Revista de Teledetección - Núm. 42 (2014)
Tabla de contenidos
Research articles
- Spatial distribution of the uncertainty in land cover maps obtained from remote sensing
- Methodology for the detection of land cover changes in time series of daily satellite images. Application to burned area detection
- Vegetation vulnerability to drought in Spain
- Weed mapping in early-season sunflower fields using images from an unmanned aerial vehicle (UAV)
- Herbaceous biomass estimation using hyperspectral data, PLS regression and continuum removal transformation
- fAPAR estimates over the Iberian Peninsula by the inversion of the 4SAIL 2 radiative transfer model
- Evaluation of the different spectral indices to map biocrust using spectral information
- Analysis of the topographic effect on the radiometric correction of MERIS images
Practical cases
- RSR Calculator, a tool for the Calibration / Validation activities
Doctoral theses
- Retrieval and assessment of CO2 uptake by mediterranean ecosystems using remote sensing and meteorological data
URI permanente para esta colecciónhttps://riunet.upv.es/handle/10251/80015
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Item type: Artículo , Access status: Abierto , Retrieval and assessment of CO2 uptake by mediterranean ecosystems using remote sensing and meteorological data(Universitat Politècnica de València, 2014-12-16) Moreno Martínez, A.; Ministerio de Ciencia e Innovación; Ministerio de Economía y CompetitividadReseña de tesis doctoralItem type: Artículo , Access status: Abierto , RSR Calculator, a tool for the Calibration / Validation activities(Universitat Politècnica de València, 2014-12-16) Durán-Alarcón, C.; Santamaría-Artigas, A.; Valenzuela, N.; Mattar, C.; Fondo Nacional de Desarrollo Científico y Tecnológico, Chile; Fundación Banco Santander[EN] The calibration/validation of remote sensing products is a key step that needs to be done before its use in different kinds of environmental applications and to ensure the success of remote sensing missions. In order to compare the measurements from remote sensors on spacecrafts and airborne platforms with in-situ data, it is necessary to perform a spectral comparison process that takes into account the relative spectral response of the sensors. This technical note presents the RSR Calculator, a new tool to estimate, through numerical convolution, the values corresponding to each spectral range of a given sensor. RSR Calculator is useful for several applications ranging from the convolution of spectral signatures of laboratory or field measurements to the parameter estimation for the calibration of sensors, such as extraterrestrial solar irradiance (ESUN) or atmospheric transmissivity (τ) per spectral band. RSR Calculator is a useful tool that allows the processing of spectral data and that it can be successfully applied in the calibration/validation remote sensing process of the optical domain.Item type: Artículo , Access status: Abierto , Analysis of the topographic effect on the radiometric correction of MERIS images(Universitat Politècnica de València, 2014-12-16) Grau, G.; Vicent, J.; Moreno, J.[EN] Topography alters the vertical structure of the atmosphere and, therefore, its radiative properties regarding the reflection and transmission of the solar radiation. Also it modifies the conditions of illumination of terrain, with remarkable influence in the remote sensing measures of the terrestrial surface in the optical spectrum. In this work we have applied two models of atmospheric and radiometric correction on an ENVISAT/MERIS image, considering the topography, to analyse the importance of such effects. For this, we have exploited the recent rise of Digital Models of Elevation (MDE) sufficiently detailed and precise, available to a global scale, that open new prospects for the topographical corrections of remote sensing data. The results show the adjustment of the conjoint correction model (atmospheric and topographical) in the considered case, improving comparison of spectral signatures of similar surfaces independently of the elevation or the conditions of illumination, compensating the relative variations caused by the topography in the reflectivity measured by sensors. Although the remote sensing of the terrestrial surface has tended traditionally to avoid the bands of atmospheric absorption, a peculiarity that presents the ENVISAT/MERIS images is the availability of a band (O2A) of absorption of the oxygen, located in the 761.5 nm. This band is used mainly for atmospheric corrections (estimate of the surface’s pressure, elevation of clouds, aerosols effects, etc.). But also it has been employed recently to determine the fluorescence of the vegetation, consequently this band of absorption has received remarkable attention in the last years. Considering that this absorption of the oxygen is strongly affected for topography, the determination of information on the terrestrial surface from this absorption of the oxygen requires a very precise correction of the topographical effects. Therefore in this work we analyse in particular the effect of the peak of reflectivity at 761.5 nm originated by an inappropriate correction of the topography and we study the existent relationship between the local atmospheric pressure and the depth band of absorption