Revista de Teledetección - Núm. 57 (2020)

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Artículos de investigación

Monitoring of atmospheric methane and nitrous oxide concentrations from Metop/IASI
Comparison of OMI-DOAS total ozone column with ground-based measurements in Argentina
Vegetation phenology from satellite imagery: the case of the Iberian Peninsula and Balearic Islands (2001-2017)
Evaluation of four classification algorithms of Landsat-8 and Sentinel-2 satellite images to identify forest cover in highly fragmented regions in Costa Rica

Casos prácticos

Spatial and temporal analysis of surface temperature in the Apacheta micro-basin using Landsat thermal data
Structural connectivity between the Páramos of Guacheneque and Los Cristales, Rabanal-Río Bogotá complex, Colombia
Damage Assessment and Recovery Mapping for the "Las Peñuelas" Wildfire, Moguer (Huelva). Satellite Imagery. Year 2017

Tesis doctorales

Processing and analysis of airborne full-waveform laser scanning data for the characterization of forest structure and fuel properties

URI permanente para esta colecciónhttps://riunet.upv.es/handle/10251/158746

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Mostrando 1 - 8 de 8

Access status: Abierto ,
Estimación de la fenología de la vegetación a partir de imágenes de satélite: el caso de la península ibérica e islas Baleares (2001-2017)
(Universitat Politècnica de València, 2020-12-28) Caparros-Santiago, J.A.; Rodríguez-Galiano, V.F.; Agencia Estatal de Investigación; Junta de Andalucía; Ministerio de Educación, Cultura y Deporte
[EN] Phenological dynamics of vegetation is considered as an important biological indicator for understanding the functioning of terrestrial ecosystems. Land surface phenology (LSP), the study of vegetation phenology from time series of vegetation indices (IV), has provided a comprehensive overview of ecosystem dynamics. Iberian Peninsula is one of the regions with the greatest diversity of ecosystems in European continent. It is therefore an excellent study area for monitoring phenological dynamics of vegetation. The aim of this study is to analyse the spatial variability of the phenology of the vegetation of the Iberian Peninsula and Balearic Islands for the period 2001-2017. NDVI (Normalized Difference Vegetation Index) time series were generated from the surface reflectance product MOD09Q1 at a spatial resolution of 250 meters and with a composite period of 8 days. Atmospheric disturbances and noise were reduced using a Savitzky-Golay smoothing filter. Different phenological metrics or phenometrics were extracted using a threshold-based method. Results showed the existence of a different behaviour between spring and autumn phenophases in the Atlantic and Mediterranean biogeographic regions. The Mediterranean mountainous areas showed a similar phenological behaviour to the Atlantic vegetation. Biogeographic regions showed an internal variability, which may be derived from the different behaviour of land covers (e.g., natural vegetation vs. crops).
Access status: Abierto ,
Processing and analysis of airborne full-waveform laser scanning data for the characterization of forest structure and fuel properties
(Universitat Politècnica de València, 2020-12-28) Crespo-Peremarch, Pablo; Ruiz Fernández, Luis Ángel; Departamento de Ingeniería Cartográfica Geodesia y Fotogrametría; Escuela Técnica Superior de Ingeniería Geodésica, Cartográfica y Topográfica; Grupo de Cartografía Geoambiental y Teledetección; Ministerio de Economía y Competitividad
[EN] This PhD thesis addresses the development of full-waveform airborne laser scanning (ALSFW) processing and analysis methods to characterize the vertical forest structure, in particular the understory vegetation. In this sense, the influence of several factors such as pulse density, voxel parameters (voxel size and assignation value), scan angle at acquisition, radiometric correction and regression methods is analyzed on the extraction of ALSFW metric values and on the estimate of forest attributes. Additionally, a new software tool to process ALSFW data is presented, which includes new metrics related to understory vegetation. On the other hand, occlusion caused by vegetation in the ALSFW, discrete airborne laser scanning (ALSD) and terrestrial laser scanning (TLS) signal is characterized along the vertical structure. Finally, understory vegetation density is detected and determined by ALSFW data, as well as characterized by using the new proposed metrics.
Access status: Abierto ,
Cartografía de la afección y recuperación vegetal del incendio de Las Peñuelas en Moguer (Huelva) con imágenes satelitales. Año 2017
(Universitat Politècnica de València, 2020-12-28) Vales, J.J.; Pino, I.; Granado, L.; Prieto, R.; Méndez, E.; Rodríguez, M.; Giménez de Azcárate, F.; Ortega, E.; Moreira, J. M.
