Mapping 20 Years of Urban Expansion in 45 Urban Areas of Sub-Saharan Africa

By 2050, half of the net increase in the world’s population is expected to reside in sub-Saharan Africa (SSA), driving high urbanization rates and drastic land cover changes. However, the data-scarce environment of SSA limits our understanding of the urban dynamics in the region. In this context, Earth Observation (EO) is an opportunity to gather accurate and up-to-date spatial information on urban extents. During the last decade, the adoption of open-access policies by major EO programs (CBERS, Landsat, Sentinel) has allowed the production of several global high resolution (10–30 m) maps of human settlements. However, mapping accuracies in SSA are usually lower, limited by the lack of reference datasets to support the training and the validation of the classification models. Here we propose a mapping approach based on multi-sensor satellite imagery (Landsat, Sentinel-1, Envisat, ERS) and volunteered geographic information (OpenStreetMap) to solve the challenges of urban remote sensing in SSA. The proposed mapping approach is assessed in 17 case studies for an average F1-score of 0.93, and applied in 45 urban areas of SSA to produce a dataset of urban expansion from 1995 to 2015. Across the case studies, built-up areas averaged a compound annual growth rate of 5.5% between 1995 and 2015. The comparison with local population dynamics reveals the heterogeneity of urban dynamics in SSA. Overall, population densities in built-up areas are decreasing. However, the impact of population growth on urban expansion differs depending on the size of the urban area and its income class.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Remote Sensing for Non‐Technical Survey

This chapter describes the research activities of the Royal Military Academy on remote sensing applied to mine action. Remote sensing can be used to detect specific features that could lead to the suspicion of the presence, or absence, of mines. Work on the automatic detection of trenches and craters is presented here. Land cover can be extracted and is quite useful to help mine action. We present here a classification method based on Gabor filters. The relief of a region helps analysts to understand where mines could have been laid. Methods to be a digital terrain model from a digital surface model are explained. The special case of multi‐spectral classification is also addressed in this chapter. Discussion about data fusion is also given. Hyper‐spectral data are also addressed with a change detection method. Synthetic aperture radar data and its fusion with optical data have been studied. Radar interferometry and polarimetry are also addressed

Complementarity Between Sentinel-1 and Landsat 8 Imagery for Built-Up Mapping in Sub-Saharan Africa

<p>The dataset contains input and output files for the following paper:</p> <p>Yann Forget, Michal Shimoni, Marius Gilbert and Catherine Linard. <em>"Complementarity Between Sentinel-1 and Landsat 8 Imagery for Built-Up Mapping in Sub-Saharan Africa"</em>. In Press. 2018.</p> <p>The source code used to produce the output files is available on <a href="https://github.com/yannforget/landsat-sentinel-fusion">Github.</a></p

Soil settlement and uplift damage to architectural heritage structures in Belgium: country-scale results from an InSAR-based analysis

Soil movement may be induced by a wide variety of natural and anthropogenic causes, which are detectable in the local scale, but may influence the movement of the soil over vast geographical expanses. Space borne interferometric synthetic aperture radar (InSAR) measurements of ground movement provide a method for the remote sensing of soil settlement and uplift over wide geographic areas. Based on this settlement and uplift evaluation, the assessment of the potential damage to architectural heritage structures is possible. In this paper an interdisciplinary monitoring and analysis method is presented that processes satellite, cadastral, patrimonial and building geometry data, used for the calculation of settlement and uplift damage to architectural heritage structures in Belgium. It uses processed InSAR data for the determination of the soil movement profile around each case study, of which the typology is determined from patrimonial information databases and the geometry is calculated from digital elevation models. The impact on the historic structures is calculated from the determined soil movement profile based on various soil-structure interaction models for buildings. The Declercqresulting damage is presented in terms of a numerical index illustrating its severity according to different criteria. In this way the potential soil movement damage is quantified in a large number of buildings in an easily interpretable and user-friendly fashion. The processing of InSAR data collected over the previous 3 decades allows the determination of the progress of settlement- and uplift-induced damage in this time period. With the integration of newly acquired and more accurate data, the methodology will continue to produce results in the coming years, both for the evaluation of soil settlement and uplift in Belgium as for introducing related damage risk data for existing architectural heritage buildings. Results of the analysis chain are presented in terms of potential current damage for selected areas and buildings.The authors wish to acknowledge the funding received by BRAIN.be, BelSPO in support of the GEPATAR research project (“GEotechnical and Patrimonial Archives Toolbox for ARchitectural conservation in Belgium” BR/132/A6/Gepatar)Peer ReviewedPostprint (published version

Advanced processing of remotely sensed big data for cultural heritage conservation

