Your search found 3 records
1 Chen, F.; Chen, X.; Van de Voorde, T.; Roberts, D.; Jiang, H.; Xu, W. 2020. Open water detection in urban environments using high spatial resolution remote sensing imagery. Remote Sensing of Environment, 242:111706. (Online first) [doi: https://doi.org/10.1016/j.rse.2020.111706]
Surface water ; Observation ; Mapping ; Remote sensing ; Urban environment ; Satellite imagery ; Multispectral imagery ; Land cover / Switzerland / Belgium / USA / Baden / Brussels / Santa Barbara
(Location: IWMI HQ Call no: e-copy only Record No: H049685)
(5.25 MB)
Commonly applied water indices such as the normalized difference water index (NDWI) and the modified normalized difference water index (MNDWI) were originally conceived for medium spatial resolution remote sensing images. In recent decades, high spatial resolution imagery has shown considerable potential for deriving accurate land cover maps of urban environments. Applying traditional water indices directly on this type of data, however, leads to severe misclassifications as there are many materials in urban areas that are confused with water. Furthermore, threshold parameters must generally be fine-tuned to obtain optimal results. In this paper, we propose a new open surface water detection method for urbanized areas. We suggest using inequality constraints as well as physical magnitude constraints to identify water from urban scenes. Our experimental results on spectral libraries and real high spatial resolution remote sensing images demonstrate that by using a set of suggested fixed threshold values, the proposed method outperforms or obtains comparable results with algorithms based on traditional water indices that need to be fine-tuned to obtain optimal results. When applied to the ASTER and ECOSTRESS spectral libraries, our method identified 3677 out of 3695 non-water spectra. By contrast, NDWI and MNDWI only identified 2934 and 2918 spectra. Results on three real hyperspectral images demonstrated that the proposed method successfully identified normal water bodies, meso-eutrophic water bodies, and most of the muddy water bodies in the scenes with F-measure values of 0.91, 0.94 and 0.82 for the three scenes. For surface glint and hyper-eutrophic water, our method was not as effective as could be expected. We observed that the commonly used threshold value of 0 for NDWI and MNDWI results in greater levels of confusion, with F-measures of 0.83, 0.64 and 0.64 (NDWI) and 0.77, 0.63 and 0.59 (MNDWI). The proposed method also achieves higher precision than the untuned NDWI and MNDWI with the same recall values. Next to numerical performance, the proposed method is also physically justified, easy-to implement, and computationally efficient, which suggests that it has potential to be applied in large scale water detection problem.
2 Nicol, Alan; Abdoubaetova, A.; Wolters, A.; Kharel, A.; Murzakolova, A.; Gebreyesus, A.; Lucasenco, E.; Chen, F.; Sugden, F.; Sterly, H.; Kuznetsova, I.; Masotti, M.; Vittuari, M.; Dessalegn, Mengistu; Aderghal, M.; Phalkey, N.; Sakdapolrak, P.; Mollinga, P.; Mogilevskii, R.; Naruchaikusol, S. 2020. Between a rock and a hard place: early experience of migration challenges under the Covid-19 pandemic. Colombo, Sri Lanka: International Water Management Institute (IWMI). 22p. (IWMI Working Paper 195) [doi: https://doi.org/10.5337/2020.216]
Migration ; COVID-19 ; Pandemics ; Labour market ; Migrant labour ; Unemployment ; Livelihoods ; Health hazards ; Income ; Remittances ; Economic activities ; Poverty ; Social inequalities ; Food supply ; Households ; Rural areas ; State intervention ; Governance ; Quarantine ; Travel restrictions ; Border closures ; Policies ; Assessment ; Uncertainty / China / Ethiopia / Kyrgyzstan / Republic of Moldova / Morocco / Nepal / Thailand
(Location: IWMI HQ Call no: IWMI Record No: H050125)
(1.92 MB)
This working paper was produced under the European Union Horizon 2020 funded AGRUMIG project and traces the impact of Covid-19 on migration trends in seven project countries – China, Ethiopia, Kyrgyzstan, Moldova, Morocco, Nepal and Thailand.
The context of global migration has changed dramatically due to the coronavirus pandemic. Both within and between countries there has been a substantial curtailment of movement. As a result of multiple lockdowns, economic activity has severely declined and labor markets have ground to a halt, with mass unemployment in industrialized economies looming on the horizon. For both migrant hosting and origin countries – some are substantially both – this poses a set of complex development challenges.
Partners of the AGRUMIG project undertook a rapid review of impacts across project countries, exploring the impacts on rural households but also identifying the persistent desire to migrate in spite of restrictions.
The context of global migration has changed dramatically due to the coronavirus pandemic. Both within and between countries there has been a substantial curtailment of movement. As a result of multiple lockdowns, economic activity has severely declined and labor markets have ground to a halt, with mass unemployment in industrialized economies looming on the horizon. For both migrant hosting and origin countries – some are substantially both – this poses a set of complex development challenges.
Partners of the AGRUMIG project undertook a rapid review of impacts across project countries, exploring the impacts on rural households but also identifying the persistent desire to migrate in spite of restrictions.
3 Qian, Y.; Chakraborty, T. C.; Li, J.; Li, D.; He, C.; Sarangi, C.; Chen, F.; Yang, X.; Leung, L. R. 2022. Urbanization impact on regional climate and extreme weather: current understanding, uncertainties, and future research directions. Advances in Atmospheric Sciences, 39(6):819-860. [doi: https://doi.org/10.1007/s00376-021-1371-9]
Climate change ; Extreme weather events ; Urbanization ; Uncertainty ; Precipitation ; Air temperature ; Air pollution ; Air quality ; Towns ; Satellite observation ; Meteorological stations ; Heat stress ; Surface temperature ; Vegetation ; Land cover ; Land use ; Boundary layers ; Turbulence ; Models / China
(Location: IWMI HQ Call no: e-copy only Record No: H051076)
https://link.springer.com/content/pdf/10.1007/s00376-021-1371-9.pdf
https://vlibrary.iwmi.org/pdf/H051076.pdf
https://vlibrary.iwmi.org/pdf/H051076.pdf
(3.73 MB) (3.73 MB)
Urban environments lie at the confluence of social, cultural, and economic activities and have unique biophysical characteristics due to continued infrastructure development that generally replaces natural landscapes with built-up structures. The vast majority of studies on urban perturbation of local weather and climate have been centered on the urban heat island (UHI) effect, referring to the higher temperature in cities compared to their natural surroundings. Besides the UHI effect and heat waves, urbanization also impacts atmospheric moisture, wind, boundary layer structure, cloud formation, dispersion of air pollutants, precipitation, and storms. In this review article, we first introduce the datasets and methods used in studying urban areas and their impacts through both observation and modeling and then summarize the scientific insights on the impact of urbanization on various aspects of regional climate and extreme weather based on more than 500 studies. We also highlight the major research gaps and challenges in our understanding of the impacts of urbanization and provide our perspective and recommendations for future research priorities and directions.
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