Research Proposal Global Change in Photosynthesis Moumita Dutta Gupta ~ GGR 904 May 5 th 2009

Transcription

1 Research Proposal Global Change in Photosynthesis Moumita Dutta Gupta ~ GGR 904 May 5 th 2009

2 ?? -The Question - How and where is Global Photosynthesis changing as captured by the SPOT VEGETATION Satellites for the time period: 1982 to 2008? Research Proposal Global Change in Photosynthesis Moumita Dutta Gupta ~ GGR 904 May 5 th 2009

3 Introduction Vegetation constitutes a major player in regulating the global climate through photosynthesis and respiration Plants convert light energy into chemical energy during photosynthesis and in the process extract relevant greenhouse gases such as carbon dioxide (CO₂) from the atmosphere and return CO₂ through respiration The primary production of photosynthesis is Biomass, which is also chemical energy for the beginning of food chains on Earth

4 Why is it important? Because of its importance it is critical to monitor changes in photosynthesis on Earth It is also important to understand changes in land cover, and where it is occurring, as it can have a tremendous impact on local communities and the global economy as well as influencing global levels of greenhouse gases From empirical evidence it is becoming clear that the flora and fauna on the surface of the Earth, from the Arctic to the tropics, are rapidly changing (Hughes 2000, McCarty 2001, Myneni et al. 1997, Parmesan and Yohe 2003)

5 Objective The Primary objective of the research is to assess changes in global photosynthesis between 1982 and 2008 For this purpose, SPOT datasets are collected and analyzed

6 Spot (Satellite Pour l'observation de la Terre) SPOT is a high resolution, optical imaging Earth observation satellite system operating from space

7 Background Changes in global scale SPOT NDVI,

8 Background

9 Background

10 Background

11 Background

12 Data SPOT Corporation provides free NDVI data for the entire world at a 1km resolution The NDVI is in a scaled format going from 0 to 255 The global data are broken into ten sub regions It comes in a 10 day maximum value composites (MVC) with three images per month image 1 = days 1 10, image 2 = days 11 20, and image 3 = days to 31 (depending on the length of the month) The data are available at:

13 Methodology Step 1: Downloading and Compiling the data into the Idrisi image processing software package Step 2: Creating Monthly MVC ( Maximum Value Composite ) Images Step 3: Creating the annual average images, or annual integrated images Step 4: Reducing Extreme events = averaging the end point years

14 Methodology Step 5: Creating the percent change image for the 25 year period

15 Methodology Step 6 : The percent change image would be then value sliced into 5 categories: Decrease greater than 20% Decrease from 10% to 20% Little change (from a decrease of 10% to an increase of 10%) Increase from 10% to 20% Increase greater than 20% Step 7: Then temporal profiles will be created from areas showing increasing or decreasing NDVI. Temporal profiles show the NDVI values for specific pixels of each year and then will be graphed in Excel.

16 PIXEL Edge Error The original image for the northern Persian Gulf which has various pixels with values above zero in the water

17 Case Study Satellite observed photosynthetic trends across boreal North America associated with climate and fire disturbance Geotz, Scott J., Andrew G. Bunn, Gregory J. Fiske and R.A. Houghton Spatial distribution of deterministic trends in seasonal photosynthetic activity across Canada and Alaska from 1982 through 2003

18 Reference List Centre National d'etudes Spatials & SPOT Image Corporation SPOT User's Handbook, (Volume 1: Reference Manual, Volume 2: SPOT Handbook. Volume 3: SPOT Handbook Appendices) (CNES & SPOT Image Corporation, Toulouse, France, 2002). Holben, B. N Characteristics of maximum value composite images from temporal AVHRR data. International Journal of Remote Sensing. Vol. 7. Maisongrande,P.,B.Duchemin,&G.Dedieu.2004.VEGETATION/SPOT:anoperationalmissionforthe Earth monitoring; presentation of new standard products. International Journal of Remote Sensing, Vol.25. Young, S.S. and R.Harris Changing pattern of global scale vegetation photosynthesis, International Journal of Remote Sensing, Vol. 26, No. 20

19 Reference List Geotz, Scott J., Andrew G. Bunn, Gregory J. Fiske and R.A. Houghton Satellite observed photosynthetic trends across boreal North America associated with climate and fire disturbance. The National Academy of Sciences of the USA, Vol. 102, No. 4. Kobayashi, Hideki and Dennis G. Dye Atmospheric condition for monitoring the long term vegetation dynamics in the Amazon using normalized difference vegetation index. Remote Sensing of Environment, Vol. 97. Notaro, Micheal, Zhengyu Liu, Robert Gallimore, Stephen J. Vavrus, and John E. Kutzbach, I. Colin Prentice and Robert L. Jacob Simulated and Observed Preindustrial to Modern Vegetation and Climate Changes. Journal of Climate, Vol. 18. Xiao, Xiangming, Qingyuang Zhang, Scott Saleska, Lucy Hutyra, Plinio De Camargo, Steven Wofsy, Stephen Frolking, Stephen Boles, Michael Keller and Berrien Moore III Satellite based modeling of gross primary production in a seasonally moist tropical evergreen forest. Remote Sensing of Environment, Vol. 94. Cihlar, Josef, Hung Ly and Qinghan Xiao Land Cover Classification with AVHRR Multichannel Composites in Northern Environments. Remote Sensing of Environment, Vol. 58.