European and Regional National Mapping

Topic of the paper : point out technical and operational issues linked to the use of  Pleiades and SPOT 6/7 imagery on the French territory.

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IGN took part in the commissioning phase of the French satellite systems Pleiades designed by CNES, and SPOT6/7 designed by Airbus Defence and Space. Willing to promote both systems, IGN experimented the suitability of both data sources for the requirements of the French NSDI and their use in various mapping processes.  For the past two years the satellite capacity has been tested and image products assessed as complements or substitute to aerial data : coverage in mono/stereoscopic modes, horizontal precision performance and information content potential for land use and land cover mapping, 3D vector accuracy of captured urban topographic features, DEM quality over bare soils and forest canopy.

As far as the French NSDI updating is concerned, Pleiades 20 km swath and 70 cm GSD seems well suited to survey man-made changes (towns, infrastructure,…) with a good performance in XYZ data capture of medium size features (houses, paths,…) and in the generation of DEM over mountainous areas and coasts particularly sensitive to erosion. Meanwhile, SPOT 6/7 with its 60 km swath and its 1,5 m GSD proved able to provide a full coverage of the metropolitan territory every year, opening the way to change detection and land use updating at a higher frequency.

Public partnerships in France tasked IGN to collect of the institutional demands, translate them into Pleiades and SPOT acquisitions requirements over the national territory and produce and disseminate geocoded image products to French public authorities. This focal point position put IGN in a unique position to master the constraints and trends in the demand for Earth observation revisit at HR and THR resolution levels, in the context of the growing “open data” phenomenon and of non “satellite fluent“ newcomers.

Despite the relatively weak penetration of satellite data in the current institutional mapping processes, the revisit capacity of these systems combined with the ongoing work to finance a perennial collaborative procurement of image coverages should foster their use, namely in the preservation of agricultural and natural land.

The Land Information System Austria (LISA) is an initiative for the implementation of a homogeneous land cover and land use solution throughout Austria. Due to the collaborative development efforts, LISA meets the needs of governmental institutions on state, provincial and municipality level. The conceptual basis consists of an object oriented data model that describes classes of land cover and land use together with a number of attributes. The data model implements the EAGLE (EiONET Action Group on Land Monitoring in Europe) data model on national scale and provides all necessary components to be transformed into an INSPIRE compliant dataset.

The land cover part of the data model defines 15 classes (e.g. “Buildings”, “Other constructed areas”, “Bare soil”, “Screes”), which describe the appearance on the earth’s surface. For each of the classes a minimum object size was defined, which starts for many classes at an area of 25 m². Objects below this size are merged with neighbouring objects in order to reduce the number of sliver polygons and to optimise the look-and-feel of the resulting map. Furthermore attributes were defined for all classes which provide additional information for each land cover object (e.g. area, height, biomass index).

The LISA data model and the production chain for operationally mapping land cover have been developed in the frame of two projects (2009-2012) as part of the Austrian Space Applications Programme (ASAP) of the Austrian Research Promotion Agency (FFG). These activities were continued within the ESA funded CadasterENV Austria project (2012-2015). While the first projects focused on creating the land cover maps with orthophotos and airborne laserscanning data, it was the aim of CadasterENV Austria to expand the production methodology for the ingestion of Pléiades imagery. While orthophotos are produced operationally each year for a third of Austria (resulting in a three-year-cycle for the entire country), acquisitions of the Pléiades constellation are possible in a more flexible and cost-efficient manner for ad-hoc requests and smaller areas. As a result up-to-date VHR land cover maps may be produced as flexible as Pléiades images can be acquired. It is important to mention that the LISA land cover maps are purely derived of remote sensing data and thus do not depend on additional thematic GIS data.

