I'm analysing the home ranges of a monkey species. I need to calculate the vegetation cover in the home range of monkeys. I'm using QGIS as my mapping software.
Really, there are a lot of ways to do it.
1. Draw the study area editing a vector file into the qGIS.
2. Import a raster dataset of global forest cover: https://earthenginepartners.appspot.com/science-2013-global-forest/download_v1.2.html
3. Calculate the forest cover area using the vector file; for example, use LecoS – Land cover analytics to extract the areas.
Honestly, its not that simple.
1. You need to do an lulc classificatiion (validated) using a remote sensing software o ArcGIS
2. you can then use QGIS to analyze the resulting data, and layout ur maps
Do you have access to remotely sensed data for the study area? eg aerial imagery or LiDAR perhaps?
It would be possible to use either to delineate polygon areas that are covered by vegetation and perform zonal statistics for the area cover, however, which precise method depends on your available data.
Hi,
I would recommend the Semi-Automatic Classification Plugin in QGIS for analysis.
Regarding data, if there is no local LULC data available, use free satellite data such as Landsat, Sentinel, etc, possibly combined with LiDAR or radar data, if available.
Hope that helps!
Best,
André
https://fromgistors.blogspot.com/p/semi-automatic-classification-plugin.html
Hi, what do you need to know about the vegetation cover? Amount of green matter? Type of forest/vegetation? Species? I understand you want to do a kind of habitat mapping, but which aspects do you expect could be important? Once you have that clear, you could think of a strategy to get that information from existing data or from remote sensing.
Kind regards,
Wietske
Hi,
You can use the Semi-Automatic Classification Plugin. It is a free open source plugin for QGIS.
https://www.researchgate.net/publication/307593091_Semi-Automatic_Classification_Plugin_Documentation_Release_5021?channel=doi&linkId=57cb03bd08ae3ac722b1ec30&showFulltext=true
https://fromgistors.blogspot.com/p/semi-automatic-classification-plugin.html
https://www.youtube.com/playlist?list=PL7mCX6pQ2k2PaCz22XyHavuA5Hu1ng7HR
Best Regards.
ORB
Technical Report Semi-Automatic Classification Plugin Documentation. Release 6.0.1.1
Hi!
You can use remotely sensed land surface data from satellites or LiDAR.
One suggestion is to use Satellite Surface Reflectance Data from MODIS, Landsat, or Sentinel and then perform a Supervised or non-Supervised Land Surface Classification of the vegetation based on the surface reflectance of every vegetation group.
More info on how to do this in QGIS can be found here: http://www.igismap.com/image-classification-in-qgis-supervised-and-unsupervised-classification/
MODIS also has a ready Land Cover Type Product (500m resolution...) that can be found here: https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table/mcd12q1
Remotely Sensed Satellite Data from all aforementioned satellites can be downloaded from here: http://earthexplorer.usgs.gov/
Hope this helped!
Best regards,
Karolina
For vast areas you may use MODIS sensor's imagery which are available on USGS website. I don't care about the software which you use, it's not something complex to extract your data for your study area out of it.
If there is any ambiguity let me know to make the procedure clear.
1- download modis-ndvi image of your area
2- use "extract by mask" analysis in arcgis to crop the raster of modis
3- use Raster to point analysis
4- change the pixel size to make the rest of the procedure easier
5- use spatial join with the polygon feature of your study area
6- now you can extract a value for each polygon or do any manipulations you want
GL
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