Air pollution from burning sugarcane is an important environmental issue in Thailand. Knowing the location and extent of sugarcane plantations would help in formulating effective strategies to reduce burning. High-resolution satellite imagery combined with deep-learning technologies can be effective to map sugarcane with high precision. However, land cover mapping using high-resolution data and computationally intensive … CONTINUE READING
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The Map Projection System used in Nepal is the MUTM (Modified Universal Transverse Mercator). Read more about Map Projection System in Nepal here.
In this exercise, I will be using ArcGIS. Other methods will be posted in the future.
- Load the data in MUTM. If you don’t have data yet, you can download from
The full code for classification after obtaining sample points is here. The full code for classification with sample points generated on the fly is here.
Note: This is a very simple method for generating Landcover maps meant for showing the basic workflow for generating Landcover maps. You can use more sophisticated algorithms like … CONTINUE READING
In this post, we will use the datasets from UMD (Tree Canopy Cover [TCC] and LOSS layers) to calculate and classify the dynamics of the forest. The TCC is available from 1988 and LOSS layers are available from 1989. Here we will be calculating different forest dynamics. Use the final assemblage using this link or … CONTINUE READING
Generating High-Resolution DSM often demands highly accurate data. Among the range of terrestrial and aerial methods available to produce such a dataset, this project tests the utility of images acquired by a fixed-wing, low-cost Unmanned Aerial Vehicle (UAV). The data processing of UAV images has been carried out using the algorithms ranging from classical photogrammetry … CONTINUE READING