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  • 1
    Online Resource
    Online Resource
    Abstracts from the 3rd International Genomic Medicine Conference (3rd IGMC 2015) : Jeddah, Kingdom of Saudi Arabia. 30 November - 3 December 2015
    Springer Science and Business Media LLC ; 2016
    In:  BMC Genomics Vol. 17, No. S6 ( 2016-7)
    Details
    In: BMC Genomics, Springer Science and Business Media LLC, Vol. 17, No. S6 ( 2016-7)
    Type of Medium: Online Resource
    ISSN: 1471-2164
    URL: Article
    DOI: 10.1186/s12864-016-2858-0
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2016
    detail.hit.zdb_id: 2041499-7
    SSG: 12
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  • 2
    Online Resource
    Online Resource
    Drought Influence on Forest Plantations in Zululand, South Africa, Using MODIS Time Series and Climate Data
    MDPI AG ; 2018
    In:  Forests Vol. 9, No. 9 ( 2018-08-30), p. 528-
    Details
    In: Forests, MDPI AG, Vol. 9, No. 9 ( 2018-08-30), p. 528-
    Abstract: South Africa has a long history of recurrent droughts that have adversely affected its economic performance. The recent 2015 drought has been declared the most serious in 26 years and impaired key agricultural sectors including the forestry sector. Research on the forests’ responses to drought is therefore essential for management planning and monitoring. The effects of the latest drought on the forests in South Africa have not been studied and are uncertain. The study reported here addresses this gap by using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived normalized difference vegetation index (NDVI) and precipitation data retrieved and processed using the JavaScript code editor in the Google Earth Engine (GEE) and the corresponding normalized difference infrared index (NDII), Palmer drought severity index (PDSI), and El Niño time series data for KwaMbonambi, northern Zululand, between 2002 and 2016. The NDVI and NDII time series were decomposed using the Breaks for Additive Seasonal and Trend (BFAST) method to establish the trend and seasonal variation. Multiple linear regression and Mann–Kendall tests were applied to determine the association of the NDVI and NDII with the climate variables. Plantation trees displayed high NDVI values (0.74–0.78) from 2002 to 2013; then, they decreased sharply to 0.64 in 2015. The Mann–Kendall trend test confirmed a negative significant (p = 0.000353) trend between 2014 and 2015. This pattern was associated with a precipitation deficit and low NDII values during a strong El Niño phase. The PDSI (−2.6) values indicated severe drought conditions. The greening decreased in 2015, with some forest remnants showing resistance, implying that the tree species had varying sensitivity to drought. We found that the plantation trees suffered drought stress during 2015, although it seems that the trees began to recover, as the NDVI signals rose in 2016. Overall, these results demonstrated the effective use of the NDVI- and NDII-derived MODIS data coupled with climatic variables to provide insights into the influence of drought on plantation trees in the study area.
    Type of Medium: Online Resource
    ISSN: 1999-4907
    URL: Article
    DOI: 10.3390/f9090528
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2527081-3
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  • 3
    Online Resource
    Online Resource
    Multi-Decadal Spatial and Temporal Forest Cover Change Analysis of Nkandla Natural Reserve, South Africa
    Informa UK Limited ; 2022
    In:  Journal of Sustainable Forestry Vol. 41, No. 10 ( 2022-11-26), p. 959-982
    Details
    In: Journal of Sustainable Forestry, Informa UK Limited, Vol. 41, No. 10 ( 2022-11-26), p. 959-982
    Type of Medium: Online Resource
    ISSN: 1054-9811 , 1540-756X
    URL: Article
    DOI: 10.1080/10549811.2021.1891441
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2094282-5
    detail.hit.zdb_id: 1160736-1
    SSG: 23
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  • 4
    Online Resource
    Online Resource
    Reprint of “Modelling the influence of temperature and rainfall on malaria incidence in four endemic provinces of Zambia using semiparametric Poisson regression ”
    Elsevier BV ; 2017
    In:  Acta Tropica Vol. 175 ( 2017-11), p. 60-70
    Details
    In: Acta Tropica, Elsevier BV, Vol. 175 ( 2017-11), p. 60-70
    Type of Medium: Online Resource
    ISSN: 0001-706X
    URL: Article
    DOI: 10.1016/j.actatropica.2017.08.014
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2017
    detail.hit.zdb_id: 1495527-1
    detail.hit.zdb_id: 2709742-0
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  • 5
    Online Resource
    Online Resource
    Remote sensing object-oriented approaches coupled with ecological informatics to map invasive plant species
    African Journals Online (AJOL) ; 2016
    In:  South African Journal of Geomatics Vol. 5, No. 3 ( 2016-11-04), p. 285-
    Details
    In: South African Journal of Geomatics, African Journals Online (AJOL), Vol. 5, No. 3 ( 2016-11-04), p. 285-
    Type of Medium: Online Resource
