2024

2023

Meza, K., Torres-Rua, A.F., Hipps, L.,  Kustas, W.P., Gao, R., Christiansen, L., Kopp, K., Nieto, H., Burchard‑Levine, V.,  Martín, M.P., Coopmans, C. and Gowing, I. (2023) Spatial estimation of actual evapotranspiration over irrigated turfgrass using sUAS thermal and multispectral imagery and TSEB model. Irrig Sci (2023). https://doi.org/10.1007/s00271-023-00899-y

Martín, M.P.; Ponce, B.; Echavarría, P.; Dorado, J.; Fernández-Quintanilla, C. (2023) Early-Season Mapping of Johnsongrass (Sorghum halepense), Common Cocklebur (Xanthium strumarium) and Velvetleaf (Abutilon theophrasti) in Corn Fields Using Airborne Hyperspectral Imagery. Agronomy, 13, 528. https://doi.org/10.3390/agronomy13020528

2022

Simpson, J., Holman, F., Nieto, H., El-Madany, T., Migliavacca, M., Martín, M.P., Burchard-Levine, V.,Carrara, A., Blöcher, S., Fiener, P. & Kaplan, J. (2022). UAS-based high resolution mapping of evapotranspiration in a Mediterranean tree-grass ecosystem. Agricultural and Forest Meteorology. 321. 108981. https://doi.org/10.1016/j.agrformet.2022.108981.

Luo, Y., Pacheco-Labrador, J., Richardson, A., Seyednasrollah, B., Pérez-Priego, O., González Cascón, R., Martín, M.P., Moreno, G., Nair, R., Wutzler, T., Bucher, S., Carrara, A., Cremonese, E., El-Madany, T.,Filippa, G., Galvagno, M., Hammer, T., Ma, X., Martini, D. & Migliavacca, M. (2022). Evergreen broadleaf greenness and its relationship with leaf flushing, aging, and water fluxes. Agricultural and Forest Meteorology. 323. 109060. https://doi.org/10.1016/j.agrformet.2022.109060.

Rodríguez-Rodríguez, D. & Martinez-Vega, J. (2022). Ecological effectiveness of marine protected areas across the globe in the scientific literature. Advances in Marine Biology. 10.1016/bs.amb.2022.07.002.

Martínez-Vega, J., & Rodríguez-Rodríguez, D. (2022). Protected Area Effectiveness in the Scientific Literature: A Decade-Long Bibliometric Analysis. Land, 11(6), 924. https://doi.org/10.3390/land11060924

Burchard-Levine, V., Riaño, D., Vilar, L., Martín, M.P. & Becerra Corral, J. (2022). A review of in-situ sampling protocols to support the remote sensing of vegetation. GeoFocus. Revista Internacional De Ciencia Y Tecnología De La Información Geográfica, (29), 59–87. https://doi.org/10.21138/GF.780

Burchard-Levine, V., Nieto, H., Kustas, W. P., Gao, F., Alfieri, J. G., Prueger, J. H., Hipps, L. E., Bambach-Ortiz, N., McElrone, A. J., Castro, S. J., Alsina, M. M., McKee, L. G., Zahn, E., Bou-Zeid, E., & Dokoozlian, N. (2022). Application of a remote-sensing three-source energy balance model to improve evapotranspiration partitioning in vineyards. Irrigation Science. https://doi.org/10.1007/s00271-022-00787-x 

Martini, D., Sakowska, K., Wohlfahrt, G., Pacheco-Labrador, J., van der Tol, C., Porcar-Castell, A., Magney, T.S., Carrara, A., Colombo, R., El-Madany, T.S., Gonzalez-Cascon, R., Martín, M.P., Julitta, T., Moreno, G., Rascher, U., Reichstein, M., Rossini, M. and Migliavacca, M. (2022), Heatwave breaks down the linearity between sun-induced fluorescence and gross primary production. New Phytol. https://doi.org/10.1111/nph.17920 

Burchard-Levine, V., Nieto, H., Riaño, D., Kustas, W. P., Migliavacca, M., El-Madany, T. S., Nelson, J. A., Andreu, A., Carrara, A., Beringer, J., Baldocchi, D., & Martín, M. P. (2022). A remote sensing-based three-source energy balance model to improve global estimations of evapotranspiration in semi-arid tree-grass ecosystems. Global Change Biology, 28, 1493–1515. https://doi.org/10.1111/gcb.16002 

2021

El‐Madany, T. S., Reichstein, M., Carrara, A., Martín, M. P., Moreno, G., Gonzalez‐Cascon, R., ...Burchard-Levine, V., ... & Migliavacca, M. (2021). How nitrogen and phosphorus availability change water use efficiency in a Mediterranean savanna ecosystem. Journal of Geophysical Research: Biogeosciences, 126(5), e2020JG006005. doi: https://doi.org/10.1016/j.envsoft.2021.105200

Burchard-Levine, V., Nieto, H., Riaño, D., Migliavacca, M., El-Madany, T. S., Guzinski, R., ... & Martín, M. P. (2021). The effect of pixel heterogeneity for remote sensing based retrievals of evapotranspiration in a semi-arid tree-grass ecosystem. Remote Sensing of Environment, 260, 112440. doi: https://doi.org/10.1016/j.rse.2021.112440 

Vilar, L., Herrera, S., Tafur-García, E., Yebra, M., Martínez-Vega, J., Echavarría, P., & Martín, M. P. (2021). Modelling wildfire occurrence at regional scale from land use/cover and climate change scenarios. Environmental Modelling & Software, 145, 105200.Chicago

Pacheco-Labrador, J., El-Madany, T. S., van der Tol, C., Martin, M. P., Gonzalez-Cascon, R., Perez-Priego, O., ... & Migliavacca, M. (2021). senSCOPE: Modeling mixed canopies combining green and brown senesced leaves. Evaluation in a Mediterranean Grassland. Remote Sensing of Environment, 257, 112352.

