Pablo Martín-Ortega

Dr. Pablo Martín-Ortega

Department of Forest and Environmental Engineering and Management, Universidad Politécnica de Madrid (UPM)

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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8 January 2020 in Remote Sensing
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Journal Article
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PMPablo Martín-Ortega
Pablo Martín-Ortega
LGLuis Gonzaga García-Montero
Luis Gonzaga García-Montero
NSNicole Sibelet
Nicole Sibelet
Vegetation indices (VI) describe vegetation structure and functioning but they are affected by illumination conditions (IC). Moreover, the fact that the effect of the IC on VI can be stronger than other biophysical or seasonal processes is under debate. Using Google Earth Engine and the latest Landsat Surface Reflectance level 1 data, we evaluated the temporal patterns of IC and two VI, the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) in a mountainous tropical forest during the years 1984–2017. We evaluated IC and VI at different times, their relationship with the topography and the correlations between them. We show that IC is useful for understanding the patterns of variation between VI and IC at the pixel level using Landsat sensors. Our findings confirmed a strong correlation between EVI and IC and less between NDVI and IC. We found a significant increase in IC, EVI, and NDVI throughout time due to an improvement in the position of all Landsat sensors. Our results reinforce the need to consider IC to interpret VI over long periods using Landsat data in order to increase the precision of monitoring VI in irregular topography.

9 July 2024 in Land
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Journal Article
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AGAmit Ghosh
Amit Ghosh
PRPierrick Rambaud
Pierrick Rambaud
YFYelena Finegold
Yelena Finegold
Inge JonckheereInge Jonckheere
Inge Jonckheere
PMPablo Martín-Ortega
Pablo Martín-Ortega
Matieu HenryMatieu Henry
Matieu Henry
A third of the world’s ecosystems are considered degraded, and there is an urgent need for protection and restoration to make the planet healthier. The Sustainable Development Goals (SDGs) target 15.3 aims at protecting and restoring the terrestrial ecosystem to achieve a land degradation-neutral world by 2030. Land restoration through inclusive and productive growth is indispensable to promote sustainable development by fostering climate change-resistant, poverty-alleviating, and environmentally protective economic growth. The SDG Indicator 15.3.1 is used to measure progress towards a land degradation-neutral world. Earth observation datasets are the primary data sources for deriving the three sub-indicators of indicator 15.3.1. It requires selecting, querying, and processing a substantial historical archive of data. To reduce the complexities, make the calculation user-friendly, and adapt it to in-country applications, a module on the FAO’s SEPAL platform has been developed in compliance with the UNCCD Good Practice Guidance (GPG v2) to derive the necessary statistics and maps for monitoring and reporting land degradation. The module uses satellite data from Landsat, Sentinel 2, and MODIS sensors for primary productivity assessment, along with other datasets enabling high-resolution to large-scale assessment of land degradation. The use of an in-country land cover transition matrix along with in-country land cover data enables a more accurate assessment of land cover changes over time. Four different case studies from Bangladesh, Nigeria, Uruguay, and Angola are presented to highlight the prospect and challenges of monitoring land degradation using various datasets, including LCML-based national land cover legend and land cover data.

28 October 2021 in Remote Sensing
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Journal Article
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LGLuis Gonzaga García-Montero
Luis Gonzaga García-Montero
CPCristina Pascual
Cristina Pascual
SMSusana Martin-Fernández
Susana Martin-Fernández
ADAlfonso Sanchez-Paus Díaz
Alfonso Sanchez-Paus Díaz
CPChiara Patriarca
Chiara Patriarca
DMDanilo Mollicone
Danilo Mollicone
Monitoring of land use, land-use changes, and forestry (LULUCF) plays a crucial role in biodiversity and global environmental challenges. In 2015, the Food and Agriculture Organization of the United Nations (FAO) launched the Global Forest Survey (GFS) integrating medium- (MR) and very-high-resolution (VHR) images through the FAO’s Collect Earth platform. More than 11,150 plots were inventoried in the Temperate FAO ecozone in Europe to monitor LULUCF from 2000 to 2015. As a result, 2.19% (VHR) to 2.77% (MR/VHR) of the study area underwent LULUCF, including a 0.37% (VHR) to 0.43% (MR/VHR) net increase in forest lands. Collect Earth and VHR images have also (i) allowed for shaping a preliminary structure of the land-use network, showing that cropland was the land type that changed most and that cropland and grassland were the more frequent land uses that generated new forest land, (ii) shown that, in 2015, mixed and monospecific forests represented 44.3% and 46.5% of the forest land, respectively, unlike other forest sources, and (iii) shown that 14.9% of the area had been affected by disturbances, particularly wood harvesting (67.47% of the disturbed forests). According to other authors, the area showed a strong correlation between canopy mortality and reported wood removals due to the transition from past clear-cut systems to “close-to-nature” silviculture.

28 January 2023 in Land
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Journal Article
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RJRashed Jalal
Rashed Jalal
RMRajib Mahamud
Rajib Mahamud
TATanjimul Alam Arif
Tanjimul Alam Arif
SRSaimunnahar Ritu
Saimunnahar Ritu
MKMondal Falgoonee Kumar
Mondal Falgoonee Kumar
Matieu HenryMatieu Henry
Matieu Henry
The influx of nearly a million refugees from Myanmar’s Rakhine state to Cox’s Bazar, Bangladesh, in August 2017 put significant pressure on the regional landscape leading to land degradation due to biomass removal to provide shelter and fuel energy and posed critical challenges for both host and displaced population. This article emphasizes geospatial applications at different stages of addressing land degradation in Cox’s Bazar. A wide range of data and methods were used to delineate land tenure, estimate wood fuel demand and supply, assess land degradation, evaluate land restoration suitability, and monitor restoration activities. The quantitative and spatially explicit information from these geospatial assessments integrated with the technical guidelines for sustainable land management and an adaptive management strategy was critical in enabling a collaborative, multi-disciplinary and evidence-based approach to successfully restoring degraded landscapes in a displacement setting.

11 September 2021 in Sustainability
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Journal Article
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LGLuis Gonzaga García-Montero
Luis Gonzaga García-Montero
CPCristina Pascual
Cristina Pascual
ADAlfonso Sanchez-Paus Díaz
Alfonso Sanchez-Paus Díaz
SMSusana Martin-Fernández
Susana Martin-Fernández
PMPablo Martín-Ortega
Pablo Martín-Ortega
DMDanilo Mollicone
Danilo Mollicone
The global distribution of forest trees is essential for monitoring land-use sustainability. For this reason, FAO developed the Global Forest Survey (GFS), a systematic regional level survey with a homogeneous sampling design. Preliminary results revealed an interest in analyzing “Trees Outside Forests” (TOFs). We analyzed more than 11,150 sample GFS plots in temperate FAO-ecozones in Europe through a photo-interpretation approach using FAO’s Collect Earth platform. Our results showed that forest land was the most predominant use of land (41%) in temperate FAO-ecozones in Europe in 2015. Forest IPCC land use followed a moderate upward trend from 2000 to 2015 (0.2%). Trees Outside Forests in temperate FAO-ecozones in Europe accounted for 22% of the inventoried area. Trees Outside Forests represent 30% and 48% of cropland and grassland IPCC land uses, respectively, as well as 75% in settlement uses. Comparing our results with previous studies on the Mediterranean, temperate FAO-ecozone TOFs showed a downward trend in Europe and an upward trend in the Mediterranean area, despite its smaller surface area. The greening of the Common Agricultural Policy may increase the extension of TOFs, although our results may indicate that this effect is not yet evident in the field.