scholarly journals A novel approach for designing large-scale river temperature monitoring networks

2015 ◽  
Vol 47 (3) ◽  
pp. 569-590 ◽  
Author(s):  
F. L. Jackson ◽  
I. A. Malcolm ◽  
David M. Hannah
Keyword(s):  
Water Temperature ◽  
Geographical Information Systems ◽  
Statistical Power ◽  
Large Scale ◽  
Full Range ◽  
Monitoring Network ◽  
Temperature Monitoring ◽  
Geographical Information ◽  
Monitoring Networks ◽  
River Temperature

Water temperature is an important control on processes in aquatic systems and particularly for freshwater fish, affecting growth, survival and demographic characteristics. In recognition of this importance, the Scottish Government has prioritised developing a robust national river temperature monitoring network. Advances in geographical information systems, spatial statistics and field data loggers make large-scale river temperature monitoring increasingly possible. However, duplication of environmental and thermal characteristics among monitoring sites means many networks have lower than expected statistical power. This paper describes a novel methodology for network design, illustrated by the development of the Scotland River Temperature Monitoring Network. A literature review identified processes controlling stream temperature and associated landscape controls. Metrics indicative of these landscape controls were calculated for points every 500 m along the river network. From these points, sites were chosen to cover the full range of observed environmental gradients and combinations of controlling variables. The resulting network contains sites with unique characteristics covering the range of relevant environmental characteristics observed in Scottish salmon rivers. The network will thus have minimal redundancy, often not seen in large networks, and high statistical power to separate the relative importance of predictor variables thereby allowing large-scale water temperature predictions.

scholarly journals Multivariate clustering of reindeer herding districts in Sweden according to range prerequisites for reindeer husbandry

Rangifer ◽  
2009 ◽  
Vol 27 (2) ◽  
pp. 107-119
Author(s):  
Henrik Lundqvist ◽  
Öje Danell
Keyword(s):  
Geographical Information Systems ◽  
Large Scale ◽  
Global Climate ◽  
Meteorological Data ◽  
Principal Component ◽  
Geographical Information ◽  
Reindeer Herding ◽  
Factors Affecting ◽  
Decision Tools ◽  
Forage Value

The 51 reindeer herding districts in Sweden vary in productivity and prerequisites for reindeer herding. In this study we characterize and group reindeer herding districts based on relevant factors affecting reindeer productivity, i.e. topography, vegetation, forage value, habitat fragmentation and reachability, as well as season lengths, snow fall, ice-crust probability, and insect harassment, totally quantified in 15 variables. The herding districts were grouped into seven main groups and three single outliers through cluster analyses. The largest group, consisting of 14 herding districts, was further divided into four subgroups. The range properties of herding districts and groups of districts were characterized through principal component analyses. By comparisons of the suggested grouping of herding districts with existing administrative divisions, these appeared not to coincide. A new division of herding districts into six administrative sets of districts was suggested in order to improve administrative planning and management of the reindeer herding industry. The results also give possibilities for projections of alterations caused by an upcoming global climate change. Large scale investigations using geographical information systems (GIS) and meteorological data would be helpful for administrative purposes, both nationally and internationally, as science-based decision tools in legislative, economical, ecological and structural assessments. Abstract in Swedish / Sammanfattning: Multivariat gruppering av svenska samebyar baserat på renbetesmarkernas grundförutsettningar Svenska renskötselområdet består av 51 samebyar som varierar i produktivitet och förutsättningar för renskötsel. Vi analyserade variationen mellan samebyar med avseende på 15 variabler som beskriver topografi, vegetation, betesvärde, fragmentering av betesmarker, klimat, skareförekomst och aktivitet av parasiterande insekter och vi föreslår en indelning av samebyar i tio grupper. Den största gruppen, som bestod av 14 samebyar, delades vidare in i 4 undergrupper. Klusteranalyser med 4 olika linkage-varianter användes till att gruppera samebyarna. Principalkomponentsanalys användes för att kartlägga undersökta variabler och de resulterande samebygruppernas karaktär. Samebygrupperna följde inte länsgränser och tre samebyar föll ut som enskilda grupper. Denna undersökning ger underlag för jämförelser mellan samebyar med beaktande av likheter och olikheter i fråga om produktivitet och funktionella särdrag istället för länsgränser och historik. Vi föreslår en ny administrativ indelning i sex områden som skulle kunna fungera som ett alternativt underlag för planering och beslut som rör produktionsaspekter i rennäringen. Resultaten ger också underlag för förutsägelser av förändringar i samebyars produktionsförutsättningar till följd av klimatförändringar.