In the CadasterENV Austria project the LISA processing chain was adapted for the use of Pléiades data. More than 5,800 km² of Pléiades data were acquired for the cities of Linz, Salzburg and Vienna and their urban hinterland. For the tasking of these satellite scenes it was crucial to specify an incidence angle near nadir in order to avoid tilting of buildings and trees in case of incidence angles larger than 10 degrees. This Pléiades coverage was complemented with orthophotos as well as WorldView-2 imagery and used for the production of VHR land cover maps for the main urban areas of Austria, totalling in more than 10,000 km², which is about an eight of entire Austria and approximately one third of the permanent habitable area. The products were completed in August of 2015 and can be freely downloaded from the project’s website (www.landinformationsystem.at).

The idea of a pan-European High Resolution Layer (HRL) of Imperviousness was born in early GMES research projects, comprising the EC FP6 geoland and the ESA GMES Service Elements SAGE and Land, in order to provide insight into urban development as one of the pressing environmental challenges in Europe and to overcome shortcomings from infrequent or too coarse land monitoring initiatives. This initial service development and demonstrations led to the first-ever operational tender in the frame of GMES Land Monitoring by the European Environment Agency. A first pan-European product was generated utilizing the high-resolution IMAGE2006 satellite database as part of the “GMES Fast Track Service Precursor on land monitoring 2006” by a consortium of European Earth Observation companies. The first product was updated for the reference year 2009 in the frame of the FP7 project geoland2. The latest update was established for the reference year 2012 as part of the GMES Initial Operations. New sensors from the Copernicus satellite missions, especially Sentinel-2, are expected to foster substantial improvements in terms of data quality and consistency.

The objective of the HRL Imperviousness is the consistent monitoring of changes in built-up areas as well as imperviousness levels on a pan-European scale. With its superior resolution (20m intermediate product, 100m validated end-product), it supplements the well-established CORINE Land Cover database with spatially more detailed information on the location, extent and development of impervious surfaces and a more frequent 3-years update cycle (2006-2009-2012). As input for the reference years 2006 and 2009 mostly bi-temporal image data from SPOT and IRS-P6 with 20m resolution were used, whereas for the update of the HRL Imperviousness to 2012 two different coverages made up from IRS-P6, Resourcesat-2 and SPOT4/5 (Coverage 1) and Rapid Eye (Coverage 2) were utilized. Sentinel-2 are expected to be the most relevant input dataset for further updates.

 The production methodology is based on the proven relationship between the Normalized Difference Vegetation Index (NDVI) and vegetation presence, or absence, respectively. Main challenges are to mitigate scene-wise deviations in acquisition dates and vegetation phenology, different sensor characteristics, as well as limitations in image quality. Based on a operational calibration and modelling approach, a per-pixel estimate of imperviousness is derived. While the HRL Imperviousness 2006 was established using a visual calibration approach applied individually to each data set, the update and change mapping is now based on an automatic calibration of the recent NDVI to the original imperviousness degrees. This step is followed by a procedure that extracts built-up change candidates with lower and higher probability. Those candidates are visually checked to differentiate true changes from classification errors. Inside built up areas imperviousness changes are calculated based on the differences of imperviousness between the actual and the reference year considering certain spectral and spatial thresholds (Gangkofner et al. 2010).

In order to derive a consistent time series of status and changes of built-up area and imperviousness levels, the full spatial resolution intermediate products are integrated to a pan-European consistent dataset and aggregated to 1ha resolution.

The HRL Imperviousness supports to analyse pressures to ecosystems or the vulnerability of people and infrastructure to natural hazards. As such, it is a key information source for policy evaluation, for information to the public and enabling policy makers to base their decisions on more evident data sources (cf. EEA, SOER 2015).

References

Gangkofner, U., Weichselbaum, J., Kuntz, S., Brodsky, L., Larsson, K., & De Pasquale, V.. Update of the European High-resolution Layer of Built-up Areas and Soil Sealing 2006 with Image2009 Data. 30th EARSeL Symposium 2010: Remote Sensing for Science, Education and Culture

Lefebvre, A.; Beaugendre, N.; Pennec, A.; Sannier, C.; Corpetti, T. Using data fusion to update built-up areas of the 2012 European High-Resolution Layer Imperviousness. In Proceedings of the 33rd EARSeL Symposium Conference, Matera, Italy, 3–6 June 2013; pp. 321–328.