Bogdanovich, E., Perez-Priego, O., El-Madany, T. S., Guderle, M., Pacheco-Labrador, J., Levick, S. R., ... & Migliavacca, M. (2021). Using terrestrial laser scanning for characterizing tree structural parameters and their changes under different management in a Mediterranean open woodland. Forest Ecology and Management, 486, 118945.Chicago 

Biriukova, K., Pacheco-Labrador, J., Migliavacca, M., Mahecha, M. D., Gonzalez-Cascon, R., Martín, M. P., and Rossini, M. (2021). Performance of singular spectrum analysis in separating seasonal and fast physiological dynamics of solar-induced chlorophyll fluorescence and PRI optical signals. Journal of Geophysical Research: Biogeosciences, 126, e2020JG006158. https://doi.org/10.1029/2020JG006158 

Hornero, A., North, P. R. J., Zarco-Tejada, P. J., Rascher, U., Martín, M. P., Migliavacca, M., & Hernandez-Clemente, R. (2021). Assessing the contribution of understory sun-induced chlorophyll fluorescence through 3-D radiative transfer modelling and field data. Remote Sensing of Environment, 253, 112195.

2020 

Burchard-Levine, V., Nieto, H., Riaño, D., Migliavacca, M., El-Madany, T. S., Perez-Priego, O., Martín, M. P. (2020). Seasonal Adaptation of the Thermal-Based Two-Source Energy Balance Model for Estimating Evapotranspiration in a Semiarid Tree-Grass Ecosystem. Remote Sensing, 12(6), 904. doi: https://doi.org/10.3390/rs12060904

Gajardo, J., Riaño, D., García, M., Salas, J., & Martín, M. P. (2020). Estimation of Canopy Gap Fraction from Terrestrial Laser Scanner Using an Angular Grid to Take Advantage of the Full Data Spatial Resolution. Remote Sensing, 12(10). doi: 10.3390/rs12101596

García, M., North, P., Viana-Soto, A., Stavros, N. E., Rosette, J., Martín, M. P., . . . Zhao, K. (2020). Evaluating the potential of LiDAR data for fire damage assessment: A radiative transfer model approach. Remote Sensing of Environment, 247, 111893. doi: https://doi.org/10.1016/j.rse.2020.111893

Pacheco-Labrador, J., El-Madany, T. S., Martin, M. P., Gonzalez-Cascon, R., Carrara, A., Moreno, G., Migliavacca, M. (2020). Combining hyperspectral remote sensing and eddy covariance data streams for estimation of vegetation functional traits. Biogeosciences Discuss., 2020, 1-38. doi: 10.5194/bg-2019-501

Martín, M.P., Pacheco-Labrador, J., González-Cascón, R., Moreno, G., Migliavacca, M., García, M., Yebra, M., & Riaño, D. (2020). Estimation of essential vegetation variables in a dehesa ecosystem using reflectance factors simulated at different phenological stages. Revista de Teledetección, No 55 [S.l.], n. 55, p. 31-48, june 2020. ISSN 1988-8740. Available at: https://polipapers.upv.es/index.php/raet/article/view/13394. Date accessed: 03 dec. 2021. doi: https://doi.org/10.4995/raet.2020.13394.

García, M., Riaño, D., Yebra M, Salas, J., Cardil A, Monedero, S., Ramirez, J., Martín, M.P., Vilar, L, Gajardo, J., Ustin, S. A. (2020). Live Fuel Moisture Content Product from Landsat TM Satellite Time Series for Implementation in Fire Behavior Models. Remote Sensing.; 12(11):1714. doi: https://doi.org/10.3390/rs12111714

Luo, Y., El-Madany, T., Ma, X., Nair, R., Jung, M., Weber, U., Filippa, G., Bucher, S.F., Moreno, G., Cremonese, E., Carrara, A., Gonzalez-Cascon, R., Cáceres Escudero, Y., Galvagno, M., Pacheco-Labrador, J., Martín, M.P., Perez-Priego, O., Reichstein, M., Richardson, A.D., Menzel, A., Römermann, C., & Migliavacca, M. (2020). Nutrients and water availability constrain the seasonality of vegetation activity in a Mediterranean ecosystem. Global Change Biology, 26, 4379-4400

El-Madany, T.S., Carrara, A., Martín, M.P., Moreno, G., Kolle,O., Pacheco-Labrador, J., Weber, U., Wutzler, T., Reichstein, M., & Migliavacca, M. (2020). Drought and heatwave impacts on semi-arid ecosystems' carbon fluxes along a precipitationgradient. Philosophical Transactions of the Royal Society B: Biological Sciences, 375, 20190519

Martínez-Vega, J., Rodríguez-Rodríguez, D., Fernández-Latorre, F.M., Ibarra, P., Echeverría, M. & Echavarría, P. (2020). Proposal of a

System for Assessment of the Sustainability of Municipalities (SASMU) Included in the Spanish Network of National Parks and Their Surroundings. Geosciences, 2020, 10, 298. https://doi.org/10.3390/geosciences10080298

Salvo Tierra, A.E., Pereña Ortiz, J., Cortes-Molino, A., Rodríguez-Rodríguez, D., & Martínez-Vega, J. (2020). Modelo de evaluación

de la efectividad, continuidad y conectividad del sistema de áreas protegidas costeras mediante el análisis de su flora y vegetación. Botanica Complutensis, 44, 73-95. https://doi.org/10.5209/bocm.73021

2019 

Huesca, M., Riaño, D., & Ustin, S. L. (2019). Spectral mapping methods applied to LiDAR data: Application to fuel type mapping. International journal of applied earth observation and geoinformation, 74, 159-168. doi: https://doi.org/10.1016/j.jag.2018.08.020

Lamelas-Gracia, M. T., Riaño, D., & Ustin, S. (2019). A LiDAR signature library simulated from 3-dimensional Discrete Anisotropic Radiative Transfer (DART) model to classify fuel types using spectral matching algorithms. GIScience & Remote Sensing, 56(7), 988-1023. doi: https://doi.org/10.1080/15481603.2019.1601805

Martini, D., Pacheco-Labrador, J., Perez-Priego, O., van der Tol, C., El-Madany, T. S., Julitta, T., . . . Migliavacca, M. (2019). Nitrogen and Phosphorus Effect on Sun-Induced Fluorescence and Gross Primary Productivity in Mediterranean Grassland. Remote Sensing, 11(21), 2562. 

