Search results for "Geologi"
showing 10 items of 1383 documents
Understanding deep learning in land use classification based on Sentinel-2 time series
2020
AbstractThe use of deep learning (DL) approaches for the analysis of remote sensing (RS) data is rapidly increasing. DL techniques have provided excellent results in applications ranging from parameter estimation to image classification and anomaly detection. Although the vast majority of studies report precision indicators, there is a lack of studies dealing with the interpretability of the predictions. This shortcoming hampers a wider adoption of DL approaches by a wider users community, as model’s decisions are not accountable. In applications that involve the management of public budgets or policy compliance, a better interpretability of predictions is strictly required. This work aims …
Transferring deep learning models for cloud detection between Landsat-8 and Proba-V
2020
Abstract Accurate cloud detection algorithms are mandatory to analyze the large streams of data coming from the different optical Earth observation satellites. Deep learning (DL) based cloud detection schemes provide very accurate cloud detection models. However, training these models for a given sensor requires large datasets of manually labeled samples, which are very costly or even impossible to create when the satellite has not been launched yet. In this work, we present an approach that exploits manually labeled datasets from one satellite to train deep learning models for cloud detection that can be applied (or transferred) to other satellites. We take into account the physical proper…
Spectral alignment of multi-temporal cross-sensor images with automated kernel canonical correlation analysis
2015
In this paper we present an approach to perform relative spectral alignment between optical cross-sensor acquisitions. The proposed method aims at projecting the images from two different and possibly disjoint input spaces into a common latent space, in which standard change detection algorithms can be applied. The system relies on the regularized kernel canonical correlation analysis transformation (kCCA), which can accommodate nonlinear dependencies between pixels by means of kernel functions. To learn the projections, the method employs a subset of samples belonging to the unchanged areas or to uninteresting radiometric differences. Since the availability of ground truth information to p…
Mapping Vegetation Density in a Heterogeneous River Floodplain Ecosystem Using Pointable CHRIS/PROBA Data
2012
River floodplains in the Netherlands serve as water storage areas, while they also have the function of nature rehabilitation areas. Floodplain vegetation is therefore subject to natural processes of vegetation succession. At the same time, vegetation encroachment obstructs the water flow into the floodplains and increases the flood risk for the hinterland. Spaceborne pointable imaging spectroscopy has the potential to quantify vegetation density on the basis of leaf area index (LAI) from a desired view zenith angle. In this respect, hyperspectral pointable CHRIS data were linked to the ray tracing canopy reflectance model FLIGHT to retrieve vegetation density estimates over a heterogeneous…
Causas y consecuencias del crecimiento urbanístico en el litoral valenciano a través de la evolución de los usos del suelo. El caso de Oliva.
2019
Mediante la fotointerpretación de imágenes aéreas con la utilización de técnicas SIG y a través de un intenso trabajo bibliográfico y de campo, se realiza un análisis diacrónico (1956, 1991 y 2015) de la evolución de los usos del suelo en Oliva (València, España). A partir de este análisis multimetodológico se estudia la evolución de la situación urbanística y de las dinámicas territoriales en un municipio paradigmático para explicar la evolución urbanística del litoral valenciano en las últimas décadas. In this paper we have carried out a diachronic analysis about land uses evolution in Olive through a mixed method of research, based on photo-interpretation of aerial images (years 1956, 19…
Estudio de bofedales en los Andes ecuatorianos a través de la comparación de imágenes Landsat-8 y Sentinel-2
2019
[EN] The objective of the present study was to compare the Landsat-8 and Sentinel-2 images to calculate the wetland´s extension, distribution and degree of conservation, in Reserva de Producción de Fauna Chinborazo (RPFCH) protected area located in the Andean region of Ecuador. This process was developed with in situ work in 16 wetlands, distributed in different conservation levels. The Landsat-8 and Sentinel-2 images were processed through a radiometric calibration (restoration of lost lines or píxels and correction of the stripe of the image) and an atmospheric correction (conversion of the digital levels to radiance values), to later calculate the Vegetation spectral indexes: NDVI, SAVI …
Synergistic use of MERIS and AATSR as a proxy for estimating Land Surface Temperature from Sentinel-3 data
2016
Land Surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. With the advent of the ESA's Sentinel 3 (S3) satellite, accurate LST retrieval methodologies exploiting the synergy between OLCI and SLSTR instruments can be developed. In this paper we propose a candidate methodology for retrieving LST from data acquired with the forthcoming S3 instruments. The LST algorithm is based on the Split-Window (SW) technique with an explicit dependence on surface emissivity, in contrast to the AATSR level 2 algorithm…
Estimating high resolution evapotranspiration from disaggregated thermal images
2016
Abstract Accurate evapotranspiration (ET) estimations based on surface energy balance from remote sensing require information in the thermal infrared (TIR) domain, normally provided with an insufficient spatial resolution. In order to estimate ET in heterogeneous agricultural areas, we inspect in this paper the use of disaggregation techniques applied to two different sensors, such as MODIS (daily revisit cycle and 1 km spatial resolution in the TIR domain) and Spot 5 (5 days revisit cycle and 10 m spatial resolution in the VNIR bands but no TIR band). Spot 5 images were used as a proxy for upcoming Sentinel-2. The Simplified Two-Source Energy Balance (STSEB) model was used for the estimati…
Using MSG-Seviri Data to Monitor the Planet in Near Real Time
2018
The SEVIRI (Spinning Enhanced Visible and Infra Red Imager) instrument onboard MSG (Meteosat Second Generation) satellite series provides valuable data for the observation of our planet. We describe here the processing chain implemented at the Global Change Unit of the University of Valencia to provide information such as vegetation index, temperatures of both land and sea, synthetic quicklooks for an easy interpretation of the data as well as fire hotspots. Vegetation index and temperature data are available for download from a dedicated portal updated every 3 hours with the most recent processed data. Additionally, a web page displays this information for a non scientific public in near r…
Comparison and Evaluation of the TES and ANEM Algorithms for Land Surface Temperature and Emissivity Separation over the Area of Valencia, Spain
2017
Land Surface temperature (LST) is a key magnitude for numerous studies, especially for climatology and assessment of energy fluxes between surface and atmosphere. Retrieval of accurate LST requires a good characterization of surface emissivity. Both quantities are coupled in a single radiance measurement; for this reason, for N spectral bands available in a remote sensor, there will always be N + 1 unknowns. To solve the indeterminacy, temperature-emissivity separation methods have been proposed, among which the Temperature Emissivity Separation (TES) algorithm is one of the most widely used. The Adjusted Normalized Emissivity Method (ANEM) was proposed as a modification of the Normalized E…