Land use change analysis
Overview of climate variability and likely climate change impacts on
agriculture across the Great...
2 steps
• Compare predicted future suitability
change from climate models and
Ecocrop maps and existing land use
data
• A ...
Not available = natural (forest, wetland, …), protected, water, bare, urban areas
Needs change = land mixed with pastorali...
• A time-series of NDVI observations can be used to examine the
dynamics of the growing season or monitor phenomena such a...
2004 – 2012
Methodology…
Download
data
• More than 300 images of NDVI 250m MODIS
sensor were downloaded from the period 2000-2013
Imag...
MODIS for analyzing the vegetation
cover
Presentation: Linh Giang
OVERVIEW OF LANDCOVER FROM GOOGLE EARTH
5/2000 5/2006
5/2012
5/2000 5/2006
5/2012
MeKong detla area
5/2000 5/2006
5/2012
Laos area
2002-2009
Forest cover change
(WWF report, 2013)
Mainland Southeast Asia: Land Cover 2004
The FLAMES project
WWF identified the key drivers of change of vegetation cover:
- Human population growth and increasing population density....
Conclusion
• MODIS data is useful to get overview of the
vegetation cover change in the long time,
• The highest changes i...
Thank you for your attention
Land use analysis in GMS
Land use analysis in GMS
Land use analysis in GMS
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Land use analysis in GMS

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Land use analysis in GMS

  1. 1. Land use change analysis Overview of climate variability and likely climate change impacts on agriculture across the Greater Mekong Sub-region (GMS) 10 – 11 March, 2014, Hanoi, Vietnam Eitzinger Anton, Giang Linh, Lefroy Rod Laderach Peter, Carmona Stephania
  2. 2. 2 steps • Compare predicted future suitability change from climate models and Ecocrop maps and existing land use data • A time-series analysis of Land Use using satellite images
  3. 3. Not available = natural (forest, wetland, …), protected, water, bare, urban areas Needs change = land mixed with pastoralism (forest, herbaceous, wetlands, …) Available = Agriculture (commercial, subsidized, irrigated, …) Land use change at risk for agriculture
  4. 4. • A time-series of NDVI observations can be used to examine the dynamics of the growing season or monitor phenomena such as droughts. • The Normalized Difference Vegetation Index (NDVI) data set is available on a 16 day. The product is derived from bands 1 and 2 of the MODerate-resolution Imaging Spectroradiometer on board NASA's Terra satellite. 2nd step A time-series analysis of Land Use
  5. 5. 2004 – 2012
  6. 6. Methodology… Download data • More than 300 images of NDVI 250m MODIS sensor were downloaded from the period 2000-2013 Image Filtering • NDVI scenes was first filtered to eliminate high and low values (poor quality data) using Quality Assessment Science Data Sets (QASDS) Noise Removal • Applying the approach of Fourier interpolation algorithm, to separate the noise spectrum from the signal spectrum of the data set frequency domain
  7. 7. MODIS for analyzing the vegetation cover Presentation: Linh Giang
  8. 8. OVERVIEW OF LANDCOVER FROM GOOGLE EARTH
  9. 9. 5/2000 5/2006 5/2012
  10. 10. 5/2000 5/2006 5/2012 MeKong detla area
  11. 11. 5/2000 5/2006 5/2012 Laos area
  12. 12. 2002-2009 Forest cover change (WWF report, 2013)
  13. 13. Mainland Southeast Asia: Land Cover 2004 The FLAMES project
  14. 14. WWF identified the key drivers of change of vegetation cover: - Human population growth and increasing population density. - Unsustainable levels of resource use throughout the region, increasing driven by the demands of export- led growth rather than subsistence use; - Unplanned and frequently unsustainable forms of infrastructure development (dams, roads…) World Population Density (people/km2)
  15. 15. Conclusion • MODIS data is useful to get overview of the vegetation cover change in the long time, • The highest changes in research area have concentrated in the Vietnam and Myanmar with deforestation reason. Laos has the contain of vegetation cover, • The result data has the good quality, recorded the same result with other projects
  16. 16. Thank you for your attention
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