Search results for "Remote sensing"

Principal polynomial analysis for remote sensing data processing

2011

Inspired by the concept of Principal Curves, in this paper, we define Principal Polynomials as a non-linear generalization of Principal Components to overcome the conditional mean independence restriction of PCA. Principal Polynomials deform the straight Principal Components by minimizing the regression error (or variance) in the corresponding orthogonal subspaces. We propose to use a projection on a series of these polynomials to set a new nonlinear data representation: the Principal Polynomial Analysis (PPA). We prove that the dimensionality reduction error in PPA is always lower than in PCA. Lower truncation error and increased independence suggest that unsupervised PPA features can be b…

On the semi-automatic retrieval of biophysical parameters based on spectral index optimization

2014

Abstract: Regression models based on spectral indices are typically empirical formulae enabling the mapping of biophysical parameters derived from Earth Observation (EO) data. Due to its empirical nature, it remains nevertheless uncertain to what extent a selected regression model is the most appropriate one, until all band combinations and curve fitting functions are assessed. This paper describes the application of a Spectral Index (SI) assessment toolbox in the Automated Radiative Transfer Models Operator (ARTMO) package. ARTMO enables semi-automatic retrieval and mapping of biophysical parameters from optical remote sensing observations. The SI toolbox facilitates the assessment of biop…

Near-Real-Time Estimation of Water Vapor Column From MSG-SEVIRI Thermal Infrared Bands: Implications for Land Surface Temperature Retrieval

2015

The Meteosat Second Generation-Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) instrument provides observations of half the globe every 15 min, at low spatial resolution. These data are an invaluable tool to observe daily to yearly cycle of land surface temperature (LST), as well as for various early warning systems. However, advanced algorithms for LST estimation requires a previous estimation of the water vapor (WV) column above the observed pixel, for which no instantaneous retrieval methods are yet available, and therefore hinders their implementation in a near-real-time processing chain for MSG-SEVIRI data. This work analyzes three different formulations for such WV retrieva…

2021

Abstract Terrestrial Essential Climate Variables, known as terrestrial ECVs, are key sources of information for both application- and scientific- oriented research. A large number of global terrestrial ECV products have been derived from satellite observations, and more are forthcoming. To unlock the full potential of these products, end-users need to know their uncertainties and error magnitudes. Due to the lack of conformity among validation strategies, a wide range of validation approaches have been employed to assess the quality of these products, and have resulted in reduced comparability even for the same terrestrial ECV. Addressing this challenge in validation practices requires the …

A local post-retrieval tool for satellite precipitation estimates

2012

As illustrated by several literature case studies spread around di erent geographic locations, satellite precipi- tation estimates, obtained by means of consolidated algorithms, often result being considerably biased. Moreover observed bias is related to geographic location since particular features such as latitude, presence of coastal areas and climatological and weather regime, a ect performances of satellite estimates. Bias adjusted products that make use of global ground-based precipitation estimates, are available as well but still these datasets may show a relevant bias level. In this study a procedure to bias-adjust satellite precipitation estimates has been devel- oped for the loca…

A simple algorithm to estimate evapotranspiration from DAIS data: Application to the DAISEX campaigns

2005

DOI:10.1016/j.jhydrol.2005.03.027; The knowledge of evapotranspiration is of great interest in many applications such as assessing irrigation water use. In this paper, a methodology is presented to estimate evapotranspiration using the surface energy balance model S-SEBI (Simplified Surface Energy Balance Index) and the evaporative fraction. The method is applicable under the assumptions of constant atmospheric conditions and sufficient wet and dry pixels over the image. The model uses remotely sensed parameters such as albedo, MSAVI (Modified Soil Adjusted Vegetation Index) and surface temperature and emissivity images. The methodology has been applied over the Barrax test site, located in…

Estimating Grass Sward Quality and Quantity Parameters Using Drone Remote Sensing with Deep Neural Networks

2022

Funding Information: Funding: This research was funded by Academy of Finland ICT 2023 Smart‐HSI—“Smart hyper‐ spectral imaging solutions for new era in Earth and planetary observations” (Decision no. 335612), by the European Agricultural Fund for Rural Development: Europe investing in rural areas, Pohjois‐ Savon Ely‐keskus (Grant no. 145346) and by the European Regional Development Fund for “Cyber‐ Grass I—Introduction to remote sensing and artificial intelligence assisted silage production” pro‐ ject (ID 20302863) in European Union Interreg Botnia‐Atlantica programme. This research was car‐ ried out in affiliation with the Academy of Finland Flagship “Forest‐Human‐Machine Interplay— Buildi…

Validation of daily global solar irradiation images from MSG over Spain

2013

Abstract Daily irradiation images over Spain – area that embraces a highly heterogeneous landscape, climatic conditions and relief – are calculated from the down-welling surface short-wave radiation flux (DSSF) product derived from the MSG SEVIRI images. Their analysis and validation is carried out using two different station networks along the year 2008. The first network covers the peninsular Spain and Balearic islands. A denser one, covering the Catalonian territory and including many stations located in rugged terrain, is found useful to assess the elevation correction to be applied to the images. The statistics from the validation using the first network shows a relative mean bias of a…

Test of the MODIS Land Surface Temperature and Emissivity Separation Algorithm With Ground Measurements Over a Rice Paddy

2016

The Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and emissivity separation (MODTES) algorithm is the basis of the MOD21 product, which provides 1-km LSTs and emissivities for bands 29 (8.55 μm), 31 (11 μm), and 32 (12 μm). The MODTES algorithm uses the TES method with the water vapor scaling (WVS) method for refined atmospheric correction. The performance of the MODTES algorithm was tested with a set of MODIS data concurrent with ground LST and emissivity measurements. The test site is a large area of homogeneous full-cover rice crops (graybody), with high atmospheric water vapor. The data included LSTs measured along transects with multiple calibrate…

Atmospheric correction of optical imagery from MODIS and Reanalysis atmospheric products

2010

article i nfo In this paper we analyze the differences obtained in the atmospheric correction of optical imagery covering bands located in the Visible and Near Infra-Red (VNIR), Short-Wave Infra-Red (SWIR) and Themal-Infrared (TIR) spectral regions when atmospheric profiles extracted from different sources are used. In particular, three sensors were used, Compact High Resolution Imaging Spectrometer (CHRIS), Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) and Landsat5 Thematic Mapper (TM), whereas four atmospheric profiles sources were considered: i) local soundings launched near the sensor overpass time, ii) Moderate Resolution Radiometer (MODIS) atmospheric profiles…