Arid
DOI10.1007/s10393-017-1307-0
Evaluating Efficacy of Landsat-Derived Environmental Covariates for Predicting Malaria Distribution in Rural Villages of Vhembe District, South Africa
Malahlela, Oupa E.1,2; Olwoch, Jane M.1,3; Adjorlolo, Clement2
通讯作者Malahlela, Oupa E.
来源期刊ECOHEALTH
ISSN1612-9202
EISSN1612-9210
出版年2018
卷号15期号:1页码:23-40
英文摘要

Malaria in South Africa is still a problem despite existing efforts to eradicate the disease. In the Vhembe District Municipality, malaria prevalence is still high, with a mean incidence rate of 328.2 per 100,0000 persons/year. This study aimed at evaluating environmental covariates, such as vegetation moisture and vegetation greenness, associated with malaria vector distribution for better predictability towards rapid and efficient disease management and control. The 2005 malaria incidence data combined with Landsat 5 ETM were used in this study. A total of nine remotely sensed covariates were derived, while pseudo-absences in the ratio of 1: 2 (presence/absence) were generated at buffer distances of 0.5-20 km from known presence locations. A stepwise logistic regression model was applied to analyse the spatial distribution of malaria in the area. A buffer distance of 10 km yielded the highest classification accuracy of 82% at a threshold of 0.9. This model was significant (q < 0.05) and yielded a deviance (D 2) of 36%. The significantly positive relationship (q < 0.05) between the soil-adjusted vegetation index and malaria distribution at all buffer distances suggests that malaria vector (Anopheles arabiensis) prefer productive and greener vegetation. The significant negative relationship between water/moisture index (a1 index) and malaria distribution in buffer distances of 0.5, 10, and 20 km suggest that malaria distribution increases with a decrease in shortwave reflectance signal. The study has shown that suitable habitats of malaria vectors are generally found within a radius of 10 km in semi-arid environments, and this insight can be useful to aid efforts aimed at putting in place evidence-based preventative measures against malaria infections. Furthermore, this result is important in understanding malaria dynamics under the current climate and environmental changes. The study has also demonstrated the use of Landsat data and the ability to extract environmental conditions which favour the distribution of malaria vector (An. arabiensis) such as the canopy moisture content in vegetation, which serves as a surrogate for rainfall.


英文关键词Vhembe District Municipality Malaria SAVI Landsat 5
类型Article
语种英语
国家South Africa ; Namibia
收录类别SCI-E
WOS记录号WOS:000435527600004
WOS关键词DIFFERENCE WATER INDEX ; SPECTRAL REFLECTANCE ; DISTRIBUTION MODEL ; VEGETATION INDEX ; PSEUDO-ABSENCES ; TRANSMISSION ; SELECTION ; FOREST ; RISK ; NDWI
WOS类目Biodiversity Conservation ; Ecology ; Environmental Sciences
WOS研究方向Biodiversity & Conservation ; Environmental Sciences & Ecology
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/208670
作者单位1.Univ Pretoria, Dept Geog Geoinformat & Meteorol, Private Bag X20, ZA-0028 Hatfield, South Africa;
2.South African Natl Space Agcy SANSA, Earth Observat Directorate, ZA-0001 Pretoria, South Africa;
3.Southern African Sci Serv Ctr Climate Change & Ad, Windhoek 91100, Namibia
推荐引用方式
GB/T 7714
Malahlela, Oupa E.,Olwoch, Jane M.,Adjorlolo, Clement. Evaluating Efficacy of Landsat-Derived Environmental Covariates for Predicting Malaria Distribution in Rural Villages of Vhembe District, South Africa[J],2018,15(1):23-40.
APA Malahlela, Oupa E.,Olwoch, Jane M.,&Adjorlolo, Clement.(2018).Evaluating Efficacy of Landsat-Derived Environmental Covariates for Predicting Malaria Distribution in Rural Villages of Vhembe District, South Africa.ECOHEALTH,15(1),23-40.
MLA Malahlela, Oupa E.,et al."Evaluating Efficacy of Landsat-Derived Environmental Covariates for Predicting Malaria Distribution in Rural Villages of Vhembe District, South Africa".ECOHEALTH 15.1(2018):23-40.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Malahlela, Oupa E.]的文章
[Olwoch, Jane M.]的文章
[Adjorlolo, Clement]的文章
百度学术
百度学术中相似的文章
[Malahlela, Oupa E.]的文章
[Olwoch, Jane M.]的文章
[Adjorlolo, Clement]的文章
必应学术
必应学术中相似的文章
[Malahlela, Oupa E.]的文章
[Olwoch, Jane M.]的文章
[Adjorlolo, Clement]的文章
相关权益政策
暂无数据
收藏/分享

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。