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dr. M. Huesca Martinez (Margarita)

Assistant Professor

About Me

I received a PhD in Forestry and Agriculture from the Technical University of Madrid. During my dissertation I developed a framework to assess the spatial and temporal variability of different environmental processes, such as forest fires, drought, vegetation dynamics, across different ecoregions, using statistical time series analysis applied to multispectral time series data. After my Ph.D., I received a postdoctoral scholar position at the University of California, Davis (USA), in the centre for spatial technologies and remote sensing (CSTARS), where I began working with imaging spectroscopy and LiDAR data. During this time, I was focused on combining several types of remote sensing data, such as multispectral, hyperspectral, LiDAR and UAV data, with in situ measurements to develop models for assessing biodiversity, drought effects, evapotranspiration, vegetation structure, functional traits, and tree mortality among others in very different ecosystems such as Mediterranean savannas, mix broadleaf-conifer forest, alpine forest, wetland o tropical forest.


Expertise

Earth & Environmental Sciences
# Forest Fire
# Index
# Modis
# Ndvi
# Time Series
# Time Series Analysis
Agriculture & Biology
# Forest Fires
# Moderate Resolution Imaging Spectroradiometer

Organisations

Research

For my future research plans, I am interested in:

(1) understanding the spatial and temporal variability in ecosystem functioning under global climate change scenarios and its relationship with biodiversity loss and the effect in natural resources;

(2) developing robust spatial and temporal models for monitoring and forecasting forest dynamics under the influence of several disturbance factors, such as forest fires, insect attacks, invasive species, and drought, among others; 

(3) determining how we can apply each type of remote sensing data to improve our knowledge of ecosystem processes and develop a monitoring system that allows for upscaling and downscaling from local to global level. 

 

Publications

Recent
Gaubert, T., Adeline, K. , Martinez, M. H., Ustin, S., & Briottet, X. (2023). Inversion of Radiative Transfer Model Through One-Dimensional Convolutional Neural Network To Retrieve Foliar Traits of Temperate Forest Canopies With Imaging Spectrocopy. Paper presented at 43rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023, Pasadena, California, United States.
Boakye, A. S. , Huesca Martinez, M. , & Paris, C. (2023). A study on the impact of the spatial and spectral resolution on plant species richness in Mediterranean regions using optical remote sensing data. In L. Bruzzone, & F. Bovolo (Eds.), Image and Signal Processing for Remote Sensing XXIX (Vol. 12733). Article 127330W SPIE. https://doi.org/10.1117/12.2679116
Huesca, M., & Ustin, S. L. (2021). Baseline invasive species community mapping at Lower Klamath Wetland, Oregon-California (USA). In IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings (pp. 5907-5909). (IEEE International Geoscience and Remote Sensing Symposium IGARSS; Vol. 2021). IEEE. https://doi.org/10.1109/IGARSS47720.2021.9553787
Huesca, M., Ustin, S. L., Shapiro, K. D., Boynton, R., & Thorne, J. H. (2021). Detection of drought‐induced blue oak mortality in the Sierra Nevada Mountains, California. Ecosphere, 12(6), 1-20. Article e03558. https://doi.org/10.1002/ecs2.3558
Miraglio, T. , Huesca, M., Gastellu-Etchegorry, J. P., Schaaf, C., Adeline, K. R. M., Ustin, S. L., & Briottet, X. (2021). Impact of modeling abstractions when estimating leaf mass per area and equivalent water thickness over sparse forests using a hybrid method. Remote sensing, 13(16), 1-22. Article 3235. https://doi.org/10.3390/rs13163235
Cicuendez, V., Rodriguez-Rastrero, M., Recuero, L. , Huesca Martinez, M., Schmid, T., Inclan, R., Litago, J., Sanchez-Giron, V., & Palacios-Orueta, A. (2020). First insights on soil respiration prediction across the growth stages of rainfed barley based on simulated MODIS and Sentinel-2 spectral indices. Remote sensing, 12(17), 1-23. https://doi.org/10.3390/rs12172724
Huesca Martinez, M., Riano, D., & Ustin, S. (2019). Spectral mapping methods applied to LiDAR data: application to fuel type mapping. International Journal of Applied Earth Observation and Geoinformation, 74, 1-10. https://doi.org/10.1016/j.jag.2018.08.020
Recuero, L., Litago, J., Pinzon, J. , Huesca Martinez, M., Moyano, M. C., & Palacios-Orueta, A. (2019). Mapping periodic patterns of global vegetation based on spectral analysis of NDVI time series. Remote sensing, 11(21), 1-21. https://doi.org/10.3390/rs11212497
Recuero, L., Wiese, K. , Huesca Martinez, M., Cicuendez, V., Litago, J., Tarquis Alfonso, A. M., & Palacios-Orueta, A. (2019). Fallowing temporal patterns assessment in rainfed agricultural areas based on NDVI time series autocorrelation values. International Journal of Applied Earth Observation and Geoinformation, 82, 1-11. https://doi.org/10.1016/j.jag.2019.05.023

UT Research Information System

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Courses Academic Year  2023/2024

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.
 

Courses Academic Year  2022/2023

Contact Details

 
 

Visiting Address

University of Twente
Faculty of Geo-Information Science and Earth Observation
Langezijds (building no. 19), room 1114
Hallenweg 8
7522NH  Enschede
The Netherlands

Mailing Address

University of Twente
Faculty of Geo-Information Science and Earth Observation
Langezijds  1114
P.O. Box 217
7500 AE Enschede
The Netherlands

Organisations

University of Twente Drienerlolaan 5
7522 NB Enschede
+31 (0)53 489 9111
info@utwente.nl
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