scholarly journals Changes in the Transmission Dynamic of Chikungunya Virus in Southeastern Senegal

Viruses ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 196 ◽  
Author(s):  
Abdourahmane Sow ◽  
Birgit Nikolay ◽  
Oumar Faye ◽  
Simon Cauchemez ◽  
Jorge Cano ◽  
...  
Keyword(s):  
Population Density ◽  
Rural Areas ◽  
Gold Mining ◽  
Chikungunya Virus ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Transmission Dynamic ◽  
Sylvatic Cycle ◽  
Mining Sites ◽  
Semivariogram Analysis

In Senegal, chikungunya virus (CHIKV) is maintained in a sylvatic cycle and causes sporadic cases or small outbreaks in rural areas. However, little is known about the influence of the environment on its transmission. To address the question, 120 villages were randomly selected in the Kedougou region of southeastern Senegal. In each selected village, 10 persons by randomly selected household were sampled and tested for specific anti-CHIKV IgG antibodies by ELISA. We investigated the association of CHIKV seroprevalence with environmental variables using logistic regression analysis and the spatial correlation of village seroprevalence based on semivariogram analysis. Fifty-four percent (51%–57%) of individuals sampled during the survey tested positive for CHIKV-specific IgG. CHIKV seroprevalence was significantly higher in populations living close to forested areas (Normalized Difference Vegetation Index (NDVI), Odds Ratio (OR) = 1.90 (1.42–2.57)), and was negatively associated with population density (OR = 0.76 (0.69–0.84)). In contrast, in gold mining sites where population density was >400 people per km2, seroprevalence peaked significantly among adults (46% (27%–67%)) compared to all other individuals (20% (12%–31%)). However, traditional gold mining activities significantly modify the transmission dynamic of CHIKV, leading to a potential increase of the risk of human exposition in the region.

scholarly journals Associations of Residential Greenness with Diabetes Mellitus in Chinese Uyghur Adults

2019 ◽  
Vol 16 (24) ◽  
pp. 5131
Author(s):  
Shujun Fan ◽  
Zhenxiang Xue ◽  
Jun Yuan ◽  
Ziyan Zhou ◽  
Yuzhong Wang ◽  
...  
Keyword(s):  
Rural Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Fasting Glucose ◽  
Cross Sectional Study ◽  
Diabetes Prevalence ◽  
Protective Effects ◽  
Cross Sectional ◽  
Glucose Levels ◽  
Lower Odds Ratio

Greenness exposure is nominated as a potential beneficial factor for health, but evidence is limited on its diabetes effects. We conducted a cross-sectional study between May and September 2016 in rural areas of northwestern China, including 4670 Uyghur adults, to explore the associations between residential greenness and fasting glucose levels and diabetes prevalence. Fasting glucose levels were determined, and information on covariates was collected by questionnaire. Normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI) were calculated to assess greenness levels. Generalized linear mixed models were applied to evaluate the associations of greenness with fasting glucose levels and diabetes prevalence. The prevalence of diabetes was 11.6%. We found that living in rural areas characterized by increased amounts of greenness was associated with reduced diabetes prevalence (e.g., NDVI1000m: OR, 0.92; 95% CI, 0.86, 0.99). Stratified analyses showed that the protective effects of greenness on diabetes prevalence were found only in women (NDVI1000m: OR, 0.90; 95% CI, 0.82, 0.99). However, none of the interaction was statistically significant. Our study suggests that greater residential greenness levels were associated with a lower odds ratio of diabetes prevalence in Xinjiang Uyghur adults. Further well-designed longitudinal studies are needed to confirm our findings.

scholarly journals Comparasion of NDBI and NDVI as Indicators of Surface Urban Heat Island Effect in Landsat 8 Imagery: A Case Study of Iasi