[EN] Deep knowledge of the regeneration processes after a forest fire is key to addressing their adverse environmental impacts, these are especially evident in the vegetation. In the post-fire environment context, the fire severity constitutes a critical variable that affects the ecosystem response in terms of vegetation recovery and hydrogeomorphological dynamics after the fire. Therefore, the severity accurate assessment is essential for the burned areas management because of it allows the identification of priority areas and, therefore, it helps to carry out recovery strategies and measures. The area of interest is located in the natural place of Las Peñuelas (Huelva), where a large fire took place on June 24, 2017 that affected almost 10 000 ha. The methodology was based on the calculation of the RBR (Relativized Burn Ratio) spectral index to estimate the severity of the fire, and the NDVI (Normalized Difference Vegetation Index) index to evaluate the recovery of vegetal vigor. For the work, images from the Sentinel-2 and Pleiades satellites, images acquired by UAV (Unmanned Aerial Vehicle) and field samplings were used. The result was a cartography showing the levels of recovery or degradation of the affected vegetation.
Access status: Abierto ,
Conectividad estructural entre los Páramos de Guacheneque y Los Cristales, complejo Rabanal-río Bogotá, Colombia
(Universitat Politècnica de València, 2020-12-28) Forero-Gómez, Y. K.; Gil-Leguizamón, P.A.; Morales-Puentes, M.E.
[EN] Structural connectivity is a measure of the spatio-temporal changes that affect the movement of species between elements of the landscape and availability of habitat; these modifications that have been documented for high mountain ecosystems in Colombia (páramo and high Andean forest) and are caused by agricultural and other economic activities that affect their integrity. The objective of this study was to evaluate the dynamics of the changes between plant cover (1987-2018) in the Guacheneque and Los Cristales páramos (Boyacá-Cundinamarca, Colombia). Images from Landsat 4 and 8 sensors were used. Pre and post-processing (supervised classification and field verification) were performed with ArcGIS and ERDAS. To estimate structural connectivity, metrics of landscape diversity, composition and configuration were calculated (Fragstats v4.2.1). Thematic reliability was 88%. Mosaic covering of pastures and crops (Mpc – 288 ha), dense grassland of firm ground (HdTf- 24 ha) and high open forest (Baa-165 ha), increased in 31 years, while dense bush (Ad) decreased 477 ha. The distance between tiles of Mpc and Ad increased (from 150.74 m to 170.70 m and from 196.96 m to 236.64 m respectively), and decreased for Baa (from 166.74 m to 159.27 m). Connectivity increased for Mpc and Baa, and decreased for Ad. The evaluated páramos make up a landscape with frequent and intensive land use, the effect of a long history of occupation of this territory. The dynamics of structural connectivity registered an increase in agricultural activities (páramo-grasslands transition). These have caused tensions and contradictions in the delimitation of páramos, a local loss of the natural area, a decrease in the average size of the tiles, and an increase in the perimeter /surface ratio distance between nuclei. The results corroborate the isolation and loss of habitat, the negative impacts on the biodiversity of the Rabanal-Río Bogotá páramos complex.
Access status: Abierto ,
Análisis espacial y temporal de la temperatura superficial en la microcuenca Apacheta mediante datos térmicos Landsat
(Universitat Politècnica de València, 2020-12-28) Moncada, W.; Willems, B.
[EN] High Andean ecosystems, such as grasslands and peatlands, are fragile and, due to the effects of climate change, their sustainability is being jeopardized. A key factor hampering sustainable management efforts from the government and communities, is the lack or scarcity of in-situ eco-hydrological and climate data. In that sense, remote sensing techniques offers a powerful alternative for the assessment of the evolution of these ecosystems, by providing a holistic view of the territory. The objective of this work is to determine both the spatial and temporal evolution of the local atmospheric temperature of the Apacheta micro-basin in Ayacucho over the past 34 years, using the soil surface temperature (SST) as a proxy. For this, thermal data of Landsat series (TM, ETM+ and TIRS sensors), covering the period from 1985 to 2018, were used. The TSS estimates were made from the emissivity correction of the brightness temperatures at the top of the atmosphere, considering the negligible atmospheric effect due to the conditions of high atmospheric transmissivity in the study area. The results show a positive trend of the SST with an increase of 4.9 °C, equivalent to 27.5% of the SST. Trends are higher (5.8 °C) in the snowy areas (equivalent to 35.3% of the TSS in the whole micro-basin). The SST in the snow area explains the 83.6% of the behavior of the snow cover derived by the NDSI, with a decreasing surface as SST increase.
Access status: Abierto ,
Evaluación de cuatro algoritmos de clasificación de imágenes satelitales Landsat-8 y Sentinel-2 para la identificación de cobertura boscosa en paisajes altamente fragmentados en Costa Rica
