Sagarmatha National Park (SNP) - Nepal

Under the regional DSS-HKKH partnership initiative, MENRIS has compiled and developed an extensive spatial database for the SNP, Nepal. The database includes various biophysical layers such as Digital Elevation Model (DEM), Drainage, trails, land cover and physical infrastructures. A number of datasets were received form Ev-K2-CNR and World Wildlife Fund (WWF)-Nepal which have also been integrated into the database. Satellite images of different dates (from 1960s to 2001) and sensors, which include Corona images, Landsat MSS, TM and ETM+, IRS and IKONOS have been collected and archived. These images are useful for various applications such as studying changes in land cover, snow cover and glacier lakes.

Monitoring Vegetation Changes with NDVI Trends and Climatic Correlations

Normalized Difference Vegetation Index (NDVI) map allows comparisons of the spatial and temporal variability in the amount and condition of vegetation. The time series satellite derived NDVI was used to monitor and analyze changes in vegetation pattern of Nepal. The NDVI maps of Nepal for the period 1998 – 2003 (6 years) was computed using 10-day’s time series SPOT Vegetation satellite image. The NDVI trends showed that the months September and October are normally best growing period and April, May, and June are normally driest period. The NDVI comparison was done among the best growing season for 6 years’ period and was observed significant differences in vegetation growth production. Annual Maximum NDVI was derived to evaluate and represent the vegetation condition through out the country. The variability in annual maximum greenness from six years of NDVI data (1998 – 2003) was computed to determine the area of potentially higher and lower inter-annual variability in agricultural production, and was found to be very useful to estimate the frequency of meteorological and agricultural drought events. The agricultural vegetation anomalies for each year (1998 – 2003) were computed to determine the agricultural production anomalies in the terai districts of Nepal, the major agricultural production domain area. The result provided insight into the spatial and temporal agricultural production anomalies events, and was the basis for the detailed analysis to determine the dynamics of these events. For this, the relationship between low agricultural production zone and precipitation variable was analyzed to determine the dynamics of agricultural production anomalies. The result showed that most of the agricultural production anomalies events are due to decrease in precipitation.

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