2017 ◽  
Vol 11 (2) ◽  
pp. 141-150 ◽  
Author(s):  
Paul Macarof ◽  
Florian Statescu
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Heat Island ◽  
Sensing Technology ◽  
Urban Heat ◽  
Surface Urban Heat Island

Abstract This study compares the normalized difference built-up index (NDBI) and normalized difference vegetation index (NDVI) as indicators of surface urban heat island effects in Landsat-8 OLI imagery by investigating the relationships between the land surface temperature (LST), NDBI and NDVI. The urban heat island (UHI) represents the phenomenon of higher atmospheric and surface temperatures occurring in urban area or metropolitan area than in the surrounding rural areas due to urbanization. With the development of remote sensing technology, it has become an important approach to urban heat island research. Landsat data were used to estimate the LST, NDBI and NDVI from four seasons for Iasi municipality area. This paper indicates than there is a strong linear relationship between LST and NDBI, whereas the relationship between LST and NDVI varies by season. This paper suggests, NDBI is an accurate indicator of surface UHI effects and can be used as a complementary metric to the traditionally applied NDVI.

scholarly journals Fractional Vegetation Cover Change Detection In Megacities Using Landsat Time-Series Images: A Case Study Of Hanoi City (Vietnam) During 1986-2019

2019 ◽  
Vol 12 (4) ◽  
pp. 175-187
Author(s):  
Thanh Tien Nguyen
Keyword(s):  
Rural Areas ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Classification Method ◽  
Landsat 8 ◽  
Landsat Images ◽  
Fractional Vegetation Cover ◽  
Multi Temporal

The objective of the study is to assess changes of fractional vegetation cover (FVC) in Hanoi megacity in period of 33 years from 1986 to 2016 based on a two endmember spectral mixture analysis (SMA) model using multi-spectral and multi-temporal Landsat-5 TM and -8 OLI images. Landsat TM/OLI images were first radiometrically corrected. FVC was then estimated by means of a combination of Normalized Difference Vegetation Index (NDVI) and classification method. The estimated FVC results were validated using the field survey data. The assessment of FVC changes was finally carried out using spatial analysis in GIS. A case study from Hanoi city shows that: (i) the proposed approach performed well in estimating the FVC retrieved from the Landsat-8 OLI data and had good consistency with in situ measurements with the statistically achieved root mean square error (RMSE) of 0.02 (R 2 =0.935); (ii) total FVC area of 321.6 km 2 (accounting for 9.61% of the total area) was slightly reduced in the center of the city, whereas, FVC increased markedly with an area of 1163.6 km 2 (accounting for 34.78% of the total area) in suburban and rural areas. The results from this study demonstrate the combination of NDVI and classification method using Landsat images are promising for assessing FVC change in megacities.

scholarly journals ANÁLISE MULTITEMPORAL DO CLIMA URBANO EM PALMAS, ESTADO DO TOCANTINS –BRASIL

2020 ◽  
Vol 12 (2) ◽  
pp. 01-14
Author(s):  
Felipe David Georges Gomes ◽  
Isabela Marega Rigolin Fuzeto ◽  
Renata Pereira Prates
Keyword(s):  
Water Balance ◽  
Rural Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Urban Climate ◽  
Life Quality ◽  
Urban Heat Islands ◽  
Small Surface ◽  
Heat Islands ◽  
Temporal Space

The urban climate changes, caused by intense urban densities, result in loss life quality. Therefore, it becomes increasingly necessary to know the dynamics climatic of a given region in search of strategies to promote socio-environmental quality. The present work aimed to analyze the temporal space variations of the urban climate and the implications of water availability and NDVI in urban heat islands. For this purpose, we adopt as case study the municipality of Palmas - Tocantins. In a first moment, the climatological characterization of the study area through the climatological water balance proposed by Thornthwaite and Mather (1955) was carried out. Then the terrestrial surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) were calculated by means of multispectral images of the LANDSAT7 and LANDSAT8 satellites and GIS software. From the climatic water balance, it was possible to verify indices characteristic of the tropical climate as well as the climatic dynamics of the region. We observed small surface heat islands diagnosed by means of satellite imagery in the urban environment with a magnitude of up to 15 ° Celsius in relation to the nearby rural areas, especially in the drier periods. We also confirmed the importance of green areas in the mitigation of land temperatures.

