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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]

Citizens are increasingly becoming involved in data collection, whether for scientific purposes, to carry out micro-tasks, or as part of a gamified, competitive application. In some cases, volunteered data collection overlaps with that of mapping agencies, e.g., the citizen-based mapping of features in OpenStreetMap. LUCAS (Land Use Cover Area frame Sample) is one source of authoritative in-situ data that are collected every three years across EU member countries by trained personnel at a considerable cost to taxpayers. This paper presents a mobile application called FotoQuest Austria, which involves citizens in the crowdsourcing of in-situ land cover and land use data, including at locations of LUCAS sample points in Austria. The results from a campaign run during the summer of 2015 suggest that land cover and land use can be crowdsourced using a simple protocol based on LUCAS. This has implications for remote sensing as this data stream represents a new source of potentially valuable information for the training and validation of land cover maps as well as for area estimation purposes. Although the most detailed and challenging classes were more difficult for untrained citizens to recognize, the agreement between the crowdsourced data and the LUCAS data for basic high level land cover and land use classes in homogeneous areas (ca. 80%) shows clear potential. Recommendations for how to further improve the quality of the crowdsourced data in the context of LUCAS are provided so that this source of data might one day be accurate enough for land cover mapping purposes. [ABSTRACT FROM AUTHOR]

Information about land cover and land use is needed for a wide range of applications such as nature protection and biodiversity, forest and water management, urban and transport planning, natural hazard prevention and mitigation, monitoring of agricultural policies and economic land use modelling. A number of different remotely-sensed global land cover products are available but studies have shown that there are large spatial discrepancies between these different products when compared. To address this issue of land cover uncertainty, a tool called Geo-Wiki was developed, which integrates online and mobile applications, high resolution satellite imagery available from Google Earth, and data collection through crowdsourcing as a mechanism for validating and improving globally relevant spatial information on land cover and land use. Through its growing network of volunteers and a number of successful data collection campaigns, almost 5 million samples of land cover and land use have been collected at many locations around the globe. This paper provides an overview of the main features of Geo-Wiki, and then using a series of examples, illustrates how the crowdsourced data collected through Geo-Wiki have been used to improve information on land cover and land use. [ABSTRACT FROM AUTHOR]

A new 1 km global IIASA- IFPRI cropland percentage map for the baseline year 2005 has been developed which integrates a number of individual cropland maps at global to regional to national scales. The individual map products include existing global land cover maps such as GlobCover 2005 and MODIS v.5, regional maps such as AFRICOVER and national maps from mapping agencies and other organizations. The different products are ranked at the national level using crowdsourced data from Geo-Wiki to create a map that reflects the likelihood of cropland. Calibration with national and subnational crop statistics was then undertaken to distribute the cropland within each country and subnational unit. The new IIASA- IFPRI cropland product has been validated using very high-resolution satellite imagery via Geo-Wiki and has an overall accuracy of 82.4%. It has also been compared with the EarthStat cropland product and shows a lower root mean square error on an independent data set collected from Geo-Wiki. The first ever global field size map was produced at the same resolution as the IIASA- IFPRI cropland map based on interpolation of field size data collected via a Geo-Wiki crowdsourcing campaign. A validation exercise of the global field size map revealed satisfactory agreement with control data, particularly given the relatively modest size of the field size data set used to create the map. Both are critical inputs to global agricultural monitoring in the frame of GEOGLAM and will serve the global land modelling and integrated assessment community, in particular for improving land use models that require baseline cropland information. These products are freely available for downloading from the website. [ABSTRACT FROM AUTHOR]

Abstract: Land cover derived from remotely sensed products is an important input to a number of different global, regional and national scale applications including resource assessments and economic land use models. During the last decade three global land cover datasets have been created, i.e. the GLC-2000, MODIS and GlobCover, but comparison studies have shown that there are large spatial discrepancies between these three products. One of the reasons for these discrepancies is the lack of sufficient in-situ data for the development of these products. To address this issue, a crowdsourcing tool called Geo-Wiki has been developed. Geo-Wiki has two main aims: to increase the amount of in-situ land cover data available for training, calibration and validation, and to create a hybrid global land cover map that provides more accurate land cover information than any current individual product. This paper outlines the components that comprise Geo-Wiki and how they are integrated in the architectural design. An overview of the main functionality of Geo-Wiki is then provided along with the current usage statistics and the lessons learned to date, in particular the need to add a mechanism for feedback and interaction as part of community building, and the need to address issues of data quality. The tool is located at geo-wiki.org. [Copyright &y& Elsevier]

