dr. M. Huesca Martinez (Margarita)

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.

Earth & Environmental Sciences

# Forest Fire
# Index
# Modis
# Ndvi
# Time Series
# Time Series Analysis

Agriculture & Biology

# Forest Fires
# Moderate Resolution Imaging Spectroradiometer

Faculty of Geo-Information Science and Earth Observation (ITC), Department of Natural Resources (NRS)

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.

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). SPIE. https://doi.org/10.1117/12.2679116

Miraglio, T., Adeline, K. , Huesca Martinez, M., Ustin, S., & Briottet, X. (2022). Assessing vegetation traits estimates accuracies from the future SBG and biodiversity hyperspectral missions over two Mediterranean Forests. International journal of remote sensing, 43(10), 3537-3562. https://doi.org/10.1080/01431161.2022.2093143

Darvishzadeh, R. , Neinavaz, E. , Huesca Martinez, M. , Skidmore, A. K. , Nieuwenhuis, W., Fernández, N., & Wårlind, D. (2022). On the relationship of primary productivity and remotely sensed canopy biophysical variables. Abstract from EGU General Assembly 2022, Vienna, Austria. https://doi.org/10.5194/egusphere-egu22-10409

Darvishzadeh, R. , Neinavaz, E. , Huesca Martinez, M. , Nieuwenhuis, W., Fernández, N. , & Skidmore, A. K. (2022). Remotely sensed vegetation biophysical parameters as proxies for primary productivity estimation. Abstract from Living Planet Symposium, LPS 2022, Bonn, North Rhine-Westphalia, Germany. https://express.converia.de/frontend/index.php?page_id=18446&v=AuthorList&do=17&day=all&q=darvish&entity_id=393612

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. 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

Miraglio, T., Adeline, K. , Huesca, M., Ustin, S., & Briottet, X. (2020). Monitoring LAI, chlorophylls, and carotenoids content of a woodland savanna using hyperspectral imagery and 3D radiative transfer modeling. Remote sensing, 12(1), 1-26. https://doi.org/doi.org/10.3390/rs12010028

Miraglio, T., Adeline, K. , Huesca Martinez, M., Ustin, S., & Briottet, X. (2020). Joint use of PROSAIL and DART for fast LUT building: application to gap fraction and leaf biochemistry estimations over sparse oak stands. Remote sensing, 12, 1-19. https://doi.org/10.3390/rs12182925

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

Miraglio, T., Adeline, K. , Huesca Martinez, M., Ustin, S., & Briottet, X. (2020). Correction: Miraglio, T., et al. Monitoring LAI, chlorophylls, and carotenoids content of a woodland savanna using hyperspectral imagery and 3D radiative transfer modeling. Remote Sensing 2020, 12 , 28. Remote sensing, 12(14), 1-7. https://doi.org/10.3390/rs12142263

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. Advance online publication. 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

Huesca Martinez, M., Roth, K., Garcia Alonso, M., & Ustin, S. (2019). Discrimination of canopy structural types in the Sierra Nevada Mountains in central California. Remote sensing, 11(9), 1-29. https://doi.org/10.3390/rs11091100

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+31534893414

m.huescamartinez@utwente.nl

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

Faculty of Geo-Information Science and Earth Observation (ITC), Department of Natural Resources (NRS)

University of Twente Drienerlolaan 5
7522 NB Enschede

+31 (0)53 489 9111
info@utwente.nl
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