EEA, 2015, The European environment — state and outlook 2015: synthesis report, European Environment Agency, Copenhagen.

The Urban Atlas provides European, comparable and detailed 20-class land use and land cover map data for the main Functional Urban Areas (FUAs). The 2006 edition covered more or less all EU urban areas with more than 100,000 inhabitants and all EU27 member state capital cities as defined by the Urban Audit, whilst the 2012 update when completed, will be covering in addition to the cities mapped in 2006, all urban areas with a population above 50,000 inhabitants corresponding to a total of 695 FUAs. The 2012 extension and update of the Urban Atlas does not only provide an update of the 2006 exercise but also a spatial extension more than doubling the number of FUAs and area covered and a thematic extension by increasing the number of classes in rural areas from 3 to 10. This raises a number of challenges particularly linked to the complex changes of the 2006 Larger Urban Zones delineation and the extension to a large number of smaller urban areas. The methodology adopted is based on the optimisation of the production process based on a careful blend of automated Object Based Image Analysis (OBIA) techniques and Computer Assisted Photo-Interpretation (CAPI) to ensure the most efficient methodology is applied whilst exceeding the minimum quality requirements. Whenever possible, processing steps were combined to avoid unnecessary duplication of tasks.

To ensure the highest level of homogeneity and compliance with the product specifications, a thorough internal independent validation procedure was developed at FUA level as part of the 2006 exercise and adapted for the 2012 update and extension. A comparison between the internal validation procedure and independent external validation exercises is made for selected representative FUAs. Results show that the internal validation procedure tend to provide lower accuracy than that of the independent validation exercise. Analysis suggests that a potential explanation could be related to the different sampling and response design procedures applied.

Conclusions are drawn by presenting the status of the production to date and future prospects for the development of the product.

The need of a homogenous and nationwide Land Cover (LC) database is critical in a world of increased human pressure on natural resources. Increased human pressure such as urban structures enhances the demands for monitoring and landscape planning on different scales and for multiple purposes. To ensure long-term usefulness a LC database must be updated on a regular basis in a cost-effective manner. A LC database should also be adapted to a multi-purposed usage and be suitable for further analysis and processing. 

CadasterENV is an initiative to create a multi-purpose LC mapping system at national scale. Biotope mapping of Stockholm and Statistics in urban areas are two examples where CadasterENV has and will serve as a basis for further processing and analysis.

National Land Cover Data (CadasterENV Sweden) for Urban Mapping and Monitoring

The objective of CadasterENV Sweden is to implement a multi-scale and multi-purpose Land Cover mapping and monitoring system in Sweden, according to national user specifications. CadasterENV is an initiative to create a national consensus for a multi-purpose LC mapping system at national scale. The system will be comprised of two components:

a Land Cover (LC) mapping component based on HR (High Resolution) and VHR (Very High Resolution) satellite data,

a Land Cover Change (LCC) alert component, based on HR satellite data.

The project is carried out in close cooperation with major LC actors in Sweden e.g. Swedish Environmental Protection Agency, Statistics Sweden, Board of Agriculture and is funded by the Data User Element program of the European Space Agency (ESA).

Classification of land cover is based on satellite imagery and LIDAR data. The main data sources have been SPOT-5 (HR) and Pleiades (VHR). The use of HR data has been in preparation for the upcoming Sentinel-2 and time series. LIDAR is also an important data source within the project as a complement to VHR EO-data.

HR is used to meet the requirements of a nationwide and cost effected method. VHR is used over lager cities to meet the higher demands on geographical delineation accuracy for urban planning.

