University of Twente Student Theses
The Potential of Hyper-temporal NDVI data to Assess Vegetation Condition and Grazing Intensity
Hamad, Amina Amri (2010) The Potential of Hyper-temporal NDVI data to Assess Vegetation Condition and Grazing Intensity.
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| Abstract: | Land degradation has been reported to be a major environmental problem in Crete for a long time and is largely caused by excessive grazing. Several attempts have been done using satellite images for the purpose of monitoring the effect of excessive grazing on vegetation as a whole and their distribution. These studies lacked the temporal aspects of monitoring grazed lands since they used satellite imagery of one date. This study used 10 years MODIS hyper temporal NDVI images of 16 days temporal resolution to assess vegetation condition and grazing intensity. Grazed areas were classified by vegetation types into 8 groups. Grass Index measured from field was used as a direct estimate of Grazing Index. Seasonal analysis was done where the pixel NDVI value at the peak and at the end of grazing season was compared separately to Grazing Index to assess vegetation conditions. Not only that but also trend analysis was used to assess vegetation conditions, where the slope of 10 years NDVI was compared to the Grazing Index by vegetation types. Assessment of Grazing Intensity was done by comparing the difference of NDVI at the peak and end of grazing season with the Grazing Index. Seasonal analysis showed that at a confidence interval of 0.05 four groups had significant positive relation between the NDVI at a peak of growing season and grazing index and one had a negative relation. Moreover trend analysis revealed that at a confidence level of 0.15 two groups had significant positive and negative relation between slope of 10 years NDVI and grazing index. These analysis indicate that different vegetation types have different response to high grazing intensities. NDVI difference was found to have a positive relation with Grazing Index indicating it is possible to use this method to estimate grazing intensity. Not only that but also R2 ranged between 25%-87% which means the analysis explained sufficient variability. MODIS hyper temporal NDVI has shown a potential to assess vegetation conditions and grazing intensity however studies should be done more on how to capture the amount of brown biomass this could improve the estimates and monitoring of grazed lands. |
| Item Type: | Essay (Master) |
| Faculty: | ITC: Faculty of Geo-information Science and Earth Observation |
| Programme: | Geoinformation Science and Earth Observation MSc (75014) |
| Link to this item: | https://purl.utwente.nl/essays/90735 |
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