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Spatio-temporal analyses of cropland degradation in the irrigated lowlands of Uzbekistan using remote-sensing and logistic regression modeling

Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-129912
  • Advancing land degradation in the irrigated areas of Central Asia hinders sustainable development of this predominantly agricultural region. To support decisions on mitigating cropland degradation, this study combines linear trend analysis and spatial logistic regression modeling to expose a land degradation trend in the Khorezm region, Uzbekistan, and to analyze the causes. Time series of the 250-m MODIS NDVI, summed over the growing seasons of 2000–2010, were used to derive areas with an apparent negative vegetation trend; this wasAdvancing land degradation in the irrigated areas of Central Asia hinders sustainable development of this predominantly agricultural region. To support decisions on mitigating cropland degradation, this study combines linear trend analysis and spatial logistic regression modeling to expose a land degradation trend in the Khorezm region, Uzbekistan, and to analyze the causes. Time series of the 250-m MODIS NDVI, summed over the growing seasons of 2000–2010, were used to derive areas with an apparent negative vegetation trend; this was interpreted as an indicator of land degradation. About one third (161,000 ha) of the region’s area experienced negative trends of different magnitude. The vegetation decline was particularly evident on the low-fertility lands bordering on the natural sandy desert, suggesting that these areas should be prioritized in mitigation planning. The results of logistic modeling indicate that the spatial pattern of the observed trend is mainly associated with the level of the groundwater table (odds = 330 %), land-use intensity (odds = 103 %), low soil quality (odds = 49 %), slope (odds = 29 %), and salinity of the groundwater (odds = 26 %). Areas, threatened by land degradation, were mapped by fitting the estimated model parameters to available data. The elaborated approach, combining remote-sensing and GIS, can form the basis for developing a common tool for monitoring land degradation trends in irrigated croplands of Central Asia.zeige mehrzeige weniger

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Metadaten
Autor(en): Olena Dubovyk, Gunter Menz, Christopher Conrad, Elena Kann, Miriam Machwitz, Asia Khamzina
URN:urn:nbn:de:bvb:20-opus-129912
Dokumentart:Artikel / Aufsatz in einer Zeitschrift
Institute der Universität:Philosophische Fakultät (Histor., philolog., Kultur- und geograph. Wissensch.) / Institut für Geographie und Geologie
Sprache der Veröffentlichung:Englisch
Titel des übergeordneten Werkes / der Zeitschrift (Englisch):Environmental Monitoring and Assessment
Erscheinungsjahr:2012
Band / Jahrgang:185
Heft / Ausgabe:6
Seitenangabe:4775-4790
Originalveröffentlichung / Quelle:Environmental Monitoring and Assessment (2013) 185:4775–4790 DOI 10.1007/s10661-012-2904-6
DOI:https://doi.org/10.1007/s10661-012-2904-6
Allgemeine fachliche Zuordnung (DDC-Klassifikation):5 Naturwissenschaften und Mathematik / 52 Astronomie / 526 Mathematische Geografie
Freie Schlagwort(e):MODIS; NDVI; cropland abandonment; linear trend analysis; logistic regression modeling; lower reaches of Amu Darya River
Datum der Freischaltung:24.11.2016
Lizenz (Deutsch):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung