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The accumulation of plastic litter in marine environments is a major environmental challenge along with the difficulties in their measurement because of the massive size of the oceans and vast circulation of plastic litter, which is being addressed as part of the United Nations (UN) Sustainable Development Goals (SDGs). Citizen science, public participation in scientific research and knowledge production, represents a potential source of data for SDG monitoring and reporting of marine plastic litter, yet there has been no evidence of its use to date. Here, we show how Ghana has become the first country to integrate existing citizen science data on marine plastic litter in their official monitoring and reporting of SDG indicator 14.1.1b for the years 2016–2020, which has also helped to bridge local data collection efforts with global monitoring processes and policy agendas by leveraging the SDG framework. The results have been used in Ghana's 2022 Voluntary National Review of the SDGs, and reported on the UN SDG Global Database, as well as helping to inform relevant policies in Ghana. In addition, here, we present a pathway that can be adopted by the relevant government authorities in other countries that have an interest in following a similar citizen science data validation and reporting process for this indicator and potentially others. [ABSTRACT FROM AUTHOR]

The growing demand for minerals has pushed mining activities into new areas increasingly affecting biodiversity-rich natural biomes. Mapping the land use of the global mining sector is, therefore, a prerequisite for quantifying, understanding and mitigating adverse impacts caused by mineral extraction. This paper updates our previous work mapping mining sites worldwide. Using visual interpretation of Sentinel-2 images for 2019, we inspected more than 34,000 mining locations across the globe. The result is a global-scale dataset containing 44,929 polygon features covering 101,583 km2 of large-scale as well as artisanal and small-scale mining. The increase in coverage is substantial compared to the first version of the dataset, which included 21,060 polygons extending over 57,277 km2. The polygons cover open cuts, tailings dams, waste rock dumps, water ponds, processing plants, and other ground features related to the mining activities. The dataset is available for download from https://doi.org/10.1594/PANGAEA.942325 and visualisation at www.fineprint.global/viewer. Measurement(s) terrestrial mining Technology Type(s) satellite imaging Factor Type(s) area • polygon geometry Sample Characteristic - Environment land Sample Characteristic - Location Earth (planet) [ABSTRACT FROM AUTHOR]

It is well established that nighttime radiance, measured from satellites, correlates with economic prosperity across the globe. In developing countries, areas with low levels of detected radiance generally indicate limited development – with unlit areas typically being disregarded. Here we combine satellite nighttime lights and the world settlement footprint for the year 2015 to show that 19% of the total settlement footprint of the planet had no detectable artificial radiance associated with it. The majority of unlit settlement footprints are found in Africa (39%), rising to 65% if we consider only rural settlement areas, along with numerous countries in the Middle East and Asia. Significant areas of unlit settlements are also located in some developed countries. For 49 countries spread across Africa, Asia and the Americas we are able to predict and map the wealth class obtained from ~2,400,000 geo-located households based upon the percent of unlit settlements, with an overall accuracy of 87%. Nighttime lights from satellite are combined with a map of human settlements, showing that 19% of these areas, mainly in Africa, the Middle East and Asia, have no detectable artificial light. These data were then used in models to predict well-being. [ABSTRACT FROM AUTHOR]

In recent decades, global oil palm production has shown an abrupt increase, with almost 90% produced in Southeast Asia alone. To understand trends in oil palm plantation expansion and for landscape-level planning, accurate maps are needed. Although different oil palm maps have been produced using remote sensing in the past, here we use Sentinel 1 imagery to generate an oil palm plantation map for Indonesia, Malaysia and Thailand for the year 2017. In addition to location, the age of the oil palm plantation is critical for calculating yields. Here we have used a Landsat time series approach to determine the year in which the oil palm plantations are first detected, at which point they are 2 to 3 years of age. From this, the approximate age of the oil palm plantation in 2017 can be derived. Measurement(s) 2-D extent • age Technology Type(s) Classification Factor Type(s) input dataset Sample Characteristic - Organism Elaeis guineensis Sample Characteristic - Environment oil palm plantation Sample Characteristic - Location Southeast Asia Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13899713 [ABSTRACT FROM AUTHOR]

The land area covered by freely available very high-resolution (VHR) imagery has grown dramatically over recent years, which has considerable relevance for forest observation and monitoring. For example, it is possible to recognize and extract a number of features related to forest type, forest management, degradation and disturbance using VHR imagery. Moreover, time series of medium-to-high-resolution imagery such as MODIS, Landsat or Sentinel has allowed for monitoring of parameters related to forest cover change. Although automatic classification is used regularly to monitor forests using medium-resolution imagery, VHR imagery and changes in web-based technology have opened up new possibilities for the role of visual interpretation in forest observation. Visual interpretation of VHR is typically employed to provide training and/or validation data for other remote sensing-based techniques or to derive statistics directly on forest cover/forest cover change over large regions. Hence, this paper reviews the state of the art in tools designed for visual interpretation of VHR, including Geo-Wiki, LACO-Wiki and Collect Earth as well as issues related to interpretation of VHR imagery and approaches to quality assurance. We have also listed a number of success stories where visual interpretation plays a crucial role, including a global forest mask harmonized with FAO FRA country statistics; estimation of dryland forest area; quantification of deforestation; national reporting to the UNFCCC; and drivers of forest change. [ABSTRACT FROM AUTHOR]

Floods affect more people globally than any other type of natural hazard. Great potential exists for new technologies to support flood disaster risk reduction. In addition to existing expert-based data collection and analysis, direct input from communities and citizens across the globe may also be used to monitor, validate, and reduce flood risk. New technologies have already been proven to effectively aid in humanitarian response and recovery. However, while ex-ante technologies are increasingly utilized to collect information on exposure, efforts directed towards assessing and monitoring hazards and vulnerability remain limited. Hazard model validation and social vulnerability assessment deserve particular attention. New technologies offer great potential for engaging people and facilitating the coproduction of knowledge. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this paper is to understand the sustainability of urban spatial transformation in the process of rapid urbanization, and calls for future research on the demographic and economic dimensions of climate change. Shanghai towards its transformation to a metropolis has experienced vast socioeconomic and ecological change and calls for future research on the impacts of demographic and economic dimensions on climate change. We look at the major questions (1) to explore economic and demographic growth, land use and land-cover changes in the context of rapid economic and city growth, and (2) to analyze how the demography and economic growth have been associated with the local air temperature and vegetation. Method: We examine urban growth, land use and land-cover changes in the context of rapid economic development and urbanization. We assess the impact of urban expansion on local air temperature and vegetation. The analysis is based on time series data of land use, normalized difference vegetation index (NDVI), and meteorological, demographic and economic data. Results and discussion: The results indicate that urban growth has been driven by mass immigration; as a consequence of economic growth and urban expansion, a large amount of farmland has been converted to paved road and residential buildings. Furthermore, the difference between air temperature in urban and exurban areas has increased rapidly. The decrease of high mean annual NDVI has mainly occurred around the dense urban areas. [ABSTRACT FROM AUTHOR]

In accordance with the concept that only full accounting of major greenhouse gases corresponds to the goals of the United Nations Framework Convention on Climate Change and its Kyoto Protocol, this paper considers uncertainties of regional (national) terrestrial biota Full Carbon Accounting (FCA), both those already achieved and those expected. We analyze uncertainties of major components of the FCA of forest ecosystems of a large boreal region in Siberia (~300 × 10 ha). Some estimates for forests of other regions and Russia as a whole are used for comparison. The systems integration of available information sources and different types of models within the landscape-ecosystem approach are shown to have enabled an estimation of the major carbon fluxes (Net Primary Production, NPP, and heterotrophic respiration, HR) for the region for a single year at the level of 7-12% (confidential interval, CI, 0.9), Net Ecosystem Production (NEP) of 35-40%, and Net Biome Production (NBP) of 60-80%. The most uncertain aspect is the assessment of change in the soil carbon pool, which limits practical application of a pool-based approach. Regionalization of global process-based models, introduction of climatic data in empirical models, use of an appropriate time period for accounting and reporting, harmonization and multiple constraints of estimates obtained by different independent methods decrease the above uncertainties of NEP and NBP by about half. The results of this study support the idea that FCA of forest ecosystems is relevant in the post-Kyoto international negotiation process. [ABSTRACT FROM AUTHOR]

In this paper we provide an analytical framework to estimate the joint production of biomass and carbon sequestration from afforestation and reforestation activities. The analysis is based on geographical explicit information on a half-degree resolution. For each grid-cell the model estimates forest growth using a global vegetation model and chooses forest management rules. Land prices, cost of forest production and harvesting are determined as a function of grid specific site productivity, population density and estimates of economic wealth. The sensitivity of the results due to scenario storylines is assessed using different population and economic growth assumptions, which are consistent with B1 and A2 of the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios (IPCC-SRES) marker scenarios. Considerable differences in the economic supply schedules are found. However, technical potentials seem to converge given constancy in other underlying assumptions of the model. [ABSTRACT FROM AUTHOR]

The area used for mineral extraction is a key indicator for understanding and mitigating the environmental impacts caused by the extractive sector. To date, worldwide data products on mineral extraction do not report the area used by mining activities. In this paper, we contribute to filling this gap by presenting a new data set of mining extents derived by visual interpretation of satellite images. We delineated mining areas within a 10 km buffer from the approximate geographical coordinates of more than six thousand active mining sites across the globe. The result is a global-scale data set consisting of 21,060 polygons that add up to 57,277 km2. The polygons cover all mining above-ground features that could be identified from the satellite images, including open cuts, tailings dams, waste rock dumps, water ponds, and processing infrastructure. The data set is available for download from 10.1594/PANGAEA.910894 and visualization at www.fineprint.global/viewer. Measurement(s) terrestrial mining Technology Type(s) satellite imaging Sample Characteristic - Environment land Sample Characteristic - Location Earth (planet) Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12594248 [ABSTRACT FROM AUTHOR]

Vegetation impacts on ecosystem functioning are mediated by mycorrhizas, plant–fungal associations formed by most plant species. Ecosystems dominated by distinct mycorrhizal types differ strongly in their biogeochemistry. Quantitative analyses of mycorrhizal impacts on ecosystem functioning are hindered by the scarcity of information on mycorrhizal distributions. Here we present global, high-resolution maps of vegetation biomass distribution by dominant mycorrhizal associations. Arbuscular, ectomycorrhizal, and ericoid mycorrhizal vegetation store, respectively, 241 ± 15, 100 ± 17, and 7 ± 1.8 GT carbon in aboveground biomass, whereas non-mycorrhizal vegetation stores 29 ± 5.5 GT carbon. Soil carbon stocks in both topsoil and subsoil are positively related to the community-level biomass fraction of ectomycorrhizal plants, though the strength of this relationship varies across biomes. We show that human-induced transformations of Earth's ecosystems have reduced ectomycorrhizal vegetation, with potential ramifications to terrestrial carbon stocks. Our work provides a benchmark for spatially explicit and globally quantitative assessments of mycorrhizal impacts on ecosystem functioning and biogeochemical cycling. Mycorrhizas—mutualistic relationships formed between fungi and most plant species—are functionally linked to soil carbon stocks. Here the authors map the global distribution of mycorrhizal plants and quantify links between mycorrhizal vegetation patterns and terrestrial carbon stocks. [ABSTRACT FROM AUTHOR]

Ongoing deforestation is a pressing, global environmental issue with direct impacts on climate change, carbon emissions, and biodiversity. There is an intuitive link between economic development and overexploitation of natural resources including forests, but this relationship has proven difficult to establish empirically due to both inadequate data and convoluting geo-climactic factors. In this analysis, we use satellite data on forest cover along national borders in order to study the determinants of deforestation differences across countries. Controlling for trans-border geo-climactic differences, we find that income per capita is the most robust determinant of differences in cross-border forest cover. We show that the marginal effect of per capita income growth on forest cover is strongest at the earliest stages of economic development, and weakens in more advanced economies, presenting some of the strongest evidence to date for the existence of at least half of an environmental Kuznets curve for deforestation. [ABSTRACT FROM AUTHOR]

The article discusses shared satellite images of the earth and calibration and validation data.