scholarly journals Characterization of the Temporal and Spatial Dynamics of the Dengue Epidemic in Northern Sri Lanka

2014 ◽  
Vol XL-8 ◽  
pp. 163-166
Author(s):  
S. Anno ◽  
K. Imaoka ◽  
T. Tadono ◽  
T. Igarashi ◽  
S. Sivaganesh ◽  
...  
Keyword(s):  
Sri Lanka ◽  
Land Cover ◽  
Spatial Association ◽  
Ecological Factors ◽  
Demographic Factors ◽  
Precipitable Water ◽  
Northern Region ◽  
Satellite Monitoring ◽  
Spatial And Temporal Patterns ◽  
Dengue Outbreaks

Dengue outbreaks are affected by biological, ecological, socio-economic and demographic factors that vary over time and space. These factors have been examined separately, with limited success, and still require clarification. The present study aimed to investigate the spatial and temporal relationships between these factors and dengue outbreaks in the northern region of Sri Lanka. Remote sensing (RS) data gathered from a plurality of satellites: TRMM TMI, Aqua AMSR-E, GCOM-W AMSR2, DMSP SSM/I, DMSP SSMIS, NOAA-19 AMSU, MetOp-A AMSU and GEO IR were used to develop an index comprising rainfall. Humidity (total precipitable water, or vertically integrated water vapor amount) and temperature (surface temperature) data were acquired from the JAXA Satellite Monitoring for Environmental Studies (JASMES) portal which were retrieved and processed from the Aqua/MODIS and Terra/MODIS data. RS data gathered by ALOS/AVNIR-2 were used to detect urbanization, and a digital land cover map was used to extract land cover information. Other data on relevant factors and dengue outbreaks were collected through institutions and extant databases. The analyzed RS data and databases were integrated into geographic information systems, enabling both spatial association analysis and spatial statistical analysis. Our findings show that the combination of ecological factors derived from RS data and socio-economic and demographic factors is suitable for predicting spatial and temporal patterns of dengue outbreaks.

scholarly journals Space-time clustering characteristics of dengue based on ecological, socio-economic and demographic factors in northern Sri Lanka

2015 ◽  
Vol 10 (2) ◽  
Author(s):  
Sumiko Anno ◽  
Keiji Imaoka ◽  
Takeo Tadono ◽  
Tamotsu Igarashi ◽  
Subramaniam Sivaganesh ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Sri Lanka ◽  
Land Cover ◽  
Demographic Factors ◽  
Space Time ◽  
Geographical Information ◽  
Temporal Association ◽  
Stable Model ◽  
The Right ◽  
Socioeconomic And Demographic Factors

The aim of the present study was to identify geographical areas and time periods of potential clusters of dengue cases based on ecological, socio-economic and demographic factors in northern Sri Lanka from January 2010 to December 2013. Remote sensing (RS) was used to develop an index comprising rainfall, humidity and temperature data. Remote sensing data gathered by the AVNIR-2 instrument onboard the ALOS satellite were used to detect urbanisation, and a digital land cover map was used to extract land cover information. Other data on relevant factors and dengue outbreaks were collected through institutions and extant databases. The analysed RS data and databases were integrated into a geographical information system (GIS) enabling space-time clustering analysis. Our results indicate that increases in the number of combinations of ecological, socio-economic and demographic factors that are present or above the average contribute to significantly high rates of space-time dengue clusters. The spatio-temporal association that consolidates the two kinds of associations into one can ensure a more stable model for forecasting. An integrated spatiotemporal prediction model at a smaller level using ecological, socioeconomic and demographic factors could lead to substantial improvements in dengue control and prevention by allocating the right resources to the appropriate places at the right time.

scholarly journals Geospatial Analysis of Extreme Weather Events in Nigeria (1985–2015) Using Self-Organizing Maps

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Adeoluwa Akande ◽  
Ana Cristina Costa ◽  
Jorge Mateu ◽  
Roberto Henriques
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Northern Region ◽  
Extreme Weather Events ◽  
Self Organizing Map ◽  
Spatial And Temporal Patterns ◽  
Self Organizing Maps ◽  
The North ◽  
Precipitation Regimes ◽  
Self Organizing

