Mapping natural habitats using remote sensing and Sparse partial least square discriminant analysis

This work presents a novel approach for mapping the spatial distribution of natural habitats in the "Foothills of Larzac" Natura 2000 listed site located in a French Mediterranean Biogeographical Region. Sparse Partial Least Square Discriminant Analysis was used to analyze two RapidEye datasets (June 2009 and July 2010) with the purpose of choosing the most informative spectral, textural and thematic variables that allow discriminating the classes of habitats. The Sparse Partial Least Square Discriminant Analysis selected relevant and stable variables for the discrimination of habitat classes that could be linked to ecological or biophysical characteristics. It also gave insight into the similarities and the differences between habitats classes with comparable physiognomic characteristics. The highest user accuracy was obtained for dry improved grasslands (u=91.97%) followed by riparian ash woods (u= 88.38%). These results are very encouraging given that these two classes were identified in Annex 1 of the EC Habitats Directive as of community interest. Due to limited data input requirements and to its computational efficiency, the approach developed in this paper is a good alternative to other types of variable selection approaches in a supervised classification framework and can be easily transferred to other Natura 2000 sites

A European Framework for Recording and Sharing Disaster Damage and Loss Data

The recently adopted ‘Sendai Framework for Action on Disaster Risk Reduction 2015-2030’ sets the goals to reduce loss of life, livelihood and critical infrastructure through enhanced national planning and international cooperation. The new Framework is expected to enhance global, regional and national efforts for building resilience to disasters, across the entire disaster management cycle (prevention, preparedness, response and early recovery). Improved monitoring and accountability frameworks, relying on harmonized disaster loss data will be required for meeting the targets and for capturing the levels of progress across different scales of governance. To overcome the problems of heterogeneous disaster data and terminologies, guidelines for reporting disaster damage and losses in a structured manner will be necessary to help national and regional bodies compile this information. In the European Union, the Member States and the European Commission worked together on the establishment of guidelines for recording and sharing disaster damage and loss data as a first step towards the development of operational indicators to translate the Sendai Framework into action. This paper describes the progress to date in setting a common framework for recording disaster damage and loss data in the European Union and identifies the challenges ahead.JRC.G.2-Global security and crisis managemen

Comparative study on the performance of multiparameter SAR Data for operational urban areas extraction using textural features

The advent of a new generation of synthetic aperture radar (SAR) satellites, such as Advanced SAR/Environmental Satellite (C-band), Phased Array Type L-band Synthetic Aperture Radar/Advanced Land Observing Satellite (L-band), and TerraSAR-X (X-band), offers advanced potentials for the detection of urban tissue. In this letter, we analyze and compare the performance of multiple types of SAR images in terms of band frequency, polarization, incidence angle, and spatial resolution for the purpose of operational urban areas delineation. As a reference for comparison, we use a proven method for extracting textural features based on a Gaussian Markov Random Field (GMRF)model. The results of urban areas delineation are quantitatively analyzed allowing performing intrasensor and intersensors comparisons. Sensitivity of the GMRF model with respect to texture window size and to spatial resolutions of SAR images is also investigated. Intrasensor comparison shows that polarization and incidence angle play a significant role in the potential of the GMRF model for the extraction of urban areas from SAR images. Intersensors comparison evidences the better performances of X-band images, acquired at 1-m spatial resolution, when resampled to resolutions of 5 and 10 m

Exploring high repetitivity remote sensing time series for mapping and monitoring natural habitats ; A new approach combining OBIA and k-partite graphs

International audienc

Visualisation of urban airborne laser scanning data with occlusion images

Airborne Laser Scanning (ALS) was introduced to provide rapid, high resolution scans of landforms for computational processing. More recently, ALS has been adapted for scanning urban areas. The greater complexity of urban scenes necessitates the development of novel methods to exploit urban ALS to best advantage. This paper presents occlusion images: a novel technique that exploits the geometric complexity of the urban environment to improve visualisation of small details for better feature recognition. The algorithm is based on an inversion of traditional occlusion techniques

