Revista de Teledetección - Núm. 48 (2017)
URI permanente para esta colecciónhttps://riunet.upv.es/handle/10251/83596
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Research articles
- Carbon use efficiency variability from MODIS data
- Estimation of grassland biophysical parameters in a “dehesa” ecosystem from field spectroscopy and airborne hyperspectral imagery
- Estimation of real evapotranspiration (ETR) and potential evapotranspiration (ETP) in the southwest of the Buenos Aires Province (Argentina) using MODIS images
- Temporal-space characterization of satellite sea surface temperature in tourist destinations: Partido de la Costa, Pinamar and Villa Gesell, Buenos Aires, Argentina
- Land use classification from Sentinel-2 imagery
- Estimation of structural attributes of walnut trees based on terrestrial laser scanning
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Publicación Estimation of structural attributes of walnut trees based on terrestrial laser scanning(Universitat Politècnica de València, 2017-06-20) Estornell, J.; Velázquez-Martí, A.; Fernández-Sarría, A.; López-Cortés, I.; Martí-Gavilá, J.; Salazar, D.; Generalitat Valenciana[EN] Juglans regia L. (walnut) is a tree of significant economic importance, usually cultivated for its seed used in the food market, and for its wood used in the furniture industry. The aim of this work was to develop regression models to predict crown parameters for walnut trees using a terrestrial laser scanner. A set of 30 trees was selected and the total height, crown height and crown diameter were measured in the field. The trees were also measured by a laser scanner and algorithms were applied to compute the crown volume, crown diameter, total and crown height. Linear regression models were calculated to estimate walnut tree parameters from TLS data. Good results were obtained with values of R2 between 0.90 and 0.98. In addition, to analyze whether coarser point cloud densities might affect the results, the point clouds for all trees were subsampled using different point densities: points every 0.005 m, 0.01 m, 0.05 m, 0.1 m, 0.25 m, 0.5 m, 1 m, and 2 m. New regression models were calculated to estimate field parameters. For total height and crown volume good estimations were obtained from TLS parameters derived for all subsampled point cloud (0.005 m – 2 m).Publicación Clasificación de usos del suelo a partir de imágenes Sentinel-2(Universitat Politècnica de València, 2017-06-20) Borràs, J.; Delegido, J.; Pezzola, A.; Pereira, M.; Morassi, G.; Camps-Valls, G.[EN] Sentinel-2 (S2), a new ESA satellite for Earth observation, accounts with 13 bands which provide high-quality radiometric images with an excellent spatial resolution (10 and 20 m) ideal for classification purposes. In this paper, two objectives have been addressed: to determine the best classification method for S2, and to quantify its improve-ment with respect to the SPOT operational mission. To do so, four classifiers (LDA, RF, Decision Trees, K-NN) have been selected and applied to two different agricultural areas located in Valencia (Spain) and Buenos Aires (Argentina). All classifiers were tested using, on the one hand, all the S2 bands and, on the other hand, only selecting those bands from S2 closer to the four bands from SPOT. In all the cases, between 10%-50% of samples were used to train the classifier while remaining the rest for validation. As a result, a land use map was generated from the best classifier, according to the Kappa index, providing scientifically relevant information such as the area of each land use class.Publicación Caracterización espacio–temporal de la temperatura superficial del mar satelital en destinos turísticos: Partido de la Costa, Pinamar y Villa Gesell en Buenos Aires, Argentina(Universitat Politècnica de València, 2017-06-20) Verón, E.; Allega, L.; Cozzolino, E.; Camiolo, M.; Lasta, C.; Codignotto, J.[EN] The coastal spaces are fragile and complex areas that receive strong pressure because of the many uses and activities that are developed in them. The tourism of sun and beaches is one of the main economic practices present in these spaces that value the physical-natural conditions and their environmental variables. Of all of them, the sea surface temperature (SST) has been the least studied variable, especially associated to tourist destinations. The coastal zone of the province of Buenos Aires, Argentina, concentrates numerous tourist centers like the Partido de la Costa, Pinamar and Villa Gesell that attract in the summer time, a great flow of population. The objective of the present paper was to perform a descriptive and comparative analysis of SST in these parties through the use of monthly satellite images obtained by the Aqua-MODIS satellite-sensor during the period 2003-2013. The results showed a spatial