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AVHRR-based spectral vegetation Index for quantitative assessment of vegetation state and productivity: calibration and validation / F. Kogan in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 8 (August 2003)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 69 n° 8 (August 2003) . - pp 899 - 906 Titre : AVHRR-based spectral vegetation Index for quantitative assessment of vegetation state and productivity: calibration and validation Type de document : Article/Communication Auteurs : F. Kogan, Auteur ; A. Gitelson, Auteur ; E. Zakarin, Auteur ; L. Spivak, Auteur ; L. Lebed, Auteur Année de publication : 2003 Article en page(s) : pp 899 - 906 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Advanced Very High Resolution Radiometer [Termes IGN] étalonnage en vol [Termes IGN] gestion des ressources [Termes IGN] indice de végétation [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] tronc Résumé : (Auteur) The goal of the work was to estimate, quantitatively, vegetation state and productivity using AVHRR based Vegetation Condition Index (VCI). The VCI algorithm includes application of postlaunch calibration to visible channels, calculation of NDVI from channels' reflectance, removal of high frequency noise from NDVI's annual time series, stratification of ecosystem resources, and separation of ecosystem and weather components in the NDVI value. The weather component was calculated by normalizing the NDVI to the difference of the extreme NDVI fluctuations (maximum and minimum), derived from multiyear data for each week and land pixel. The VCI was compared with wheat density measured in Kazakhstan. Six test fields were located in different climatic (annual precipitation 150 to 700 mm) and ecological (semi desert to steppe forest) zones with elevations from 200 to 700 m and a wide range of NDVI variation over space and season from 0.05 to 0.47. Plant density (PD) was measured in wheat fields by calculating the number of stems per unit area. PD deviation from year to year (PDD) was expressed as a deviation from median density calculated from multiyear data. The correlation between PDD and VCI all stations was positive and quite strong (r2 > 0.75) with the Standard Errors of Estimates (SEE) of PDD less than 16 percent ; for individual stations, the SEE was less than 11 percent. The results indicate that VCI is an appropriate index for monitoring weather impact on vegetation and for assessment of pasture and crop productivity in Kazakhstan. Because satellite observations provide better spatial and temporal coverage, the VCI based system will provide efficient tools for management of water resources and the improvement of agricultural planning. This system will serve as a prototype in the other parts of the world where ground observations are limited or not available. Numéro de notice : A2003-170 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.69.8.899 En ligne : https://doi.org/10.14358/PERS.69.8.899 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22466 [article]

Drought monitoring based on thermal and microwave satellite data / Katarzyna Dabrowska-Zielinska (31/05/1999)

Public contenu dans Remote sensing in the 21st century : economic and environmental applications / José Luis Casanova (2000) Titre : Drought monitoring based on thermal and microwave satellite data Type de document : Article/Communication Auteurs : Katarzyna Dabrowska-Zielinska, Auteur ; A. Ciolkosz, Auteur ; Marta Gruszczynska, Auteur ; W.S. Kowalik, Auteur ; F. Kogan, Auteur Editeur : Lisse et Amsterdam : Balkema (August Aimé) Année de publication : 31/05/1999 Conférence : EARSeL 1999, 19th symposium, Remote sensing in the 21st century : economic and environmental applications 31/05/1999 02/06/1999 Valladolid Espagne Importance : pp 75 - 78 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] céréales [Termes IGN] cultures [Termes IGN] image ERS-SAR [Termes IGN] image NOAA-AVHRR [Termes IGN] image thermique [Termes IGN] radar à antenne synthétique [Termes IGN] sécheresse [Termes IGN] surveillance agricole [Termes IGN] télédétection en hyperfréquence Résumé : (Auteur) The Remote Sensing and Spatial Information Centre - OPOLIS in co-operation with NOAA/NESDIS Satellite Laboratory in Washington and ESA has conducted multidisciplinary studies on impacts of environment on agriculture with application of remote sensing data for several years. Research activities included vegetation monitoring using NOAA/AVHRR as well as high resolution ERS-2.SAR data. Recently, a successful attempt was launched to use low resolution AVHRR data for early drought detection in Poland. NOAA images have been used to derive Temperature Condition Index (TCI) characterising the status of crop development. TCI index represents the relation between actual weekly value of temperature and the temperature, which occurred during both favourable and stress crop growing conditions in the last decade. The differences in TCI values and their spatial distribution for the whole country give information where and when the drought has started and how intensive it was. The research also demonstrated that backscattering coefficient calculated from ERS-1/2.SAR data characterises soil moisture condition and can be used for drought detection. Our research has been conducted for cereals and validated through detailed ground measurements. This paper presents the results obtained for 1992 (drought conditions), 1994 (mean moisture conditions) and 1998 (favourable moisture conditions) for cereals. Numéro de notice : C1999-038 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Communication Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=65804