Damage assessment, protection and preservation of built patrimony are a priority at national and local levels due to their importance to many cultural and economic aspects. This paper presents a methodology to estimate the potential damage caused by ground settlement for cultural heritage buildings using remotely sensed big data. Specifically, it presents a framework to assess the potential damage caused by ground settlement for masonry, infilled and bare frames structures using Persistent Scatterer Interferometric (PSI) measurements. The proposed solution advances the state-of-the-art by integrating big Earth observation (EO), environmental, architectural and historical data, for estimating the settlement induced damage to hundreds thousands of buildings. The fully automatic scheme was created within cloud computing environment for accelerating data transfer, processing and modeling and for improving the visualization of image-derived products.Peer ReviewedPostprint (author's final draft

Extending Data for Urban Health Decision-Making : a Menu of New and Potential Neighborhood-Level Health Determinants Datasets in LMICs

Area-level indicators of the determinants of health are vital to plan and monitor progress toward targets such as the Sustainable Development Goals (SDGs). Tools such as the Urban Health Equity Assessment and Response Tool (Urban HEART) and UN-Habitat Urban Inequities Surveys identify dozens of area-level health determinant indicators that decision-makers can use to track and attempt to address population health burdens and inequalities. However, questions remain as to how such indicators can be measured in a cost-effective way. Area-level health determinants reflect the physical, ecological, and social environments that influence health outcomes at community and societal levels, and include, among others, access to quality health facilities, safe parks, and other urban services, traffic density, level of informality, level of air pollution, degree of social exclusion, and extent of social networks. The identification and disaggregation of indicators is necessarily constrained by which datasets are available. Typically, these include household- and individual-level survey, census, administrative, and health system data. However, continued advancements in earth observation (EO), geographical information system (GIS), and mobile technologies mean that new sources of area-level health determinant indicators derived from satellite imagery, aggregated anonymized mobile phone data, and other sources are also becoming available at granular geographic scale. Not only can these data be used to directly calculate neighborhood- and city-level indicators, they can be combined with survey, census, administrative and health system data to model household- and individual-level outcomes (e.g., population density, household wealth) with tremendous detail and accuracy. WorldPop and the Demographic and Health Surveys (DHS) have already modeled dozens of household survey indicators at country or continental scales at resolutions of 1 × 1 km or even smaller. This paper aims to broaden perceptions about which types of datasets are available for health and development decision-making. For data scientists, we flag area-level indicators at city and sub-city scales identified by health decision-makers in the SDGs, Urban HEART, and other initiatives. For local health decision-makers, we summarize a menu of new datasets that can be feasibly generated from EO, mobile phone, and other spatial data—ideally to be made free and publicly available—and offer lay descriptions of some of the difficulties in generating such data products

Characterization of Cyclin E Expression in Multiple Myeloma and Its Functional Role in Seliciclib-Induced Apoptotic Cell Death

Multiple Myeloma (MM) is a lymphatic neoplasm characterized by clonal proliferation of malignant plasma cell that eventually develops resistance to chemotherapy. Drug resistance, differentiation block and increased survival of the MM tumor cells result from high genomic instability. Chromosomal translocations, the most common genomic alterations in MM, lead to dysregulation of cyclin D, a regulatory protein that governs the activation of key cell cycle regulator – cyclin dependent kinase (CDK). Genomic instability was reported to be affected by over expression of another CDK regulator - cyclin E (CCNE). This occurs early in tumorigenesis in various lymphatic malignancies including CLL, NHL and HL. We therefore sought to investigate the role of cyclin E in MM. CCNE1 expression was found to be heterogeneous in various MM cell lines (hMMCLs). Incubation of hMMCLs with seliciclib, a selective CDK-inhibitor, results in apoptosis which is accompanied by down regulation of MCL1 and p27. Ectopic over expression of CCNE1 resulted in reduced sensitivity of the MM tumor cells in comparison to the paternal cell line, whereas CCNE1 silencing with siRNA increased the cell sensitivity to seliciclib. Adhesion to FN of hMMCLs was prevented by seliciclib, eliminating adhesion–mediated drug resistance of MM cells. Combination of seliciclib with flavopiridol effectively reduced CCNE1 and CCND1 protein levels, increased subG1 apoptotic fraction and promoted MM cell death in BMSCs co-culture conditions, therefore over-coming stroma-mediated protection. We suggest that seliciclib may be considered as essential component of modern anti MM drug combination therapy

Report on the 2014 IEEE GRSS Data Fusion Contest: Multiresolution Fusion of Thermal Hyperspectral and VIS Data [Technical Committees]

none3mixedGabriele Moser;Devis Tuia;Michal ShimoniMoser, Gabriele; Tuia, Devis; Michal, Shimon