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  • 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...
  • BB

  • Simulation of Forest Evapotranspiration Using Time-Series Parameterization of the Surface Energy Balance System (SEBS) over the Qilian Mountains

    • Authors: Tian, Xin;  Advisor: -;  Participants: - (2013)

  • We propose a long-term parameterization scheme for two critical parameters, zero-plane displacement height (d) and aerodynamic roughness length (z0m), that we further use in the Surface Energy Balance System (SEBS). A sensitivity analysis of SEBS indicated that these two parameters largely impact the estimated sensible heat and latent heat fluxes. First, we calibrated regression relationships between measured forest vertical parameters (Lorey’s height and the frontal area index (FAI)) and forest aboveground biomass (AGB). Next, we derived the interannual Lorey’s height and FAI values from our calibrated regression models and corresponding forest AGB dynamics that were converted from interannual carbon fluxes, as simulated from two incorporated ecological models and a 2009 forest bas...
  • 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...
  • LA

  • Identifying and classifying slum areas using remote sensing

    • Authors: Stein, A. ; Kohli, D.;  Advisor: -;  Participants: - (2015)

  • Thesis taking UN-HABITAT’s definition of slum household as a basis, this study proposes an ontological framework that conceptualizes slums using morphological indicators of the built environment; demonstrates a case of applicability of GSO and explores the transferability of an OOA method for slum classification developed on a single image area to other image areas; proposes a hierarchical method for slum detection by using a combination of texture and spatial metrics; demonstrates a method to quantify the uncertainties of slum interpretations performed by experts; presents the main research findings and conclusions corresponding to each research objective.
  • BB

  • Remote Sensing for Biodiversity

    • Authors: Skidmore, A.K.;  Advisor: -;  Participants: - (2017)

  • Remote sensing (RS)—taking images or other measurements of Earth from above—provides a unique perspective on what is happening on the Earth and thus plays a special role in biodiversity and conservation applications. The periodic repeat coverage of satellite-based RS is particularly useful for monitoring change and so is essential for understanding trends, and also provides key input into assessments, international agreements, and conservation management. Historically, RS data have often been expensive and hard to use, but changes over the last decade have resulted in massive amounts of global data being available at no cost, as well as significant (if not yet complete) simplification of access and use. This chapter provides a baseline set of information about using RS for conservat...
  • LT

  • Remote sensing of essential biodiversity :Powerpoint

    • Authors: Mucher, S.; Skidmore, A.K.;  Advisor: -;  Participants: - (2014)

  • This lecture presents: Global biodiversity loss; What are essential biodiversity variables (ebv)?; Global climate observing system essential climate variables (ecv); Agree biodiversity metrics to track from space; Definitive set of biodiversity variables to track from space; Mismatch in the definition of remote sensing and ecological units; Progress in satellites.
  • BB

  • Satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems

    • Authors: Muller‐Karger, F.E.;  Advisor: -;  Participants: - (2018)

  • The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite-based sensors can repeatedly record the visible and near-infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae).