Search results for "Sentinel 2"
showing 4 items of 4 documents
Estimating crop coefficients and actual evapotranspiration in citrus orchards with sporadic cover weeds based on ground and remote sensing data
2022
AbstractAccurate estimations of actual crop evapotranspiration are of utmost importance to evaluate crop water requirements and to optimize water use efficiency. At this aim, coupling simple agro-hydrological models, such as the well-known FAO-56 model, with remote observations of the land surface could represent an easy-to-use tool to identify biophysical parameters of vegetation, such as the crop coefficient Kc under the actual field conditions and to estimate actual crop evapotranspiration. This paper intends, therefore, to propose an operational procedure to evaluate the spatio-temporal variability of Kc in a citrus orchard characterized by the sporadic presence of ground weeds, based o…
Multitemporal water quality study in Sitjar (Castelló, Spain) reservoir using Sentinel-2 images
2020
[EN] Water quality is a subject of intense scientific inquiry because of its repercussion in human’s life, agriculture or even energy generation. Remote sensing can be used to control water masses by analyzing biophysical variables. Chlorophyll-a (Chl-a) and Total Suspended Solids (SS) are a well-known feature of water quality. These variables have been measured in Sitjar reservoir (Castelló, Spain) as a part of the project Ecological Status of Aquatic Systems with Sentinel Satellites (ESAQS), in order to compare the results with satellite reflectance data. Two processes were compared to correct atmospherically the level 1C Sentinel 2 (S2) images. The results show that Case 2 Regional Coast…
Estudio integral de humedales altoandinos (andean peatlands) con Teledetección y SIG
2022
La Reserva de Producción de Fauna Chimborazo (RPFCH) es un ecosistema de alto valor situado en los andes ecuatorianos, ocupado en su mayor parte por turberas, también llamados bofedales o peatlands. El objetivo de esta tesis es el estudio de dichos ecosistemas a partir de una extensa base de datos de campo obtenida en 2016 y usando datos de teledetección óptica y radar y variables topográficas, ambientales y climáticas con SIG. Para ello se analizaron los mejores métodos para el cartografiado de los peatlands en la RPFCH, la estimación del carbono bajo el suelo (COS) en la capa 0-30 cm y la estimación del carbono almacenado en la vegetación calculado a partir de la biomasa. Como resultado s…
Machine Learning Regression Approaches for Colored Dissolved Organic Matter (CDOM) Retrieval with S2-MSI and S3-OLCI Simulated Data
2018
The colored dissolved organic matter (CDOM) variable is the standard measure of humic substance in waters optics. CDOM is optically characterized by its spectral absorption coefficient, a C D O M at at reference wavelength (e.g., ≈ 440 nm). Retrieval of CDOM is traditionally done using bio-optical models. As an alternative, this paper presents a comparison of five machine learning methods applied to Sentinel-2 and Sentinel-3 simulated reflectance ( R r s ) data for the retrieval of CDOM: regularized linear regression (RLR), random forest regression (RFR), kernel ridge regression (KRR), Gaussian process regression (GPR) and support vector machines (SVR). Two different datasets of radiative t…