Despite being recognized as a key baseline dataset for many applications, especially those relating to biogeochemical cycles, land cover products in their current form are limiting. Typically they lack the thematic detail necessary for driving the models that depend upon them. This study has demonstrated the ability to produce a highly detailed (both spatially and thematically) land cover/land use dataset over Russia – by combining existing datasets into a hybrid information system. The resulting dataset contains detailed subclasses of land cover and attributes necessary for biogeochemical modeling. In lieu of suitable validation data, a confidence map was produced creating six classes of confidence in the agreement between the various remote sensing and statistical datasets. In specific regions, a significant difference between the remote sensing products and the official statistics was observed. For example, in the northwest of Russia the statistics appear to be underreporting the amount of forest land which has likely been increasing in recent decades because of encroachment of forests on abandoned marginal agricultural land. [ABSTRACT FROM AUTHOR]

Abstract: This study aims to determine whether carbon sequestration policies could present a significant contribution to the global portfolio of climate change mitigation options. The objective is to model the effects of policies designed to induce landowners to change land use and management patterns with a view to sequester carbon or to reduce deforestation. The approach uses the spatially explicit Dynamic Integrated Model of Forestry and Alternative Land Use (DIMA) to quantify the economic potential of global forests. The model chooses which of the land-use processes (afforestation, reforestation, deforestation, or conservation and management options) would be applied in a specific location, based on land prices, cost of forest production and harvesting, site productivity, population density, and estimates of economic growth. The approach is relevant in that it (1) couples a revised and updated version of the Special Report on Emissions Scenarios with the dynamic development of climate policy implications through integration with the Model for Energy Supply Strategy Alternatives and their General Environmental Impact (MESSAGE); (2) is spatially explicit on a 0.5° grid; and (3) is constrained by guaranteeing food security and land for urban development. As outputs, DIMA produces 100-year forecasts of land-use change, carbon sequestration, impacts of carbon incentives (e.g., avoided deforestation), biomass for bioenergy, and climate policy impacts. The modeling results indicate that carbon sequestration policies could contribute to a significant part of the global portfolio of efficient climate mitigation policies, dependent upon carbon prices. [Copyright &y& Elsevier]

To assess CO2 fluxes of the terrestrial biosphere, ground-based inventories, flux measurements and bottom-up modeling approaches are used. In most cases inventory-based approaches are not able to produce a full carbon account (FCA). The FCA refers to a carbon budget that is complete, encompasses all components, and is applied continuously in time. Atmospheric inversion modeling implicitly measures the sum of all fluxes, meaning a FCA. Eddy-covariance measurements have huge variations and are difficult to scale up to regional and decadal levels. Bookkeeping up to more complex process-based models rely on land-use change estimates over time, which have large uncertainties. To overcome the accounting gap between top-down and bottom-up measurements, the IPCC introduced the terrestrial ‘missing sink’ concept by taking long-term land-use changes into account to further break down the global carbon budget. IIASA has developed a bottom-up FCA approach that breaks down the terrestrial carbon balance of Russia for 1990 (1988–1992) resulting in a sink. This was then combined with the terrestrial sink strength of the extra-tropical Northern Hemisphere (approximately > 30°N) determined via top-down atmospheric inversion. Using this approach, the remainder, the terrestrial sink strength of the extratropical Northern Hemisphere without Russia, could then be determined with a relative uncertainty that is smaller (i.e., < 100%) than the uncertainties exhibited by inverse models. From the analysis it can be concluded that the ‘missing sink’ issue can be reduced to an issue of relevant accounting due to the fact that the combined top-down/bottom-up approach does not identify any missing sink. [ABSTRACT FROM AUTHOR]

Abstract: Preservation of biodiversity and reduction of deforestation are considered as key elements when addressing an increased use of bioenergy in the future. This paper presents different combinations of scenarios for global feedstock supply for the production of bioenergy under specified social and environmental safeguard provisions. The objectives of this study were threefold: a) to present a global perspective using an integrated modeling approach; b) to frame the boundaries for lower scale assessments; and c) to identify potential trade-offs to be considered in future research. The aggregate results, achieved through the application of an integrated global modeling cluster, indicate that under a high global demand for bioenergy by mid-century, biomass will to a large extent be sourced from the conversion of unmanaged forest into managed forest, from new fast-growing short-rotation plantations, intensification, and optimization of land use. Depending on the underlying scenario, zero net deforestation by 2020 could be reached and maintained with only a minor conversion of managed forests into other land cover types. Results further indicate that with rising populations and projected consumption levels, there will not be enough land to simultaneously conserve natural areas completely, halt forest loss, and switch to 100% renewable energy. Especially in the tropical regions of the southern hemisphere, it will be important to achieve a controlled conversion from unmanaged to sustainably managed forest as well as increased protection of areas for ecosystems services such as biodiversity. The study concludes with the recommendation to focus on targeted regional policy design and its implementation based on integrated global assessment modeling. [Copyright &y& Elsevier]