首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Visualizing and quantifying the movement of vegetative drought using remote-sensing data and GIS
Authors:Coco M Rulinda  Alfred Stein  Ulan D Turdukulov
Institution:1. Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente , Enschede , The Netherlands coco.rulinda@gmail.com;3. Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente , Enschede , The Netherlands
Abstract:Remote-sensing-based drought monitoring methods provide fast and useful information for a sustainable management strategy of drought impact over a region. Common pixel-based monitoring methods are limited in the analysis of the dynamics of this impact at regional scale. For instance, these hardly allow us to quantify the movement of drought in space and time and to compare drought with rainfall deficits without losing the variability of these events within a region. This study proposed an object-based approach that allowed us to visualize and quantify the spatio-temporal movement of drought impact on vegetation, called vegetative drought, in a region. The GIS software Dynomap was used to extract and track objects. Measures of distance and angle were used for determining the speed and direction of vegetative drought and rainfall deficit objects, calculated from the National Oceanic and Atmospheric Administration's (NOAA's) normalized difference vegetation index and rainfall estimates data. The methods were applied to the two rainy seasons during the drought year 1999 in East Africa. Results showed that vegetative drought objects moved into the southwestern direction at an average angle of??138.5° during the first season and??144.5° during the second season. The speed of objects varied between 38 km dekad?1 and 185 km dekad?1 during the first season and between 33 km dekad?1 and 144 km dekad?1 during the second season, reflecting the rate of spread between dekads. Vegetative drought objects close to rainfall deficit objects showed similar trajectories and sometimes regions overlapped. This indicated that the two events are related. We conclude that a spatiotemporal relationship existed between the two types of events and that this could be quantified.
Keywords:drought  trajectories  spatio-temporal objects  spatial data quality  remote sensing  GIS
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号