of the oxygen in this wavelength.Item type: Artículo , Access status: Abierto , Evaluation of the different spectral indices to map biocrust using spectral information(Universitat Politècnica de València, 2014-12-16) Alonso, M.; Rodríguez-Caballero, E.; Chamizo, S.; Escribano, P.; Cantón, Y.; Junta de Andalucía; European Regional Development Fund; Ministerio de Ciencia e Innovación[EN] Biological soil crusts (BSC) are complex communities formed by a close association of soil particles and cyanobacteria, algae, microfungi, lichens or bryophytes that live within or immediately on top of the uppermost millimeters of the soil surface. These communities cover non vegetated areas in most of the arid and semiarid ecosystems, and modify numerous soil surface properties and ecosystem processes. Given the importance of BSC in ecosystem functioning, accurate and spatially explicit information on the distribution of BSC is mandatory. With this objective, considerable effort has been devoted to identify and map BSC using remote sensing data, and some spectral indices have been developed. These indexes use the spectral differences among BSC and other surface components like vegetation or bare soil to identify the areas dominated by BSC. Our main objective is to test the feasibility of the previous indices published in the literature for mapping different types of BSC in a complex study area, where these index have not been developed, at different spatial scales. Our results showed the low capability of indexes based on multiespectral images to identify areas covered by BSCat field and image spatial scales. Hyperspetral indices, on the other hand, showed better results than those obtained with multispectral indices, with an accuracy around 71% because they analyzed specific absorption features related with photosynthetic pigments like chlorophyll and carotenoids. We can conclude that the spatial heterogeneity of the area and the spectral similarities among BSC, green and dry vegetation or bare soil makes it difficult to correctly distinguish BSC in arid and semiarid ecosystems using only multispectral information, whereas hyperspectral images offer an important tool to map different types of BSC and to discriminate among these and other surface components.Item type: Artículo , Access status: Abierto , fAPAR estimates over the Iberian Peninsula by the inversion of the 4SAIL 2 radiative transfer model(Universitat Politècnica de València, 2014-12-16) Martínez, B.; Albargues, E.; Camacho, F.; Moreno, A.; Gilabert, M A.; Ministerio de Ciencia e Innovación[EN] This work aims to the estimation of fAPAR over the Iberian Peninsula using MODIS data. First, the 4SAIL2 and PROSPECT radiative transfer models have been used to simulate a data set of reflectance and fAPAR. Second, an artificial neuronal network (ANN) has been trained using the simulated data and finally, it has been inverted to derive fAPAR estimates over the Iberian Peninsula from MODIS reflectances images. Moreover, the impact that the observation and illumination configuration have on the fAPAR estimates has been assessed. The fAPAR estimates from MODIS have been compared with other validated fAPAR products. The results confirm an overall error around the user requirements (0.1) when the fAPAR estimated from the (PROSPECT+4SAIL2+Nadir) combination is compared with the selected products. This combination is proposed as an alternative to estimate fAPAR over the Iberian Peninsula due to the ability to characterize different land cover types as well as the high intra-annual variability of particular canopiesItem type: Artículo , Access status: Abierto , Estimación de biomasa en herbáceas a partir de datos hiperespectrales, regresión PLS y la transformación continuum removal(Universitat Politècnica de València, 2014-12-16) Marabel-García, M.; Álvarez-Taboada, F.[EN] The aim of this research work was to compare the results of two methods to estimate aboveground biomass by using field spectrometer data: (i) Partial least squares regression (PLSR), and (ii) linear regression applied to the Maximum Band Depth (MBD) and Area Over the Minimum (AOM) indices. In both cases different regions of the spectrum were transformed by Continuum Removal (CR). Since the results using PLSR (R2=0.920, RMSE=3.622 g/m2) were similar to the results achieved by the indices (R2=0.915, RMSE=3.615 g/m2 for AOM), using the indices derived from CR is recommended, since their interpretation is easier than the PLS output.Item type: Artículo , Access status: Abierto , Detección de malas hierbas en girasol en fase temprana mediante imágenes tomadas con un vehículo aéreo no tripulado (UAV)(Universitat Politècnica de València, 2014-12-16) Peña, J.M.; Torres-Sánchez, J.; Serrano-Pérez, A.; López-Granados, F.; Ministerio de Economía y Competitividad; European Regional Development Fund; Consejo Superior de Investigaciones Científicas[EN] Weed mapping in early season requires of very high spatial resolution images (pixels <5 cm). Currently only Unmanned Aerial Vehicles (UAV) can take such images. The aim of this work was to evaluate the optimal flight altitude for mapping weeds in an early season sunflower field using a low-cost camera that took images in the visible spectrum at several flight altitudes (40, 60, 80 and 100 m). The object based