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  • Data  (2)
  • Maps
  • Database  (1)
  • Hyperspectral  (1)
  • Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten  (2)
  • English  (2)
  • 2010-2014  (2)
  • 2005-2009
Collection
  • Data  (2)
  • Maps
Publisher
  • Geographisches Institut der Universität zu Köln - Kölner Geographische Arbeiten  (2)
Language
  • English  (2)
Years
  • 2010-2014  (2)
  • 2005-2009
Year
  • 1
    Publication Date: 2022-01-14
    Description: Abstract
    Description: Nitrogen (N) is one of the most essential elements in agriculture and ecology due to its direct role in determining crop yield and grain quality, as well as its association with canopy photosynthetic capacity and carbon-nitrogen cycling in the earth ecosystem. Remote sensing provides a useful way to capture canopy nitrogen and biomass with high spatial and temporal resolution. However, seasonal dynamics of plant morphophysiological variation hinder the simultaneous estimation of canopy N concentration (%N) and biomass using a traditional method such as vegetation indices because of the distinct dynamics of canopy biochemical and physical traits. In contrast, multivariate analysis method offers the capability of calibrating a model with multiple dependent variables of interest. Therefore, the main objective of this study was to, simultaneously, estimate canopy %N and biomass of rice using the partial least squares regression (PLSR) model. A field experiment was conducted for paddy rice fertilized with five N rates across five growth stages in 2008, located in the Sanjiang Plain, China. Results showed that the PLS regression model simultaneously explained 84% and 91% of the variation in %N and biomass, respectively, across the five growth stages. Our results also suggest that biomass is the dominant factor that affects the link between canopy dynamical traits and canopy reflectance measures. This study demonstrates that, by incorporating with PLSR for retrieving biophysical and biochemical properties from the full-spectrum analysis, to what extent canopy %N and biomass can be simultaneously estimated from canopy reflectance measurement.
    Keywords: Nitrogen ; Biomass ; Hyperspectral ; Remote Sensing ; Agriculture ; 550 Earth sciences
    Language: English
    Type: Text , Workshop paper
    Format: 5 Pages
    Format: 1130 Kilobytes
    Format: application/pdf
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  • 2
    Publication Date: 2022-01-14
    Description: Abstract
    Description: AMMA program includes in situ measurements at many locations of West Africa and in the Gulf of Guinea, an intensive use of satellite data, diverse modelling studies, as well as human sciences field surveys and value-added products processing. Therefore, AMMA database aims at storing a great amount and a large variety of data, and at providing the data as rapidly and safely as possible to the AMMA research community. In order to stimulate the exchange of information and collaboration between researchers from different disciplines or using different tools, the database provides a detailed description of the products and uses standardized formats. AMMA database and the associated online tools have been fully developed and are managed by two teams in France (IPSL Data Centre, Palaiseau and OMP Data Centre, Toulouse). Datasets are stored in one or the other centre depending on their types, but all of them can be accessed through a single and friendly data request user interface. The complete system has been duplicated at AGHRYMET Regional Centre (CRA) in Niamey, Niger and is operational there since January 2009.
    Description: SeriesInformation
    Description: Proceedings of the Data Management Workshop, 29-30 October 2009, University of Cologne, Germany, Kölner Geographische Arbeiten, 90, pp. 45-51
    Keywords: Multidisciplinarity ; Database ; Data Management
    Language: English
    Type: Text , Workshop paper
    Format: 1119 Kilobytes
    Format: 7 Pages
    Format: application/pdf
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