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Dr

Angelica Suarez

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Overview

Background

Angelica is a senior spatial scientist with a strong background in remote sensing and environmental analysis. Her work bridges science and practice, applying spatial technologies to improve land and resource management. She has contributed to research across a wide range of applications — from crop and vegetation monitoring to assessing land use change driven by different sectors.

Her research interests include the evaluation and adoption of remote sensing technologies for crop and vegetation monitoring, tracking native vegetation clearing and regrowth, analysing environmental and production factors that influence crop performance, and developing spatial datasets for yield forecasting, crop phenotyping, and long-term landscape monitoring.

Availability

Dr Angelica Suarez is:
Available for supervision

Qualifications

  • Doctor of Philosophy of Remote Sensing, University of Southern Queensland

Research impacts

Through her work, Angelica plays a key role in building and strengthening the capability of government partners and researchers to monitor environmental change at multiple scales using Earth observation technologies.

Works

Search Professor Angelica Suarez’s works on UQ eSpace

11 works between 2014 and 2025

1 - 11 of 11 works

2025

Book Chapter

Sensing and geotechnologies for soil characterization

Tighe, M., Novais, J. J.M., Demattê, J. A.M., Ravansari, R. and Suarez, L. A. (2025). Sensing and geotechnologies for soil characterization. Unlocking the secrets of soil: applying AI and sensor technologies for sustainable land use. (pp. 203-231) edited by David C. Weindorf, Somsubhra Chakraborty and Bin Li. Amsterdam, Netherlands: Elsevier. doi: 10.1016/b978-0-443-29879-0.00001-0

Sensing and geotechnologies for soil characterization

2024

Journal Article

Exploring the relationship between very-high-resolution satellite imagery data and fruit count for predicting mango yield at multiple scales

Torgbor, Benjamin Adjah, Sinha, Priyakant, Rahman, Muhammad Moshiur, Robson, Andrew, Brinkhoff, James and Suarez, Luz Angelica (2024). Exploring the relationship between very-high-resolution satellite imagery data and fruit count for predicting mango yield at multiple scales. Remote Sensing, 16 (22) 4170, 1-23. doi: 10.3390/rs16224170

Exploring the relationship between very-high-resolution satellite imagery data and fruit count for predicting mango yield at multiple scales

2024

Journal Article

Forecasting carrot yield with optimal timing of Sentinel 2 image acquisition

Suarez, L. A., Robertson-Dean, M., Brinkhoff, J. and Robson, A. (2024). Forecasting carrot yield with optimal timing of Sentinel 2 image acquisition. Precision Agriculture, 25 (2), 570-588. doi: 10.1007/s11119-023-10083-z

Forecasting carrot yield with optimal timing of Sentinel 2 image acquisition

2023

Journal Article

Early-season forecasting of citrus block-yield using time series remote sensing and machine learning: A case study in Australian orchards

Suarez, Luz Angelica, Robson, Andrew and Brinkhoff, James (2023). Early-season forecasting of citrus block-yield using time series remote sensing and machine learning: A case study in Australian orchards. International Journal of Applied Earth Observation and Geoinformation, 122 103434, 103434. doi: 10.1016/j.jag.2023.103434

Early-season forecasting of citrus block-yield using time series remote sensing and machine learning: A case study in Australian orchards

2021

Conference Publication

Olive treewater stress detection using daily multispectral imagery

Brinkhoff, James, Schultz, Alex, Suarez, Luz Angelica and Robson, Andrew J. (2021). Olive treewater stress detection using daily multispectral imagery. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Electronic Network, 12-16 July 2021. Piscataway, NJ, United States: IEEE. doi: 10.1109/igarss47720.2021.9553729

Olive treewater stress detection using daily multispectral imagery

2020

Journal Article

Accuracy of carrot yield forecasting using proximal hyperspectral and satellite multispectral data

Suarez, Luz Angelica, Robson, Andrew, McPhee, John, O'Halloran, Julie and van Sprang, Celia (2020). Accuracy of carrot yield forecasting using proximal hyperspectral and satellite multispectral data. Precision Agriculture, 21 (6), 1304-1326. doi: 10.1007/s11119-020-09722-6

Accuracy of carrot yield forecasting using proximal hyperspectral and satellite multispectral data

2017

Journal Article

Multi-spectral imaging from an unmanned aerial vehicle enables the assessment of seasonal leaf area dynamics of sorghum breeding lines

Potgieter, Andries B., George-Jaeggli, Barbara, Chapman, Scott C., Laws, Kenneth, Cadavid, Luz A. Suarez, Wixted, Jemima, Watson, James, Eldridge, Mark, Jordan, David R. and Hammer, Graeme L. (2017). Multi-spectral imaging from an unmanned aerial vehicle enables the assessment of seasonal leaf area dynamics of sorghum breeding lines. Frontiers in Plant Science, 8 1532. doi: 10.3389/fpls.2017.01532

Multi-spectral imaging from an unmanned aerial vehicle enables the assessment of seasonal leaf area dynamics of sorghum breeding lines

2017

Journal Article

The rate, extent and spatial predictors of forest loss (2000-2012) in the terrestrial protected areas of the Philippines

Apan, Armando, Suarez, Luz Angelica, Maraseni, Tek and Castillo, Jose Alan (2017). The rate, extent and spatial predictors of forest loss (2000-2012) in the terrestrial protected areas of the Philippines. Applied Geography, 81, 32-42. doi: 10.1016/j.apgeog.2017.02.007

The rate, extent and spatial predictors of forest loss (2000-2012) in the terrestrial protected areas of the Philippines

2017

Journal Article

Detection of phenoxy herbicide dosage in cotton crops through the analysis of hyperspectral data

Suarez, L. A., Apan, A. and Werth, J. (2017). Detection of phenoxy herbicide dosage in cotton crops through the analysis of hyperspectral data. International Journal of Remote Sensing, 38 (23), 6528-6553. doi: 10.1080/01431161.2017.1362128

Detection of phenoxy herbicide dosage in cotton crops through the analysis of hyperspectral data

2016

Journal Article

Hyperspectral sensing to detect the impact of herbicide drift on cotton growth and yield

Suarez, L. A., Apan, A. and Werth, J. (2016). Hyperspectral sensing to detect the impact of herbicide drift on cotton growth and yield. ISPRS Journal of Photogrammetry and Remote Sensing, 120, 65-76. doi: 10.1016/j.isprsjprs.2016.08.004

Hyperspectral sensing to detect the impact of herbicide drift on cotton growth and yield

2014

Conference Publication

Prioritising carbon sequestration areas in southern queensland using time series modis net primary productivity (npp) imagery 

Apan, A., Cadavid, L. A. Suarez, Richardson, L. and Maraseni, T. (2014). Prioritising carbon sequestration areas in southern queensland using time series modis net primary productivity (npp) imagery . ISPRS Technical Commission VIII Symposium, Hyderabad, India, 9-12 December 2014. Gottinge, Germany: Copernicus Gesellschaft MBH. doi: 10.5194/isprsarchives-xl-8-549-2014

Prioritising carbon sequestration areas in southern queensland using time series modis net primary productivity (npp) imagery 

Supervision

Availability

Dr Angelica Suarez is:
Available for supervision

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Media

Enquiries

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