Mapping Natural Forest Remnants with Multi-Source and Multi-Temporal Remote Sensing Data for More Informed Management of Global Biodiversity Hotspots

Abstract

Global terrestrial biodiversity hotspots (GBH) represent areas featuring exceptional concentrations of endemism and habitat loss in the world. Unfortunately, geospatial data of natural habitats of the GBHs are often outdated, imprecise, and coarse, and need updating for improved management and protection actions. Recent developments in satellite image availability, combined with enhanced machine learning algorithms and computing capacity, enable cost-efficient updating of geospatial information of these already severely fragmented habitats. This study aimed to develop a more accurate method for mapping closed canopy evergreen natural forest (CCEF) of the Eastern Arc Mountains (EAM) ecoregion in Tanzania and Kenya, and to update the knowledge on its spatial extent, level of fragmentation, and conservation status. We tested 1023 model possibilities stemming from a combination of Sentinel-1 (S1) and Sentinel-2 (S2) satellite imagery, spatial texture of S1 and S2, seasonality derived from Landsat-8 time series, and topographic information, using random forest modelling approach. We compared the best CCEF model with existing spatial forest products from the EAM through independent accuracy assessment. Finally, the CCEF model was used to estimate the fragmentation and conservation coverage of the EAM. The CCEF model has moderate accuracy measured in True Skill Statistic (0.57), and it clearly outperforms other similar products from the region. Based on this model, there are about 296,000 ha of Eastern Arc Forests (EAF) left. Furthermore, acknowledging small forest fragments (1–10 ha) implies that the EAFs are more fragmented than previously considered. Currently, the official protection of EAFs is disproportionally targeting well-studied mountain blocks, while less known areas and small fragments are underrepresented in the protected area network. Thus, the generated CCEF model should be used to design updates and more informed and detailed conservation allocation plans to balance this situation. The results highlight that spatial texture of S2, seasonality, and topography are the most important variables describing the EAFs, while spatial texture of S1 increases the model performance slightly. All in all, our work demonstrates that recent developments in Earth observation allows significant enhancements in mapping, which should be utilized in areas with outstanding biodiversity values for better forest and conservation planning.

Environmental Performance of Regional Protected Area Network: Typological Diversity and Fragmentation of Forests

“…It is shown that the average area of PAs, which ensures the maintenance of 75% of the typological diversity of communities in the study region, is about 1000 ha. A similar conclusion was obtained in the work [68].…”

“…Recognition of typological units was carried out at the maximum level of hierarchy detail (overall accuracy 0.59). Similar model accuracy (0.57) was obtained in the closed canopy evergreen natural forest study in Tanzania and Kenya [68]. The relatively low accuracy of our model is explained by the complex polydominant composition of the tree layer, the combination of nemoral and boreal species groups in subordinate layers, and the silvicultural origin of most coniferous communities.…”

Remote Sensing Applied in Forest Management to Optimize Ecosystem Services: Advances in Research

“…This urban growth will affect terrestrial ecosystems and will produce an increase in demands on the services they provide [3]. The United Nations (UN) exposes the importance that environmental services and ecosystems offer to human beings as natural goods and services, and on which social well-being and economic development depend directly, and which are currently declining globally at a dizzying rate [4,5]. On the other hand, the establishment of forest ecosystems requires a minimum of conditions that allow the growth of trees.…”

“…An ecological reserve or nature reserve is a semi-protected area, of importance for wildlife, flora, or fauna, or with geological features of special interest that is protected and managed by man, for the purpose of conservation, and to provide opportunities for research and education. It is a human delimitation where activities harmful to the environment are prohibited, which is established mainly to conserve biological diversity of regional and local interest, and maintain the continuity of essential ecological processes, in addition to the provision of environmental services derived from them [5,82,122 Cross Border Biophysical Forest Phenomena: the phenomenon of shyness of the tree canopy consists of a limited growth of the treetops, so that the leaves and branches of adjacent trees do not touch each other, producing figures and patterns with the background sky when observing the trees from the ground. The shyness of the crown has been observed in certain species of European oak and pine, and species of tropical and subtropical habitats.…”

“…Political forests are not accurately mapped to forest cover and are different from common sense interpretations of the forest as natural formations characterized by associated trees and species, such as FAO forest classifications based on vegetation assessment. The creation of political forests implies coercion and violence, that is, wars, insurgencies, and other forms of political violence impact these areas, often forcing the displacement of resident peoples[5,127]. •…”