and seasonal behavior of the SST differentiated for the entire study area. The SST for the warm period (January-March) ranged between 21.5 - 24.5°C and for the cold (July-September) between 9.4 - 11.5°C. This difference was lower in the cold period, allowing distinguishing 3 thermal zones with variations smaller than 0.5°C between them: Costa Norte, Costa Centro- Costa Sur, and Pinamar-Villa Gesell. The warm period presented more intense spatial thermal variations between the studied tourist destinations. Four thermal zones with 0.5°C differences were identified: Costa Norte, Costa Centro, Costa Sur, and Pinamar-Villa Gesell.Publicación Estimación de evapotranspiración real (ETR) y de evapotranspiración potencial (ETP) en el sudoeste bonaerense (Argentina) a partir de imágenes MODIS(Universitat Politècnica de València, 2017-06-20) Marini, F.; Santamaría, M.; Oricchio, P.; Di Bella, C. M.; Basualdo, A.[EN] Using regression analysis between actual evapotranspiration (ETR) and potential evapotranspiration (ETP) values obtained in seven meteorological observatories and remote sensing derived data from MODIS images (Surface temperature and Normalized Difference Vegetation Index - NDVI) models for estimating ETR and ETP in the southwest of the Buenos Aires Province (Argentina) were developed for the 2000–2014 period. Both models were satisfactorily evaluated in the meteorological observatories used. A regression model was adjusted for ETR with a determination coefficient of 0,6959. Regression model was nonlinear in the case of the ETP variable with a determination coefficient of 0,8409. The individual regression analysis for each meteorological observatories explicate the behavior of the regression for the total data set of ETR and ETP. According to these results, the utility of remote sensing in determination of ETR and ETP in areas without meteorological data was confirmed.Publicación Estimación de variables biofísicas del pastizal en un ecosistema de dehesa a partir de espectro-radiometría de campo e imágenes hiperespectrales aeroportadas(Universitat Politècnica de València, 2017-06-20) Melendo-Vega, J. R.; Martín, M. P.; Vilar del Hoyo, L.; Pacheco-Labrador, J.; Echavarría, P.; Martínez-Vega, J.; Ministerio de Ciencia e Innovación; Ministerio de Economía y Competitividad[EN] The aim of this paper is the estimation of biophysical vegetation parameters from its optical properties. The variables Fuel Moisture Content (FMC), Canopy Water Content (CWC), Leaf Area Index (LAI), dry matter (Cm) and AboveGround Biomass (AGB) were estimated in the laboratory from vegetation samples collected simultaneously with the acquisition of spectral data from the Compact Airborne Spectrographic Imager (CASI) sensor and the field spectroradiometer ASD FieldSpec® 3. Spectral vegetation indices found in the literature were computed from hyperspectral data. Their linear relationships with the biophysical variables measured in the field were analysed. Results show consistent relationships between analysed biophysical parameters and spectral indices, mainly those using SWIR and red-egde bands which reveal the importance of these spectral regions for the estimation of biophysical variables in herbaceous covers. Determination coefficients (R2) above 0.91 and RRMSE of 21.4% have been obtained for the spectral indexes calculated whit ASD data, and 0.91 R2 and RRMSE of 15.5% for the spectral indexes calculated whit CASI data.Publicación Variabilidad de la eficiencia en el uso del carbono a partir de datos MODIS(Universitat Politècnica de València, 2017-06-20) Cañizares, M.; Moreno, A.; Sánchez-Ruiz, S.; Gilabert, M.A.; European Commission; Ministerio de Economía y Competitividad[EN] Carbon use efficiency (CUE) describes how efficiently plants incorporate the carbon fixed during photosynthesis into biomass gain and can be calculated as the ratio between net primary production (NPP) and gross primary production (GPP). In this work, annual CUE has been obtained from annual GPP and NPP MODIS products for the peninsular Spain study area throughout eight years. CUE is spatially and temporally analyzed in terms of the vegetation type and annual precipitation and annual average air temperature. Results show that dense vegetation areas with moderate to high levels of precipitation present lower CUE values, whereas more arid areas present the highest CUE values. However, the temperature effect on the spatial variation of CUE is not well characterized. On the other hand, inter-annual variations of CUE of different ecosystems are discussed in terms of inter-annual variations of temperature and precipitation. It is shown that CUE exhibited a positive correlation with precipitation and a negative correlation with temperature in most ecosystems. Thus, CUE decreases when the ecosystem conditions change towards aridity.