Generating Up-to-Date and Detailed Land Use and Land Cover Maps Using OpenStreetMap and GlobeLand30

With the opening up of the Landsat archive, global high resolution land cover maps have begun to appear. However, they often have only a small number of high level land cover classes and they are static products, corresponding to a particular period of time, e.g., the GlobeLand30 (GL30) map for 2010. The OpenStreetMap (OSM), in contrast, consists of a very detailed, dynamically updated, spatial database of mapped features from around the world, but it suffers from incomplete coverage, and layers of overlapping features that are tagged in a variety of ways. However, it clearly has potential for land use and land cover (LULC) mapping. Thus the aim of this paper is to demonstrate how the OSM can be converted into a LULC map and how this OSM-derived LULC map can then be used to first update the GL30 with more recent information and secondly, enhance the information content of the classes. The technique is demonstrated on two study areas where there is availability of OSM data but in locations where authoritative data are lacking, i.e., Kathmandu, Nepal and Dar es Salaam, Tanzania. The GL30 and its updated and enhanced versions are independently validated using a stratified random sample so that the three maps can be compared. The results show that the updated version of GL30 improves in terms of overall accuracy since certain classes were not captured well in the original GL30 (e.g., water in Kathmandu and water/wetlands in Dar es Salaam). In contrast, the enhanced GL30, which contains more detailed urban classes, results in a drop in the overall accuracy, possibly due to the increased number of classes, but the advantages include the appearance of more detailed features, such as the road network, that becomes clearly visible

Highlighting Current Trends in Volunteered Geographic Information

Volunteered Geographic Information (VGI) is a growing area of research. This Special Issue aims to capture the main trends in VGI research based on 16 original papers, and distinguishes between two main areas, i.e., those that deal with the characteristics of VGI and those focused on applications of VGI. The topic of quality assessment and assurance dominates the papers on VGI characteristics, whereas application-oriented work covers three main domains: human behavioral analysis, natural disasters, and land cover/land use mapping. In this Special Issue, therefore, both the challenges and the potentials of VGI are addressed

TOWARDS FINE SCALE CHARACTERIZATION OF GLOBAL URBAN EXTENT, CHANGE AND STRUCTURE

Urbanization is a global phenomenon with far-reaching environmental impacts. Monitoring, understanding, and modeling its trends and impacts require accurate, spatially detailed and updatable information on urban extent, change, and structure. In this dissertation, new methods have been developed to map urban extent, sub-pixel impervious surface change (ISC), and vertical structure at national to global scales. First, an innovative multi-level object-based texture classification approach was adopted to overcome spectral confusion between urban and nonurban land cover types. It was designed to be robust and computationally affordable. This method was applied to the 2010 Global Land Survey Landsat data archive to produce a global urban extent map. An initial assessment of this product yielded over 90% overall accuracy and good agreement with other global urban products for the European continent. Second, for sub-pixel ISC mapping, the uncertainty caused by seasonal and phenological variations is one of the greatest challenges. To solve this issue, I developed an iterative training and prediction (ITP) approach and used it to map the ISC of entire India between 2000 and 2010. At 95% confidence, the total ISC for India between 2000 and 2010 was estimated to be 2274.62±7.84 km2. Finally, using an object-based feature extraction approach and the synergy of Landsat and freely available elevation datasets, I produced 30m building height and volume maps for England, which for the first time characterized urban vertical structure at the scale of a country. Overall, the height RMSE was only ±1.61 m for average building height at 30m resolution. And the building volume RMSE was ±1142.3 m3. In summary, based on innovative data processing and information extraction methods, this dissertation seeks to fill in the knowledge gaps in urban science by advancing the fine scale characterization of global urban extent, change, and structure. The methods developed in this dissertation have great potentials for automated monitoring of global urbanization and have broad implications for assessing the environmental impact, disaster vulnerability, and long-term sustainability of urbanization