Mili, S., & Martínez-Vega, J. (2019). Accounting for Regional Heterogeneity of Agricultural Sustainability in Spain. Sustainability, 11(2), 299. doi: https://doi.org/10.3390/su11020299

Moreno-Ruiz, J. A., García-Lázaro, J. R., Arbelo, M., & Riaño, D. (2019). A Comparison of Burned Area Time Series in the Alaskan Boreal Forests from Different Remote Sensing Products. Forests, 10(5), 363. doi: https://doi.org/10.3390/f10050363

Pacheco-Labrador, J., Perez-Priego, O., El-Madany, T. S., Julitta, T., Rossini, M., Guan, J., . . . Migliavacca, M. (2019). Multiple-constraint inversion of SCOPE. Evaluating the potential of GPP and SIF for the retrieval of plant functional traits. Remote Sensing of Environment, 234, 111362. doi: https://doi.org/10.1016/j.rse.2019.111362

Rodríguez-Rodríguez, D., Ibarra, P., Echeverría, M., & Martínez-Vega, J. (2019). Perceptions, attitudes and values of two key stakeholders on the oldest and newest Spanish national parks. Environment, Development and Sustainability, 21(2), 1053-1073. doi: https://doi.org/10.1007/s10668-017-0051-5

Rodríguez-Rodríguez, D., & Martínez-Vega, J. (2019). Analysing subtle threats to conservation: A nineteen year assessment of fragmentation and isolation of Spanish protected areas. Landscape and Urban Planning, 185, 107-116. doi: https://doi.org/10.1016/j.landurbplan.2019.01.012 https://www.sciencedirect.com/science/article/pii/S0169204619301355

Rodríguez-Rodríguez, D., Martínez-Vega, J., & Echavarría, P. (2019). A twenty year GIS-based assessment of environmental sustainability of land use changes in and around protected areas of a fast developing country: Spain. International journal of applied earth observation and geoinformation, 74, 169-179. doi: https://doi.org/10.1016/j.jag.2018.08.006 https://www.sciencedirect.com/science/article/pii/S0303243418305002

Rodríguez-Rodríguez, D., Sebastiao, J., Salvo Tierra, Á. E., & Martínez-Vega, J. (2019). Effect of protected areas in reducing land development across geographic and climate conditions of a rapidly developing country, Spain. Land Degradation & Development, 30(8), 991-1005. doi: 10.1002/ldr.3286[Link] https://onlinelibrary.wiley.com/doi/abs/10.1002/ldr.3286

Vilar, L., Garrido, J., Echavarría, P., Martínez-Vega, J., & Martín, M. P. (2019). Comparative analysis of CORINE and climate change initiative land cover maps in Europe: Implications for wildfire occurrence estimation at regional and local scales. International journal of applied earth observation and geoinformation, 78, 102-117. doi: https://doi.org/10.1016/j.jag.2019.01.019 https://www.sciencedirect.com/science/article/abs/pii/S0303243418311243

Yebra, M., Scortechini, G., Badi, A., Beget, M. E., Boer, M. M., Bradstock, R., . . . Ustin, S. (2019). Globe-LFMC, a global plant water status database for vegetation ecophysiology and wildfire applications. Scientific Data, 6(1), 155. doi: https://doi.org/10.1038/s41597-019-0164-9

2018 

El-Madany, T. S., Reichstein, M., Perez-Priego, O., Carrara, A., Moreno, G., Martín, M. P., . . . Weber, U. (2018). Drivers of spatio-temporal variability of carbon dioxide and energy fluxes in a Mediterranean savanna ecosystem. Agricultural and forest meteorology, 262, 258-278. doi: https://doi.org/10.1016/j.agrformet.2018.07.010

García-Lázaro, J. R., Moreno-Ruiz, J. A., Riaño, D., & Arbelo, M. (2018). Estimation of Burned Area in the Northeastern Siberian Boreal Forest from a Long-Term Data Record (LTDR) 1982–2015 Time Series. Remote Sensing, 10 (6), 940. https://doi.org/10.3390/rs10060940

Garrido, J., Vilar, L., Echavarría, P., Martínez-Vega, J., & P., M. M. (2018). ¿Pueden las interfaces de usos del suelo explicar la ocurrencia de incendios forestales a escala provincial? Los casos de Zamora y Madrid. Geofocus(22), 71-95. doi: http://dx.doi.org/10.21138/GF.611

Luo, Y., El-Madany, T., Filippa, G., Ma, X., Ahrens, B., Carrara, A., . . . Hammer, T. (2018). Using Near-Infrared-Enabled Digital Repeat Photography to Track Structural and Physiological Phenology in Mediterranean Tree–Grass Ecosystems. Remote Sensing, 10(8), 1293. doi: https://doi.org/10.3390/rs10081293

Melendo-Vega, J., Martín, M., Pacheco-Labrador, J., González-Cascón, R., Moreno, G., Pérez, F., Migliavacca, M., García, M., North, P., Riaño, D. (2018). Improving the Performance of 3-D Radiative Transfer Model FLIGHT to Simulate Optical Properties of a Tree-Grass Ecosystem. Remote Sensing, 10(12), 2061. doi: https://doi.org/10.3390/rs10122061

Mili, S., & Martínez-Vega, J. (2018). Evaluating Agricultural Sustainability in Spanish Provinces. Ideas, 2133-2018-5437. https://ideas.repec.org/p/ags/eaa166/276206.html

Rodríguez-Rodríguez, D., & Martínez-Vega, J. (2018). Effect of legal protection and management of protected areas at preventing land development: a Spanish case study. Regional Environmental Change, 18(8), 2483-2494. doi: https://doi.org/10.1007/s10113-018-1369-8

Rodríguez-Rodríguez, D., & Martínez-Vega, J. (2018). Protected area effectiveness against land development in Spain. Journal of Environmental Management, 215, 345-357. doi: https://doi.org/10.1016/j.jenvman.2018.03.011

Rodríguez-Rodríguez, D., & Martínez-Vega, J. (2018). A Centennial Path Towards Sustainability in Spanish National Parks: Biodiversity Conservation and Socioeconomic Development (1918-2018). intechopen. doi: https://doi.org/10.5772/intechopen.73196

Yebra, M., Quan, X., Riaño, D., Rozas Larraondo, P., van Dijk, A. I. J. M., & Cary, G. J. (2018). A fuel moisture content and flammability monitoring methodology for continental Australia based on optical remote sensing. Remote Sensing of Environment, 212, 260-272. doi: https://doi.org/10.1016/j.rse.2018.04.053

