Page 84 - Module_4_en
P. 84

Module     GIS is not only a storage and analysis tool, but it is a very powerful visual and universal language. GIS
       4          systems are clearly of great value to environmental managers. They exist as standalone data management

                  systems, and can perform analysis of complex data. Simulations and models can be presented in a
                  GIS to help predict potential impacts and future changes under current management programmes or
                  environmental conditions.

            9-12 December, 2013  BOX 6  Assessment of rangeland degradation and development of a strategy


                                    for rehabilitationon climate change





                       This study used satellite data from different sensor systems to analyze and explain the
                       causes, processes, and impacts of desertification in a Steppe grazing area in Syria, with
                       the aim of supporting the formulation of a strategy for rehabilitating desertified areas.
                       Through the mapping of parameters such as barley fields, eolian sand distribution, and
                       drainage patterns from Thematic Mapper (TM) data, it was identified barley cultivation

                       as one major reason for increased sand erosion or its downhill deposition. With regard
                       to the degradation of natural vegetation covers, the study discriminate between climate-
                       triggered and human-induced vegetation degradation by analyzing the natural response
                       pattern  of  vegetation  to  rainfall.  For  the  monitoring  of  vegetation  covers,  composited
                       10-day interval 8-km Advanced Very High Resolution Radiometer (AVHRR) Normalized
                       Difference Vegetation Index (NDVI) data from 1981 to 1996 were used. A consistently
                       changing response of vegetation to rainfall over this time period, expressed in the residuals

                       of the NDVImax/Rainfall linear regression calculations, is interpreted as nonclimate or
                       human driven, where correlations between residuals and the time of their occurrence
                       produce  correlation  coefficients  >|0.6|.  Pixels  showing  a  negative  temporal  trend  in
                       residuals coincide with areas that are most heavily used by humans. Heavily used areas
                       were located through detecting nomadic campsites from Indian Remote Sensing Satellite
                       (IRS)-1C data. By combining campsite distribution with census data, such as flock size,
                       average annual offtake, and grazing habits, grazing pressures were assessed and put them
                       in relation to the natural resources. This information provided the basis for the definition
                       of protected areas or rehabilitation plots, and for elaborating measures to support the

                       Steppe dwellers.


                       Source: Geerken, R. and Ilaiwi, M., 2004. Assessment of rangeland degradation and development of a strategy
                                      for rehabilitation. Remote Sensing of Environment,Volume 90, Issue 4, 2004, pp 490-504







                    82       Monitoring, Data and Indicators
   79   80   81   82   83   84   85   86   87   88   89