| Title: | Use of satellite image for crop classification in Angola |
| Authors: | Alexandra Lissouba, Author |
| Material Type: | ISU Individual Project |
| Publisher: | Illkirch-Graffenstaden (France) : International Space University, 2023 |
| Format: | 1 electronic resource (v, 24 p.) / col. ill. |
| Bibliography note: | Includes bibliographical references |
| Languages: | English |
| Subjects: | Agriculture ; Artificial satellites in remote sensing ; Geographical Information System (GIS) |
| Description: | Agriculture is a critical economic sector for the socioeconomic development of Angola and is aligned with the United Nations' second sustainable development goal, SDG "Zero Hunger and Sustainable Agriculture." However, 8 % of Angola arable land is cultivated, partially due to insufficient tools and methods to track crop production. There is, therefore, the need to invest in technologies for improving agriculture. The current project is a quantitative study using satellite imagery and machine learning (ML) techniques focused on the Unicanda farm, a maize-growing farm located in the province of Malanje, during three consecutive growing seasons, from 2018 until 2021, to detect and classify crops in order to obtain baseline information to improve agricultural practices. We used Sentinel-2 imagery over the Unicanda farm and extracted 18 different spectral and temporal features. We used four different machine learning algorithms to generate crop masks and validated them using Kappa coefficient, Overall accuracy and completeness. This project represent the first steps to develop a model using remote sensing images to estimate and predict crop yield in Angola. This project combines remote sensing, GIS and ML to study and improve Angola’s agricultural practices, decision-making and help reduce production costs, which is critical for Angola’s socioeconomic development. |
| ISU program : | Master of Space Studies |
| Format : | Open Access |
| Permalink: | https://isulibrary.isunet.edu/index.php?lvl=notice_display&id=11883 |
Read online (1)
 Lissouba, Alexandra_IP (0.98MB) Adobe Acrobat PDF |