2017

Gonzalez-Cascon, R., Jiménez-Fenoy, L., Verdú-Fillola, I., & Martín, M. P. (2017). Aqueous-acetone extraction improves the drawbacks of using dimethylsulfoxide as solvent for photometric pigment quantification in Quercus ilex leaves. Forest Systems, 26(2), 04. 10.5424/fs/2017262-11099[Link] https://revistas.inia.es/index.php/fs/article/view/11099

Martínez-Vega, J., Díaz, A., Nava, J. M., Gallardo, M., & Echavarría, E. (2017). Assessing Land Use-Cover Changes and Modelling Change Scenarios in Two Mountain Spanish National Parks. Environments, 4(79), 1-29. doi: https://doi.org/10.3390/environments4040079 https://www.mdpi.com/2076-3298/4/4/79

Melendo-Vega, J. R., Martín, M. P., Vilar del Hoyo, L., Pacheco-Labrador, J., Echavarría, P., & Martínez-Vega, J. (2017). Estimación de variables biofísicas del pastizal en un ecosistema de dehesa a partir de espectro-radiometría de campo e imágenes hiperespectrales aeroportadas. Revista de Teledetección(48), 13-28. doi: https://doi.org/10.4995/raet.2017.7481https://polipapers.upv.es/index.php/raet/article/view/7481

Migliavacca, M., Perez‐Priego, O., Rossini, M., El‐Madany, T. S., Moreno, G., van der Tol, C., . . . Burkart, A. (2017). Plant functional traits and canopy structure control the relationship between photosynthetic CO 2 uptake and far‐red sun‐induced fluorescence in a Mediterranean grassland under different nutrient availability. New Phytologist, 214(3), 1078-1091. https://doi.org/10.1111/nph.14437 https://nph.onlinelibrary.wiley.com/doi/full/10.1111/nph.14437

Pacheco-Labrador, J., El-Madany, T., Martín, M., Migliavacca, M., Rossini, M., Carrara, A., & Zarco-Tejada, P. J. (2017). Spatio-temporal relationships between optical information and carbon fluxes in a mediterranean tree-grass ecosystem. Remote Sensing, 9(6), 608. https://doi.org/10.3390/rs9060608  https://www.mdpi.com/2072-4292/9/6/608

Perez-Priego, O., El-Madany, T. S., Migliavacca, M., Kowalski, A. S., Jung, M., Carrara, A., . . . Moreno, G. (2017). Evaluation of eddy covariance latent heat fluxes with independent lysimeter and sapflow estimates in a Mediterranean savannah ecosystem. Agricultural and forest meteorology, 236, 87-99. http://dx.doi.org/10.1016/j.agrformet.2017.01.009https://www.sciencedirect.com/science/article/pii/S0168192317300096?via%3Dihub https://digital.csic.es/handle/10261/201272

Rodríguez-Rodríguez, D., Ibarra, P., Martínez-Vega, J., Echeverría, M., & Echavarría, P. (2017). Fine-Tuning of a Protected Area Effectiveness Evaluation Tool: Implementation on Two Emblematic Spanish National Parks. Environments, 4(4), 68. https://doi.org/10.3390/environments4040068 https://www.mdpi.com/2076-3298/4/4/68https://digital.csic.es/handle/10261/201272

Rodríguez-Rodríguez, D., & Martínez-Vega, J. (2017). Assessing recent environmental sustainability in the Spanish network of National Parks and their statutory peripheral areas. Applied Geography, 89, 22-31. doi: https://doi.org/10.1016/j.apgeog.2017.09.008 http://www.sciencedirect.com/science/article/pii/S0143622817303041

2016

Gallardo, M., & Martínez-Vega, J. (2016). Three decades of land-use changes in the region of Madrid and how they relate to territorial planning. European Planning Studies, 24(5), 1016-1033. doi: https://doi.org/10.1080/09654313.2016.1139059 https://doi.org/10.1080/09654313.2016.1139059

González-Cascón, R., Pacheco-Labrador, J., & Martín, M. (2016). Evolución del comportamiento espectral y la composición química en el dosel arbóreo de una dehesa. Revista de Teledetección, 46, 31-43. https://polipapers.upv.es/index.php/raet/article/view/5688

Martínez-Vega, J., Mili, S., & Echavarría, P. (2016). Assessing forest sustainability: Evidence from Spanish provinces. Geoforum, 70, 1-10. doi: https://doi.org/10.1016/j.geoforum.2015.12.013http://www.sciencedirect.com/science/article/pii/S0016718516000038

Pacheco-Labrador, J., Martín, M. P., Riaño, D., Hilker, T., & Carrara, A. (2016). New approaches in multi-angular proximal sensing of vegetation: Accounting for spatial heterogeneity and diffuse radiation in directional reflectance distribution models. Remote Sensing of Environment, 187, 447-457. doi: http://dx.doi.org/10.1016/j.rse.2016.10.051http://www.sciencedirect.com/science/article/pii/S0034425716304308

Rodríguez-Rodríguez, D., & Martínez-Vega, J. (2016). What should be evaluated from a manager's perspective? Developing a salient protected area effectiveness evaluation system for managers and scientists in Spain. Ecological Indicators, 64, 289-296. doi: https://doi.org/10.1016/j.ecolind.2016.01.011http://www.sciencedirect.com/science/article/pii/S1470160X16000157

Vilar, L., Camia, A., San-Miguel-Ayanz, J., & Martín, M. P. (2016). Modeling temporal changes in human-caused wildfires in Mediterranean Europe based on Land Use-Land Cover interfaces. Forest Ecology and Management, 378, 68-78. doi: http://dx.doi.org/10.1016/j.foreco.2016.07.020https://www.sciencedirect.com/science/article/pii/S0378112716303760?via%3Dihub

Vilar, L., Gómez, I., Martínez-Vega, J., Echavarría, P., Riaño, D., & Martín, M. P. (2016). Multitemporal Modelling of Socio-Economic Wildfire Drivers in Central Spain between the 1980s and the 2000s: Comparing Generalized Linear Models to Machine Learning Algorithms. PLoS ONE, 11(8), e0161344. doi: https://doi.org/10.1371/journal.pone.0161344 https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0161344

