It's All Coming Together (Finally!)

Do you remember the song, "Ain't No Mountain High Enough" by Debelah Morgan? Well, the catchy lyrics go something like this:

"Don't you know there ain't no mountain high enough

Ain't no valley low enough

Ain't no river wide enough

To keep me from getting to you."

This song perfectly describes the mission Amintas and I have been on to find data for our Reforestation model in Paragominas. However, even after searching and searching for the data over high mountains, low valleys, and wide rivers some of the data is still evasive and has been deemed non-existent. That being the case here are a few mug-shots of the data we have found... but before debuting the data...

To refresh your memory, the data is being used as variables to understand where the most suitable locations are for reforestation projects in Paragominas, Para, Brazil using Multi-Criteria Decision Analysis. Here's the roll call for the data:

• Forest Cover
• Aridity Index
• Elevation √
• Slope √
• Land Use/Land Cover
• Land Opportunity Cost
• Population Density
• Net Primary Productivity
• Soil Zoning Type √
• Potential Vegetation √
• Soil Vegetation Association √
• Fire Probability
• Bodies of Water √
• Urban Areas
• Deforestation Date √

All data without check marks are absent and remain unknown (at least for the time being).

So the model is constructed using constraints, which limit the alternative solutions under consideration, and factors, which "enhance or detract from the suitability of a specific alternative under consideration" (Eastman, 2006).

Constraints + Factors = Multi-Criteria Evaluation (solution)

*APP = 100 meters of protected area on either side of rivers/streams

*The column of the left shows the data in its raw form and on the right the data has been "normalized." A normalized data set contains data using

*SVA = Soil Vegetation Association and is created by "intersecting" or "overlaying" soil data with vegetation data.

*SRTM = radar data that shows land elevation

In the diagram above, the warmer the color, the better the sight is for reforestation activities. Of course, this map will change as more data is found and inputted into the model.

But for now the model is workable, though far from its full potential...

Sources:

Eastman, Ronald J. (2006). IDRISI Manual. Clark Labs, Clark University. Worcester, MA.

http://www.anysonglyrics.com/lyrics/d/debelahmorgan/aint.htm

Progress...

Back and forth, back and forth. My hammock swings side to side like the hand of a metronome. I think I am in 3/4 time; a nice slow waltz. Tick, tick, tick. Nothing rushes in Brazil. Even the women who walk the beaches match this slow and methodic beat, as if they were walking down the fashion runway, each step originating from their hips- long, and elegant. I have had to adjust my walk and my watch. No one rushes; there is no hurry.

Despite the slow beat here in Belem, my time here runs away from me at an allegro pace. On August 7^th I will have been here for two whole months. Two whole months and I have a measly little tan to show for it. But that is a testament to my time at Imazon. If I could get a tan from the fluorescent glow of my computer screen, well lets just say I would have quite the tan! My project at Imazon is coming along well. Amintas – my IDRISI guru – and I have a preliminary model working to delineate the most suitable locations for reforestation projects in Paragominas, however issues with a lack of available data continue to plague us at each corner. Look left: no land opportunity cost data. Look right: cloudy satellite data (clouds obscure the satellite image and thus its overall quality/integrity).

The current data deadlock has not derailed progress. I am pushing ahead to design a preliminarily outline for a short publication. It will complement an Imazon publication series called: "The State of the Amazon." The State of the Amazon contains policy briefs designed to alert policy makers as well as the public about current issues flourishing in the Amazon.