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Ms. Irini Soubry
University of Saskatchewan

Basic Info


Research Keywords & Expertise

0 ecosystem health assessment
0 Remote sensing – land
0 Grassland monitoring
0 Ecosystem monitoring and modelling
0 Remote Sensing (laser scanning and photogrammetry)

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Short Biography

Irini Soubry is a PhD Candidate at the Department of Geography and Planning, University of Saskatchewan. She has a MSc. in Geoinformation in Environmental Management from the Mediterranean Agronomic Institute of Chania, Greece (2019), and a MEng in Rural and Surveying Engineering from the Aristotle University of Thessaloniki, Greece (2016), where she specialized in Remote Sensing, Photogrammetry, Cartography, and Cadastre. She has participated in research projects in Greece, Spain, and Canada involving precision agriculture in vineyards, wildfire management, land surface phenology, cultural heritage documentation, and grassland and forest health with the use of remote sensing, UAVs, GIS, and laser scanning techniques. She is a member of the Canadian Remote Sensing Society (CRSS) and a general member of its student chapter. Her current scientific interests lie within grassland ecology and ecosystem health monitoring with remote sensing approaches.

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Review
Published: 18 August 2021 in Remote Sensing
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It is important to protect forest and grassland ecosystems because they are ecologically rich and provide numerous ecosystem services. Upscaling monitoring from local to global scale is imperative in reaching this goal. The SDG Agenda does not include indicators that directly quantify ecosystem health. Remote sensing and Geographic Information Systems (GIS) can bridge the gap for large-scale ecosystem health assessment. We systematically reviewed field-based and remote-based measures of ecosystem health for forests and grasslands, identified the most important ones and provided an overview on remote sensing and GIS-based measures. We included 163 English language studies within terrestrial non-tropical biomes and used a pre-defined classification system to extract ecological stressors and attributes, collected corresponding indicators, measures, and proxy values. We found that the main ecological attributes of each ecosystem contribute differently in the literature, and that almost half of the examined studies used remote sensing to estimate indicators. The major stressor for forests was “climate change”, followed by “insect infestation”; for grasslands it was “grazing”, followed by “climate change”. “Biotic interactions, composition, and structure” was the most important ecological attribute for both ecosystems. “Fire disturbance” was the second most important for forests, while for grasslands it was “soil chemistry and structure”. Less than a fifth of studies used vegetation indices; NDVI was the most common. There are monitoring inconsistencies from the broad range of indicators and measures. Therefore, we recommend a standardized field, GIS, and remote sensing-based approach to monitor ecosystem health and integrity and facilitate land managers and policy-makers.

ACS Style

Irini Soubry; Thuy Doan; Thuan Chu; Xulin Guo. A Systematic Review on the Integration of Remote Sensing and GIS to Forest and Grassland Ecosystem Health Attributes, Indicators, and Measures. Remote Sensing 2021, 13, 3262 .

AMA Style

Irini Soubry, Thuy Doan, Thuan Chu, Xulin Guo. A Systematic Review on the Integration of Remote Sensing and GIS to Forest and Grassland Ecosystem Health Attributes, Indicators, and Measures. Remote Sensing. 2021; 13 (16):3262.

Chicago/Turabian Style

Irini Soubry; Thuy Doan; Thuan Chu; Xulin Guo. 2021. "A Systematic Review on the Integration of Remote Sensing and GIS to Forest and Grassland Ecosystem Health Attributes, Indicators, and Measures." Remote Sensing 13, no. 16: 3262.

Technical note
Published: 22 June 2021 in Environments
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Woody plant encroachment (WPE), the expansion of native and non-native trees and shrubs into grasslands, has led to degradation worldwide. In the Canadian prairies, western snowberry and wolfwillow shrubs are common encroachers, whose cover is currently unknown. As the use of remote sensing in grassland monitoring increases, opportunities to detect and map these woody species are enhanced. Therefore, the purpose of this study is to identify the optimal season for detection of the two shrubs, to determine the sensitive wavelengths and bands that allow for their separation, and to investigate differences in separability potential between a hyperspectral and broadband multispectral approach. We do this by using spring, summer, and fall field-based spectra of both shrubs for the calculation of spectral separability metrics and for the simulation of broadband spectra. Our results show that the summer offers higher discrimination between the two species, especially when using the red and blue spectral regions and to a lesser extent the green region. The fall season fails to provide significant spectral separation along the wavelength spectrum. Moreover, there is no significant difference in the results from the hyperspectral or broadband approach. Nevertheless, cross-validation with satellite imagery is needed to confirm the current results.

ACS Style

Irini Soubry; Xulin Guo. Seasonal Spectral Separation of Western Snowberry and Wolfwillow in Grasslands with Field Spectroradiometer and Simulated Multispectral Bands. Environments 2021, 8, 60 .

