Preprints

Filtering by Subject: Computer Sciences

Characterising Land Cover Change in Brunei Darussalam’s Capital District

Matthew Kok Ming Ng, Zahratu Shabrina, Boyana Buyuklieva

Published: 2019-06-03
Subjects: Computer Sciences, Earth Sciences, Environmental Indicators and Impact Assessment, Environmental Monitoring, Environmental Sciences, Natural Resources and Conservation, Physical Sciences and Mathematics

In fast-developing regions, like Southeast-Asia, monitoring urban areas presents a challenge given the lack of publicly available data. This is an issue that precludes the nuances of a citys growth and undermines the way land-use is considered with respect to planning. The issue of data availability is very much present in the small nation of Brunei. Little is still known about the spatiotemporal [...]

Investigation of the Likelihood of Green Infrastructure (GI) Enhancement along Linear Waterways or on Derelict Sites (DS) Using Machine Learning.

S M Labib

Published: 2019-05-08
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Environmental Monitoring, Environmental Sciences, Geographic Information Sciences, Geography, Physical Sciences and Mathematics, Social and Behavioral Sciences, Spatial Science

Studies evaluating potential of Green Infrastructure (GI) development using traditional Boolean logic-based multi-criteria analysis methods are not capable of predicting future GI development under dynamic urban scape. This study evaluated robust soft-computing-based methods of artificial intelligence (Artificial Neural Network, Adaptive Neuro-Fuzzy Interface-System) and used statistical [...]

What has Global Sensitivity Analysis ever done for us? A systematic review to support scientific advancement and to inform policy-making in earth system modelling

Thorsten Wagener, Francesca Pianosi

Published: 2019-04-08
Subjects: Civil and Environmental Engineering, Computer Sciences, Earth Sciences, Engineering, Environmental Sciences, Life Sciences, Mathematics, Medicine and Health Sciences, Physical Sciences and Mathematics, Risk Analysis, Statistics and Probability

Computer models are essential tools in the earth system sciences. They underpin our search for understanding of earth system functioning and support decision- and policy-making across spatial and temporal scales. To understand the implications of uncertainty and environmental variability on the identification of such earth system models and their predictions, we can rely on increasingly powerful [...]

Matlab/R workflows to assess critical choices in Global Sensitivity Analysis using the SAFE toolbox

Valentina Noacco, Fanny Sarrazin, Francesca Pianosi, Thorsten Wagener

Published: 2019-04-05
Subjects: Applied Mathematics, Civil and Environmental Engineering, Computer Sciences, Earth Sciences, Engineering, Environmental Sciences, Physical Sciences and Mathematics, Risk Analysis, Statistics and Probability

Global Sensitivity Analysis (GSA) is a set of statistical techniques to investigate the effects of the uncertainty in the input factors of a mathematical model on the model’s outputs. The value of GSA for the construction, evaluation, and improvement of earth system models is reviewed in a companion paper by Wagener and Pianosi [n.d.]. The present paper focuses on the implementation of GSA and [...]

Reconstruction of Cloud Vertical Structure with a Generative Adversarial Network

Jussi Leinonen, Alexandre Guillaume, Tianle Yuan

Published: 2019-02-19
Subjects: Artificial Intelligence and Robotics, Atmospheric Sciences, Computer Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics

We demonstrate the feasibility of solving atmospheric remote sensing problems with machine learning using conditional generative adversarial networks (CGANs), implemented using convolutional neural networks (CNNs). We apply the CGAN to generating two-dimensional cloud vertical structures that would be observed by the CloudSat satellite-based radar, using only the collocated Moderate-Resolution [...]

Gap Filling of High-Resolution Soil Moisture for SMAP/Sentinel-1: A Two-Layer Machine Learning-Based Framework

Hanzi Mao, Dhruva Kathuria, Nicholas Duffield, Binayak P. Mohanty

Published: 2019-02-11
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Environmental Sciences, Hydrology, Physical Sciences and Mathematics, Water Resource Management

As the most recent 3 km soil moisture product from the Soil Moisture Active Passive (SMAP) mission, the SMAP/Sentinel-1 L2_SM_SP product has a unique capability to provide global-scale 3 km soil moisture estimates through the fusion of radar and radiometer microwave observations. The spatial and temporal availability of this high-resolution soil moisture product depends on concurrent radar and [...]