OPEN SOURCE SOFTWARE AND OPEN EDUCATIONAL MATERIAL ON LAND COVER MAPS INTERCOMPARISON AND VALIDATION

Land Cover (LC) maps represent key resources to understand, model and address many global and local dynamics affecting our planet. They are usually derived from the classification of satellite imagery, after which a validation or intercomparison process is performed to assess their accuracy. This paper presents the project “Capacity Building for High-Resolution Land Cover Intercomparison and Validation”, an educational initiative funded by the International Society for Photogrammetry and Remote Sensing (ISPRS) and mainly targeting developing countries. First, with the help of two open surveys, an analysis of the state of the art was performed which assessed the overall good awareness on LC maps and the needs and requirements for validating and comparing them, as well as the rich availability of educational material on this topic. The second task, currently under finalization, is the development of new educational material, based on open source software and released under an open access license, consisting of: an introduction to the GlobeLand30 (GL30) LC map and its online platform; a desktop GIS procedure showing two use cases on GL30 validation; and an application to collect LC data on the field to be used for validation. Finally, this educational material will be tested in practice in three workshops during the second half of the project, two of which held in developing countries: Dar es Salaam, Tanzania and Nairobi, Kenya

Habitat preferences of juvenile Scottish ospreys (Pandion haliaetus) at stopover and wintering sites

In this study, we use satellite-tracking data from five juvenile Scottish Ospreys Pandion haliaetus to explore habitat preferences at stopover and wintering sites. Daily activity patterns were analysed using a binomial generalised linear model. Kernel density estimation was used to identify core areas at stopover sites and seasonal ranges at the wintering site. A ‘use versus available habitat’ study design was implemented to test whether Ospreys showed preference for a variety of landscape and land-cover variables and for protected areas. Autumn migration strategies varied between individuals, with some Ospreys using stopover sites in France, Spain and Morocco. Ospreys wintered at sites in West Africa. Activity levels varied through the day, with localised peaks at 11:00 and 15:00 h. Ospreys preferred to be near to water features (rivers, lakes, ocean) while avoiding urban areas. Individual differences were observed when considering preference for forest and open-area land-cover classes. Overall, Ospreys did not preferentially use protected areas. Our research confirms already well-established preferences for aquatic habitats, but preference for or avoidance of other habitats, including protected areas, varied between individuals. We highlight the potential of combining satellite-tracking data with environmental data sources to explore the spatial ecology of migratory birds at stopover and wintering sites abroad.PostprintPeer reviewe

A global assessment of gross and net land change dynamics for current conditions and future scenarios

The consideration of gross land changes, meaning all area gains and losses within a pixel or administrative unit (e.g. country), plays an essential role in the estimation of total land changes. Gross land changes affect the magnitude of total land changes, which feeds back to the attribution of biogeochemical and biophysical processes related to climate change in Earth System Models. Global empirical studies on gross land changes are currently lacking. Whilst the relevance of gross changes for global change has been indicated in the literature, it is not accounted for in future land change scenarios. In this study, we extract gross and net land change dynamics from large-scale and high-resolution (30-100m) remote sensing products to create a new global gross and net change dataset. Subsequently, we developed an approach to integrate our empirically derived gross and net changes with the results of future simulation models, by accounting for the gross and net change addressed by the land use model and the gross and net change that is below the resolution of modelling. Based on our empirical data, we found that gross land change within 0.5-degree grid cells were substantially larger than net changes in all parts of the world. As 0.5- degree grid cells are a standard resolution of Earth System Models, this leads to an underestimation of the amount of change. This finding contradicts earlier studies, which assumed gross land changes to appear in shifting cultivation areas only. Applied in a future scenario, the consideration of gross land changes led to approximately 50% more land changes globally compared to a net land change representation. Gross land changes were most important in heterogeneous land systems with multiple land uses (e.g. shifting cultivation, smallholder farming, and agro-forestry systems). Moreover, the importance of gross changes decreased over time due to further polarization and intensification of land use. Our results serve as empirical database for land change dynamics that can be applied in Earth System Models and Integrated Assessment Model

TOWARDS THE INTEGRATION OF AUTHORITATIVE AND OPENSTREETMAP GEOSPATIAL DATASETS IN SUPPORT OF THE EUROPEAN STRATEGY FOR DATA