scholarly journals Using 1D HEC-RAS Modeling and LiDAR Data to Improve Flood Hazard Maps Accuracy: A Case Study from Jijia Floodplain (NE Romania)

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1624 ◽  
Author(s):  
Elena Huţanu ◽  
Alin Mihu-Pintilie ◽  
Andrei Urzica ◽  
Larisa Elena Paveluc ◽  
Cristian Constantin Stoleriu ◽  
...  
Keyword(s):  
Geographical Information Systems ◽  
Large Scale ◽  
Flood Hazard ◽  
Hydraulic Modeling ◽  
Geographical Information ◽  
Computer Algorithms ◽  
Hazard Maps ◽  
Modeling Software ◽  
Recurrence Intervals ◽  
Flood Hazard Maps

The ability to extract flood hazard settings in highly vulnerable areas like populated floodplains by using new computer algorithms and hydraulic modeling software is an important aspect of any flood mitigation efforts. In this framework, the 1D/2D hydraulic models, which were generated based on a Light Detection and Ranging (LiDAR) derivate Digital Elevation Model (DEM) and processed within Geographical Information Systems (GIS), can improve large-scale flood hazard maps accuracy. In this study, we developed the first flood vulnerability assessment for 1% (100-year) and 0.1% (1000-year) recurrence intervals within the Jijia floodplain (north-eastern Romania), based on 1D HEC-RAS hydraulic modeling and LiDAR derivate DEM with 0.5 m spatial resolution. The results were compared with official flood hazards maps developed for the same recurrence intervals by the hydrologists of National Administration “Romanian Waters” (NARW) based on MIKE SHE modeling software and a DEM with 2 m spatial resolutions. It was revealed that the 1D HEC-RAS provides a more realistic perspective about the possible flood threats within Jijia floodplain and improves the accuracy of the official flood hazard maps obtained according to Flood Directive 2007/60/EC.

scholarly journals Assessment of Switchgrass-Based Bioenergy Supply Using GIS-Based Fuzzy Logic and Network Optimization in Missouri (U.S.A.)

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4516
Author(s):  
Huynh Truong Gia Nguyen ◽  
Erik Lyttek ◽  
Pankaj Lal ◽  
Taylor Wieczerak ◽  
Pralhad Burli
Keyword(s):  
Land Use ◽  
Fuzzy Logic ◽  
Network Optimization ◽  
Urban Areas ◽  
Geographical Information Systems ◽  
Large Scale ◽  
Spatial Information ◽  
Geographical Information ◽  
Negative Consequences ◽  
Analytical Approaches

Bioenergy has been globally recognized as one of the sustainable alternatives to fossil fuels. An assured supply of biomass feedstocks is a crucial bottleneck for the bioenergy industry emanating from uncertainties in land-use changes and future prices. Analytical approaches deriving from geographical information systems (GIS)-based analysis, mathematical modeling, optimization analyses, and empirical techniques have been widely used to evaluate the potential for bioenergy feedstock. In this study, we propose a three-phase methodology integrating fuzzy logic, network optimization, and ecosystem services assessment to estimate potential bioenergy supply. The fuzzy logic analysis uses multiple spatial criteria to identify suitable biomass cultivating regions. We extract spatial information based on favorable conditions and potential constraints, such as developed urban areas and croplands. Further, the network analysis uses the road network and existing biorefineries to evaluate feedstock production locations. Our analysis extends previous studies by incorporating biodiversity and ecologically sensitive areas into the analysis, as well as incorporating ecosystem service benefits as an additional driver for adoption, ensuring that biomass cultivation will minimize the negative consequences of large-scale land-use change. We apply the concept of assessing the potential for switchgrass-based bioenergy in Missouri to the proposed methodology.

Wildland fire spread modelling using cellular automata: evolution in large-scale spatially heterogeneous environments under fire suppression tactics

2011 ◽  
Vol 20 (5) ◽  
pp. 633 ◽  
Author(s):  
A. Alexandridis ◽  
L. Russo ◽  
D. Vakalis ◽  
G. V. Bafas ◽  
C. I. Siettos
Keyword(s):  
Cellular Automata ◽  
Geographical Information Systems ◽  
Large Scale ◽  
Fire Suppression ◽  
Meteorological Data ◽  
Fire Spread ◽  
Geographical Information ◽  
Heterogeneous Environments ◽  
Detailed Model ◽  
Technical Specifications

