Performance and Sensitivity of Individual Tree Segmentation Methods for UAV-LiDAR in Multiple Forest Types

Using unmanned aerial vehicles (UAV) as platforms for light detection and ranging (LiDAR) sensors offers the efficient operation and advantages of active remote sensing; hence, UAV-LiDAR plays an important role in forest resource investigations. However, high-precision individual tree segmentation, in which the most appropriate individual tree segmentation method and the optimal algorithm parameter settings must be determined, remains highly challenging when applied to multiple forest types. This article compared the applicability of methods based on a canopy height model (CHM) and a normalized point cloud (NPC) obtained from UAV-LiDAR point cloud data. The watershed algorithm, local maximum method, point cloud-based cluster segmentation, and layer stacking were used to segment individual trees and extract the tree height parameters from nine plots of three forest types. The individual tree segmentation results were evaluated based on experimental field data, and the sensitivity of the parameter settings in the segmentation methods was analyzed. Among all plots, the overall accuracy F of individual tree segmentation was between 0.621 and 1, the average RMSE of tree height extraction was 1.175 m, and the RMSE% was 12.54%. The results indicated that compared with the CHM-based methods, the NPC-based methods exhibited better performance in individual tree segmentation; additionally, the type and complexity of a forest influence the accuracy of individual tree segmentation, and point cloud-based cluster segmentation is the preferred scheme for individual tree segmentation, while layer stacking should be used as a supplement in multilayer forests and extremely complex heterogeneous forests. This research provides important guidance for the use of UAV-LiDAR to accurately obtain forest structure parameters and perform forest resource investigations. In addition, the methods compared in this paper can be employed to extract vegetation indices, such as the canopy height, leaf area index, and vegetation coverage.

Does the Policy of Ecological Forest Rangers (EFRs) for the Impoverished Populations Reduce Forest Disasters?—Empirical Evidence from China

The effective prevention and control of forest disasters is important for forest resources and the well-being of those living in forested areas. This study evaluates the impact of a policy that employs a rural impoverished population as ecological forest rangers (EFRs) for the incidence of forest disasters. We estimate a generalized difference in differences (DID) model using nationwide provincial-level forest disaster data combined with regional data in all policy pilot areas. There are three primary findings. (1) The implementation of the EFR policy failed to effectively reduce the incidence of forest fires, forest pests, forest diseases, forest rodents and other forest disasters, which shows that the EFR policy has not achieved the goal of “forest protection”. (2) The effect of the EFR policy on forest disaster control is not significantly different among provinces with different forest resource endowments and different levels of social and economic development. This shows that there is no significant difference in the implementation of EFR policies between different forest resource endowments and different socioeconomic development areas. (3) The EFR policy failed to achieve the effective coordination of the dual goals of “poverty reduction” and “ecological protection”; this is the main reason for the failure to reduce the incidence of forest disasters while reducing poverty. The pressure of this policy neglected the “forest management and protection” function of the policy and the corresponding assessment requirements. At the same time, the central government also neglected the assessment of the prevention and control of “forest disasters” by local governments when implementing this policy. Ultimately, the opportunism of local governments and ecological rangers was strengthened. Therefore, the goals of environmental service payment items and the corresponding evaluation index settings need to be matched to truly achieve the established goals.

Raw Material Consumption Controls on Environment Impacts of Sofa Production: A Case Study Based on Ecological Footprint

Wooden furniture production consumes a lot of forest resource and other resources, so it is important to estimate its environmental effect. In this research, we collected data in a sofa factory of China and appraised its environment impacts by the ecological footprint (EF) methodology. The results showed that the total EF of the sofa factory was 2 316.25 gha/year (gha: global hectare). The average EF of a sofa was 0.18 gha/year. For the total EF of the sofa factory, main contribution came from wooden materials (55%), followed by non-wooden materials (41.26%), and these two categories contributed above 96% of the total EF. Human labor accounted for 2.21% of the total footprint. The built land and water contributed a little to the total EF. For the total EF of the wooden materials, main contribution came from wood beams (57.6%), followed by plywood (41.08%); and for the total EF of the non-wooden materials, main contribution came from sponge (95.37%). In the end, we concluded that the incorporate of recycled wooden material and reused sponge in the sofa production could be viewed as an important strategy to achieve more sustainable manufacturing.

Quantifying the Preference of Stakeholders in the Utilization of Forest Resources

The economic contribution of forest resources to the communities surrounding nature reserves cannot be ignored. The method for which to find a forest resource utilization path to balance the contradiction between local farmers’ economic development and ecological protection in the development of nature reserves is important. However, little attention has been given to the effect of forest resource users’ behavioral preferences on forest resource utilization. This study selected Wolong Nature Reserve as a case study and randomly interviewed different stakeholders with semi-structured questionnaires to investigate the differences in forest resource utilization patterns among stakeholders with different behavioral preferences. According to the results of multi-attribute decision analysis with behavioral preference, stakeholders form different behavioral preferences by judging their own resource endowment. With a change of in the behavioral preference value λ, when the behavioral preference of stakeholders is more pessimistic (λ = 0.1), cautious (λ = 0.3), or neutral (λ = 0.5), they are more inclined to choose the economically dominant forest resource utilization mode; when the behavioral preference of stakeholders is optimistic (λ = 0.7) or even radical (λ = 0.9), they choose the eco-economic or eco-dominant forest resource utilization mode, respectively. This study confirms that stakeholders’ behavioral preferences have an important impact on forest resource utilization patterns. Therefore, policy making should focus on improving the economic benefits of forest resources and providing alternative livelihoods, which will change the resource endowment of the stakeholders of nature reserve, guide them to turn to relatively optimistic behavioral preferences, enhance their awareness and motivation of ecological protection, and thereby improve forest conservation outcomes.

Agricultural expansion and the ecological marginalization of forest-dependent people

Agricultural expansion into subtropical and tropical forests causes major environmental damage, but its wider social impacts often remain hidden. Forest-dependent smallholders are particularly strongly impacted, as they crucially rely on forest resources, are typically poor, and often lack institutional support. Our goal was to assess forest-smallholder dynamics in relation to expanding commodity agriculture. Using high-resolution satellite images across the entire South American Gran Chaco, a global deforestation hotspot, we digitize individual forest-smallholder homesteads (n = 23,954) and track their dynamics between 1985 and 2015. Using a Bayesian model, we estimate 28,125 homesteads in 1985 and show that forest smallholders occupy much larger forest areas (>45% of all Chaco forests) than commonly appreciated and increasingly come into conflict with expanding commodity agriculture (18% of homesteads disappeared; n = 5,053). Importantly, we demonstrate an increasing ecological marginalization of forest smallholders, including a substantial forest resource base loss in all Chaco countries and an increasing confinement to drier regions (Argentina and Bolivia) and less accessible regions (Bolivia). Our transferable and scalable methodology puts forest smallholders on the map and can help to uncover the land-use conflicts at play in many deforestation frontiers across the globe. Such knowledge is essential to inform policies aimed at sustainable land use and supply chains.