    ISSN: 2225-8531
    URL: Article
    DOI: 10.4314/sajg.v5i3.2
    Language: Unknown
    Publisher: African Journals Online (AJOL)
    Publication Date: 2016
    detail.hit.zdb_id: 2655943-2
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  • 6
    Online Resource
    Online Resource
    A hybrid partial least squares and random forest approach to modelling forest structural attributes using multispectral remote sensing data
    African Journals Online (AJOL) ; 2017
    In:  South African Journal of Geomatics Vol. 6, No. 3 ( 2017-11-03), p. 377-
    Details
    In: South African Journal of Geomatics, African Journals Online (AJOL), Vol. 6, No. 3 ( 2017-11-03), p. 377-
    Type of Medium: Online Resource
    ISSN: 2225-8531
    URL: Article
    DOI: 10.4314/sajg.v6i3.8
    Language: Unknown
    Publisher: African Journals Online (AJOL)
    Publication Date: 2017
    detail.hit.zdb_id: 2655943-2
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  • 7
    Online Resource
    Online Resource
    Modelling the effect of terrain variability in even-aged Eucalyptus species using LiDAR-derived DTM variables
    African Journals Online (AJOL) ; 2022
    In:  South African Journal of Geomatics Vol. 9, No. 2 ( 2022-09-06), p. 118-135
    Details
    In: South African Journal of Geomatics, African Journals Online (AJOL), Vol. 9, No. 2 ( 2022-09-06), p. 118-135
    Abstract: Accurate multi-source forest inventory attributes are necessary for estimating productivity and timber stock in commercial forest plantations. This study aims to uncover the effects of terrain variation on the growth of even aged Eucalyptus forest species using Light Detection and Ranging (LiDAR) topographical variables. Using 32 generated variables at 5 different spatial resolutions (1m, 3m, 5m, 7m, 9m), the random forest (RF) regression successfully revealed variations for structural attributes such as volume (Vol/ha), dominant tree height (HtD), mean tree height (Htm), and diameter breast heights (DBH). Results indicate that smaller spatial resolutions performed better for younger stands while larger resolutions produced the best results for mature stands. Using the multi-resolution approach results improved with variable selection. Incoming solar radiation and slope variables were among the most important terrain variables for modelling forest structural variability. The findings from this study demonstrates the value of stratifying forest productivity across the commercial forest landscapes of South Africa.
    Type of Medium: Online Resource
    ISSN: 2225-8531
    URL: Article
    DOI: 10.4314/sajg.v9i2.9
    Language: Unknown
    Publisher: African Journals Online (AJOL)
    Publication Date: 2022
    detail.hit.zdb_id: 2655943-2
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  • 8
    Online Resource
    Online Resource
    Earth observation in support of malaria control and epidemiology: MALAREO monitoring approaches
    PAGEPress Publications ; 2015
    In:  Geospatial Health Vol. 10, No. 1 ( 2015-06-03)
    Details
    In: Geospatial Health, PAGEPress Publications, Vol. 10, No. 1 ( 2015-06-03)
    Abstract: Malaria affects about half of the world’s population, with the vast majority of cases occuring in Africa. National malaria control programmes aim to reduce the burden of malaria and its negative, socioeconomic effects by using various control strategies ( 〈 em 〉 e.g. 〈 /em 〉 vector control, environmental management and case tracking). Vector control is the most effective transmission prevention strategy, while environmental factors are the key parameters affecting transmission. Geographic information systems (GIS), earth observation (EO) and spatial modelling are increasingly being recognised as valuable tools for effective management and malaria vector control. Issues previously inhibiting the use of EO in epidemiology and malaria control such as poor satellite sensor performance, high costs and long turnaround times, have since been resolved through modern technology. The core goal of this study was to develop and implement the capabilities of EO data for national malaria control programmes in South Africa, Swaziland and Mozambique. High- and very high resolution (HR and VHR) land cover and wetland maps were generated for the identification of potential vector habitats and human activities, as well as geoinformation on distance to wetlands for malaria risk modelling, population density maps, habitat foci maps and VHR household maps. These products were further used for modelling malaria incidence and the analysis of environmental factors that favour vector breeding. Geoproducts were also transferred to the staff of national malaria control programmes in seven African countries to demonstrate how EO data and GIS can support vector control strategy planning and monitoring. The transferred EO products support better epidemiological understanding of environmental factors related to malaria transmission, and allow for spatio-temporal targeting of malaria control interventions, thereby improving the cost-effectiveness of interventions.