(Universitat Politècnica de València, 2020-12-28) Ávila-Pérez, I.D.; Ortiz-Malavassi, E.; Soto-Montoya, C.; Vargas-Solano, Y.; Aguilar-Arias, H.; Miller-Granados, C.
[EN] Mapping of land use and forest cover and assessing their changes is essential in the design of strategies to manage and preserve the natural resources of a country, and remote sensing have been extensively used with this purpose. By comparing four classification algorithms and two types of satellite images, the objective of the research was to identify the type of algorithm and satellite image that allows higher global accuracy in the identification of forest cover in highly fragmented landscapes. The study included a treatment arrangement with three factors and six randomly selected blocks within the Huetar Norte Zone in Costa Rica. More accurate results were obtained for classifications based on Sentinel-2 images compared to Landsat-8 images. The best classification algorithms were Maximum Likelihood, Support Vector Machine or Neural Networks, and they yield better results than Minimum Distance Classification. There was no interaction among image type and classification methods, therefore, Sentinel-2 images can be used with any of the three best algorithms, but the best result was the combination of Sentinel-2 and Support Vector Machine. An additional factor included in the study was the image acquisition date. There were significant differences among months during which the image was acquired and an interaction between the classification algorithm and this factor was detected. The best results correspond to images obtained in April, and the lower to September, month that corresponds with the period of higher rainfall in the region studied. The higher global accuracy identifying forest cover is obtained with Sentinel-2 images from the dry season in combination with Maximum Likelihood, Support Vector Machine, and Neural Network image classification methods.
Access status: Abierto ,
Comparison of OMI-DOAS total ozone column with ground-based measurements in Argentina
(Universitat Politècnica de València, 2020-12-28) Orte, P. F.; Luccini, E.; Wolfram, E.; Nollas, F.; Pallotta, J.; D'Elia, R.; Carbajal, G.; Mbatha, N.; Hlongwane, N.
[EN] Total ozone column (TOC) measurements through the Ozone Monitoring Instrument (OMI/NASA EOSAura) are compared with ground-based observations made using Dobson and SAOZ instruments for the period 2004–2019 and 2008–02/2020, respectively. The OMI data were inverted using the Differential Optical Absorption Spectroscopy algorithm (overpass OMI-DOAS). The four ground-based sites used for the analysis are located in subpolar and subtropical latitudes spanning from 34°S to 54°S in the Southern Hemisphere, in the Argentine cities of Buenos Aires (34.58°S, 58.36°W; 25 m a.s.l.), Comodoro Rivadavia (45.86°S, 67.50°W; 46 m a.s.l.), Río Gallegos (51.60°S, 69.30°W; 72 m a.s.l.) and Ushuaia (54.80°S, 68.30°W; 14 m a.s.l.). The linear regression analyzes showed correlation values greater than 0.90 for all sites. The OMI measurements revealed an overestimation of less than 4 % with respect to the Dobson instruments, while the comparison with the SAOZ instrument presented a very low underestimation of less than 1 %.
Access status: Abierto ,
Monitorización de las concentraciones atmosféricas de metano y óxido nitroso a partir del Metop/IASI
(Universitat Politècnica de València, 2020-12-28) García, O.; Schneider, M.; Ertl, B.; Sepúlveda, E.; Borger, C.; Diekmann, C.; Hase, F.; Khosrawi, F.; Cansado, A.; Aullé, M.; European Commission; Ministerio de Economía y Competitividad
[EN] Future of the Earth-atmosphere system will depend, to a large extent, on our capability of understanding all the processes driving climate change and, in this context, of outstanding importance are the monitoring and the investigation of greenhouse gases (GHGs), as main drivers of the Earth’s climate change. With this idea the project INMENSE (IASI for Surveying Methane and Nitrous Oxide in the Troposphere) was born, which aims to improve our current understanding of the atmospheric budgets of two of the most important well-mixed greenhouse gases, methane (CH4) and nitrous oxide (N2O). To this end, INMENSE has generated a new global observational data set of middle/upper tropospheric concentrations of CH4 and N2O from the space-based remote sensor IASI (Infrared Atmospheric Sounding Interferometer), on board the meteorological satellites EUMETSAT/Metop. In this work the INMENSE IASI CH4 and N2O products are presented, characterized and comprehensively validated by using a multiplatform reference database (aircraft vertical profiles, ground-based in-situ and remote-sensing observations). This extensive validation exercise suggests that the IASI CH4 and N2O products shows a precision between 1-3% and a bias of 2% as well as they are consistent temporally and spatially. Finally, the CH4 and N2O IASI observations over the Iberian Peninsula have been compared to MOCAGE chemical transport simulations, assessing the degree of agreement between both datasets.

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