2015

Cáceres, J., Martín, M. P., & Salas, J. (2015). Análisis temporal de biomasa y stocks de carbono en un ecosistema de dehesa mediante imágenes Landsat, y su relación con factores climáticos. Ciencias Espaciales, 8(1). doi: http://dx.doi.org/10.5377/ce.v8i1.2049 https://www.camjol.info/index.php/CE/article/view/2049

Fernández, D., Martín, M. P., Vilar, L., & Pacheco-Labrador, J. (2015). Estimación del contenido de humedad de la vegetacion herbácea en una zona de dehesa a partir de imágenes hiperespectrales adquiridas por el sensor aeroportado CASI. GeoFocus, 16, 117-204. http://www.geofocus.org/index.php/geofocus/article/view/399

Gallardo, M., Gómez, I., Vilar, L., Martínez-Vega, J., & Martín, M. P. (2015). Impacts of future land use/land cover on wildfire occurrence in the Madrid region (Spain). Regional Environmental Change, 1-15. doi: https://doi.org/10.1007/s10113-015-0819-9 https://link.springer.com/article/10.1007%2Fs10113-015-0819-9

García, M., Gajardo, J., Riaño, D., Zhao, K., Martín, P., & Ustin, S. (2015). Canopy clumping appraisal using terrestrial and airborne laser scanning. Remote Sensing of Environment, 161, 78-88. doi: http://dx.doi.org/10.1016/j.rse.2015.01.030http://www.sciencedirect.com/science/article/pii/S0034425715000541

Gómez Nieto I., Martín Isabel M. P., & J., S. R. F. (2015). Análisis del régimen de incendios forestales y su relación con los cambios de uso del suelo en la comunidad autónoma de Madrid (1989-2010). Geofocus, 16, 281-304. http://www.geofocus.org/index.php/geofocus/article/view/401

Martínez-Vega, J., Gallardo, M., & Echavarría, P. (2015). Satellite images and teaching of Geography. Journal of Research and Didactics in Geography (J-READING), 1(4), 55-66. doi: https://doi.org/10.4458/5196-06 http://www.j-reading.org/index.php/geography/article/view/90

Mendiguren, G., Martín, M. P., Nieto, H., Pacheco-Labrador, J., & Jurdao, S. (2015). Seasonal variation in grass water content estimated from proximal sensing and MODIS time series in a Mediterranean Fluxnet site. Biogeosciences, 12(18), 5523-5535. doi: https://doi.org/10.5194/bg-12-5523-2015 http://www.biogeosciences.net/12/5523/2015/

Pacheco-Labrador, J., & Martín, M. (2015). Characterization of a Field Spectroradiometer for Unattended Vegetation Monitoring. Key Sensor Models and Impacts on Reflectance. Sensors, 15(2), 4154. http://www.mdpi.com/1424-8220/15/2/4154

Porcar-Castell, A., Mac Arthur, A., Rossini, M., Eklundh, L., Pacheco-Labrador, J., Anderson, K., . . . Vescovo, L. (2015). EUROSPEC: at the interface between remote-sensing and ecosystem CO₂ flux measurements in Europe. Biogeosciences, 12(20), 6103-6124. doi: https://doi.org/10.5194/bg-12-6103-2015https://www.biogeosciences.net/12/6103/2015/

Rey-Caramés, C., Diago, M., Martín, M., Lobo, A., & Tardaguila, J. (2015). Using RPAS Multi-Spectral Imagery to Characterise Vigour, Leaf Development, Yield Components and Berry Composition Variability within a Vineyard. Remote Sensing, 7(11), 14458. http://www.mdpi.com/2072-4292/7/11/14458

Vilar, L., Camia, A., & San-Miguel-Ayanz, J. (2015). A comparison of remote sensing products and forest fire statistics for improving fire information in Mediterranean Europe. European Journal of Remote Sensing, 48, 345-364. doi: 10.5721/EuJRS20154820 http://www.aitjournal.com/DefaultNew.aspx#sthash.CdZe2qiC.dpuf

2014

Casas, A., Riaño, D., Ustin, S. L., Dennison, P., & Salas, J. (2014). Estimation of water-related biochemical and biophysical vegetation properties using multitemporal airborne hyperspectral data and its comparison to MODIS spectral response. Remote Sensing of Environment, 148, 28-41. doi: http://dx.doi.org/10.1016/j.rse.2014.03.011http://www.sciencedirect.com/science/article/pii/S0034425714000820

Cheng, T., Riaño, D., & Ustin, S. L. (2014). Detecting diurnal and seasonal variation in canopy water content of nut tree orchards from airborne imaging spectroscopy data using continuous wavelet analysis. Remote Sensing of Environment, 143, 39-53. doi: https://doi.org/10.1016/j.rse.2013.11.018https://www.sciencedirect.com/science/article/pii/S0034425713004409

Moreno-Ruiz, J. A., García Lázaro, J. R., Riaño, D., & Kefauver, S. C. (2014). The synergy of the 0.05º (~5 km) AVHRR Long Term Data Record (LTDR) and Landsat TM archive to map large fires in the North American boreal region from 1984 to 1998. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 4, 1157-1166.https://polipapers.upv.es/index.php/raet/article/view/2280

Pacheco-Labrador, J., Ferrero, A., & Martín, M. P. (2014). Characterizing integration time and gray-level-related nonlinearities in a NMOS sensor. Applied Optics, 53(32), 7778-7786. doi: https://doi.org/10.1364/AO.53.007778http://ao.osa.org/abstract.cfm?URI=ao-53-32-7778

Pacheco-Labrador, J., González-Cascón, R., Martín, M. P., & Riaño, D. (2014). Understanding the optical responses of leaf nitrogen in Mediterranean Holm oak (Quercus ilex) using field spectroscopy. International Journal of Applied Earth Observation and Geoinformation, 26, 105-118. doi: http://dx.doi.org/10.1016/j.jag.2013.05.013http://www.sciencedirect.com/science/article/pii/S0303243413000627

Pacheco-Labrador, J., & Martin, M. P. (2014). Nonlinear Response in a Field Portable Spectroradiometer: Characterization and Effects on Output Reflectance. IEEE Transactions on Geoscience and Remote Sensing, 52(2), 920-928. doi: https://doi.org/10.1109/TGRS.2013.2245671 https://ieeexplore.ieee.org/document/6504503

