Assessment of a Rock Pillar Failure by Using Change Detection Analysis and FEM Modelling

In this paper, various methods have been used to control and evaluate engineering difficulties in mining accurately. Different unstable scenarios occurring at the surfaces of underground mine walls, have been identified by comparing 3D terrestrial laser scanning surveys and subsequent point cloud 3D analysis. These techniques, combined with a change detection analysis approach and the integration of rock mechanics’ modelling, represent an asset for the assessment and management of the risk in mining. The change detection analysis can be used as control of mining and industrial processes as well as to identify valid model scenarios for establishing possible failure causes. A pillar spalling failure has been identified in an Italian underground marble quarry and this topic represents the basis of the present paper. A Finite-Element Method was used to verify the occurrence of relatively high-stress concentrations in the pillar. The FEM modelling revealed that stresses in the proximity of the pillar may have sufficient magnitude to induce cracks growth and spalling failure.

Patterns and Drivers of Deforestation and Forest Degradation in Myanmar

Myanmar is one of the most forested countries of mainland Southeast Asia and is a globally important biodiversity hotspot. However, forest cover has declined from 58% in 1990 to 44% in 2015. The aim of this paper was to understand the patterns and drivers of deforestation and forest degradation in Myanmar since 2005, and to identify possible policy interventions for improving Myanmar’s forest management. Remote sensing derived land cover maps of 2005, 2010 and 2015 were accessed from the Forest Department, Myanmar. Post-classification change detection analysis and cross tabulation were completed using spatial analyst and map algebra tools in ArcGIS (10.6) software. The results showed the overall annual rate of forest cover loss was 2.58% between 2005 and 2010, but declined to 0.97% between 2010 and 2015. The change detection analysis showed that deforestation in Myanmar occurred mainly through the degradation of forest canopy associated with logging rather than forest clearing. We propose that strengthening the protected area system in Myanmar, and community participation in forest conservation and management. There needs to be a reduction in centralisation of forestry management by sharing responsibilities with local governments and the movement away from corruption in the timber trading industry through the formation of local-based small and medium enterprises. We also recommend the development of a forest monitoring program using advanced remote sensing and GIS technologies.

Coastal Reef and Seagrass Monitoring for Coastal Ecosystem Management

The growth of human occupations in coastal areas and climate change impact have changed the dynamics of seagrass cover and accelerated the damage to coral reefs globally. For these reasons, coastal management measures need to be developed and renewed to preserve the state of seagrass beds and coral reefs. An example includes the improvement of spatial and multitemporal analyses. This study sought to analyze changes in seagrass cover and damages to coral reefs in Gili Sumber Kima, Buleleng Regency, Bali based on multitemporal Sentinel 2A-MSI imagery. The algorithms of a machine learning, Random Forest (RF), and a Support Vector Machine (SVM) were used to classify the benthic habitats (seagrass beds and coral reefs). Also, a change detection analysis was performed to identify the pattern and the extent to which seagrass beds had changed. The multispectral classification of, particularly, coral reefs was used to explain the condition of this benthic habitat. The results showed +-70% to +-83% accuracies of estimated seagrass cover, and the change detection analysis revealed three directions of change, namely an increase of 27.9 ha, a decrease by 86 ha, and a preserved state in 157 ha of seagrass cover. The product of coral reefs mapping had an accuracy of 42%, and the coral reefs in Gili Sumber Kima were split almost equally between the good (1505 ha) and damaged ones (1397 ha). With the spatial information on seagrass beds and coral reefs in every region, the ecological functions of the coast can be assessed more straightforwardly and appropriately incorporated as the basis for monitoring the dynamics of resources and coastal area management.

Temporal Change Detection Analysis of Monroe County, NY tree cover from 2009 to 2017

Forests provide many ecosystem services which are enjoyed by nearby residing communities. This includes pollution and flood mitigation, carbon sequestration, oxygen production, food, fuel, education, recreation, and aesthetics. These ecosystem services also come from urban and suburban forests. Urban ecosystems, specifically urban green spaces services have been noted to improve human health significantly. Yet urban forests and ecosystem services have not and are not distributed. Understanding where and when forest cover and green spaces are changing can give insight into corresponding changes in services and access within and between communities. Thus, our objective was to complete a temporal analysis of the tree canopy-cover in the city of Rochester, NY was performed to examine change in tree cover and green spaces from 2009-2017. We did this using three-band orthorectified data; red, green, and blue bands and unsupervised and supervised classifications. A stacked-PCA image was created and applied to the change-detection PCA technique. In running the stack PCA analysis band 3 was found to be indicative of change, highlighting the expansion of agriculture as a major drive of change. The stacked PCA change detection technique determined that 8,448,898,967 tons/ha of vegetation was gained during these two time periods. The attempted NDVI change detection indicated that 1.89089353510 tons/ha of vegetation was gained. The NDVI change detection analysis revealed the most vegetation gains occurring in the rural and suburban regions of Monroe County, NY between 2090 and 2017. Given the many benefits of forests and green spaces for health and well-being, we make recommendations for future researchers attempting this kind of assessment for Monroe County and identify local programs that may be mitigating some of the green space disparities in the county.