    Type of Medium: Online Resource
    ISSN: 1970-7096 , 1827-1987
    URL: Article
    DOI: 10.4081/gh.2015.335
    Language: Unknown
    Publisher: PAGEPress Publications
    Publication Date: 2015
    detail.hit.zdb_id: 2276179-2
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  • 9
    Online Resource
    Online Resource
    Application of geo-spatial technology in schistosomiasis modelling in Africa: a review
    PAGEPress Publications ; 2015
    In:  Geospatial Health Vol. 10, No. 2 ( 2015-11-04)
    Details
    In: Geospatial Health, PAGEPress Publications, Vol. 10, No. 2 ( 2015-11-04)
    Abstract: Schistosomiasis continues to impact socio-economic development negatively in sub-Saharan Africa. The advent of spatial technologies, including geographic information systems (GIS), Earth observation (EO) and global positioning systems (GPS) assist modelling efforts. However, there is increasing concern regarding the accuracy and precision of the current spatial models. This paper reviews the literature regarding the progress and challenges in the development and utilization of spatial technology with special reference to predictive models for schistosomiasis in Africa. Peer-reviewed papers identified through a PubMed search using the following keywords: 〈 em 〉 geo-spatial analysis 〈 /em 〉 OR 〈 em 〉 remote sensing 〈 /em 〉 OR 〈 em 〉 modelling 〈 /em 〉 OR 〈 em 〉 earth observation 〈 /em 〉 OR 〈 em 〉 geographic information systems 〈 /em 〉 OR 〈 em 〉 prediction 〈 /em 〉 OR 〈 em 〉 mapping 〈 /em 〉 AND 〈 em 〉 schistosomiasis 〈 /em 〉 AND 〈 em 〉 Africa 〈 /em 〉 were used. Statistical uncertainty, low spatial and temporal resolution satellite data and poor validation were identified as some of the factors that compromise the precision and accuracy of the existing predictive models. The need for high spatial resolution of remote sensing data in conjunction with ancillary data 〈 em 〉 viz. 〈 /em 〉 ground-measured climatic and environmental information, local presence/absence intermediate host snail surveys as well as prevalence and intensity of human infection for model calibration and validation are discussed. The importance of a multidisciplinary approach in developing robust, spatial data capturing, modelling techniques and products applicable in epidemiology is highlighted.
    Type of Medium: Online Resource
    ISSN: 1970-7096 , 1827-1987
    URL: Article
    DOI: 10.4081/gh.2015.326
    Language: Unknown
    Publisher: PAGEPress Publications
    Publication Date: 2015
    detail.hit.zdb_id: 2276179-2
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  • 10
    Online Resource
    Online Resource
    MALAREO: a user-driven project
    PAGEPress Publications ; 2015
    In:  Geospatial Health Vol. 10, No. 2 ( 2015-11-04)
    Details
    In: Geospatial Health, PAGEPress Publications, Vol. 10, No. 2 ( 2015-11-04)
    Abstract: The aim of this study is to assess the capacity gaps and requirements of Earth observation (EO) and related technologies for malaria vector control and management in the Lubombo Spatial Development Initiative regions of South Africa, Swaziland and Mozambique. In order to achieve the core objective of this study, available EO data (including main characteristics and resources required to utilize them) and their potential applications for malaria epidemiology are reviewed. In addition, a survey was conducted to assess the availability of human and facility resources to operate EO and related technologies for control and management of the malaria control programs in these countries resulting in an analysis of capacity gaps, priorities and requirements. Earth observation in malaria vector control and management has two different applications: i) collection of relevant remotely sensed data for epidemiological use; and ii) direct support of ongoing malaria vector control activities. All malaria control programs and institutions recognize the significance of EO products to detect mosquito vector habitats, to monitor environmental parameters affecting mosquito vector populations as well as house mapping and distribution of information supporting residual spray planning and monitoring. It was found that only the malaria research unit (MRU) of the medical research council (MRC) in South Africa and the national malaria control program (MCP) in Swaziland currently have a fully functional geographic information systems (GIS), whereas the other surveyed MCPs in South Africa and Mozambique currently do not have this in place. Earth observation skills only exist in MRU of MRC, while spatial epidemiology is scarce in all institutions, which was identified as major gap. The survey has also confirmed that EO and GIS technologies have enormous potential as sources of spatial data and as analytical frameworks for malaria vector control. It is therefore evident that planning and management require capacity building with respect to GIS, EO and spatial epidemiology.
    Type of Medium: Online Resource
    ISSN: 1970-7096 , 1827-1987
    URL: Article
    DOI: 10.4081/gh.2015.329
    Language: Unknown
    Publisher: PAGEPress Publications
    Publication Date: 2015
    detail.hit.zdb_id: 2276179-2
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