image analysis procedure used for weed mapping was divided in two main phases: 1) crop-row identification, and 2) crop, weed and bare soil classification. The algorithm identified the crop rows with 100% accuracy at every flight altitude (phase 1) and it detected weed-free zones with 100% accuracy in the images captured at 40 and 60 m flight altitude. In weed-infested zones, the classification algorithm obtained the best results in the images captured at low altitude (40 m), reporting 71% of correctly classified sampling frames (phase 2). Most of errors committed (incorrectly classified frames) were produced by non-detection of weeds (negative false). Subsequent studies would consist in a multi-temporal study aiming to detect weeds are at a more advance growth stage. It could reduce the percentage of negative false in the classification.Item type: Artículo , Access status: Abierto , Vulnerabilidad de la vegetación a la sequía en España(Universitat Politècnica de València, 2014-12-16) García-Haro, F.J.; Campos-Taberner, M.; Sabater, N.; Belda, F.; Moreno, A.; Gilabert, M.A.; Martínez, B.; Pérez-Hoyos, A.; Meliá, J.; Ministerio de Economía y Competitividad; European Commission; Ministerio de Educación y Ciencia[EN] Frequency of climatic extremes like long duration droughts has increased in Spain over the last century.The use of remote sensing observations for monitoring and detecting drought is justified on the basis that vegetation vigor is closely related to moisture condition. We derive satellite estimates of bio-physical variables such as fractional vegetation cover (FVC) from MODIS/EOS and SEVIRI/MSG time series. The study evaluates the strength of temporal relationships between precipitation and vegetation condition at time-lag and cumulative rainfall intervals. From this analysis, it was observed that the climatic disturbances affected both the growing season and the total amount of vegetation. However, the impact of climate variability on the vegetation dynamics has shown to be highly dependent on the regional climate, vegetation community and growth stages. In general, they were more significant in arid and semiarid areas, since water availability most strongly limits vegetation growth in these environments.Item type: Artículo , Access status: Abierto , Desarrollo de una metodología para la detección de cambios de la cubierta vegetal en series temporales de imágenes de satélite diarias. Aplicación a la detección de áreas quemadas(Universitat Politècnica de València, 2014-12-16) Moreno-Ruiz, J.A.; Arbelo, M.; García-Lázaro, J.R.; Riaño-Arribas, D.; Ministerio de Economía y Competitividad[EN] We have developed a methodology for detection of observable phenomena at pixel level over time series of daily satellite images, based on using a Bayesian classifier. This methodology has been applied successfully to detect burned areas in the North American boreal forests using the LTDR dataset. The LTDR dataset represents the longest time series of global daily satellite images with 0.05° (~5 km) of spatial resolution. The proposed methodology has several stages: 1) pre-processing daily images to obtain composite images of n days; 2) building of space of statistical variables or attributes to consider; 3) designing an algorithm, by selecting and filtering the training cases; 4) obtaining probability maps related to the considered thematic classes; 5) post-processing to improve the results obtained by applying multiple techniques (filters, ranges, spatial coherence, etc.). The generated results are analyzed using accuracy metrics derived from the error matrix (commission and omission errors, percentage of estimation) and using scattering plots against reference data (correlation coefficient and slope of the regression line). The quality of the results obtained improves, in terms of spatial and timing accuracy, to other burned area products that use images of higher spatial resolution (500 m and 1 km), but they are only available after year 2000 as MCD45A1 and BA GEOLAND-2: the total burned area estimation for the study region for the years 2001-2011 was 28.56 millions of ha according to reference data and 12.41, 138.43 and 19.41 millions of ha for the MCD45A1, BA GEOLAND-2 and BA-LTDR burned area products, respectively.Item type: Artículo , Access status: Abierto , Distribución espacial de la incertidumbre en mapas de cubiertas obtenidos mediante teledetección(Universitat Politècnica de València, 2014-12-16) Pons, X.; Sevillano, E.; Moré, G.; Serra, P.; Cornford, D.; Ninyerola, M.; European Commission; Ministerio de Economía y Competitividad[EN] When combining remote sensing imagery with statistical classifiers to obtain categorical thematic maps it is not usual to provide data about the spatial distribution of the error and uncertainty of the resulting maps. This paper describes, in the context of GeoViQua FP7 project, feasible approaches for methods based on several steps such as hybrid classifiers. Both for “per pixel” and “per polygon” strategies, the proposal is based on the use of the available ground truth, which is used to properly model the spatial distribution of the errors. Results allow mapping the classification success with a very high level of reliability (R2>0,94), providing users a sound knowledge of the accuracy at every area of the map.