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  • BB

  • Simultaneous atmospheric correction and quantification of suspended particulate matter in the Guadalquivir estuary from Landsat images

    • Authors: Capintero,Mariam;  Advisor: -;  Participants: - (2015)

  • Earth observations (EOs) following empirical and/or analytical approaches are a feasible alternative to obtain spatial and temporal distribution of water quality variables. The limitations observed in the use of empirical approaches to estimate high concentrations of suspended particulate matter (SPM) in the estuarine water of Guadalquivir have led the authors to use a semi-analytical model, which relates the water constituents’ concentration to the water leaving reflectance. In this work, the atmospheric correction has been carried out simultaneously and the aerosol reflectance and backscattering coefficients of SPM obtained. The results are validated using in situ SPM data series provided by a monitoring network in the study area. The results show that the model allows us to succe...
  • LT

  • STARS project overview :Powerpoint

    • Authors: de By, R.A.;  Advisor: -;  Participants: - (2015)

  • This lecture presents: Project synopsis; Project facts; Objectives; Main hypotheses; High dimensionality of problem space; Compared to high-income ag; STARS Data collection.
  • BB

  • Modeling forest above-ground biomass dynamics using multi-source data and incorporated models: A case study over the qilian mountains

    • Authors: Tian, X.;  Advisor: -;  Participants: - (2017)

  • In this work, we present a strategy for obtaining forest above-ground biomass (AGB) dynamics at a fine spatial and temporal resolution. Our strategy rests on the assumption that combining estimates of both AGB and carbon fluxes results in a more accurate accounting for biomass than considering the terms separately, since the cumulative carbon flux should be consistent with AGB increments. Such a strategy was successfully applied to the Qilian Mountains, a cold arid region of northwest China. Based on Landsat Thematic Mapper 5 (TM) data and ASTER GDEM V2 products (GDEM), we first improved the efficiency of existing non-parametric methods for mapping regional forest AGB for 2009 by incorporating the Random Forest (RF) model with the k-Nearest Neighbor (k-NN). Validation using forest m...
  • LT

  • The STARS project :Powerpoint

    • Authors: de By, R.A.;  Advisor: -;  Participants: - (2015)

  • This lecture presents: Project synopsis; Project facts; Objectives; Main hypotheses; High dimensionality of problem space; Compared to high-income ag; STARS Data collection.
  • BB

  • How to effectively obtain metadata from remote sensing big data?

    • Authors: Körting, T.S.;  Advisor: -;  Participants: - (2016)

  • What can be considered big data when dealing with remote sensing imagery? In general terms, big data is defined as data requiring high management capabilities characterized by 3 V’s: Volume, Velocity and Variety. In the past, (e.g. 1975), considering the computational and databases resources available, a series of Landsat-1 imagery from the same region could be considered big data. Nowadays, several satellites are available, and they produce massive amounts of data. Certainly, an image data set obtained by a single satellite, for a specific region and along time, fills the 3 V’s requirements to be considered big data as well. In order to deal with remote sensing big data, we propose to explore the generation of metadata based on the detection of simple features. Besides the intrinsi...