BGD Biogeosciences Discussions BGD 1810-6285 Copernicus GmbH Göttingen, Germany 10.5194/bgd-8-3953-2011 Analysis of vegetation and land cover dynamics in north-western Morocco during the last decade using MODIS NDVI time series data Höpfner C. 1 Scherer D. 1 Chair of Climatology, Department of Ecology, Technische Universität Berlin, Rothenburgstraße 12, 12165 Berlin, Germany 18 04 2011 8 2 3953 3998 This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This article is available from http://www.biogeosciences-discuss.net/8/3953/2011/bgd-8-3953-2011.html The full text article is available as a PDF file from http://www.biogeosciences-discuss.net/8/3953/2011/bgd-8-3953-2011.pdf

Vegetation phenology as well as current variability and dynamics of vegetation and land cover including its climatic and human drivers are examined in a region in north-western Morocco of nearly 22 700 km<sup>2</sup>. A gapless time series of Normalized Differenced Vegetation Index (NDVI) composite raster data from 29 September 2000 to 29 September 2009 with a spatial resolution of 250 m and acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor is utilised. The presented approach allows to compose and analyse yearly land cover maps in a widely unknown region with scarce validated ground truth data by deriving phenological parameters. Results show that high temporal resolution of 16 d is sufficient (a) for determining land cover better than global land cover classifications of Plant Functional Types (PFT) and Global Land Cover 2000 (GLC2000), and (b) for drawing conclusions on vegetation dynamics and its drivers. Areas of stably classified land cover types show climatically driven inter- and intra-annual variability with indicated influence of droughts. The presented approach to determine human-driven influence on vegetation dynamics caused by agriculture results in a more than ten times larger area compared to the stably classified areas. Change detection based on yearly land cover maps shows a gain of high-productive vegetation (cropland) of about 259.3 km<sup>2</sup>. However, statistically significant inter-annual trends in vegetation dynamics during the last decade could not be discovered. A sequence of correlations was done to extract the most important period of rainfall for production of green biomass and for the extent of land cover types, respectively. Results show that mean daily precipitation from 1 October to 15 December has high correlation results (max. <i>r</i><sup>2</sup>=0.85) at intra-annual time scale to NDVI percentiles (50%) of land cover types. Correlation results of mean daily precipitation from 16 September to 15 January and percentage of yearly classified area of each land cover type are medium up to high (max. <i>r</i><sup>2</sup>=0.64). In all, an offset of nearly 1.5 months is detected between precipitation rates and NDVI in 16 d steps. High-productive vegetation (cropland) is proved to be mainly rain-fed. We conclude that identification, understanding and knowledge about vegetation phenology, and current variability of vegetation and land cover as well as prediction methods of land cover change can be improved using multi-year MODIS NDVI time series data. This study enhances the comprehension of current land surface dynamics and variability of vegetation and land cover in north-western Morocco offering a fast access especially for estimating the extent of agricultural lands.

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