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Application of aerial remote sensing technology using drones for biomass monitoring and precision agriculture and forestry

Publicerad 2020-11-05

Om uppdragsgivaren
Mälardalen University MDH is with 16 000 students one of Sweden’s large Higher Education Institutions. MDH is characterized by close partnerships with industry and the public sector. Engineering research at MDH is particularly strong.

Beskrivning av examensarbetet
Recent advances in Unmanned Aerial Systems UAS also known as drones bring great opportunities for monitoring and inspection in industries such as infrastructure and construction, forestry and agriculture, transportation, security and insurance, telecommunications and mining, among others. According to PwC’s study on commercial applications of drone technology, the emerging global market for business services using drones is valued to over 115 billion EUR. The UAS/drones allow for use of various types of cameras enabling aerial remote sensing. One of the important applications is to equip the UAS/drone with multispectral and hyperspectral systems enabling monitoring and assessment of crops and forests for biomass production via real-time optical imagining using green, red, red-edge and near-infrared wavebands and image processing algorithms. This technology allows the biomass producers to manage crops, forests, soil, fertilization and irrigation more effectively i.e. to minimizing the use of fertilizers, overuse of water and at the same time increasing the yield from crops and forests.

Proposed tasks:
The proposed activities within this project work may include sensing of the trees in forests as well crops on agriculture fields as well biomass wood piles using a drone equipped with multispectral and thermal imaging cameras. We will evaluate distribution of moisture in the fields, risk of ignitions and energy loss, nutrient uptake i.e. Nitrogen, vegetation indexes, identification of plants infected with pests, farming yield etc. The aim will also be to enable discrimination of tree species, discrimination between healthy and damaged trees etc. The acquired images will be pre-processed merged and information of interest extracted from the data. This will be done by applying image processing algorithms as well as machine learning and artificial intelligence algorithms. The obtained information will allow the biomass producers to manage forests, crops, biomass and waste storage, landfills, soil, fertilizing and irrigation more effectively. Permission of sensing crops and trees in forests and agriculture lands has been received from owners in advance.
Special emphasis of the student work needs to be on meeting requirements for energy engineering degree project work as the proposed topic may not directly relate to energy.

Jan Skvaril
Högskoleplan 1, 722 20 Västerås

Mälardalens University


Sista ansökningdag

2020, 2021

Project description

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