Monitoring the effects of<i>Dracunculiasis</i>remediation on agricultural productivity using satellite data

Ahearn, Sean C.; Rooy, Carel de

doi:10.1080/01431169608949055

Cited by 15 publications

(8 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This work has continued and the GIS database elaborated and maintained to enable analysis of the spatial patterns of dracunculiasis in Benin, and to evaluate the e ectiveness of various intervention policies designed to combat the spread of the disease ( Tempalski 1994). Ahearn and De Rooy ( 1996) set out to test the hypothesis that optimization of water and sanitation interventions in areas with high dracunculiasis had a measurable socio-economic impact (as assessed by the area of land cultivated ) using a temporal analysis of Landsat-TM data. The study was centred on the Kwara state in Nigeria where dracunculiasis is prevalent throughout, but UNICEF control e orts have been targeted in particular areas.…”

Section: Application Of High Spatial Resolution Imagerymentioning

confidence: 99%

Review article The impact of remote sensing on the study and control of invertebrate intermediate hosts and vectors for disease

Hay¹,

Packer²,

Rogers³

1997

International Journal of Remote Sensing

121

View full text Add to dashboard Cite

This paper reviews the application of remote sensing to the study and control of invertebrate intermediate hosts and vectors for some of the most prevalent of human diseases worldwide. Examples are also taken from studies involving animal diseases that have considerable adverse e ects on human welfare. The current status of remote sensing in epidemiology is assessed and suggestions are made on how, in the future, the two ® elds might be most pro® tably combined.

show abstract

Section: Application Of High Spatial Resolution Imagerymentioning

confidence: 99%

Review article The impact of remote sensing on the study and control of invertebrate intermediate hosts and vectors for disease

Hay¹,

Packer²,

Rogers³

1997

International Journal of Remote Sensing

121

View full text Add to dashboard Cite

show abstract

“…In Nigeria, a temporal analysis of Landsat Thematic Mapper (TM) satellite data was carried out to test the significance of the guinea worm eradication program based on changes in agricultural production [11]. And, it was also employed to predict and map the location of some of the major diseases affecting human health as well [10,14].…”

Section: Introductionmentioning

confidence: 99%

Untitled

2005

View full text Add to dashboard Cite

Background: Vector-borne diseases are the most dreaded worldwide health problems. Although many campaigns against it have been conducted, Dengue Fever (DF) and Dengue Haemorrhagic Fever (DHF) are still the major health problems of Thailand. The reported number of dengue incidences in 1998 for the Thailand was 129,954, of which Sukhothai province alone reported alarming number of 682. It was the second largest epidemic outbreak of dengue after 1987. Government arranges the remedial facilities as and when dengue is reported. But, the best way to control is to prevent it from happening. This will be possible only when knowledge about the relationship of DF/DHF with climatic and physio-environmental agents is discovered. This paper explores empirical relationship of climatic factors rainfall, temperature and humidity with the DF/ DHF incidences using multivariate regression analysis. Also, a GIS based methodology is proposed in this paper to explore the influence of physio-environmental factors on dengue incidences. Remotely sensed data provided important data about physical environment and have been used for many vector borne diseases. Information Values (IV) method was utilised to derive influence of various factors in the quantitative terms. Researchers have not applied this type of analysis for dengue earlier. Sukhothai province was selected for the case study as it had high number of dengue cases in 1998 and also due to its diverse physical setting with variety of land use/land cover types.

show abstract

“…Also, optical remote sensing during the dry season can be strongly influenced by atmospheric dust (e.g. the cold-dry and dusty trade wind known as the Harmattan) causing a noisy NDVI signal (Achard & Blasco, 1990;Ahearn & de Rooy, 1996). Finally, a well-known factor reducing the capability of NDVI to estimate biomass is the saturation effect due to the strong absorption in the red wavelength (Sellers, 1985).…”

Section: Introductionmentioning

confidence: 99%

Remote sensing of vegetation dynamics in drylands: Evaluating vegetation optical depth (VOD) using AVHRR NDVI and in situ green biomass data over West African Sahel

Tian

Brandt

Liu

et al. 2016

Remote Sensing of Environment

194

129

View full text Add to dashboard Cite

Monitoring long-term biomass dynamics in drylands is of great importance for many environmental applications including land degradation and global carbon cycle modeling. Biomass has extensively been estimated based on the normalized difference vegetation index (NDVI) as a measure of the vegetation greenness. The vegetation optical depth (VOD) derived from satellite passive microwave observations is mainly sensitive to the water content in total aboveground vegetation layer. VOD therefore provides a complementary data source to NDVI for monitoring biomass dynamics in drylands, yet further evaluations based on ground measurements are needed for an improved understanding of the potential advantages. In this study, we assess the capability of a long-term VOD dataset (1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011) to capture the temporal and spatial variability of in situ measured green biomass (herbaceous mass and woody plant foliage mass) in the semi-arid Senegalese Sahel. Results show that the magnitude and peak time of VOD are sensitive to the woody plant foliage whereas NDVI seasonality is primarily governed by the green herbaceous vegetation stratum in the study area. Moreover, VOD is found to be more robust against typical NDVI drawbacks of saturation effect and dependence on plant structure (herbaceous and woody compositions) across the study area when used as a proxy for vegetation productivity. Finally, both VOD and NDVI well reflect the spatial and inter-annual dynamics of the in situ green biomass data; however, the seasonal metrics showing the highest degree of explained variance differ between the two data sources. While the observations in October (period of in situ data collection) perform best for VOD (r 2 = 0.88), the small growing season integral (sensitive to recurrent vegetation) have the highest correlations for NDVI (r 2 = 0.90). Overall, in spite of the coarse resolution, the study shows that VOD is an efficient proxy for estimating green biomass of the entire vegetation stratum in the semi-arid Sahel and likely also in other dryland areas.

show abstract

Monitoring the effects ofDracunculiasisremediation on agricultural productivity using satellite data

Cited by 15 publications

References 2 publications

Review article The impact of remote sensing on the study and control of invertebrate intermediate hosts and vectors for disease

Review article The impact of remote sensing on the study and control of invertebrate intermediate hosts and vectors for disease

Untitled

Remote sensing of vegetation dynamics in drylands: Evaluating vegetation optical depth (VOD) using AVHRR NDVI and in situ green biomass data over West African Sahel

Contact Info

Product

Resources

About