Click to edit Master title style Monitoring Vegetation Changes w ith - - PowerPoint PPT Presentation

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Monitoring Vegetation Changes w ith NDVI Trends and Delineating Agricultural Droughts

Sushil Pradhan

GIS Specialist

Mountain Environment and Natural Resources’ Information Systems (MENRIS) International Centre for Integrated Mountain Development (ICIMOD) E-mail: suspradhan@icimod.org.np

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Monitoring of vegetation pattern is important as it is related to crop production levels, and to perennial vegetation/rangeland production Need to improve basic understanding of dynamics of the vegetation cover changes Methodology to map and monitor land cover and vegetation behavior by remote sensing is useful

Background

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Study of Greenness using annual and seasonal NDVI (Normalized Difference Vegetation Index) 10 days’ time series SPOT Vegetation satellite images (1km x 1km) 1998 – 2004 (7 years) Background

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SPOT Vegetation Satellite Image

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NDVI Calculation Method

GRID NDVI Calculations ArcView Script

Individual NDVI GRIDs NDVI = - 0.1 + (0.00400 x G) Where, G = individual GRIDs exported from individual images.

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Normalized Difference Vegetation Index (NDVI) Referred as “Greenness” maps Indicative of the amount of green vegetation on earth’s surface Allows to compare spatial and temporal variability in the amount and condition of vegetation Useful to monitor seasonal development of vegetation it responds to rainfall and other factors affecting growth and production

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NDVI Maps

January 21, 2003 February 21, 2003 June 21, 2003

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10-Day’s Vegetation Pattern Changes of Myanmar

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Vegetation Growth Trend Analysis, 1999 - 2004

Vegetation Growing Trend of MYANMAR 1999 - 2004

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Jan-99 Mar-99 May-99 Jul-99 Sep-99 Nov-99 Jan-00 Mar-00 May-00 Jul-00 Sep-00 Nov-00 Jan-01 Mar-01 May-01 Jul-01 Sep-01 Nov-01 Jan-02 Mar-02 May-02 Jul-02 Sep-02 Nov-02 Jan-03 Mar-03 May-03 Jul-03 Sep-03 Nov-03 Jan-04 Mar-04 May-04 Jul-04 Sep-04 Nov-04 Months/Years

Vegetation Indices

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Comparison of growing seasons

Best Growing season –October and November Dry season – June and July Basis for detailed analysis

Monthly Vegetation Growth Pattern of MYANMAR 1999 - 2004

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Months

Vegetation Indices

1999 2000 2001 2002 2003 2004

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Agricultural Vegetation Anomalies

1999 2000 2001 2002 2003 2004

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Drought Analysis

Shows the most severe dryness occurred for different locations – the worst growing season of the six-year period Derived by selecting the minimum of six annual maximum NDVI values, i.e. the lowest greenness value of the six primary growing seasons Provides insight into the annual variability of precipitation, resulting in drought-induced vegetation production anomalies

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Drought Analysis (1999 – 2004)

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Vegetation Monitoring - Afghanistan

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Vegetation Monitoring - Bhutan

2003 December 21 2003 December 11 2003 December 1 2003 November 21 2003 November 11 2003 November 1 2003 October 21 2003 October 11 2003 October 1 2003 September 21 2003 September 11 2003 September 1 2003 August 21 2003 August 11 2003 August 1 2003 July 21 2003 June1 2003 May 11 2003 April 11 2003 March 1 2003 February 1 2003 January 1

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Vegetation Monitoring– TAR/China

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Vegetation Monitoring – HP, India

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Agricultural Vegetation Anomalies - Nepal

Nepal Nepal Nepal Nepal

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Rainfall 1998 Rainfall 1999

Annual Precipitation

Rainfall 2000

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Correlation Analysis: Low Agricultural Production with Precipitation, 1999 77% are within poor rainfall zone

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Rangeland Management

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Rangeland Management

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Conclusion

NDVI time series can be used to monitor vegetation growth, crop monitoring and harvest forecasting, drought monitoring, soil erosion monitoring, forest fire monitoring, etc. The real-time availability of the imagery can be applied for food security early warning monitoring by comparing annual curves with long time averages Detecting NDVI anomalies early in the growing season mitigating measure could be taken to prevent crop losses Correlation of NDVI with climatic parameters provides the dynamics of vegetation pattern changes However, correlation of NDVI with other parameters is required, e.g. socio-economic parameters