Urban sprawl and its impact on sustainable urban development: a combination of remote sensing and social media data

Urbanization is one of the most impactful human activities across the world today affecting the quality of urban life and its sustainable development. Urbanization in Africa is occurring at an unprecedented rate and it threatens the attainment of Sustainable Development Goals (SDGs). Urban sprawl has resulted in unsustainable urban development patterns from social, environmental, and economic perspectives. This study is among the first examples of research in Africa to combine remote sensing data with social media data to determine urban sprawl from 2011 to 2017 in Morogoro urban municipality, Tanzania. Random Forest (RF) method was applied to accomplish imagery classification and location-based social media (Twitter usage) data were obtained through a Twitter Application Programming Interface (API). Morogoro urban municipality was classified into built-up, vegetation, agriculture, and water land cover classes while the classification results were validated by the generation of 480 random points. Using the Kernel function, the study measured the location of Twitter users within a 1 km buffer from the center of the city. The results indicate that, expansion of the city (built-up land use), which is primarily driven by population expansion, has negative impacts on ecosystem services because pristine grasslands and forests which provide essential ecosystem services such as carbon sequestration and support for biodiversity have been replaced by built-up land cover. In addition, social media usage data suggest that there is the concentration of Twitter usage within the city center while Twitter usage declines away from the city center with significant spatial and numerical increase in Twitter usage in the study area. The outcome of the study suggests that the combination of remote sensing, social sensing, and population data were useful as a proxy/inference for interpreting urban sprawl and status of access to urban services and infrastructure in Morogoro, and Africa city where data for urban planning is often unavailable, inaccurate, or stale

Pervasiveness of biological impacts of artificial light at night

This is the author accepted manuscript. The final version is available on open access from Oxford University Press via the DOI in this recordArtificial light at night (ALAN) and its associated biological impacts have regularly been characterised as predominantly urban issues. Although far from trivial, this would imply that these impacts only affect ecosystems that are already heavily modified by humans and are relatively limited in their spatial extent, at least as compared with some key anthropogenic pressures on the environment that attract much more scientific and public attention, such as climate change or plastic pollution. However, there are a number of reasons to believe that ALAN and its impacts are more pervasive, and therefore need to be viewed from a broader geographic perspective rather than an essentially urban one. Here we address, in turn, 11 key issues when considering the degree of spatial pervasiveness of the biological impacts of ALAN. First, the global extent of ALAN is likely itself commonly underestimated, as a consequence of limitations of available remote sensing data sources and how these are processed. Second and third, more isolated (rural) and mobile (e.g.,vehicle headlight) sources of ALAN may have both very widespread and important biological influences. Fourth and fifth, the occurrence and impacts of ALAN in marine systems and other remote settings, need much greater consideration. Sixth, seventh and eighth, there is growing evidence for important biological impacts of ALAN at low light levels, from skyglow, and over long distances (because of the altitudes from which it may be viewed by some organisms), all of which would increase the areas over which impacts are occurring. Ninth and tenth, ALAN may exert indirect biological effects that may further expand these areas, because it has a landscape ecology (modifying movement and dispersal and so hence with effects beyond the direct extent of ALAN), and because ALAN interacts with other anthropogenic pressures on the environment. Finally, ALAN is not stable, but increasing rapidly in global extent, and shifting towards wavelengths of light that often have greater biological impacts.Natural Environment Research Council (NERC

Evaluating the Potential of LJ1-01 Nighttime Light Data for Modeling Socio-Economic Parameters

The LJ1-01 satellite is the first dedicated nighttime light remote sensing satellite in the world and offers a higher spatial resolution than the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) satellites of the United States. This study compared the LJ1-01 nighttime light data with NPP/VIIRS data in the context of modeling socio-economic parameters. In the eastern and central regions of China, 10 parameters from the four aspects of gross regional product (annual average population, electricity consumption, and area of land in use) were selected to build linear regression models. The results showed that the LJ1-01 nighttime light data offered better potential for modeling socio-economic parameters than the equivalent NPP/VIIRS data; the former can be an effective tool for establishing models for socio-economic parameters. There were significant positive correlations between the two types of nighttime light data and the 10 socio-economic parameters; that for the gross regional product was the highest