I am new to GIS, and I am developing a project evaluating forest cover change over 10 years (2010-2020) for a specific area in the state of São Paulo/ Brazil. I have this area as a shapefile, and I have managed to clip this area from the raster of forest cover change in a single year (I can sure do it for the other years). I then proceeded to extract the value of the resulting raster to inspect the output. However, I don't know where to go from there to compile the forest cover change data over the years and compute statistics. The output from the extraction is a list I cannot interpret. Does anyone know how to do this? And what is the best sequence of steps to do it?
Hi Julia, can you kindly send the out from the extraction? We can start there.
As I understand it, what you want to do is
(1) Crop the forest cover layers from 2010-2020 from the shapefile.
(2) Count the change in cover from year to year in the study area
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libaray(raster)
files
It is quite an elaborate exercise considering the current status of the forest you wish to consider for this purpose. It is indeed a right approach comparing the changes in forest cover. The forest cover (secondary data) will present the original picture of the area. The current ground truth facilitates species composition and communities. You need to specifically categorize them depending upon the ;Sequestration Potential' (normally, one hectare of NEW forest sequesters 6.24 tons of Carbon dioxide, as a thumb rule) . Further, deciduous species have double the potential compared to Evergreen.
NOW, comparing the forest loss over 10 year period tells you the potential areas of sequestration loss. Tabulating them and doing a statistical analysis would throw up the desired data.
BUT, it is not that easy as I said in the beginning as you need to gather much more data in terms of interfering with the carbon emissions although I have suggested just one of them.
All the best.
Kolade Victor Otokiti thank you for your reply! I created a repository on GitHub where I put the files and the code: https://github.com/Julia-Lunardi/PAvsPESinBrazil. I now stumbled upon the problem of cropping the stack of rasters — the cropped area does not match the shapefile area, even though I projected the .shp to the rasters' CRS. So I couldn't extract it yet for the whole stack of rasters (I tried with just one before and it worked)
Ziyan Liao Thank you for your reply! I am stuck at the crop part though: it returns the wrong area after I stacked the rasters. In the comment above I put the link with the code, if you have some time to take a look
Is your core purpose a research goal or developing remote sensing / GIS skills?
Although I certainly believe everyone should, at least once, attempt pre-processing, reconciling and harmonizing a set of remote sensing scenes, just so they know how difficult it can be, land cover change is a central theme in climate change, so ESA / NASA have established global change time series datasets that have been derived from sometimes multiple satellite platforms ( SAR, Landsat, Modis, et. al. ) so that research teams can operate from a common source and avoid the heavy lifting. And related to these programs are more regional focused projects at a higher resolution or longer time period - cropping the scenes is only the start, that's why the USGS provides U.S. Landsat Analysis Ready Data for the continental United States ( see https://www.usgs.gov/core-science-systems/nli/landsat/us-landsat-analysis-ready-data for some of the analytical issues ).
If you are also using other themes like human settlement, soils, etc. in your model, there are change datasets for those also.
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