Factor Analysis by R Programming to Assess Variability Among Environmental Determinants of the Mariana Trench

Polina Lemenkova

Published: 2019-01-28
Subjects: Computer Sciences, Earth Sciences, Education, Engineering, Environmental Monitoring, Environmental Sciences, Environmental Studies, Geographic Information Sciences, Geography, Geology, Geomorphology, Geophysics and Seismology, Graphics and Human Computer Interfaces, Life Sciences, Marine Biology, Oceanography, Oceanography and Atmospheric Sciences and Meteorology, Other Earth Sciences, Other Geography, Other Oceanography and Atmospheric Sciences and Meteorology, Physical and Environmental Geography, Physical Sciences and Mathematics, Programming Languages and Compilers, Remote Sensing, Science and Mathematics Education, Sedimentology, Social and Behavioral Sciences, Spatial Science, Tectonics and Structure, Water Resource Management

The aim of this work is to identify main impact factors affecting variations in the geomorphology of the Mariana Trench which is the deepest place of the Earth, located in the west Pacific Ocean: steepness angle and structure of the sediment compression. The Mariana Trench presents a complex ecosystem with highly interconnected factors: geology (sediment thickness and tectonics including four [...]

Google Earth web service as a support for GIS mapping in geospatial research at universities

Polina Lemenkova

Published: 2019-01-25
Subjects: Computer Sciences, Earth Sciences, Ecology and Evolutionary Biology, Education, Environmental Education, Environmental Monitoring, Environmental Sciences, Environmental Studies, Geographic Information Sciences, Geography, Life Sciences, Natural Resources Management and Policy, Other Computer Sciences, Other Earth Sciences, Other Environmental Sciences, Other Geography, Physical and Environmental Geography, Physical Sciences and Mathematics, Remote Sensing, Science and Mathematics Education, Social and Behavioral Sciences, Spatial Science, Terrestrial and Aquatic Ecology

The geospatial work has been performed using combination of the Google Earth imagery, Landsat TM images and Erdas Imagine GIS software. The advantage of utilizing Google Earth scenes with Landsat TM satellite imagery, along with GIS techniques and methods, for inventorying land cover types has been demonstrated for landscape studies. Combination of land cover type characteristics and landscape [...]

The Use of Satellite Images for Assessment of Environmental Vulnerability and Resilience of the Arctic Wetlands

Polina Lemenkova

Published: 2019-01-25
Subjects: Computer Sciences, Earth Sciences, Education, Environmental Education, Environmental Indicators and Impact Assessment, Environmental Monitoring, Environmental Sciences, Environmental Studies, Geographic Information Sciences, Geography, Geomorphology, Life Sciences, Natural Resources and Conservation, Natural Resources Management and Policy, Other Earth Sciences, Other Environmental Sciences, Physical Sciences and Mathematics, Remote Sensing, Science and Mathematics Education, Social and Behavioral Sciences, Spatial Science, Water Resource Management

The research paper focuses on the environmental problem of Yamal region, geographically located in the Russian Yamal-Nenets autonomous region, northern-central Russia. This region is characterized by the unique nature and environmental conditions, combining two physical-geographical regions: sub-Arctic and Arctic moss-lichen tundra and permafrost conditions. The recent changes in global climate [...]

Topology, homogeneity and scale factors for object detection: application of eCognition software for urban mapping using multispectral satellite image

Polina Lemenkova

Published: 2019-01-25
Subjects: Computer Sciences, Earth Sciences, Education, Educational Methods, Engineering, Environmental Education, Environmental Monitoring, Environmental Sciences, Environmental Studies, Geographic Information Sciences, Geography, Graphics and Human Computer Interfaces, International and Area Studies, Life Sciences, Natural Resources Management and Policy, Other Computer Sciences, Other Earth Sciences, Other Environmental Sciences, Other Physical Sciences and Mathematics, Physical and Environmental Geography, Physical Sciences and Mathematics, Remote Sensing, Science and Mathematics Education, Social and Behavioral Sciences, Spatial Science, Sustainability

The research scope of this paper is to apply spatial object based image analysis (OBIA) method for processing panchromatic multispectral image covering study area of Brussels for urban mapping. The aim is to map different land cover types and more specifically, built-up areas from the very high resolution (VHR) satellite image using OBIA approach. A case study covers urban landscapes in the [...]

