Set of exercises that offers training on different techniques to map forests and its degradation. Training is based on working with the IMPACT toolbox, processing Landsat and Sentinel data. Each of the exercises is shown on real case in particular area in Eastern Africa. Different types of landscapes are reviewed, and a series of tools and methods available in IMPACT are tested. For each exercise the necessary data are available for download. The data exercises for 2., 3. and 4. are provided also in lighter version, where some heavy files are missing (details under each exercise). Guide Book
Overview and testing of all the features that IMPACT tool offers.
Example on the area of Ogo Mountains in Somalia. Processing and mosaicking three Landsat scenes from the year 2000. Subsequently producing a pixel classification, reviewing the results and recoding the classification (forest / non-forest). In the end a vector segmentation should be created.
Data: ex2_Ogo.zip ex2_Ogo_light.zip Light version of the dataset contains only one image which is already process and is covering only one part of Ogo area. The provided processed image can be clipped by Ogo shape file and then the exercise can be continued from the step g.)
Case study over the Solio area in Kenya. Sentinel-2 data are used to map the proportions of grassland and woodland in Solio protected area. Different types of classifications (Automatic, K-means, NDVI_cluster, PCA_cluster, UNMIX cluster) are tested in order to choose the most precise one, which should be used to create a vector segmentation.
Data: ex3_solio.zip ex3_solio_light.zip Light version of this dataset contains all necessary images to run all the steps of the exercise. The only difference is that the Landsat images are already processed and clipped for the Solio area
Example in Mwingi region in Kenya. Estimation of the areas of forest removed or degraded in two periods of time, using Landsat and Sentinel 2 images. Subsequently corresponding amount of carbon released is counted using the carbEF module.
Data: ex4_dryforest.zip ex4_dryforest_light.zip Light version of the dataset include everything except General data folder which is needed only for very last part of this exercise. General data folder contains activity and biomass maps for Kenya, Sudan, Ethiopia, Mozambique, Rwanda and Uganda
Case study on Nandi forest in Kenya. A random sample of boxes (fishnet) over the area is used to estimate degradation from 2001 to 2015. Subsequently a vector legend is created to identify changes (deforestation and degradation). In the end the statistic tool is used to calculate the changes that have occurred.
Data: ex5_nandi.zip