scholarly journals MODEL SPASIAL KERUSAKAN LAHAN DAN PENCEMARAN AIR AKIBAT KEGIATAN PERTAMBANGAN EMAS TANPA IZIN DI DAERAH ALIRAN SUNGAI RAYA, KALIMANTAN BARAT

2015 ◽  
Vol 17 (2) ◽  
pp. 47
Author(s):  
Romiyanto Romiyanto ◽  
Baba Barus ◽  
Untung Sudadi
Keyword(s):  
Water Pollution ◽  
Land Degradation ◽  
Spatial Model ◽  
Gold Mining ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Nutrient Deficiency ◽  
Distribution Analysis ◽  
Mining Activities ◽  
Degraded Area

<p>Illegal gold mining activities create mine pits, taillings, stressed vegetation and unvegetated land. The aims of this study were to identify and to develop spatial model of land degradation and water pollution caused by illegal gold mining activities in Raya watershed, West Kalimantan. The spatial land degradation model was developed by multiplication the score of mine age and type of mine tailings, while the scores for water pollution was based on the results of spatial distribution analysis of the water’s total dissolved solids (TDS) and Hg concentration levels in Lake Serantangan. Vegetations of the degraded area showed nutrient deficiency and toxicity symptoms. Based on the NDVI (normalized difference vegetation index), the degraded area generated a value range of 0.1-0.6. Mine land in the study area were classified as rather degraded (29.33%), degraded (28.70%), and severe degraded (41.97% of the total 4,551 ha area). While, 65.87% or 83 ha of the Lake Serantangan area was classified as severely polluted based on the water’s concentration of Hg and TDS. The accuracy of the spatial model developed was 88.30 and 82.57% for land degradation and water pollution, respectively.</p><p><br />Keywords: Illegal gold mining, land degradation, spatial model, water pollution</p>

Measuring the Loss of Arable and Rural Lands on the Maltese Islands through Satellite Images

2020 ◽  
Vol 4 (1) ◽  
pp. 52-68
Author(s):  
Steve Zerafa
Keyword(s):  
Land Use ◽  
Urban Growth ◽  
Rural Areas ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Land ◽  
Water Flooding ◽  
Vegetation Density ◽  
Maltese Islands

The Maltese Islands went through a rapid urban growth and increase in population. Such trends normally contribute to the loss of agricultural land, trees, soil and rural land. Urban growth is often responsible for a variety of urban environmental issues: Decreased air quality, increased runoff and subsequent water flooding, increased local temperature, losses of agricultural land and deterioration of water table. During such times, it is crucial to monitor the use of land resources, understand the changes of biodiversity and ecosystems, and ensure the long-term productive potential of soil, land and plants. Although the islands are small in size, such a monitoring task is quite challenging due to the effects of weather on the islands, the dynamics of the vegetation, and the continued activities of locals all across the islands. In this context, geospatial technologies and remote sensing techniques could serve as an essential tool for the analysis of land use and detecting changes occurring within the ecosystems. This study attempts to assess the land use change detection at a pixel level and highlight the vegetation density, and workout the loss of vegetative in arable and rural areas across the islands during the years 2015 to 2019. The created models are derived from the observation of the Normalized Difference Vegetation Index (NDVI) as obtained by Sentinel-2 satellite images. The results showed that from Spring 2017 to Spring 2019, the islands experienced a 2.45km² reduction of green vegetation colour. Over a period of 4 years the islands experienced a 1.25km² erosion of arable and rural lands. Among other reasons, this loss is the result of more development and the extension of the urbanization zones.

