This is a sequential slideshow I made of the bi-monthly global NDVI data averaged over the years 1981-2008. It plays from January to December (I should have added the months in the video) and you can clearly see the vegetation react to the seasons. The raw data comes from NASA GIMMS. From these maps in combination with a global map of vegetation types one can calculate other vegetation parameters such as the Leaf Area Index in my case. LAI is the area of leaves per area of ground and is an important parameter in hydrology because it intercepts and stores rainwater and transpirates water which plants extract from the soil. The maps I generate will then be used in a hydrological model to see how it performs with respect to the current LAI implementation which uses standard vegetation 'curves'. This is the main subject of my thesis.If you want to see the maps in higher resolution you can download the PNGs here.
Wednesday, March 02, 2011
Global average NDVI over time
Plants strongly absorb red light and are highly reflective in infrared which keeps them from overheating. Other earthly surfaces don't show this behavior. NDVI (Normalized Difference Vegetation Index) is based is based on the ratio of measured near-infrared and red light and therefor is a strong indicator of vegetation density and health.
This is a sequential slideshow I made of the bi-monthly global NDVI data averaged over the years 1981-2008. It plays from January to December (I should have added the months in the video) and you can clearly see the vegetation react to the seasons. The raw data comes from NASA GIMMS. From these maps in combination with a global map of vegetation types one can calculate other vegetation parameters such as the Leaf Area Index in my case. LAI is the area of leaves per area of ground and is an important parameter in hydrology because it intercepts and stores rainwater and transpirates water which plants extract from the soil. The maps I generate will then be used in a hydrological model to see how it performs with respect to the current LAI implementation which uses standard vegetation 'curves'. This is the main subject of my thesis.If you want to see the maps in higher resolution you can download the PNGs here.
This is a sequential slideshow I made of the bi-monthly global NDVI data averaged over the years 1981-2008. It plays from January to December (I should have added the months in the video) and you can clearly see the vegetation react to the seasons. The raw data comes from NASA GIMMS. From these maps in combination with a global map of vegetation types one can calculate other vegetation parameters such as the Leaf Area Index in my case. LAI is the area of leaves per area of ground and is an important parameter in hydrology because it intercepts and stores rainwater and transpirates water which plants extract from the soil. The maps I generate will then be used in a hydrological model to see how it performs with respect to the current LAI implementation which uses standard vegetation 'curves'. This is the main subject of my thesis.If you want to see the maps in higher resolution you can download the PNGs here.
Subscribe to:
Post Comments (Atom)
6 comments:
nice. very nice.
I'll save my questions for your graduation day ;)
Yes, very nice!
Siberia and Canada change a lot.
Morocco is greener than I thought.
What do the colors mean? What's the difference between min and max?
Is there any significant difference between years? And did anything change over those 30 years of measurements?
Great maps!
Very naughty of me not to include a symbology. However it wouldn't mean much, the colors go from 0 brown to 1 very green on the NDVI index.
The huge changes in the north are due to snow cover which messes with the satellite measurements.
I had some problems with some functions of ArcGIS which I have figured out now. A map of standard deviation should be produced next week which should show areas of large change or variability.
Yes, the colors are obvious if it is a linear scale.
Ha, a standard deviation map is already in development :) Nice and very scientific :)
Very interesthing and nice animated maps.
Got some questions: why is green more reflected then blue and red?
filesavr can't find the files.
North Africa is way behind with the plants compares to the country's at the same latitude. I once saw a documentary with a crazy plans to make a moving city (on solar power),witch let a trail behind of vegetables. This was specially made to give the green back to North Africa. I will try to find it
The reflection of green is a structural property of chlorophyl as far as I know and not some strategy of the plant. This reflection is also why plants ARE green.
North Africa has so little plants because it's so dry. This is mostly due to it being such a large landmass in the wrong position. The other countries on the same lattitude are next to oceans which bring in moisture. You would expect then that the west coast of Africa would be greener because it's next to the Atlantic, however the prevailing wind (Trade winds) is from the land to the ocean (due to Coriolis effect).
Weird that the files are offline. I'll reupload them when I'm home.
Post a Comment