Vlassova, L., Perez-Cabello, F., Nieto, H., Martín, P., Riaño, D., & de la Riva, J. (2014). Assessment of Methods for Land Surface Temperature Retrieval from Landsat-5 TM Images Applicable to Multiscale Tree-Grass Ecosystem Modeling. Remote Sensing, 6(5), 4345. http://www.mdpi.com/2072-4292/6/5/4345  

Timmermans, W., Van der Tol, C., Timmermans, J., Ucer, M., Chen, X., Alonso, L., Moreno, J., Carrara, A., Lopez, R., de la Cruz Tercero, F., Corcoles, H., de Miguel, E., Sanchez, J.G., Pérez, I., Franch, B., Munoz, J.-C., Skokovic, D., Sobrino, J., Soria, G., MacArthur, A., Vescovo, L., Reusen, I., Andreu, A., Burkart, A., Cilia, C., Contreras, S., Corbari, C., Calleja, J., Guzinski, R., Hellmann, C., Herrmann, I., Kerr, G., Lazar, A.-L., Leutner, B., Mendiguren, G., Nasilowska, S., Nieto, H., Pacheco-Labrador, J., Pulanekar, S., Raj, R., Schikling, A., Siegmann, B., von Bueren, S., & Su, Z. (2014). An overview of the regional experiments for land-atmosphere exchanges 2012 (REFLEX 2012) campaign. Acta Geophysica, 1-20

2013

Anderson, K., Rossini, M., Pacheco-Labrador, J., Balzarolo, M., Mac Arthur, A., Fava, F., Julitta, T., & Vescovo, L. (2013). Inter-comparison of hemispherical conical reflectance factors (HCRF) measured with four fibre-based spectrometers. Optics Express, 21, 605-617

Cheng, T., Riaño, D., Koltunov, A., Whiting, M. L., Ustin, S. L., & Rodriguez, J. (2013). Detection of diurnal variation in orchard canopy water content using MODIS/ASTER airborne simulator (MASTER) data. Remote Sensing of Environment, 132, 1-12. doi: http://dx.doi.org/10.1016/j.rse.2012.12.024http://www.sciencedirect.com/science/article/pii/S0034425713000023

Durá, E., Mendiguren, G., Pacheco-Labrador, J., Martín, M. P., Riaño, D., Iturrate, M., . . . Carrara, A. (2013). Validación de productos MODIS relacionados con la estimación de flujos de carbono en un ecosistema de dehesa. Geofocus, 13(1). http://www.geofocus.org/index.php/geofocus/article/view/271

Yebra, M., Dennison, P. E., Chuvieco, E., Riaño, D., Zylstra, P., Hunt, E. R., . . . Jurdao, S. (2013). A global review of remote sensing of live fuel moisture content for fire danger assessment: Moving towards operational products. Remote Sensing of Environment, 136, 455-468. doi: https://doi.org/10.1016/j.rse.2013.05.029https://www.sciencedirect.com/science/article/pii/S0034425713001831  

2012

Casas, A., Riaño, D., Greenberg, J., & Ustin, S. (2012). Assessing levee stability with geometric parameters derived from airborne LiDAR. Remote Sensing of Environment, 117, 281-288. doi: http://dx.doi.org/10.1016/j.rse.2011.10.003http://www.sciencedirect.com/science/article/pii/S0034425711003518

García, M., Popescu, S., Riaño, D., Zhao, K., Neuenschwander, A., Agca, M., & Chuvieco, E. (2012). Characterization of canopy fuels using ICESat/GLAS data. Remote Sensing of Environment, 123, 81-89. doi: http://dx.doi.org/10.1016/j.rse.2012.03.018 http://www.sciencedirect.com/science/article/pii/S003442571200137X

Greenberg, J. A., Hestir, E. L., Riano, D., Scheer, G. J., & Ustin, S. L. (2012). Using LiDAR Data Analysis to Estimate Changes in Insolation Under Large-Scale Riparian Deforestation1. JAWRA Journal of the American Water Resources Association, 48(5), 939-948. doi: https://doi.org/10.1111/j.1752-1688.2012.00664.x http://dx.doi.org/10.1111/j.1752-1688.2012.00664.x

Moreno Ruiz, J. A., Riaño, D., Arbelo, M., French, N. H. F., Ustin, S. L., & Whiting, M. L. (2012). Burned area mapping time series in Canada (1984–1999) from NOAA-AVHRR LTDR: A comparison with other remote sensing products and fire perimeters. Remote Sensing of Environment, 117, 407-414. doi: http://dx.doi.org/10.1016/j.rse.2011.10.017http://www.sciencedirect.com/science/article/pii/S0034425711003749

Qi, Y., Dennison, P. E., Spencer, J., & Riaño, D. (2012). Monitoring Live Fuel Moisture Using Soil Moisture and Remote Sensing Proxies. The Journal of the Association for Fire Ecology, 8(3), 71-87. doi: https://doi.org/10.4996/fireecology.0803071 https://link.springer.com/article/10.4996/fireecology.0803071

Ustin, S. L., Riaño, D., & Hunt, E. R. (2012). Estimating canopy water content from spectroscopy. Israel Journal of Plant Sciences, 60(1-2), 9-23. doi: https://doi.org/10.1560/IJPS.60.1-2.9http://www.tandfonline.com/doi/abs/10.1560/IJPS.60.1-2.9  

2011

Balzarolo, M., Anderson, K., Nichol, C., Rossini, M., Vescovo, L., Arriga, N., . . . Martín, M. P. (2011). Ground-Based Optical Measurements at European Flux Sites: A Review of Methods, Instruments and Current Controversies. Sensors, 11(8), 7954. doi: https://doi.org/10.3390/s110807954 http://www.mdpi.com/1424-8220/11/8/7954

Barreto, L., Fernández-Quintanilla, C., Martín, M. P., Riaño, D., & Vaughan, P. (2011). Assessing the potential of hyperspectral remote sensing for the discrimination of grassweeds in winter cereal crops. International Journal of Remote Sensing, 32, 49-67. http://hdl.handle.net/10261/37405

Bastarrika, A., Chuvieco, E., & Martin, M. P. (2011). Automatic Burned Land Mapping From MODIS Time Series Images: Assessment in Mediterranean Ecosystems. IEEE Transactions on Geoscience and Remote Sensing, 49(9), 3401-3413. doi: https://doi.org/10.1109/TGRS.2011.2128327 https://ieeexplore.ieee.org/document/5756655