scholarly journals Assessment of the impact of ungoverned spaces on insurgency in Borno State, Nigeria

2021 ◽  
Vol 13 (2) ◽  
Author(s):  
Sylvanus Helda Bernard ◽  
Mwanret Gideon Daful
Keyword(s):  
Population Density ◽  
Satellite Data ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Population Data ◽  
Information Criterion ◽  
The State ◽  
High Incidence ◽  
The Impact ◽  
Vegetal Cover

This study examines the relationship between ungoverned spaces and insurgency in the Borno State, Nigeria. The aim is to understand the influence of geographical variables on the activities of insurgence. The study used satellite data, population data and data on insurgency attack in the study area. Normalized Difference Vegetation Index, percentage rise in slope analysis and reclassification were used for the satellite data processing.  Geographically Weighted Regression (GWR) models was employed for data analysis. The findings revealed that LGAs in the central and the southern parts of the state recorded the highest number of insurgency attacks. The central and far northern part of the state has more vegetal cover, which has influenced the high incidence of insurgency attack observed. In addition, the very high incidence of insurgency attack (145) observed in Gwoza LGA, is largely attributed to the presence of the Gwoza Mountain, which is one of the main strong holds of the insurgents in Borno State. The GWR analysis reveals that the performance of the model with the population density was much better than the other variables with a corrected Akaike Information Criterion (AICc) value of 273.15, R-Squared values of 0.0323, 0.0224, 0.0203 and 0.8901 for the undulating terrain, vegetation, combination of vegetation and undulating terrain, and population density respectively. Thus, the study concludes that vegetal cover and population density have more influence on insurgency attack in the study area. Hence, the need for policy makers and security establishments to properly monitor the forested areas.

scholarly journals What built environmental factors mitigate decline in older adults’ step count? Three-year longitudinal study with a large sample in Yokohama, Japan

2020 ◽  
Author(s):  
Kimihiro Hino ◽  
Hiroyuki Usui ◽  
Masamichi Hanazato
Keyword(s):  
Older Adults ◽  
Land Use ◽  
Population Density ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Average Distance ◽  
Step Count ◽  
Multilevel Regression ◽  
Railway Station ◽  
Intersection Density

Abstract Background: Neighborhood walkability achieved through land-use and transport planning is an important determinant of physical activity, especially for older adults who spend more time in their neighborhoods than do other ages. This three-year study aimed to examine the longitudinal association between the change in the step count of older adults and the built environment (BE) around their homes in Yokohama, Japan. Methods: We analyzed pedometer data in March 2016 and March 2019 that was acquired from 21 557 older adults aged 65–79 years at baseline, who lived in 758 neighborhoods in Yokohama city who participated in the Yokohama Walking Point Program (YWPP). Neighborhoods were classified into quartiles for each of the six built environmental variables (population density, intersection density, the proportion of commercial land use, normalized difference vegetation index (NDVI), the average distance to the nearest railway station, and average distance to the nearest bus stop), which were selected based on previous studies. Using multilevel regression analysis, we examined the connection between the BE variables, baseline step count, and the change in step count during the three years. Results: Higher population density, lower intersection density, and the second shortest quartile of the average distance to the nearest railway station were associated with a higher baseline step count. A lower intersection density and shorter average distance to the nearest railway station were associated with a smaller decline. The lowest quartile of population density was reversely associated. Additionally, female and older groups recorded a lower baseline step count and a larger decline. A higher baseline step count was associated with a larger decline, as well. Conclusions: The neighborhood BEs (i.e., population density, intersection density, and average distance to the nearest railway station) of older adults were not only associated with their step count at a certain time point, but also widened the disparity of the step count over the three years. Urban planners and designers should place emphasis on interdisciplinary collaboration with health promotion professionals in order to create compact cities centered around railway stations that are protected from traffic, so older adults feel safe.