A test case for application of convolutional neural networks to spatio-temporal climate data: Re-identifying clustered weather patterns

Ashesh Kumar Chattopadhyay, Pedram Hassanzadeh, Saba Pasha

Published: 2019-01-01
Subjects: Applied Mathematics, Computer Sciences, Earth Sciences, Engineering, Environmental Sciences, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Planetary Sciences

Convolutional neural networks (CNNs) can potentially provide powerful tools for classifying and identifying patterns in climate and environmental data. However, because of the inherent complexities of such data, which are often spatio-temporal, chaotic, and non-stationary, the CNN algorithms must be designed/evaluated for each specific dataset and application. Yet to start, CNN, a supervised [...]

Calibration of astigmatic particle tracking velocimetry based on generalized Gaussian feature extraction

Simon Franchini, Alexandros Charogiannis, Christos N. Markides, Martin J. Blunt, Sam Krevor

Published: 2018-11-20
Subjects: Artificial Intelligence and Robotics, Computer Sciences, Earth Sciences, Engineering, Fluid Dynamics, Hydrology, Life Sciences, Physical Sciences and Mathematics, Physics

Flow and transport in porous media are driven by pore scale processes. Particle tracking in transparent porous media allows for the observation of these processes at the time scale of ms. We demonstrate an application of defocusing particle tracking using brightfield illumination and a CMOS camera sensor. The resulting images have relatively high noise levels. To address this challenge, we [...]

SSPipeline: A pipeline for estimating and characterizing uncertainty in coastal storm surge levels

John Letey, Mingxuan Zhang, Tony Wong

Published: 2018-10-22
Subjects: Computer Sciences, Engineering, Numerical Analysis and Scientific Computing, Physical Sciences and Mathematics, Statistical Models, Statistics and Probability

Effective management of coastal risks demands projections of flood hazards that account for a wide variety of potential sources of uncertainty. Two typical approaches for estimating flood hazards include (1) direct physical process-based modeling of the storms themselves and (2) statistical modeling of the distributions and relevant characteristics of extreme sea level events. Recently, flexible [...]

Quantifying natural delta variability using a multiple-point geostatistics prior uncertainty model

Céline Scheidt, Anjali M. Fernandes, Chris Paola, Jef Caers

Published: 2018-09-30
Subjects: Artificial Intelligence and Robotics, Civil and Environmental Engineering, Computer Sciences, Earth Sciences, Electrical and Computer Engineering, Engineering, Environmental Engineering, Geology, Geomorphology, Other Civil and Environmental Engineering, Other Engineering, Physical Sciences and Mathematics, Sedimentology, Stratigraphy, Theory and Algorithms

We address the question of quantifying uncertainty associated with autogenic pattern variability in a channelized transport system by means of a modern geostatistical method. This question has considerable relevance for practical subsurface applications as well, particularly those related to uncertainty quantification relying on Bayesian approaches. Specifically, we show how the autogenic [...]

Learning about climate change uncertainty enables flexible water infrastructure planning

Sarah Marie Fletcher, Megan Lickley, Kenneth Strzepek

Published: 2018-09-29
Subjects: Civil and Environmental Engineering, Civil Engineering, Climate, Computer Sciences, Earth Sciences, Engineering, Environmental Sciences, Hydrology, Numerical Analysis and Scientific Computing, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Statistics and Probability, Water Resource Management

Water resources planning requires making decisions about infrastructure development under substantial uncertainty in future regional climate conditions. However, uncertainty in climate change projections will evolve over the 100-year lifetime of a dam as new climate observations become available. Flexible strategies in which infrastructure is proactively designed to be changed in the future have [...]

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