AMA Style

Irini Soubry, Xulin Guo. Seasonal Spectral Separation of Western Snowberry and Wolfwillow in Grasslands with Field Spectroradiometer and Simulated Multispectral Bands. Environments. 2021; 8 (7):60.

Chicago/Turabian Style

Irini Soubry; Xulin Guo. 2021. "Seasonal Spectral Separation of Western Snowberry and Wolfwillow in Grasslands with Field Spectroradiometer and Simulated Multispectral Bands." Environments 8, no. 7: 60.

Journal article
Published: 29 April 2021 in Sensors
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Woody plant encroachment (WPE), the expansion of native and non-native trees and shrubs into grasslands, is a less studied factor that leads to declines in grassland ecosystem health. With the increasing application of remote sensing in grassland monitoring and measuring, it is still difficult to detect WPE at its early stages when its spectral signals are not strong enough. Even at late stages, woody species have strong vegetation characteristics that are commonly categorized as healthy ecosystems. We focus on how shrub encroachment can be detected through remote sensing by looking at the biophysical and spectral properties of the WPE grassland ecosystem, investigating the appropriate season and wavelengths that identify shrub cover, testing the spectral separability of different shrub cover groups and by revealing the lowest shrub cover that can be detected by remote sensing. Biophysical results indicate spring as the best season to distinguish shrubs in our study area. The earliest shrub encroachment can be identified most likely only when the cover reaches between 10% and 25%. A correlation between wavelength spectra and shrub cover indicated four regions that are statistically significant, which differ by season. Furthermore, spectral separability of shrubs increases with their cover; however, good separation is only possible for pure shrub pixels. From the five separability metrics used, Transformed divergence and Jeffries-Matusita distance have better interpretations. The spectral regions for pure shrub pixel separation are slightly different from those derived by correlation and can be explained by the influences from land cover mixtures along our study transect.

ACS Style

Irini Soubry; Xulin Guo. Identification of the Optimal Season and Spectral Regions for Shrub Cover Estimation in Grasslands. Sensors 2021, 21, 3098 .

AMA Style

Irini Soubry, Xulin Guo. Identification of the Optimal Season and Spectral Regions for Shrub Cover Estimation in Grasslands. Sensors. 2021; 21 (9):3098.

Chicago/Turabian Style

Irini Soubry; Xulin Guo. 2021. "Identification of the Optimal Season and Spectral Regions for Shrub Cover Estimation in Grasslands." Sensors 21, no. 9: 3098.

Conference paper
Published: 01 January 2021 in Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management
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ACS Style

Irini Soubry; Ioannis Manakos; Chariton Kalaitzidis. Recent Advances in Land Surface Phenology Estimation with Multispectral Sensing. Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management 2021, 134 -145.

AMA Style

Irini Soubry, Ioannis Manakos, Chariton Kalaitzidis. Recent Advances in Land Surface Phenology Estimation with Multispectral Sensing. Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management. 2021; ():134-145.

Chicago/Turabian Style

Irini Soubry; Ioannis Manakos; Chariton Kalaitzidis. 2021. "Recent Advances in Land Surface Phenology Estimation with Multispectral Sensing." Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management , no. : 134-145.

Journal article
Published: 01 June 2017 in Journal of Unmanned Vehicle Systems
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This paper deals with the monitoring of vineyards for the assessment of water stress and grape maturity using an unmanned aerial vehicle (UAV) equipped with multispectral/infrared and red-green-blue (RGB) cameras. The study area is the Gerovassiliou winery in the region of Epanomi, Greece, cultivated with the local grape variety of Malagouzia. Fifteen flights were conducted with a fixed-wing UAV during the months of April to August 2015 with a mean interval of 2 weeks. The flight images were photogrammetrically processed for the production of orthoimages and then used to extract indices for the detection of water stress. Grape samples were collected 2 days before harvest and then analyzed and correlated with remote sensing indices. The TCARI/OSAVI index showed the best correlation with the grape samples with regards to maturity and the likelihood of water stress. Furthermore, the final results were of high resolution as far as farm purposes are concerned (a scale of 1:500 for all three sensors). These facts suggest that the instruments used in this study represent a fast, reliable, and efficient solution to the evaluation of crops for agricultural applications.

ACS Style

I. Soubry; P. Patias; V. Tsioukas. Monitoring vineyards with UAV and multi-sensors for the assessment of water stress and grape maturity. Journal of Unmanned Vehicle Systems 2017, 5, 37 -50.

AMA Style

I. Soubry, P. Patias, V. Tsioukas. Monitoring vineyards with UAV and multi-sensors for the assessment of water stress and grape maturity. Journal of Unmanned Vehicle Systems. 2017; 5 (2):37-50.

Chicago/Turabian Style

I. Soubry; P. Patias; V. Tsioukas. 2017. "Monitoring vineyards with UAV and multi-sensors for the assessment of water stress and grape maturity." Journal of Unmanned Vehicle Systems 5, no. 2: 37-50.