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ArticleCloud computing solution for monitoring dryland forests dynamics in Morocco
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.The wide availability of free satellite imagery and the recent development of cloud-based geospatial analysis platforms dedicated to spatial Big Data that integrates both image archives from different providers, processing algorithms, distributed processing capabilities as well as an application programming interface that facilitate scripting and automation process, opened new perspectives for the use of vegetation observation time series over long time series and over large spatial scales. This work aims at harnessing these technologies and building up an automated solution to monitor forests rehabilitation dynamics in arid lands and to assess the effectiveness of stakeholder’s management or restoration strategies. Such solution is based on graphical user interface that facilitate the process and on the use of analysis functions relaying on analyzing temporal trajectories (time series) of different spectral indices derived from satellite images (Landsat, MODIS or Sentinel) at the required spatial analysis scale. The solution is implemented using java script language by the functions offered by Google Earth Engine (GEE) API. The graphical user interface of the first prototype is exploitable by the means of a standard web browser. It is accessible even to people without any background in regard to programming languages or to remote sensing skills and to overcome managers lack of technical skills or computing infrastructure capacities. The process was tested for two arid regions on Morocco mainly on sites recently rehabilitated: acacia ecosystems on the southern part of Morocco and the argan ecosystem which is an emblematic agrosilvopastoral system. The output has been qualified as promising solution and the prototype represent decision-support tool which contribute to managing and communicating forest information and management at different levels and facilitating the assessment of ecosystem trends and then to plan restoration interventions. Furthermore, field data collected by involving local communities can greatly facilitate results validation, which makes possible to compensate errors due to data sources. Key words: Google earth engine; remote sensing; monitoring; Dryland forests, Morocco ID: 3623147 -
DocumentAnalyzing the occurrence trend of sediment-related disasters and post-disaster recovery cases in mountain regions in North Korea based on a literature review and satellite image observations
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.This study investigated spatiotemporal trends of sediment-related disasters in North Korea from 1960 to 2019 and post-disaster recovery cases based on a literature review and satellite images. Results showed that occurrence status of sediment-related disasters was initially externally reported in 1995 (during the Kim Jongil era); their main triggering factor was heavy summer rainfall. Furthermore, forest degradation rate was positively correlated with population density (R2 = 0.4347, p = 0.02) and occurrence number of sediment-related disasters was relatively high on the west coast region, where both variables showed high values. This indicates that human activity was a major cause of forest degradation and thus, significantly affected sediment-related disasters in mountain regions. Finally, sediment- related disasters due to shallow landslides, debris flow, and slow-moving landslides were observed in undisturbed forest regions and human-impacted forest regions, including terraced fields, opencast mines, forest roads, and post-wildfire areas, via satellite image analysis. These disaster-hit areas remained mostly abandoned without any recovery works, whereas hillside erosion control work (e.g., treeplanting with terracing) or torrent erosion control work (e.g., check dam, debris flow guide bank) were implemented in certain areas. These findings can provide reference information to expand inter-Korean exchange and cooperation in forest rehabilitation and erosion control works of North Korea. Keywords: Climate change, Deforestation and forest degradation, Sustainable forest management, Monitoring and data collection, Research ID: 3616353 -
DocumentTimber loading productivity of remote controlled forestry equipment through image of monitor
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Forest operations like timber harvesting have already been mechanized to reduce hazards to the worker and increase productivity. However, timber harvesting operations have still been considered potentially dangerous and expensive on steep terrain. Teleoperation, to control the timber harvesting machine at a distance, has the potential to improve the safety, productivity and efficiency of harvesting operations on steep terrain. To verify the effects of teleoperation, an experimental prototype system of a monitor image-based teleoperation was constructed using a real forestry machine. In this study, the productivity of excavator based grapple loader, which is one of the most used mechanized harvesting equipment in the timber production, was analyzed using time-study method. Factors like skill and age of operators, influencing loader productivity in timber loading operation were also evaluated by statistical analysis. Productivity analysis results showed that less experienced operators were more productive than experienced operators for teleoperation through image of monitors in the operator cabin. These results are shown to be unfamiliar to the monitor image and different loading operation pattern by operators. According to the results, the monitor image-based teleoperation system of forestry machine need to improve the resolution and installation position of camera. It was expected that additional studies will be needed for real-time remote control of forestry machine in the future. Keywords: Research, Financial mechanisms ID: 3622426
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