Bastarrika, A., Chuvieco, E., & Martín, M. P. (2011). Mapping burned areas from Landsat TM/ETM+ data with a two-phase algorithm: Balancing omission and commission errors. Remote Sensing of Environment, 115(4), 1003-1012. doi: http://dx.doi.org/10.1016/j.rse.2010.12.005 http://www.sciencedirect.com/science/article/pii/S0034425710003433

García, M., Danson, F. M., Riaño, D., Chuvieco, E., Ramirez, F. A., & Bandugula, V. (2011). Terrestrial laser scanning to estimate plot-level forest canopy fuel properties. International journal of applied earth observation and geoinformation, 13(4), 636-645. doi: http://dx.doi.org/10.1016/j.jag.2011.03.006http://www.sciencedirect.com/science/article/pii/S0303243411000493

Gómez, I., & Martín, M. P. (2011). Prototyping an artificial neural network for burned area mapping on a regional scale in Mediterranean areas using MODIS images. International journal of applied earth observation and geoinformation, 13(5), 741-752. doi: http://dx.doi.org/10.1016/j.jag.2011.05.002http://www.sciencedirect.com/science/article/pii/S0303243411000596

Kasischke, E. S., Loboda, T., Giglio, L., French, N. H. F., Hoy, E. E., de Jong, B., & Riano, D. (2011). Quantifying burned area for North American forests: Implications for direct reduction of carbon stocks. Journal of Geophysical Research: Biogeosciences, 116(G4). doi: https://doi.org/10.1029/2011jg001707 https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2011JG001707

Martín, M. P., Barreto, L., & Fernández-Quintanilla, C. (2011). Discrimination of sterile oat (Avena sterilis) in winter barley (Hordeum vulgare) using QuickBird satellite images. Crop Protection, 30(10), 1363-1369. doi: http://dx.doi.org/10.1016/j.cropro.2011.06.008 https://doi.org/10.1080/01431160903439874

Martin, M. P., Barreto, L., Riaño, D., Fernandez-Quintanilla, C., & Vaughan, P. (2011). Assessing the potential of hyperspectral remote sensing for the discrimination of grassweeds in winter cereal crops. International Journal of Remote Sensing, 32(1), 49-67. doi: https://doi.org/10.1080/01431160903439874 http://www.sciencedirect.com/science/article/pii/S0261219411002249

Oliva, P., Martín, M. P., & Chuvieco, E. (2011). Burned area mapping with MERIS post-fire image. International Journal of Remote Sensing, 32(15), 4175-4201. doi: https://doi.org/10.1080/01431161.2010.489062https://www.tandfonline.com/doi/full/10.1080/01431161.2010.489062

Rodriguez, J. M., Ustin, S. L., & Riaño, D. (2011). Contributions of imaging spectroscopy to improve estimates of evapotranspiration. Hydrological Processes, 25, 4069-4081. https://onlinelibrary.wiley.com/doi/10.1002/hyp.8368

Vilar, L., Martín, M. P., & Martínez, F. J. (2011). Logistic regression models for human-caused wildfire risk estimation: analysing the effect of the spatial accuracy in fire occurrence data. European Journal of Forest Research, 130(6), 983-996. doi: https://doi.org/10.1007/s10342-011-0488-2 https://link.springer.com/article/10.1007/s10342-011-0488-2  

2010

Chuvieco, E., Aguado, I., Yebra, M., Nieto, H., Salas, J., Martín, M. P., . . . Zamora, R. (2010). Development of a framework for fire risk assessment using remote sensing and geographic information system technologies. Ecological Modelling, 221, 46-58. doi: https://doi.org/10.1016/j.ecolmodel.2008.11.017http://www.sciencedirect.com/science/article/pii/S0304380008005735

García, M., Riaño, D., Chuvieco, E., & Danson, F. M. (2010). Estimating biomass carbon stocks for a Mediterranean forest in central Spain using LiDAR height and intensity data. Remote Sensing of Environment, 114(4), 816-830. doi: http://dx.doi.org/10.1016/j.rse.2009.11.021 http://www.sciencedirect.com/science/article/pii/S0034425709003551

Martín Isabel, M. P., García Alonso, M., & Martínez Vega, F. J. (2010). Avances en teledetección instrumentos y aplicaciones. Ciudad y territorio: Estudios territoriales, 165-166, 551-564. https://recyt.fecyt.es/index.php/CyTET/article/view/76016

Martín Isabel, M. P., & Rejalaga Noguera, L. K. (2010). Cartografía de incendios forestales en Paraguay mediante imágenes AQUA-MODIS Serie Geográfica, 2007-2008, 16, 61-70. http://hdl.handle.net/10017/14223

Vilar, L., Woolford, D. G., Martell, D. L., & Martín, M. P. (2010). A model for predicting human-caused wildfire occurrence in the region of Madrid, Spain. International Journal of Wildland Fire, 19, 325-337. doi: https://doi.org/10.1071/WF09030 https://www.publish.csiro.au/WF/WF09030  

2009

Bastarrika, A., Chuvieco, E., Martin, M.P. (2009). Comparación de productos de área quemada obtenidos mediante imágenes de satélite en la península ibérica. Uned. Espacio, Tiempo y Forma. Serie VI, Nueva época. Geografía(1). [Link] http://revistas.uned.es/index.php/ETFVI/article/view/1458

Cuevas-González, M., Gerard, F., Balzter, H., & Riaño, D. (2009). Analysing forest recovery after wildfire disturbance in boreal Siberia using remotely sensed vegetation indices. Global Change Biology, 15(3), 561-577. doi: https://doi.org/10.1111/j.1365-2486.2008.01784.x http://dx.doi.org/10.1111/j.1365-2486.2008.01784.x

García, M., Prado, E., Riaño, D., Chuvieco, E., & Danson, M. (2009). Ajuste planimétrico de datos Lidar para la estimación de características dasométricas en el parque natural del alto Tajo Geofocus(9). http://www.geofocus.org/index.php/geofocus/article/view/167

Moreno-Ruiz, J. A., Riano, D., Garcia-Lazaro, J. R., & Ustin, S. L. (2009). Intercomparison of AVHRR PAL and LTDR Version 2 Long-Term Data Sets for Africa From 1982 to 2000 and Its Impact on Mapping Burned Area. IEEE Geoscience and Remote Sensing Letters, 6(4), 738-742. doi: https://doi.org/10.1109/LGRS.2009.2024436https://ieeexplore.ieee.org/document/5164948  

