Search for: All records

Ecosystem destruction and biodiversity loss are now widespread, extremely rapid, and among the top global anthropogenic risks both in terms of likelihood and overall impact. Thorough impact evaluation of these environmental abuses—essential for conservation and future project planning—requires good analysis of local ecological and environmental data in addition to social and economic impacts. We characterized the deforestation and biodiversity impacts of energy investments in Southeast Asia using multiple geospatial data sources related to forest cover and loss data from 2000 to 2018, other landcover data, and the location, type, and characteristics of energy investments. This study paid particular attention to different types of power plants and financing sources. We identified critical buffer zones and forest structures impacted by these projects in accordance with IUCN criteria and spatial ecology. The paper introduces a novel, replicable analytical framework that goes beyond earlier studies in which all forests are treated as equivalent. It characterizes forests based on spatial morphological structures such as core forest, edges, islands, and bridges, allowing for a more nuanced understanding of deforestation and its impacts on biodiversity. Preliminary findings suggest that projects financed by Chinese development banks pose different risks compared to non-Chinese financing. The study also reveals significant differences in biodiversity impacts based on the type of energy source, be it coal or hydro. The study offers critical insights into the trade-offs between energy development and biodiversity conservation. It provides actionable metrics and strategies for policymakers, conservationists, and development banks to prioritize forest and habitat preservation in Southeast Asia and globally. 

Land Use and Land Cover Changes (LULCC) are occurring rapidly around the globe, particularly in developing island nations. We use the lens of the United Nations’ Sustainable Development Goals (SDG) to determine potential policies to address LULCC due to increasing population, suburbia, and rubber plantations in Semarang, Indonesia between 2006 and 2015. Using remote sensing, overlay analysis, optimized hot spot analysis, expert validation, and Continuous Change Detection and Classification, we found that there was a spread of urban landscapes towards the southern and western portions of Semarang that had previously been occupied by forests, plantations, agriculture, and aquaculture. We also witnessed a transition in farming from agriculture to rubber plantations, a cash crop. The implications of this study show that these geospatial analyses and big data can be used to characterize the SDGs, the complex interplay of these goals, and potentially alleviate some of the conflicts between disparate SDGs. We recommend certain policies that can assist in preserving the terrestrial ecosystem of Semarang (SDG 15) while creating a sustainable city (SDG 11, SDG 9) and providing sufficient work for individuals (SDG 1) in a growing economy (SDG 8) while simultaneously maintaining a sufficient food supply (SDG 2). 

Land subsidence and flooding events in coastal Semarang City, Central Java, has had severe impacts on the region's population and economy. This work presents a methodology based on a combination of InSAR subsidence mapping and optical classification and change detection techniques to estimate the spatial distribution of subsidence rate and assess its impact on urbanization growth, land conversion and coastal flooding. Significant spatial relationships were found between urban zones (building density), flood extent (shoreline retreat) and subsidence rates. The overexploitation of aquifers and city zoning development contribute to accelerate subsidence rates.