Quality Assessment of Hydrogeomorphological Features Derived from Digital Terrain Models

Digital terrain models (DTM) provide a model for representing the continuous earth elevation surface that can contain errors introduced by the main phases of generation and modelling. Uncertainty of the model is rarely considered by users. Assessment of uncertainty require information on the nature, amount and spatial structure of the errors. DTMs of di®erent original resolution were compared in order to assess the quality of derived hydrological and morphological features. SRTM dataset with resolution of 100m, DEM dataset mosaic from various sources with a resolution of 60m and ASTER derived dataset with a resolution of 30m were used. The error propagation was modelled with a stochastic approach. The probabilistic distribution of extracted hydrological features was drawn considering the spatial structure of errors in the datasets. The features considered were stream network and watershed divides net. The distribution of the Strahler order of the features was studied. An analysis of the overall probability of features extracted from variously prepared datasets was carried in order to get information on where is the most probable stream network or watershed divides net.JRC.H.6-Spatial data infrastructure

IMAGE-2006 Mosaic: Product Description

This report describes the IMAGE-2006 mosaic products. Each product consists of a range of information layers grouped into three categories: base layers, mosaic layers, and quality layers. A mosaic product is available for each coverage and data/country region of interest combination.JRC.H.6-Digital Earth and Reference Dat

IMAGE-2006 Mosaic: Geometric and Radiometric Consistency of Input Imagery

Within their domain of overlap, two images may differ in both geometry and radiometry. Consequently, when they are mosaiced, these differences may reveal the position of the seam lines even if they follow salient image structures such as roads and streams. A pair of overlapping images is said to be consistent if they are in agreement to one another in both geometry and radiometry. In this report, the consistency is measured using correlation computations and linear regressions. Measurements are produced for all existing pairs of overlapping images (given the 3,699 IMAGE-2006 input images, there are 29,447 such pairs). The quality layers of the IMAGE-2006 mosaics rely directly on these measurements. Indeed, the agreement between any pair of adjacent pieces of the mosaic is determined by the consistency measurements calculated within the domain of overlap of the two images leading to these two mosaic pieces.JRC.H.6-Digital Earth and Reference Dat

IMAGE-2006 Mosaic: Data Ingestion and Organisation v1.0

This report details how the IMAGE-2006 data has been ingested and organised in view of creating the IMAGE-2006 mosaic. In particular, it details the method developed for merging the two coverages (delivered on a country basis) into a unique pan-European coverage. The concept of data and country regions of interest is introduced and a method for compositing identical scenes originating from more than one country is detailed. The resulting reference coverage contains 3,533 unique scenes, starting from a total of 3,699 delivered scenes. While the number of received scenes matches those reported by the DLR/Metria report, it is not possible to check whether the received scenes actually match the IMAGE-2006 data set since to this date no master list is available.JRC.H.6-Digital Earth and Reference Dat

Contents lists available at ScienceDirect Pattern Recognition

journal homepage: www.elsevier.com/locate/pr Edge-preserving smoothing using a similarity measure in adaptive geodesi

IMAGE-2006 Mosaic: Analysis of Image Footprints

This technical note presents an evaluation of the footprints of the IMAGE-2006 received imagery (as of April 15th 2008). The first coverage (2080 images) is nearly covering the full target territory (some small gaps, the largest one being the Porto Santo Island, Madeira, Portugal). The second coverage (1619 images) accounts for 96.5{\%} of the territory with Iceland and all Atlantic Islands missing plus a series of large gaps mainly in Scandinavia. Note that imagery was delivered as a union of country coverages rather than a truly European coverage. Consequently, some images overlapping two or more countries were delivered more than once. In addition, these duplicated images are not always exactly identical.JRC.H.6-Digital Earth and Reference Dat

Rubble detection from VHR aerial imagery data using differential morphological profiles

Rubble detection is a key element in post disaster crisis assessment and response procedures. In this paper we present an automated method for rapid detection and quantification of rubble from very high resolution (VHR) aerial imagery of urban regions. It is a two step procedure in which the input image is projected on to a hierarchical representation structure for efficient mining and decomposition. Image features matching the geometric and chromatic properties of rubble are fused into a rubble layer that can be re-adjusted interactively. The targeted objects are evaluated based on a density metric given by spatial aggregation. The method is tested on a small-scale exercise on the publically available aerial imagery of Port-au-Prince, Haiti. Performance and preliminary results are discussed.JRC.G.2-Global security and crisis managemen

Conditional toggle mappings: principles and applications

International audienceWe study a class of mathematical morphology filters to operate conditionally according to a set of pixels marked by a binary mask. The main contribution of this paper is to provide a general framework for several applications including edge enhancement and image denoising, when it is affected by salt-and-pepper noise. We achieve this goal by revisiting shock filters based on erosions and dilations and extending their definition to take into account the prior definition of a mask of pixels that should not be altered. New definitions for conditional erosions and dilations leading to the concept of conditional toggle mapping. We also investigate algebraic properties as well as the convergence of the associate shock filter. Experiments show how the selection of appropriate methods to generate the masks lead to either edge enhancement or salt-and-pepper denoising. A quantitative evaluation of the results demonstrates the effectiveness of the proposed methods. Additionally, we analyse the application of conditional toggle mapping in remote sensing as pre-filtering for hierarchical segmentation

Crop classification from Sentinel-2 time series with temporal convolutional neural networks

Automated crop identification tools are of interest to a wide range of applications related to the environment and agriculture including the monitoring of related policies such as the European Common Agriculture Policy. In this context, this work presents a parcel-based crop classification system which leverages on 1D convolutional neural network supervised learning capacity. For the training and evaluation of the model, we employ open and free data: (i) time series of Sentinel-2 optical data selected to cover the crop season of one year, and (ii) a cadastre-derived database providing detailed delineation of parcels. By considering the most dominant crop types and the temporal features of the optical data, the proposed lightweight approach discriminates a considerable number of crops with high accuracy