Built-up areas within and around protected areas: Global patterns and 40-year trends

Protected areas (PAs) are a key strategy in global efforts to conserve biodiversity and ecosystem services that are critical for human well-being. Most PAs have some built-up structures within their boundaries or in surrounding areas, ranging from individual buildings to villages, towns and cities. These structures, and the associated human activities, can exert direct and indirect pressures on PAs. Here we present the first global analysis of current patterns and observed long-term trends in built-up areas within terrestrial PAs and their immediate surroundings. We calculate for each PA larger than 5 km2 and for its 10-km unprotected buffer zone the percentage of land area covered by built-up areas in 1975, 1990, 2000 and 2014. We find that globally built-up areas cover only 0.12% of PA extent and a much higher 2.71% of the unprotected buffers as of 2014, compared to 0.6% of all land (protected or unprotected). Built-up extent in and around PAs is highest in Europe and Asia, and lowest in Africa and Oceania. Built-up area percentage is higher in coastal and small PAs, and lower in older PAs and in PAs with stricter management categories. From 1975 to 2014, the increase in built-up area was 23 times larger in the 10-km unprotected buffers than within PAs. Our findings show that the development of built-up structures remains limited within the boundaries of PAs but highlight the need to carefully manage the considerable pressure that PAs face from their immediate surroundings

Synergetic use of Sentinel-1 and Sentinel-2 for assessments of heathland conservation status

Habitat quality assessments often demand wall‐to‐wall information about the state of vegetation. Remote sensing can provide this information by capturing optical and structural attributes of plant communities. Although active and passive remote sensing approaches are considered as complementary techniques, they have been rarely combined for conservation mapping. Here, we combined spaceborne multispectral Sentinel‐2 and Sentinel‐1 SAR data for a remote sensing‐based habitat quality assessment of dwarf shrub heathland, which was inspired by nature conservation field guidelines. Therefore, three earlier proposed quality layers representing (1) the coverage of the key dwarf shrub species, (2) stand structural diversity and (3) an index reflecting co‐occurring vegetation were mapped via linking in situ data and remote sensing imagery. These layers were combined in an RGB‐representation depicting varying stand attributes, which afterwards allowed for a rule‐based derivation of pixel‐wise habitat quality classes. The links between field observations and remote sensing data reached correlations between 0.70 and 0.94 for modeling the single quality layers. The spatial patterns shown in the quality layers and the map of discrete quality classes were in line with the field observations. The remote sensing‐based mapping of heathland conservation status showed an overall agreement of 76% with field data. Transferring the approach in time (applying a second set of Sentinel‐1 and ‐2 data) caused a decrease in accuracy to 73%. Our findings suggest that Sentinel‐1 SAR contains information about vegetation structure that is complimentary to optical data and therefore relevant for nature conservation. While we think that rule‐based approaches for quality assessments offer the possibility for gaining acceptance in both communities applied conservation and remote sensing, there is still need for developing more robust and transferable methods

A crowdsourced global data set for validating built-up surface layers

Several global high-resolution built-up surface products have emerged over the last five years, taking full advantage of open sources of satellite data such as Landsat and Sentinel. However, these data sets require validation that is independent of the producers of these products. To fill this gap, we designed a validation sample set of 50 K locations using a stratified sampling approach independent of any existing global built-up surface products. We launched a crowdsourcing campaign using Geo-Wiki (https://www.geo-wiki.org/) to visually interpret this sample set for built-up surfaces using very high-resolution satellite images as a source of reference data for labelling the samples, with a minimum of five validations per sample location. Data were collected for 10 m sub-pixels in an 80 × 80 m grid to allow for geo-registration errors as well as the application of different validation modes including exact pixel matching to majority or percentage agreement. The data set presented in this paper is suitable for the validation and inter-comparison of multiple products of built-up areas