We show how microscopic modelling techniques such as Cellular Automata linked with detailed geographical information systems (GIS) and meteorological data can be used to efficiently predict the evolution of fire fronts on mountainous and heterogeneous wild forest landscapes. In particular, we present a lattice-based dynamic model that includes various factors, ranging from landscape and earth statistics, attributes of vegetation and wind field data to the humidity of the fuel and the spotting transfer mechanism. We also attempt to model specific fire suppression tactics based on air tanker attacks utilising technical specifications as well as operational capabilities of the aircrafts. We use the detailed model to approximate the dynamics of a large-scale fire that broke out in a region on the west flank of the Greek National Park of Parnitha Mountain in June of 2007. The comparison between the simulation and the actual results showed that the proposed model predicts the fire-spread characteristics in an adequate manner. Finally, we discuss how such a detailed model can be exploited in order to design and develop, in a systematic way, fire risk management policies.

Large-scale patterns in habitat structure on subtidal rocky reefs in New South Wales

2000 ◽  
Vol 51 (3) ◽  
pp. 255 ◽  
Author(s):  
N. L. Andrew ◽  
A. L. O'Neill
Keyword(s):  
Sea Urchin ◽  
Geographical Information Systems ◽  
Large Scale ◽  
Size Structure ◽  
New South ◽  
New South Wales ◽  
Geographical Information ◽  
South Wales ◽  
Subtidal Rocky Reefs ◽  
A Site

Aerial photography was used to estimate the representation of shallow subtidal habitats in New South Wales. Sixty sites, each between 4 and 5 hectares, were mapped with Geographical Information Systems software using ortho-rectified images digitized from 1:8000-scale photographs and ‘ground truthed’ in the field by divers. Barrens habitat covered an estimated 50% (s.e. = 3.9) of nearshore reefs between Port Stephens and Disaster Bay. Coverage of barrens habitat was greatest in Disaster Bay (68%, s.e. = 6.7) and least south of Disaster Bay (1%, s.e. = 0.3). There were clear differences among localities in the area of reef within the mapped sites; those at Cape Howe, Nadgee, and Turingal were significantly smaller in area than all others. There was no clear latitudinal trend in these differences but there was evidence of sand inundation at a site at Nadgee, where the reef was small. Differences in the densities and size-structure of the sea urchin Centrostephanus rodgersiiat 27 of the mapped sites provide a basis for testing relationships between the demography of this species and the persistence of the barrens habitat. The extensive coverage of the barrens habitat in New South Wales is likely to limit the productivity of the abalone industry. The development of a sea urchin fishery may have large impacts on habitat representation on nearshore reefs.

scholarly journals Application and Design of Patient Temperature Acquisition System Based on Wireless Sensor Network

2017 ◽  
Vol 13 (05) ◽  
pp. 18
Author(s):  
Huijie Ding
Keyword(s):  
Large Scale ◽  
Monitoring Network ◽  
Temperature Monitoring ◽  
Wireless Sensor ◽  
Large Hospital ◽  
Clinical Measurement ◽  
Number Of Patients ◽  
Abnormal Phenomenon ◽  
Time Acquisition ◽  
Abnormal Temperature

The purpose of this study is to achieve large-scale real-time acquisition and monitoring of the patient’s body temperature, for noticing abnormal phenomenon of temperature in time. In the ward, arrange ZigBee wireless temperature monitoring network, realize the ward patients temperature measurement and gathering of temperature related clinical data, achieve the temperature monitoring network through the serial RS232 and PC communication, and PC receives, displays, and processes the data through the serial port. The results showed that the system can also realize the acquisition, transmission and monitoring of a plurality of temperature signals, and send out the alarm in abnormal temperature. As a result, the system can be widely used in clinical measurement, suitable for popularization in large hospital with a large number of patients

Understanding Effectiveness of Eco Monitoring Networks: Information Theoretical Perspective

2013 ◽  
Vol 765-767 ◽  
pp. 2213-2219
Author(s):  
Su Min Li
Keyword(s):  
Large Scale ◽  
Theoretical Perspective ◽  
Monitoring Network ◽  
The Internet ◽  
Monitoring Networks ◽  
Large Networks ◽  
Moderate Size ◽  
Large Scale Data ◽  
Underlying Network ◽  
Scale Data

This work studies eco monitoring networks. As eco monitoring networks have been used to monitor large networks, questions arise whether decentralized inference is efficient and whether an eco monitoring network with a moderate size can monitor an underlying network at the Internet scale. This work studies the local effectiveness of decentralized inference done by individual monitors. Information theoretical measures, i.e., conditional non-uniformity factor is applied to quantify the effectiveness. Large-scale data from DShield is used to access the effectiveness of a real eco monitoring network.

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