Global trends in exposure to light pollution in natural terrestrial ecosystems

This is a freely-available open access publication. Please cite the published version which is available via the DOI link in this record.The rapid growth in electric light usage across the globe has led to increasing presence of artificial light in natural and semi-natural ecosystems at night. This occurs both due to direct illumination and skyglow - scattered light in the atmosphere. There is increasing concern about the effects of artificial light on biological processes, biodiversity and the functioning of ecosystems. We combine intercalibrated Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) images of stable night-time lights for the period 1992 to 2012 with a remotely sensed landcover product (GLC2000) to assess recent changes in exposure to artificial light at night in 43 global ecosystem types. We find that Mediterranean-climate ecosystems have experienced the greatest increases in exposure, followed by temperate ecosystems. Boreal, Arctic and montane systems experienced the lowest increases. In tropical and subtropical regions, the greatest increases are in mangroves and subtropical needleleaf and mixed forests, and in arid regions increases are mainly in forest and agricultural areas. The global ecosystems experiencing the greatest increase in exposure to artificial light are already localized and fragmented, and often of particular conservation importance due to high levels of diversity, endemism and rarity. Night time remote sensing can play a key role in identifying the extent to which natural ecosystems are exposed to light pollution.European Research Council/ European Union’s Seventh Framework Programme (FP7/2007–2013

SPATIOTEMPORAL EVOLUTION OF THE IMBALANCED REGIONAL DEVELOPMENT IN MAINLAND CHINA USING DMSP-OLS DATA

The Defense Meteorological Satellite Programs Operational Linescan System (DMSP-OLS) nighttime lights imagery has been widely used to monitor economic activities and regional development in recent decades. In this paper, we firstly processed the nighttime light imageries of the Mainland China from 1992 to 2013 due to the radiation or geometric errors. Secondly, by dividing the Mainland China into seven regions, we found high correlation between the sum light values and GDP of each region. Thirdly, we extracted the economic centers of each region based on their nighttime light images. Through the analysis, we found the distribution of these economic centers was relatively concentrated and the migration of these economic centers showed certain directional trend or circuitous changes, which suggested the imbalanced socio-economic development of each region. Then, we calculated the Regional Development Gini of each region using the nighttime light data, which indicated that social-economic development in South China presents great imbalance while it is relatively balanced in Southwest China. This study would benefit the macroeconomic control to regional economic development and the introduction of appropriate economic policies from the national level

ESTIMATING INDUSTRIAL STRUCTURE CHANGES IN CHINA USING DMSP – OLS NIGHT-TIME LIGHT DATA DURING 1999–2012

The Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) night-time light imagery has been proved to be a powerful tool to monitor economic development with its relatively high spatial resolution at large scales. Night-time lights caused by human activities derived from DMSP-OLS satellite imagery are widely used in socioeconomic parameter estimations and urbanization monitoring. In this paper, DMSP-OLS night-time stable light data from 1999 to 2012 are utilized to analyze inter-annual variation in GDP of per unit light intensity (RGDP) in China. Furthermore, RGDP was compared with statistical data of the tertiary industry structure for 28 provincial regions. The results show that the provincial RGDP decreased abruptly in 2001–2002, 2008–2009 and 2011–2012, which is consistent with the proportional growth of the tertiary industry in GDP. These results indicate that the changes in RGDP can reflect tertiary industry structural changes in China's province-level regions

Remote sensing satellite image processing techniques for image classification: a comprehensive survey

This paper is a brief survey of advance technological aspects of Digital Image Processing which are applied to remote sensing images obtained from various satellite sensors. In remote sensing, the image processing techniques can be categories in to four main processing stages: Image preprocessing, Enhancement, Transformation and Classification. Image pre-processing is the initial processing which deals with correcting radiometric distortions, atmospheric distortion and geometric distortions present in the raw image data. Enhancement techniques are applied to preprocessed data in order to effectively display the image for visual interpretation. It includes techniques to effectively distinguish surface features for visual interpretation. Transformation aims to identify particular feature of earth’s surface and classification is a process of grouping the pixels, that produces effective thematic map of particular land use and land cover

Macroecological Patterns of Plant Species and Anthropogenic Activities

The study of macroecology not only identifies patterns in the distribution and abundance of species at large spatial and temporal scales, it also gives insight into the processes underlying those patterns. The contribution of this work is not limited to helping develop the field of ecology per se, but also provides important insights into the understanding of large scale processes like climate change, the spread of introduced species, pest control and how increasing pressure from anthropogenic activities threatens biodiversity and ecosystem services. During the first decade following its formal inception, most of the progress in macroecology was made through studies of animal species, and research into plant species continues to lag far behind. This thesis contributes to the study of the macroecology of plant species by examining some selected macroecological patterns that have been studied only for animal species and by including an important issue that might have significant effects on diverse macroecological patterns, namely anthropogenic activities. The second and third chapters of the thesis address the generalised individuals-area relationship (GIAR) and the patch individuals-area relationship (PIAR), two macroecological relationships not previously explored for plant species. I show for the first time the existence of negative GIARs at the intraspecific and interspecific levels in plant species, similar to those documented for animal species. Unlike animal species, I did not find a broadly consistent intraspecific PIAR in plant species; more than half of the tested species showed negative PIARs. The resource concentration hypothesis may help explain those positive PIARs that were observed. The fourth chapter considers the effect of past human activities on current patterns of plant species richness at a landscape scale. Using a detailed database on the historical anthropogenic activities for Cornwall, U.K., I examine the relationship between species richness and the area covered by each historical land-use at two different spatial resolutions (10km x 10km and 2km x 2km). I find that at the 10km x10km scale human activities carried out since the 17th and 19th centuries explain an important proportion of the variation in current plant species richness. In contrast, a model at 2km x 2km scale with upland woods and the total land area of a grid cell explain only 5% of the variation. The fifth and sixth chapters focus on how artificial light at night (ALAN), which has increasingly come to attention as a significant anthropogenic pressure on species, is interacting with the distributions of plant species. In the fourth chapter, I consider the plant family Cactaceae to determine the proportion of the global distribution ranges of species that is being influenced by ALAN, and how this changes with the size of these distribution ranges and over a 21-year period (1992 to 2012). I found that >80% of cacti species are experiencing ALAN somewhere in their distribution range, and that there is a significant upward trend in ALAN in the ranges of the vast majority of species. For the sixth chapter, I consider similar issues for the threatened plant species of Britain, exploiting new remote sensing imagery of nighttime lighting at a very fine spatial resolution (c.340x340m2). Only 8% of Britain is free of artificial light at night and in consequence a high number of threatened plant species have a high proportion of their range under some influence of ALAN.CONACyT (National Council of Science and Technology, Mexico)SEP (Ministry of Education, Mexico