Land cover classification is pre-processed and post-processed with additional geospatial data from Lantmäteriet (Swedish mapping, cadastral and land registration authority), Swedish Transport Administration, Board of Agriculture and Swedish Forest Agency to add information on land use to the initial land cover classification. Geocoded administrative data from the Swedish Tax Agency are used to derive information on land ownership and to classify green space in terms of public access. Calculations of population proximity to urban green areas are based on Statistics Sweden’s population register geocoded to location of dwellings by use of authoritative address records from the National Mapping Agency.

The users have emphasized a need for a homogenous and nationwide LC database, which can be updated, on a regular basis in a cost-effective manner. The classes and attributes of the LC data model are primarily based on an analysis of user requirements. The aim is that the LC mapping and LCC Alert system will be fully integrated into a national monitoring system to continuously update the LC/LU data in Sweden.

The production line for CadasterENV has been adapted t for further processing and analysis such as the following two examples of analysis of urban green structure and biotope mapping

Analysis of urban green structures with an adapted CadasterENV

In growing cities, balancing the need to develop land for housing with preservation of green space is a true challenge. City planners have the seemingly contradictory task of creating dense and green cities. In order to find out how green Swedish cities are, Statistics Sweden has undertaken a study on green structure in the largest urban areas. The statistics are widely used to assess urban planning policies and for monitoring of environmental objectives.

Examples of measures that have been produced are; Total green space per capita, Public green space per capita, Number of green areas by size, etc. In the future CadasterENV Land Cover data can form the basis for further processing, to provide a product suitable for these statistical exercises.

Biotope mapping in Stockholm County with an adapted CadasterENV

The Stockholm region is growing dramatically. High-quality comprehensive planning documents are required to meet the demand of new housing constructions and infrastructure. A reliable, up to date biotope map is essential for general and detailed planning in the region, as well as for the municipalities. Stockholm County consists of 26 municipalities. In many applications regarding green infrastructure and green corridors, homogenous seamless datasets are needed in order to be able to run different models and receive reliable results that can be used for regional planning.

Biotope mapping usually requires manual interpretation of aerial photos. The main goal of this project was to provide satellite based input to the production of the biotope map as to facilitate its production. By further processing CadasterENV for this particular purpose, semi-automatically derived delineations and attributes were delivered. Some classes in the existing biotope map will likely be obtained via this method, while others will require subsequent manual yet facilitated interpretation of aerial photos.

The European Settlement Map (ESM) 2014 is a built-up density map produced by applying the general Global Human Settlement Layer (GHSL) methodology to the pan-European GMES/Copernicus imagery collection. This collection consists in SPOT-5/6 pan-sharpened images of 2.5 and 1.5m spatial resolution. In total, more than 3,500 scenes were processed and classified at 2.5m resolution ESM has been produced in support of EU policy making. Currently, ESM is available as a 100m map, while the 10m product will be released in the near future. The high level of semantic abstraction of the built-up class allows straightforward rescaling of the ESM to other spatial resolutions. The ESM can be used in a range of applications (examples) that require high spatial resolution settlement information and may be used to complement or substitute other products, such as the European Imperviousness (SSL), CORINE Land Cover (CLC) or Urban Atlas (UA).

In this study we present a comparison of the ESM with other products, namely SSL, CLC and MODIS urban, by using cartographic data as a reference. The reference set consists in building footprints, which were gathered from available cadastre datasets. Open Street Map data has been considered as well. The final reference set covers the whole Tuscany region, Turin and Pavia cities. The analysis has been done at 10m resolution using 5km² tiles. The quality of the datasets under test has been compared with the built-up density in the reference set. In general, the results show that all products overestimate the total built-up area with respect to the values calculated from the reference data (at least double as much). Apart from the analysis of commission and omission errors, a detailed analysis of the built-up density of the tiles has been performed. As for the balanced accuracy, ESM has better performance always. According to the informedness, ESM also outperforms the other sources in all the built-up density ranges (greater than 0.2%).