Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Felix Ndayisaba"'
Publikováno v:
IEEE Access, Vol 8, Pp 164268-164281 (2020)
Land surface temperature (LST) is an important indicator for assessing the surface urban heat island (SUHI) effect. This paper presents a novel approach to derive LST estimates by integrating machine learning algorithm and spatiotemporal fusion model
Externí odkaz:
https://doaj.org/article/c2ff6d1c2ea04db69d267801ab884bd3
Autor:
Alphonse Kayiranga, Felix Ndayisaba, Lamek Nahayo, Fidele Karamage, Jean Baptiste Nsengiyumva, Christophe Mupenzi, Enan Muhire Nyesheja
Publikováno v:
Geosciences, Vol 7, Iss 1, p 17 (2017)
This paper aimed to investigate the influence of climatic and topographic factors on the distribution of vegetation in the Virunga Volcanoes Massif using GIS and remote sensing techniques. The climatic variables considered were precipitation, Land Su
Externí odkaz:
https://doaj.org/article/a1ac007a5b9b41e2a02ae8fb95cfdfd1
Autor:
Fidele Karamage, Chi Zhang, Xia Fang, Tong Liu, Felix Ndayisaba, Lamek Nahayo, Alphonse Kayiranga, Jean Baptiste Nsengiyumva
Publikováno v:
Water, Vol 9, Iss 2, p 147 (2017)
Stormwater runoff poses serious environmental problems and public health issues in Rwanda, a tropical country that is increasingly suffering from severe floods, landslides, soil erosion and water pollution. Using the WetSpa Extension model, this stud
Externí odkaz:
https://doaj.org/article/142c33b53d9147fdb1293eeab5ddddfb
Autor:
Fidele Karamage, Hua Shao, Xi Chen, Felix Ndayisaba, Lamek Nahayo, Alphonse Kayiranga, James Kehinde Omifolaji, Tong Liu, Chi Zhang
Publikováno v:
Forests, Vol 7, Iss 11, p 281 (2016)
Deforestation and natural grassland conversion to agricultural land use constitute a major threat to soil and water conservation. This study aimed at assessing the status of land cover and land use (LCLU) in the Lake Kivu basin, and its related impac
Externí odkaz:
https://doaj.org/article/205be9ccb9394f56a763205a550b9968
Publikováno v:
Remote Sensing, Vol 8, Iss 5, p 379 (2016)
In this paper, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) is analyzed for the assessment of meteorological drought. The evaluation is conducted over China at 0.5° s
Externí odkaz:
https://doaj.org/article/03a27f2d7b4f482bb3205cd618001349
Publikováno v:
Remote Sensing, Vol 8, Iss 2, p 129 (2016)
Knowledge of current vegetation dynamics and an ability to make accurate predictions of ecological changes are essential for minimizing food scarcity in developing countries. Vegetation trends are also closely related to sustainability issues, such a
Externí odkaz:
https://doaj.org/article/bb317b169b404ec191613329d428d327
Autor:
Adil Dilawar, José Bofana, Fidele Karamage, Venus Tuankrua, Felix Ndayisaba, Alphonse Kayiranga, Huifang Zhang, Shaobo Sun, Yongyut Trisurat, Fei Wang, Baozhang Chen, Winny Nthangeni, Simon Measho
Publikováno v:
Journal of Geophysical Research: Biogeosciences. 125
Autor:
Tie Liu, Attia M. El-Tantawi, Philippe De Maeyer, Felix Ndayisaba, Anming Bao, Hao Guo, Guli Jiapaer
Publikováno v:
Journal of Hydrology. 564:1165-1178
Understanding the space-time structure and characteristics of drought is crucial for drought risk mitigation and forecasting efforts. In this paper, the drought events are identified by an improved 3-dimensional clustering algorithm. The 3-month Stan
Autor:
Tie Liu, Anming Bao, Felix Ndayisaba, Alishir Kurban, Philippe De Maeyer, Hao Guo, Liangliang Jiang, Guli Jiapaer
Publikováno v:
Science of The Total Environment. 624:1523-1538
In drought-prone regions like Central Asia, drought monitoring studies are paramount to provide valuable information for drought risk mitigation. In this paper, the spatiotemporal drought characteristics in Central Asia are analyzed from 1966 to 2015
Autor:
Simon Measho, Alphonse Kayiranga, Felix Ndayisaba, Winny Nthangeni, Huifang Zhang, Baozhang Chen
Publikováno v:
Science of The Total Environment. 798:149281
Ecosystem functioning and related risks could become compromised by climate change and severely affect livestock in different ways. Based on four climate indices (i.e., SPI, SPEI, PDSI and SEDI), livestock determinants and biogeochemical proxies, we