2008

Cheng, Y.-B., Ustin, S. L., Riaño, D., & Vanderbilt, V. C. (2008). Water content estimation from hyperspectral images and MODIS indexes in Southeastern Arizona. Remote Sensing of Environment, 112(2), 363-374. doi: http://dx.doi.org/10.1016/j.rse.2007.01.023 http://www.sciencedirect.com/science/article/pii/S0034425707002982

Cuevas-Gonzalez, M., Gerard, F., Balzter, H., & Riano, D. (2008). Studying the change in fAPAR after forest fires in Siberia using MODIS. Int. J. Remote Sens., 29(23), 6873-6892. doi: https://doi.org/10.1080/01431160802238427https://www.tandfonline.com/doi/abs/10.1080/01431160802238427

Gómez Nieto, I., & Martín Isabel, M. (2008). Estudio comparativo de índices espectrales para la cartografía de áreas quemadas con imágenes MODIS. Revista de Teledetección, 29, 15-24. http://www.aet.org.es/revistas/revista29/Revista-AET-29-2.pdf

Li, L., Cheng, Y. B., Ustin, S., Hu, X. T., & Riaño, D. (2008). Retrieval of vegetation equivalent water thickness from reflectance using genetic algorithm (GA)-partial least squares (PLS) regression. Advances in Space Research, 41(11), 1755-1763. doi: http://dx.doi.org/10.1016/j.asr.2008.02.015http://www.sciencedirect.com/science/article/pii/S027311770800104X

Nieto Solana, H., Chuvieco Salinero, E., Aguado, I., Yebra Álvarez, M., García Alonso, M., Salas Rey, F. J., . . . Martín Fernández, S. (2008). Propuesta de un sistema espacialmente explícito para evaluar el peligro de incendios. Serie Geográfica, 2007-2008, 14, 109-130. https://ebuah.uah.es/dspace/handle/10017/2079

Trombetti, M., Riaño, D., Rubio, M. A., Cheng, Y. B., & Ustin, S. L. (2008). Multi-temporal vegetation canopy water content retrieval and interpretation using artificial neural networks for the continental USA. Remote Sensing of Environment, 112(1), 203-215. doi: http://dx.doi.org/10.1016/j.rse.2007.04.013http://www.sciencedirect.com/science/article/pii/S0034425707001915

Vilar, L., Martín, M. P., & Martínez, F. J. (2008). Empleo de técnicas de regresión logística para la obtención de modelos de riesgo humano de incendio forestal a escala regional. Boletín de la AGE, 47, 5–29. [Link] https://bage.age-geografia.es/ojs/index.php/bage/article/view/2027Yebra, M., Chuvieco, E., & Riaño, D. (2008). Estimation of live fuel moisture content from MODIS images for fire risk assessment. Agricultural and forest meteorology, 148(4), 523-536. doi: http://dx.doi.org/10.1016/j.agrformet.2007.12.005 http://www.sciencedirect.com/science/article/pii/S0168192307003140

2007

Chuvieco, E., De Santis, A., Riaño, D., & Halligan, K. (2007). Simulation Approaches for Burn Severity Estimation Using Remotely Sensed Images. Fire Ecology, 3(1), 129-150. doi: https://doi.org/10.4996/fireecology.0301129https://link.springer.com/article/10.4996/fireecology.0301129

Khanna, S., Palacios-Orueta, A., Whiting, M. L., Ustin, S. L., Riaño, D., & Litago, J. (2007). Development of angle indexes for soil moisture estimation, dry matter detection and land-cover discrimination. Remote Sensing of Environment, 109(2), 154-165. doi: http://dx.doi.org/10.1016/j.rse.2006.12.018http://www.sciencedirect.com/science/article/pii/S003442570700003X

Li, L., Ustin, S. L., & Riano, D. (2007). Retrieval of Fresh Leaf Fuel Moisture Content Using Genetic Algorithm Partial Least Squares (GA-PLS) Modeling. IEEE Geoscience and Remote Sensing Letters, 4(2), 216-220. doi: https://doi.org/10.1109/LGRS.2006.888847 https://ieeexplore.ieee.org/document/4156162

Martín M.P., Chuvieco, E., Oliva, P., Verdú, F., Nieto, H., & Padrón, D. (2007). Un ejemplo práctico de aplicación operativa de la teledetección a la gestión de riesgos naturales: Cartografía y evaluación urgente de áreas quemadas en Galicia. Cuadernos de Investigación Geográfica, 33, 19-37. https://dialnet.unirioja.es/servlet/articulo?codigo=2569783

Riaño, D., Chuvieco, E., Ustin, S. L., Salas, J., Rodríguez-Pérez, J. R., Ribeiro, L. M., . . . Fernández, H. (2007). Estimation of shrub height for fuel-type mapping combining airborne LiDAR and simultaneous color infrared ortho imaging. International Journal of Wildland Fire, 16(3), 341-348. doi: http://dx.doi.org/10.1071/WF06003http://www.publish.csiro.au/paper/WF06003

Riaño, D., Moreno Ruiz, J. A., Isidoro, D., & Ustin, S. L. (2007). Global spatial patterns and temporal trends of burned area between 1981 and 2000 using NOAA-NASA Pathfinder. Global Change Biology, 13(1), 40-50. doi: https://doi.org/10.1111/j.1365-2486.2006.01268.x https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-2486.2006.01268.x

Riaño, D., Moreno Ruiza, J. A., Barón Martínez, J., & Ustin, S. L. (2007). Burned area forecasting using past burned area records and Southern Oscillation Index for tropical Africa (1981–1999). Remote Sensing of Environment, 107(4). doi: https://doi.org/10.1016/j.rse.2006.10.008 https://www.sciencedirect.com/science/article/pii/S0034425706003853

Rodríguez-Pérez, J. R., Riaño, D., Carlisle, E., Ustin, S., & Smart, D. R. (2007). Evaluation of Hyperspectral Reflectance Indexes to Detect Grapevine Water Status in Vineyards. Am. J. Enol. Vitic 58(3), 302-317 https://www.ajevonline.org/content/58/3/302