Technology has introduced airborne laser scanning for the forest industry. Even though airborne laser scanning is a useful tool, the data it produces is too extensive to store easily. The goal of the project was to create a program that can compress data from airborne laser scanning so that it can be stored and still be used for workload and cost estimates of the project. The program also needed a user interface. The project is based on a python application that has been improved in the previous theses on the subject, and it has been under continuous development since. The goal of the project was to translate the program into C# language and create a graphic user interface as well as to make it possible to compress LAS data to CLM datatype. During the development process the program was also equipped with new ways to calculate growth and urgency classifications, and it also has a feature to draw the calculated areas to a visual map on the screen or to a file in the same way as in the python pre-version. The visualization of data was made possible with the use of the open-source library Oxyplot. Airborne laser scanning is a useful tool for forest industry, however, the analysis of the data needs more resources and specific expertise about forestry. Unfortunately, the project ran out of time and not all of the planned parts were imple-mented. The application does not have a reader for the original LAS-datatype and it cannot do calculations for workload or projections for cost estimates. The main goal, compression of LAS-txt data to the CLM-datatype was achieved. Also, new ways to calculate growth and urgency classifications from point cloud data were experimented.