The explosion of data in the information age has provided an opportunity to explore the possibility of characterizing the climate patterns using data mining techniques. Nigeria has a unique tropical climate with two precipitation regimes: low precipitation in the north leading to aridity and desertification and high precipitation in parts of the southwest and southeast leading to large scale flooding. In this research, four indices have been used to characterize the intensity, frequency, and amount of rainfall over Nigeria. A type of Artificial Neural Network called the self-organizing map has been used to reduce the multiplicity of dimensions and produce four unique zones characterizing extreme precipitation conditions in Nigeria. This approach allowed for the assessment of spatial and temporal patterns in extreme precipitation in the last three decades. Precipitation properties in each cluster are discussed. The cluster closest to the Atlantic has high values of precipitation intensity, frequency, and duration, whereas the cluster closest to the Sahara Desert has low values. A significant increasing trend has been observed in the frequency of rainy days at the center of the northern region of Nigeria.

Stratigraphy and palaeoenvironmental interpretation of late Quaternary colluvial slope deposits in southern Africa

2021 ◽  
Author(s):  
J. Knight
Keyword(s):  
Southern Africa ◽  
Land Surface ◽  
Late Quaternary ◽  
Ecological Factors ◽  
Surface Instability ◽  
Sediment Supply ◽  
Spatial And Temporal Patterns ◽  
Catchment Scale ◽  
Accommodation Space ◽  
Slope Sediment

Abstract Slope and lowland sediment systems throughout southern Africa are dominated by the presence of colluvium with interbedded palaeosols and hardground duricrusts. These sediments correspond to phases of land surface instability and stability, respectively, during the late Quaternary. This study examines the stratigraphy and environmental interpretation of slope sediment records from specific sites in southern Africa for the period of marine isotope stages (MIS) 6 to 1 (~191 ka to present), informed by theoretical ideas of the dynamics of slope systems including sediment supply and accommodation space. Based on this analysis, phases of land surface instability and stability for the period MIS 6 to 1 are identified. The spatial and temporal patterns of land surface conditions are not a simple reflection of climate forcing, but rather reflect the workings of slope systems in response to climate in addition to the role of geologic, edaphic and ecological factors that operate within catchment-scale sediment systems. Considering these systems dynamics can yield a better understanding of the usefulness and limitations of slope sediment stratigraphies.

30 m Land Cover Dataset of Sri Lanka (2018)

GCdataPR ◽  
2021 ◽  
Author(s):  
Bo ZHONG ◽  
Longfei HU ◽  
Junjun WU ◽  
Aixia YANG
Keyword(s):  
Sri Lanka ◽  
Land Cover

ECOLOGICAL FACTORS OF THE NORTHERN REGION AND HIGHLAND ZONE INFLUENCE ON YIELD FORMATION OF EARLY MATURING POTATOES VARIETIES

1970 ◽  
pp. 35-39
Author(s):  
Е. V. Oves ◽  
Е. V. Nikolaeva
Keyword(s):  
Humus Content ◽  
Temperature Drop ◽  
Ecological Factors ◽  
Northern Region ◽  
Light Period ◽  
Average Weight ◽  
North Caucasus ◽  
The North ◽  
Early Maturing ◽  
June July

