Search results for " REMOTE SENSING"

Cloud screening and multitemporal unmixing of MERIS FR data

2007

The operational use of MERIS images can be hampered by the presence of clouds. This work presents a cloud screening algorithm that takes advantage of the high spectral and radiometric resolutions of MERIS and the specific location of some of its bands to increase the cloud detection accuracy. Moreover, the proposed algorithm provides a per-pixel probabilistic map of cloud abundance rather than a binary cloud presence flag. In order to test the proposed algorithm we propose a cloud screening validation method based on temporal series. In addition, we evaluate the impact of the cloud screening in a multitemporal unmixing application, where a temporal series of MERIS FR images acquired over Th…

Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties – A review

2015

Abstract: Forthcoming superspectral satellite missions dedicated to land monitoring, as well as planned imaging spectrometers, will unleash an unprecedented data stream. The processing requirements for such large data streams involve processing techniques enabling the spatio-temporally explicit quantification of vegetation properties. Typically retrieval must be accurate, robust and fast. Hence, there is a strict requirement to identify next-generation bio-geophysical variable retrieval algorithms which can be molded into an operational processing chain. This paper offers a review of state-of-the-art retrieval methods for quantitative terrestrial bio-geophysical variable extraction using op…

Performance of Spectral Fitting Methods for vegetation fluorescence quantification

2010

The Fraunhofer Line Discriminator (FLD) principle has long been considered as the reference method to quantify solar-induced chlorophyll fluorescence (F) from passive remote sensing measurements. Recently, alternative retrieval algorithms based on the spectral fitting of hyperspectral radiance observations, Spectral Fitting Methods (SFMs), have been proposed. The aim of this manuscript is to investigate the performance of such algorithms and to provide relevant information regarding their use. FLD and SFMs were used to estimate F starting from Top Of Canopy (TOC) fluxes at very high spectral resolution (0.12 nm) and sampling interval (0.1 nm), exploiting the O2-B (687.0 nm) and O2-A (760.6 …

Water erosion prediction by stochastic and empirical models in the Mediterranean: A case study in Northern Sicily (Italy)

2012

The present thesis aimed to explore the methodological advantages as well as limitations in applying different modelling approaches to predict water soil erosion in Mediterranean environments. The research was accomplished in the central northern part of Sicily (Italy), considering this region to be representative of Mediterranean environmental conditions. In this region soil degradation problems, due to water erosion are becoming more and more serious. Consequently, defining models being able to predict erosion susceptibility and to discriminate environmental factors causing erosion is important to protect soil resources. The prediction of the spatial distribution of soil erosion processes…

Batch Methods for Resolution Enhancement of TIR Image Sequences

2015

Thermal infrared (TIR) time series are exploited by many methods based on Earth observation (EO), for such applications as agriculture, forest management, and meteorology. However, due to physical limitations, data acquired by a single sensor are often unsatisfactory in terms of spatial or temporal resolution. This issue can be tackled by using remotely sensed data acquired by multiple sensors with complementary features. When nonreal-time functioning or at least near real-time functioning is admitted, the measurements can be profitably fed to a sequential Bayesian algorithm, which allows to account for the correlation embedded in the successive acquisitions. In this work, we focus on appli…

Advances in Kernel Machines for Image Classification and Biophysical Parameter Retrieval

2017

Remote sensing data analysis is knowing an unprecedented upswing fostered by the activities of the public and private sectors of geospatial and environmental data analysis. Modern imaging sensors offer the necessary spatial and spectral information to tackle a wide range problems through Earth Observation, such as land cover and use updating, urban dynamics, or vegetation and crop monitoring. In the upcoming years even richer information will be available: more sophisticated hyperspectral sensors with high spectral resolution, multispectral sensors with sub-metric spatial detail or drones that can be deployed in very short time lapses. Besides such opportunities, these new and wealthy infor…

Soil Water Content Assessment: Critical Issues Concerning the Operational Application of the Triangle Method

2015

Knowledge of soil water content plays a key role in water management efforts to improve irrigation efficiency. Among the indirect estimation methods of soil water content via Earth Observation data is the triangle method, used to analyze optical and thermal features because these are primarily controlled by water content within the near-surface evaporation layer and root zone in bare and vegetated soils. Although the soil-vegetation-atmosphere transfer theory describes the ongoing processes, theoretical models reveal limits for operational use. When applying simplified empirical formulations, meteorological forcing could be replaced with alternative variables when the above-canopy temperatu…

Surface soil humidity retrieval using remote sensing techniques: a triangle method validation

2010

Soil humidity plays a key-role in hydrological and agricultural processes. In the rainfall-runoff processes the knowledge of its spatial distribution is fundamental to accurately model these phenomena. Furthermore in agronomy and agricultural sciences, assessing the water content of the root zone is required in order to optimize the plant productivity and to improve the irrigation systems management. Despite the importance of this variable the in situ measurements techniques based on Time Domain Reflectometry (TDR) or on the standard thermo-gravimetric methods, are neither cost-effective nor representative of its spatial and temporal variability. Indirect estimations via Earth Observation (…

Challenges and Opportunities in Lidar Remote Sensing

2021

Monitoring Subaquatic Vegetation Using Sentinel-2 Imagery in Gallocanta Lake (Aragón, Spain)

2022

Remote sensing allows the study of aquatic vegetation cover in shallow lakes from the different spectral responses of the water as the vegetation grows from the bottom toward the surface. In the case of Gallocanta Lake, its seasonality and shallow depth (less than 2 m) allow us to appreciate the variations in the aquatic vegetation with the apparent color. Six common vegetation indices were tested, and the one with the best response was the so-called NDI45, which uses the normalized ratio between the far red (705 nm) and red (665 nm) bands. Our aims are to show the variations in the surface area covered by vegetation at the bottom of the lagoon, its growth and disappearance when drying occu…