scholarly journals Time-Series Assessment of Camp-Type Artisanal and Small-Scale Gold Mining Sectors with Large Influxes of Miners Using LANDSAT Imagery

2021 ◽  
Vol 18 (18) ◽  
pp. 9441
Author(s):  
Satomi Kimijima ◽  
Masayuki Sakakibara ◽  
Masahiko Nagai ◽  
Nurfitri Gafur
Keyword(s):  
Time Series ◽  
Gold Mining ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat Imagery ◽  
Market Price ◽  
Fold Increase ◽  
Google Earth ◽  
Small Scale ◽  
Field Investigations

Mining sites development have had a significant impact on local socioeconomic conditions, the environment, and sustainability. However, the transformation of camp-type artisanal and small-scale gold mining (ASGM) sites with large influxes of miners from different regions has not been properly evaluated, owing to the closed nature of the ASGM sector. Here, we use remote sensing imagery and field investigations to assess ASGM sites with large influxes of miners living in mining camps in Bone Bolango Regency, Gorontalo Province, Indonesia, in 1995–2020. Built-up areas were identified as indicators of transformation of camp-type ASGM sites, using the Normalized Difference Vegetation Index, from the time series of images obtained using Google Earth Engine, then correlated with the prevalent gold market price. An 18.6-fold increase in built-up areas in mining camps was observed in 2020 compared with 1995, which correlated with increases in local gold prices. Field investigations showed that miner influx also increased after increases in gold prices. These findings extend our understanding of the rate and scale of development in the closed ASGM sector and the driving factors behind these changes. Our results provide significant insight into the potential rates and levels of socio-environmental pollution at local and community levels.

scholarly journals What Are the Driving Forces of Urban CO2 Emissions in China? A Refined Scale Analysis between National and Urban Agglomeration Levels

2019 ◽  
Vol 16 (19) ◽  
pp. 3692 ◽  
Author(s):  
Wang ◽  
Liu ◽  
Shi
Keyword(s):  
Population Density ◽  
Co2 Emissions ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Driving Forces ◽  
National Level ◽  
Probit Model ◽  
Environmental Problems ◽  
Urban Agglomeration ◽  
Temperature And Precipitation

With the advancement of society and the economy, environmental problems have increasingly emerged, in particular, problems with urban CO2 emissions. Exploring the driving forces of urban CO2 emissions is necessary to gain a better understanding of the spatial patterns, processes, and mechanisms of environmental problems. Thus, the purpose of this study was to quantify the driving forces of urban CO2 emissions from 2000 to 2015 in China, including explicit consideration of a comparative analysis between national and urban agglomeration levels. Urban CO2 emissions with a 1-km spatial resolution were extracted for built-up areas based on the anthropogenic carbon dioxide (ODIAC) fossil fuel emission dataset. Six factors, namely precipitation, slope, temperature, population density, normalized difference vegetation index (NDVI), and gross domestic product (GDP), were selected to investigate the driving forces of urban CO2 emissions in China. Then, a probit model was applied to examine the effects of potential factors on urban CO2 emissions. The results revealed that the population, GDP, and NDVI were all positive driving forces, but that temperature and precipitation had negative effects on urban CO2 emissions at the national level. In the middle and south Liaoning urban agglomeration (MSL), the slope, population density, NDVI, and GDP were significant influencing factors. In the Pearl River Delta urban agglomeration (PRD), six factors had significant impacts on urban CO2 emissions, all of which were positive except for slope, which was a negative factor. Due to China’s hierarchical administrative levels, the model results suggest that regardless of which level is adopted, the impacts of the driving factors on urban CO2 emissions are quite different at the national compared to the urban agglomeration level. The degrees of influence of most factors at the national level were lower than those of factors at the urban agglomeration level. Based on an analysis of the forces driving urban CO2 emissions, we propose that it is necessary that the environment play a guiding role while regions formulate policies which are suitable for emission reductions according to their distinct characteristics.

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