Country-scale mapping of individual forest and non-forest trees and
shrubs in Africa - the example of Rwanda
Abstract
Forest and non-forest trees and shrubs (hereafter collectively referred
to as trees), are the basis for the functioning of tree-dominated
ecosystems, and are regularly monitored at country scale via forest
inventories. However, traditional inventories and large-scale forest
mapping projects are expensive, labour-intensive and time-consuming,
resulting in a trade-off between the details recorded, spatial coverage,
accuracy, regularity of updates, and reproducibility. Also, forest
inventories typically do not account for individual trees outside
forests, although these trees play a vital role in sustaining
communities through food supply, agricultural support, among other
benefits. Moreover, the alarming rate of tree cover loss resulting from
different natural and human-induced processes has brought both political
and economic motives to attract efforts for landscape restoration
especially in Africa. Nevertheless, currently, there is no accurate and
regularly updated monitoring platform to track the progress and
biophysical impact of such ongoing initiatives. Recent approaches
counting trees in satellite images in Africa used very costly commercial
images, were limited to isolated trees in savannas excluding small
trees, and did not cover other complex and heterogeneous ecosystems such
as forests. Here, we make use of novel deep learning techniques and
publicly available aerial imagery, and introduce an accurate and rapid
method to map the crown size, number of trees inside and outside
forests, and corresponding carbon stock, regardless of tree size and
ecosystem types in Rwanda. The applied deep learning model follows a
UNet architecture and was trained using 67,088 manually labeled tree
crowns. We mapped over 200 million individual trees in forests,
farmlands, wetlands, grasslands, and urban areas, and found about 67.2%
of the mapped trees outside forests. An average tree density of 94.6 and
70.8 trees per ha, and average crown size of 38.7 m2
and 15.2 m2 were mapped inside and outside forests,
respectively. In savannas we found 64 trees per ha with an average crown
size of 15.6 m2. In farmlands we found 79.6 trees per
ha with an average crown size of 16.3 m2. We expect
methods and results of this kind to become standard in the near future,
enabling tree inventory reports to be of unprecedented accuracy.