Airborne imaging spectroscopy in mapping of heterogeneous tropical land cover in Eastern Africa

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http://urn.fi/URN:ISBN:978-951-51-3992-4
Title: Airborne imaging spectroscopy in mapping of heterogeneous tropical land cover in Eastern Africa
Author: Piiroinen, Rami
Contributor: University of Helsinki, Faculty of Science, Department of Geosciences and Geography
Doctoral Programme in Atmospheric Sciences
Thesis level: Doctoral dissertation (article-based)
Abstract: Understanding the patterns and changes in land cover is vital for determining how our actions as humans impact our planet. The science of modeling and mapping land cover using remote sensing (RS) has thus become increasingly important, as we are consuming natural resources and impacting our planet’s ecosphere at an unprecedented rate and scale. Through sensors aboard aircraft and satellites, RS can provide valuable information about these changes on both a local and global scale. During recent decades, Africa has experienced considerable loss of natural forests, woodlands, and grasslands, and the simultaneous expansion of agricultural land. Some of the native forests have been replaced by plantation forests, which have economic value but low species diversity compared to native forests and, in some cases, have a negative impact on the local ecosystem. Agroforestry systems have been proposed as possible solutions to mitigate the negative impact of deforestation and the expansion of agricultural land; in these systems trees and crops are planted side by side, which, when properly planned and maintained, is considered a more sustainable option in the tropics. At the regional and global level, low- and medium-resolution satellite-based RS data provide important insights into changes in land cover types. Since these technologies have a limited capability to map heterogeneous land cover at a detailed level (e.g. crop types and tree species), however, airborne imaging spectroscopy (AIS) is considered the state-of-the-art technology for mapping land cover at the species level and for assessing the biophysical properties of vegetation. When airborne laser scanning data are collected simultaneously, the three-dimensional structural characteristics of land cover can be captured. Although these technologies have been studied widely in developed countries, fewer studies have been conducted in Africa, despite the urgent need for accurate land cover information in the area. I assess the current state of the research in the field of AIS in Africa, then use the novel findings from the original research articles of this thesis to assess the potential and limitations of these technologies in accurate land cover modeling in support of sustainability and conservation efforts in tropical Africa. The results of this thesis show how, when using AIS as the primary data source, major crops and tree species can be detected and mapped even in the complex rural African landscape. A novel approach for applying a one-class classification method for mapping potentially invasive species was introduced; this was particularly useful in the rural African context, where collecting field data is a laborious and time-consuming process. These invasive species were found abundantly in close proximity to the largest remaining native forest fragment on the study site. This is valuable information for future conservation efforts of the remaining native forest fragments of the Taita Hills. A novel approach for mapping the short-term flowering cycle of melliferous plants using AIS data was also introduced, providing detailed information on the changes of flowering intensity and thus contributing to a better understanding of the interrelationship between the flowering plants, bee diversity, and hive integrity. In conclusion, AIS has many viable uses in tropical Africa in support of conservation and sustainability efforts, although the vast species diversity of the tropical ecosystems and the high costs of acquiring AIS data are major limitations of these technologies.-
URI: URN:ISBN:978-951-51-3992-4
http://hdl.handle.net/10138/256037
Date: 2018-11-09
Subject: Geoinformatics
Rights: This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.


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