space was studied. Spatial patterns of the residential sensitivity to heatwaves over the study area were characterized at fine scales, using the information extracted from remote sensing information, spatial analysis, and time series analysis. The results showed that the observed residential sensitivity to urban heatwave events (HWEs), extracted from Weibo data (Chinese Twitter), best matched the temporal trends of HWEs in geographic space. At the same time, the spatial distribution of observed residential sensitivity to HWEs in the cities had similar characteristics, with low sensitivity in the urban center but higher sensitivity in the countryside. This research illustrates the benefits of applying multi-source Big Data and intelligent analysis technologies to the understand of impacts of heatwave events on residential life, and provide decision-making data for urban planning and management.

Geospatial Big Data: New Paradigm of Remote Sensing Applications

2019 ◽  
Vol 12 (10) ◽  
pp. 3841-3851 ◽  
Author(s):  
Xingdong Deng ◽  
Penghua Liu ◽  
Xiaoping Liu ◽  
Ruoyu Wang ◽  
Yuanying Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Big Data ◽  
New Paradigm ◽  
Sensing Applications ◽  
Remote Sensing Applications

scholarly journals RS-DARTS: A Convolutional Neural Architecture Search for Remote Sensing Image Scene Classification

2021 ◽  
Vol 14 (1) ◽  
pp. 141
Author(s):  
Zhen Zhang ◽  
Yang Zhang ◽  
Shanghao Liu ◽  
Wenbo Chen
Keyword(s):  
Remote Sensing ◽  
Network Architecture ◽  
Classification Performance ◽  
Scene Classification ◽  
New Paradigm ◽  
Neural Architecture ◽  
Optimal Network ◽  
Evaluation Phase ◽  
Benchmark Datasets ◽  
Two Phases

Due to the superiority of convolutional neural networks, many deep learning methods have been used in image classification. The enormous difference between natural images and remote sensing images makes it difficult to directly utilize or modify existing CNN models for remote sensing scene classification tasks. In this article, a new paradigm is proposed that can automatically design a suitable CNN architecture for scene classification. A more efficient search framework, RS-DARTS, is adopted to find the optimal network architecture. This framework has two phases. In the search phase, some new strategies are presented, making the calculation process smoother, and better distinguishing the optimal and other operations. In addition, we added noise to suppress skip connections in order to close the gap between trained and validation processing and ensure classification accuracy. Moreover, a small part of the neural network is sampled to reduce the redundancy in exploring the network space and speed up the search processing. In the evaluation phase, the optimal cell architecture is stacked to construct the final network. Extensive experiments demonstrated the validity of the search strategy and the impressive classification performance of RS-DARTS on four public benchmark datasets. The proposed method showed more effectiveness than the manually designed CNN model and other methods of neural architecture search. Especially, in terms of search cost, RS-DARTS consumed less time than other NAS methods.

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