Deutsch
 
Hilfe Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT
  Exploiting synergies of global land cover products for carbon cycle modeling

Jung, M., Henkel, K., Herold, M., & Churkina, G. (2006). Exploiting synergies of global land cover products for carbon cycle modeling. Remote Sensing of Environment, 101(4), 534-553.

Item is

Dateien

einblenden: Dateien
ausblenden: Dateien
:
BGC0890.pdf (Verlagsversion), 626KB
 
Datei-Permalink:
-
Name:
BGC0890.pdf
Beschreibung:
-
OA-Status:
Sichtbarkeit:
Eingeschränkt (Max Planck Institute for Biogeochemistry, MJBK; )
MIME-Typ / Prüfsumme:
application/octet-stream
Technische Metadaten:
Copyright Datum:
-
Copyright Info:
-
Lizenz:
-

Externe Referenzen

einblenden:

Urheber

einblenden:
ausblenden:
 Urheber:
Jung, M.1, Autor           
Henkel, K.2, Autor           
Herold, M., Autor
Churkina, G.1, Autor           
Affiliations:
1Department Biogeochemical Systems, Prof. M. Heimann, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1497755              
2Department Biogeochemical Processes, Prof. E.-D. Schulze, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1497751              

Inhalt

einblenden:
ausblenden:
Schlagwörter: Land cover Carbon cycle Fuzzy logic Remote sensing Global Igbp discover Classification accuracy Data sets Resolution Map Satellite Dynamics Scale Modis
 Zusammenfassung: Within the past decade, several global land cover data sets derived from satellite observations have become available to the scientific community. They offer valuable information on the current state of the Earth's land surface. However, considerable disagreements among them and classification legends not primarily suited for specific applications such as carbon cycle model parameterizations pose significant challenges and uncertainties in the use of such data sets. This paper addresses the user community of global land cover products. We first review and compare several global land cover products, i.e. the Global Land Cover Characterization Database (GLCC), Global Land Cover 2000 (GLC2000), and the MODIS land cover product, and highlight individual strengths and weaknesses of mapping approaches. Our overall objective is to present a straightforward method that merges existing products into a desired classification legend. This process follows the idea of convergence of evidence and generates a 'best-estimate' data set using fuzzy agreement. We apply our method to develop a new joint I-km global land cover product (SYNMAP) with improved characteristics for land cover parameterization of the carbon cycle models that reduces land cover uncertainties in carbon budget calculations. The overall advantage of the SYNMAP legend is that all classes are properly defined in terms of plant functional type mixtures, which can be remotely sensed and include the definitions of leaf type and longevity for each class with a tree component. SYNMAP is currently used for parameterization in a European model intercomparison initiative of three global vegetation models: BIOME-BGC, LPJ, and ORCHIDEE. Corroboration of SYNMAP against GLCC, GLC2000 and MODIS land cover products reveals improved agreement of SYNMAP with all other land cover products and therefore indicates the successful exploration of synergies between the different products. However, given that we cannot provide extensive validation using reference data we are unable to prove that SYNMAP is actually more accurate. SYNMAP is available on request from Martin Jung. (c) 2006 Elsevier Inc. All rights reserved. [References: 38]

Details

einblenden:
ausblenden:
Sprache(n):
 Datum: 2006
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: Anderer: BGC0890
 Art des Abschluß: -

Veranstaltung

einblenden:

Entscheidung

einblenden:

Projektinformation

einblenden:

Quelle 1

einblenden:
ausblenden:
Titel: Remote Sensing of Environment
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: New York : Elsevier
Seiten: - Band / Heft: 101 (4) Artikelnummer: - Start- / Endseite: 534 - 553 Identifikator: CoNE: https://pure.mpg.de/cone/journals/resource/954925437513
ISSN: 0034-4257