Saleh M.,Islamic University of Lebanon |
Faour G.,National Center for Remote Sensing
Proceedings of the 18th Mediterranean Electrotechnical Conference: Intelligent and Efficient Technologies and Services for the Citizen, MELECON 2016 | Year: 2016
Snow Cover Area monitoring is an important factor in studies of global climate change, regional water balance and soil moisture. Recently, the usage of remote sensing techniques has flourished. In fact, remote sensing data provides timely adequate snow cover information for large areas. While the National Center for Remote Sensing in Lebanon (CNRS) has recently established an operational monitoring room for natural resources and natural disasters, this paper presents the implementation of a fully automated snow cover monitoring system based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images. The system uses snow products from EOS Terra, and Aqua satellites to monitor the Snow Cover of Lebanon during the snow season (i.e. November-April). The importance of this project lies in its daily and fully automated process of acquiring, processing, storing and displaying statistics of the snow covered areas in Lebanon. Applying a custom algorithm based on combining Terra and Aqua snow products will reduce cloud contamination. © 2016 IEEE.
Fadel A.,University Paris Est Creteil |
Fadel A.,National Center for Remote Sensing |
Atoui A.,Laboratory of Microorganisms and Food Irradiation |
Lemaire B.J.,University Paris Est Creteil |
And 3 more authors.
Environmental Monitoring and Assessment | Year: 2015
Eutrophication and harmful algal blooms have become a worldwide environmental problem. Understanding the mechanisms and processes that control algal blooms is of great concern. The phytoplankton community of Karaoun Reservoir, the largest water body in Lebanon, is poorly studied, as in many freshwater bodies around the Mediterranean Sea. Sampling campaigns were conducted semi-monthly between May 2012 and August 2013 to assess the dynamics of its phytoplankton community in response to changes in physical-chemical and hydrological conditions. Karaoun Reservoir is a monomictic waterbody and strongly stratifies between May and August. Changes in its phytoplankton community were found to be a result of the interplay between water temperature, stratification, irradiance, nutrient availability and water level. Thermal stratification established in spring reduced the growth of diatoms and resulted in their replacement by green algae species when nutrient availability was high and water temperatures lower than 22 °C. At water temperature higher than 25 °C and low nutrient concentrations in summer, blooms of the cyanobacterium Microcystis aeruginosa occurred. Despite different growth conditions in other lakes and reservoir, cyanobacterium Aphanizomenon ovalisporum dominated at temperatures lower than 23 °C in weakly stratified conditions in early autumn and dinoflagellate Ceratium hirundinella dominated in mixed conditions, at low light intensity and a water temperature of 19 °C in late autumn. We believe that the information presented in this paper will increase the knowledge about phytoplankton dynamics in the Mediterranean region and contribute to a safer usage of reservoir waters. © 2015, Springer International Publishing Switzerland.
Awad M.,National Center for Remote Sensing
Ecological Informatics | Year: 2014
The use of satellite hyperspectral images has improved the extraction of information compared to multispectral images. Although designed as a technical demonstration for land applications, Hyperion satellite hyperspectral images are used to estimate sea water parameters in the coastal area. A combination of turbid river inputs, as well as the open sea flushing, determines the quality of the sea water in the coastal area and the status of its environment. In addition, the existence of different source of pollution adds to the complexity of the coastal sea water analysis. The field campaigns to retrieve sea water parameters provided by the past completed projects were coincident with acquisition of the Hyperion image covering the pilot area. A robust method based on a supervised Feed-Forward Back-Propagation Artificial Neural Network (ANN-BP) algorithm is applied to retrieve the concentration of chlorophyll-a from hyperspectral image. In addition, Hyperion images are used to show the variation of chlorophyll-a during two different periods of time. The variation is due to many manmade environmental disasters such as oil spill and continuous discharge of chemical and solid wastes. The research proves that the new method based on ANN has improved the mathematical regression methods to a coefficient of determination almost equal 1 compared to about 0.4 for the methods not based on ANN-BP. © 2014 Elsevier B.V.
Arodudu O.,Leibniz Center for Agricultural Landscape Research |
Ibrahim E.,National Center for Remote Sensing |
Voinov A.,University of Twente |
Van Duren I.,University of Twente
Ecological Indicators | Year: 2014
The production of bioenergy is dependent on the supply of biomass. Biomass production for bioenergy may cause large land use conversions, impact agricultural production, food prices, forest conservation, etc. The best solution is to use biomass that does not have agricultural or ecological value. Some of such unconventional sources of biomass are found within urban spaces. We employed Geographic Information System (GIS) and quantitative Life Cycle Assessment (LCA) methodologies to identify and estimate bioenergy potential of green roofs and other bioenergy options within urban areas. Net Energy Gain (NEG) and Energy Return on Energy Invested (EROEI) were used as indicators to assess the bioenergy potential of urban spaces within the Overijssel province of the Netherlands as a case study. Data regarding suitable areas were geometrically extracted from available GIS datasets, and used to estimate the biomass/bioenergy potential of different species with different yields per hectare, growing under different environmental conditions. We found that potential net-energy gain from built-up areas can meet 0.6-7.7% of the 2030 renewable energy targets of the province without conflicting with socio-ecological concerns, while also improving human habitat. © 2014 Elsevier Ltd. All rights reserved.
Adigun A.B.,Swiss Tropical and Public Health Institute |
Adigun A.B.,University of Basel |
Adigun A.B.,National Center for Remote Sensing |
Gajere E.N.,National Center for Remote Sensing |
And 3 more authors.
Malaria Journal | Year: 2015
Background: In 2010, the National Malaria Control Programme with the support of Roll Back Malaria partners implemented a nationally representative Malaria Indicator Survey (MIS), which assembled malaria burden and control intervention related data. The MIS data were analysed to produce a contemporary smooth map of malaria risk and evaluate the control interventions effects on parasitaemia risk after controlling for environmental/climatic, demographic and socioeconomic characteristics. Methods: A Bayesian geostatistical logistic regression model was fitted on the observed parasitological prevalence data. Important environmental/climatic risk factors of parasitaemia were identified by applying Bayesian variable selection within geostatistical model. The best model was employed to predict the disease risk over a grid of 4 km2 resolution. Validation was carried out to assess model predictive performance. Various measures of control intervention coverage were derived to estimate the effects of interventions on parasitaemia risk after adjusting for environmental, socioeconomic and demographic factors. Results: Normalized difference vegetation index and rainfall were identified as important environmental/climatic predictors of malaria risk. The population adjusted risk estimates ranges from 6.46% in Lagos state to 43.33% in Borno. Interventions appear to not have important effect on malaria risk. The odds of parasitaemia appears to be on downward trend with improved socioeconomic status and living in rural areas increases the odds of testing positive to malaria parasites. Older children also have elevated risk of malaria infection. Conclusions: The produced maps and estimates of parasitaemic children give an important synoptic view of current parasite prevalence in the country. Control activities will find it a useful tool in identifying priority areas for intervention. © 2015 Adigun et al.; licensee BioMed Central.