Abstract. Digital transformation is at core of Europe's future and the importance of data is well highlighted by the recently published European strategy for data, which envisions the establishment of so-called European data spaces enabling seamless data flows across actors and sectors to ultimately boost the economy and generate innovation. Integrating datasets produced by multiple actors, including citizen-generated data, is a key objective of the strategy. This study focuses on OpenStreetMap (OSM), the most popular crowdsourced geographic information project, and is the first step towards an exploration of pros and cons of integrating its open-licensed data with authoritative geospatial datasets from European National Mapping Agencies. In contrast to previous work, which has only tested data integration at the local or regional level, an experiment was presented to integrate the national address dataset published by the National Land Survey (NLS) of Finland with the corresponding dataset from OSM. The process included the analysis of the two datasets, a mapping between their data models and a set of processing steps – performed using the open source QGIS software – to transform and finally combine their content. The resulting dataset confirms that, while addresses from the NLS are in general more complete across Finland, in some areas OSM addresses provide a higher detail and more up-to-date information to usefully complement the authoritative one. Whilst the analysis confirms that an integration between OSM and authoritative geospatial datasets is technically and semantically feasible, future work is needed to evaluate enablers and barriers that also exist at the legal and organisational level

An open source approach for the intrinsic assessment of the temporal accuracy, up-to-dateness and lineage of OpenStreetMap

Abstract. OpenStreetMap (OSM) is the most popular crowdsourced geographic information project. The main factor that still limits the practical use of OSM is the lack of quality assurance. OSM quality assessment is thus a well-studied topic in literature, with most of the studies evaluating the quality by comparison against reference datasets. In contrast to these extrinsic approaches, OSM intrinsic assessment evaluates the quality by only analysing OSM itself. This study contributes to OSM intrinsic assessment by introducing an open source procedure to evaluate the temporal accuracy, up-to-dateness and lineage of OSM. Two workflows are presented: the first allows accessing the historical evolution of single OSM objects through an interactive web application, while the second aggregates and stores results on a user-defined grid to enable further GIS processing. The methodology is applied on the OSM nodes in the city of Dar es Salaam, Tanzania, by computing the following measures on the cells of an hexagonal grid: total number of nodes, average date of creation and last edit of nodes, average update frequency of nodes, average number of versions of nodes, average and total number of different contributors on nodes. Results highlight the mapping dynamics driven by the Dar Ramani Huria project, focused on increasing flood preparedness and resilience. When moving from the peripheral areas to the city centre, OSM is characterized by a progressively higher density of nodes, created earlier in time and updated by a higher number of contributors, which are all indexes of a general higher data quality. Document type: Articl

A global assessment of gross and net land change dynamics for current conditions and future scenarios

The consideration of gross land changes, meaning all area gains and losses within a pixel or administrative unit (e.g. country), plays an essential role in the estimation of total land changes. Gross land changes affect the magnitude of total land changes, which feeds back to the attribution of biogeochemical and biophysical processes related to climate change in Earth system models. Global empirical studies on gross land changes are currently lacking. Whilst the relevance of gross changes for global change has been indicated in the literature, it is not accounted for in future land change scenarios. In this study, we extract gross and net land change dynamics from large-scale and high-resolution (30–100 m) remote sensing products to create a new global gross and net change dataset. Subsequently, we developed an approach to integrate our empirically derived gross and net changes with the results of future simulation models by accounting for the gross and net change addressed by the land use model and the gross and net change that is below the resolution of modelling. Based on our empirical data, we found that gross land change within 0.5° grid cells was substantially larger than net changes in all parts of the world. As 0.5° grid cells are a standard resolution of Earth system models, this leads to an underestimation of the amount of change. This finding contradicts earlier studies, which assumed gross land changes to appear in shifting cultivation areas only. Applied in a future scenario, the consideration of gross land changes led to approximately 50% more land changes globally compared to a net land change representation. Gross land changes were most important in heterogeneous land systems with multiple land uses (e.g. shifting cultivation, smallholder farming, and agro-forestry systems). Moreover, the importance of gross changes decreased over time due to further polarization and intensification of land use. Our results serve as an empirical database for land change dynamics that can be applied in Earth system models and integrated assessment models