Publication details
Phenological Patterns for Central Asia. Vegetation Dynamics by the Means of Remote Sensing
| Authors | |
|---|---|
| Year of publication | 2011 |
| Type | Article in Proceedings |
| Conference | 31st EARSeL Symposium Proceedings |
| MU Faculty or unit | |
| Citation | |
| Web | http://www.earsel.org/symposia//2011-symposium-Prague/Proceedings/index.htm |
| Field | Atmosphere sciences, meteorology |
| Keywords | phenology NDVI Central Asia MODIS GIMMS |
| Description | Phenology is an important indicator for climate conditions. Thus studying vegetation dynamics could lead to a better understanding of present and future climate changes. For assessing of vegetation dynamics on a regional scale remote sensing is currently the only method that offers at the same time the possibility for continuous monitoring over long time spans. In this study, we extracted and analyzed phenological parameters from remotely sensed time series data for Central Asia at different scales. At regional (Central Asia) level time series of the Normalized Difference Vegetation Index (NDVI) from the Global Inventory Modeling and Mapping Studies (GIMMS) derived from imagery of the Advanced Very High Resolution Radiometer (AVHRR) instrument were utilized. These data cover a time period of 25 years (1982-2006) and have a spatial resolution of 8 km. At the sub-regional level (Naryn, Karadarya and Zerafshan catchments, Fergana Valley and Fergana and Chatkal ranges of Tien-Shan) 250 m NDVI products of the Moderate Resolution Imaging Spectroradiometer (MODIS) were processed for the years 2001-2009. Different methods for filtering satellite time series and extracting phenological parameters were employed using TIMESAT software. The Asymmetric Gaussian method with a 25% threshold was selected for computation of the start of the spring season (SOS) and length of season (LOS) from the two data-sets. We show the general pattern of spring phenology for Central Asia with an early start south-west and continuing towards north-east up to 3 months later. Agricultural sites show a later start and longer vegetation season than surrounding areas. However for arid regions the method is not suitable due to the very low vegetation signal in these areas. The results revealed additionally that this satellite based method offers rather relative than absolute measures of seasonality and that phenological metrics are sensible to resolution level. |