The aim of the research was to study the yield indicators of 36 early maturing potato varieties in the northern region (Arkhangelsk region) and the highlands of the North Caucasus (an altitude of 2500 m above sea level). The experimental work was carried out in 2015–2020. The characteristic features of the northern region are the light period (up to 21 hours in June – July), which contributes to an increase in the duration of the interphase periods of plant development, in the highlands – a short light period (14 hours), a sharp temperature drop in the daytime (15.1 – 25.8 °С) and night (7.8 – 15.2 ° C) hours, intense solar insolation. The peat-podzolic-gley soils of the northern region were characterized by a lower humus content (3.7%) and a high content of potassium (240 – 267 mg / kg) in comparison with the mountain meadow subalpine soils of the highlands (6.7% and 102 – 120 mg / kg, respectively). Potatoes were planted in early June and harvested in early September, 25 tubers of each variety according to the scheme 0.7×0.3 m, the area of the registration plot was 5.25 m². Using the methods of cluster and discriminant analyzes, the varieties were grouped and the most productive genotypes were identified by a set of indicators: the multiplication factor, plant productivity and the average tuber weight. In the northern region, the best varieties were Gulliver, Udacha, Krepysh, Solist, Leader, Darenka, Breeze, Red Lady, Riviera and Vineta, which formed from 8.1 to 11.4 tubers per plant with an average weight of 37.0 – 67.9 g and productivity 400 – 633 g. In the highlands, the most productive varieties were Gulliver, Yakutyanka, Yugana, Darenka, Leader, Breeze, Red Lady, Impala and Rosara, which formed from 11.8 to 19.8 tubers per plant with an average weight of  56.5 – 70, 6 g and productivity 830 – 1140 g.

scholarly journals Retrieval of water vapor using SSM/I and its relation with the onset of monsoon

2004 ◽  
Vol 22 (8) ◽  
pp. 3079-3083 ◽  
Author(s):  
R. P. Singh ◽  
S. Dey ◽  
A. K. Sahoo ◽  
M. Kafatos
Keyword(s):  
Water Vapor ◽  
Interannual Variability ◽  
Seasonal Variations ◽  
Indian Monsoon ◽  
Precipitable Water ◽  
Climatic Conditions ◽  
Satellite Monitoring ◽  
Onset Date ◽  
Microwave Imager ◽  
Onset Of Monsoon

Abstract. The seasonal variations and interannual variability of total precipitable water (TPW) deduced from the Special Sensor Microwave Imager (SSM/I) satellite over oceanic regions of the Indian sub-continent during the years between 1988 to 1998 show characteristic behavior. The weekly patterns of TPW are found to be closely related to the dynamics of the climatic conditions and the onset date of monsoon. The present results show that the satellite monitoring of TPW may prove as a good and reliable indicator in forecasting Indian monsoon.

scholarly journals Revealing two dynamic dengue epidemic clusters in Thailand

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Jue Tao Lim ◽  
Yiting Han ◽  
Borame Sue Lee Dickens ◽  
Esther Li Wen Choo ◽  
Lawrence Zheng Xiong Chew ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Land Cover ◽  
Regime Switching ◽  
Urban Population ◽  
Urban Land ◽  
Dengue Case ◽  
Urban Land Cover ◽  
Dengue Outbreaks ◽  
Spatio Temporal ◽  
Dengue Epidemic

Abstract Background Thailand is home to around 69 million individuals. Dengue is hyper-endemic and all 4 serotypes are in active circulation in the country. Dengue outbreaks occur almost annually within Thailand in at least one province but the spatio-temporal and environmental interface of these outbreaks has not been studied. Methods We develop Bayesian regime switching (BRS) models to characterize outbreaks, their persistence and infer their likelihood of occurrence across time for each administrative province where dengue case counts are collected. BRS was compared against two other classification tools and their agreement is assessed. We further examine how these spatio-temporal clusters of outbreak clusters arise by comparing reported dengue case counts, urban population, urban land cover, climate and flight volumes on the province level. Results Two dynamic dengue epidemic clusters were found nationally. One cluster consists of 47 provinces and is highly outbreak prone. Provinces with a large number of case counts, urban population, urban land cover and incoming flight passengers are associated to the epidemic prone cluster of dengue. Climate has an effect on determining the probability of outbreaks over time within provinces, but have less influence on whether provinces belong to the epidemic prone cluster. BRS found high agreement with other classification tools. Conclusions Importation and urbanization drives the risk of outbreaks across regions strongly. In provinces estimated to have high epidemic persistence, more resource allocation to vector control should be applied to those localities as heightened transmission counts are likely to occur over a longer period of time. Clustering of epidemic and non-epidemic prone areas also highlights the need for prioritization of resource allocation for disease mitigation over provinces in Thailand.

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