Limits...
Optimum land cover products for use in a Glossina-morsitans habitat model of Kenya.

DeVisser MH, Messina JP - Int J Health Geogr (2009)

Bottom Line: Efforts to control the disease were hampered by a lack of information and costs associated with the identification of infested areas.For single date applications, Africover was determined to be the best land use land cover (LULC) product for tsetse modeling.The method can be used to differentiate between various LULC products and be applied to any such research when there is a known relationship between a species and land cover.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Geography and Center for Global Change and Earth Observations, Michigan State University, East Lansing, MI, USA. devisse6@msu.edu

ABSTRACT

Background: Tsetse flies are the primary vector for African trypanosomiasis, a disease that affects both humans and livestock across the continent of Africa. In 1973 tsetse flies were estimated to inhabit 22% of Kenya; by 1996 that number had risen to roughly 34%. Efforts to control the disease were hampered by a lack of information and costs associated with the identification of infested areas. Given changing spatial and demographic factors, a model that can predict suitable tsetse fly habitat based on land cover and climate change is critical to efforts aimed at controlling the disease. In this paper we present a generalizable method, using a modified Mapcurves goodness of fit test, to evaluate the existing publicly available land cover products to determine which products perform the best at identifying suitable tsetse fly land cover.

Results: For single date applications, Africover was determined to be the best land use land cover (LULC) product for tsetse modeling. However, for changing habitats, whether climatically or anthropogenically forced, the IGBP DISCover and MODIS type 1 products where determined to be most practical.

Conclusion: The method can be used to differentiate between various LULC products and be applied to any such research when there is a known relationship between a species and land cover.

Show MeSH

Related in: MedlinePlus

The suitability map produced when the binary suitability maps for Africover, IGBP DISCover, MODIS t1, UMd Global Land Cover, and GLC2000 were combined.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2710327&req=5

Figure 11: The suitability map produced when the binary suitability maps for Africover, IGBP DISCover, MODIS t1, UMd Global Land Cover, and GLC2000 were combined.

Mentions: Based on the results of Mapcurves GOF analysis of the binary suitability maps the five LULC data sets used to create the combined suitability map were: Africover, IGBP DISCover, MODIS type 1, UMd Global Land Cover, and CLIPcover. MODIS types 2 & 3 were excluded despite their high GOF scores to avoid redundancy given their similarity to MODIS type 1, and alternatively CLIPcover and UMd GLCC were included due to their significant level of agreement with at least one of the two ground truth maps. GLC2000, MODIS 1 km type 4 & 5, and all of the MODIS 500 m LULC data sets were excluded due to their low GOF scores. The resulting suitability map is a categorical map with six classes; 0 representing an area where none of the five LULC data sets predicted suitable tsetse habitat, 5 representing an area where all five of the LULC data sets predicted suitable habitat (Figure 11). The combined FAO/IAEA distribution map was then reclassified into a six class categorical map, from 0 – 100% in ~16.6% increments, to mirror the classification scheme of the newly created combined suitability map.


Optimum land cover products for use in a Glossina-morsitans habitat model of Kenya.

DeVisser MH, Messina JP - Int J Health Geogr (2009)

The suitability map produced when the binary suitability maps for Africover, IGBP DISCover, MODIS t1, UMd Global Land Cover, and GLC2000 were combined.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2710327&req=5

Figure 11: The suitability map produced when the binary suitability maps for Africover, IGBP DISCover, MODIS t1, UMd Global Land Cover, and GLC2000 were combined.
Mentions: Based on the results of Mapcurves GOF analysis of the binary suitability maps the five LULC data sets used to create the combined suitability map were: Africover, IGBP DISCover, MODIS type 1, UMd Global Land Cover, and CLIPcover. MODIS types 2 & 3 were excluded despite their high GOF scores to avoid redundancy given their similarity to MODIS type 1, and alternatively CLIPcover and UMd GLCC were included due to their significant level of agreement with at least one of the two ground truth maps. GLC2000, MODIS 1 km type 4 & 5, and all of the MODIS 500 m LULC data sets were excluded due to their low GOF scores. The resulting suitability map is a categorical map with six classes; 0 representing an area where none of the five LULC data sets predicted suitable tsetse habitat, 5 representing an area where all five of the LULC data sets predicted suitable habitat (Figure 11). The combined FAO/IAEA distribution map was then reclassified into a six class categorical map, from 0 – 100% in ~16.6% increments, to mirror the classification scheme of the newly created combined suitability map.

Bottom Line: Efforts to control the disease were hampered by a lack of information and costs associated with the identification of infested areas.For single date applications, Africover was determined to be the best land use land cover (LULC) product for tsetse modeling.The method can be used to differentiate between various LULC products and be applied to any such research when there is a known relationship between a species and land cover.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Geography and Center for Global Change and Earth Observations, Michigan State University, East Lansing, MI, USA. devisse6@msu.edu

ABSTRACT

Background: Tsetse flies are the primary vector for African trypanosomiasis, a disease that affects both humans and livestock across the continent of Africa. In 1973 tsetse flies were estimated to inhabit 22% of Kenya; by 1996 that number had risen to roughly 34%. Efforts to control the disease were hampered by a lack of information and costs associated with the identification of infested areas. Given changing spatial and demographic factors, a model that can predict suitable tsetse fly habitat based on land cover and climate change is critical to efforts aimed at controlling the disease. In this paper we present a generalizable method, using a modified Mapcurves goodness of fit test, to evaluate the existing publicly available land cover products to determine which products perform the best at identifying suitable tsetse fly land cover.

Results: For single date applications, Africover was determined to be the best land use land cover (LULC) product for tsetse modeling. However, for changing habitats, whether climatically or anthropogenically forced, the IGBP DISCover and MODIS type 1 products where determined to be most practical.

Conclusion: The method can be used to differentiate between various LULC products and be applied to any such research when there is a known relationship between a species and land cover.

Show MeSH
Related in: MedlinePlus