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6,335 results returned

  1. Title: Wildebeest Observations: Athi-Kapiti Plains, Kenya, 1977-78 and 1994-96

    Contributors:

    Summary: This polygon shapefile portrays number of wildebeest observed in 1977-78 and 1994-96 in the Athi-Kapiti Plains, Kenya. Note: This data shows numbers of wildebeest observed during the wet season by low-altitude flights. The data was then aggregated to 5km grid cells by number observed. This data was used in Map 5.15 in Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. International Livestock Research Institute. (2007). Wildebeest Observations: Athi-Kapiti Plains, Kenya, 1977-78 and 1994-96. ILRI. Available at: http://purl.stanford.edu/vd704zq1972 Note: A number of wildebeest nul should be interpreted as "No observation of wildebeest". Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  2. Title: Wildlife Density in Rangelands of Kenya, 1977-1978

    Contributors:

    Summary: This polygon shapefile represents the wildlife density in Kenya's rangelands for 1977-78. This data was used in Map 5.10 in Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. International Livestock Research Institute. (2007). Wildlife Density in Rangelands of Kenya, 1977-1978. World Resources Institute. Available at: http://purl.stanford.edu/sj353sg1449 Species numbers were aggregated using a "tropical livestock unit" (TLU) (which is equivalent to an animal weight of 250 kilograms) to grid cells of 5x5 km and then averaged by square kilometer. The wildlife counts include 21 different large grazing animals that can be observed during low-altitude flights in Kenya. Note: A wildlife density nul should be interpreted as "No observation of wildlife". Please refer to DRSRS for updates. Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  3. Title: Wildlife Density in Rangelands of Kenya, 1994-1996

    Contributors:

    Summary: This polygon shapefile represents wildlife density in Kenya's rangelands for 1994-96. This data was used in Map 1.4, Map 4.10, and Map 5.11 in Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. International Livestock Research Institute. (2007). Wildlife Density in Rangelands of Kenya, 1994-1996. World Resources Institute. Available at: http://purl.stanford.edu/fj435mx2689 Species numbers are aggregated using a "tropical livestock unit" (TLU) (which is equivalent to an animal weight of 250 kilograms) to grid cells of 5x5 km and then averaged by square kilometer. The wildlife counts include 21 different large grazing animals that can be observed during low-altitude flights in Kenya. Units are in "tropical livestock unit per sq. kilometer." Note: A livestock density nul should be interpreted as "No observation of animals". Please refer to DRSRS for updates. Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty.

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  4. Title: Livestock Density in Kenya's Rangelands, 1994 to 1996

    Contributors:

    Summary: This polygon shapefile portrays livestock density in Kenya's rangelands for 1994-96. Most of Kenya’s rangelands contain livestock. Higher livestock numbers can be found in the wetter part of the rangelands and closer to permanent water sources. Livestock densities in large parts of the northeastern rangelands reflect pastoral production systems where herders move livestock periodically to follow the seasonal supply of water and feed. In a number of locations in Narok, Kajiado, and Laikipia Districts, high wildlife and livestock densities coincide. This data was used in Map 1.5 and Map 4.7 in Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. International Livestock Research Institute. (2007). Livestock Density in Kenya's Rangelands, 1994 to 1996. World Resources Institute. Available at: http://purl.stanford.edu/pp492fg6473 Species numbers are aggregated using a "tropical livestock unit" (TLU) (which is equivalent to an animal weight of 250 kilograms) to grid cells of 5x5 km and then averaged by square kilometer. Livestock includes cattle, sheep, goats, camels and donkeys that were observed during low-altitude flights. Units are in "tropical livestock unit per sq. kilometer." Note: A livestock density nul should be interpreted as "No observation of animals". Please refer to DRSRS for updates. Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty.

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  5. Title: Elephant Distribution: Kenya, 1994-1996

    Contributors:

    Summary: This polygon shapefile portrays the spatial distribution of elephant numbers observed in Kenya from 1994 to 1996. Wildlife counts came from a rangeland census using low altitude flights. Animals are aggregated to squares of 5 kilometers by 5 kilometers.. This data was used in Map 6.2 in Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. International Livestock Research Institute. (2007). Elephant Distribution: Kenya, 1994-1996. ILRI. Available at: http://purl.stanford.edu/xk308vh0908 Wildlife counts come from a rangeland census using low-altitude flights in Kenya. Numbers of animals observed were aggregated to 5km grid cells. Note: A number of elephants nul should be interpreted as "No observation of elephants". Please refer to DRSRS for updates. Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  6. Title: Change in Wildlife Density in Rangelands of Kenya, 1977-1978 to 1994-1996

    Contributors:

    Summary: This polygon shapefile shows changes in wildlife density in Kenya's rangelands between 1977-78 and 1994-96. Many places in Kenya experienced gains in wildlife density between the 1970s and the 1990s, with sites of most rapid recovery concentrated in southwest Narok District, near the Masai Mara Game Reserve; in Kajiado District, near Amboseli National Park; in Laikipia District, northwest of Mount Kenya National Park; and in selected areas near the coast in Lamu District. Sites with sharp declines in wildlife density are found throughout large parts of central Narok District, south of Nairobi in Kajiado District, northern Laikipia District, locations along the Samburu-Laikipia border, and in Isiolo and Garissa Districts near the Wajir border. Note: To estimate changes in wildlife densities, species numbers are aggregated (using TLUs) to squares of 10 km by 10 km and then averaged by square kilometer for each reference period. The wildlife counts include 21 different large grazing animals that can be observed during low-altitude flights. This data was used in Map 5.12 in Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. International Livestock Research Institute. (2007). Change in Wildlife Density in Rangelands of Kenya 1977-1996. World Resources Institute. Available at: http://purl.stanford.edu/cx018dg2570 Species numbers were aggregated using a "tropical livestock unit" (TLU) (which is equivalent to an animal weight of 250 kilograms) to grid cells of 10x10 km and then averaged by square kilometer. The wildlife counts include 21 different large grazing animals that can be observed during low-altitude flights in Kenya. Note: Beware of differentiating a "No change" and a "No observation of wildlife at both dates" using the field "No data" in conjunction with "CHG7090". Please refer to DRSRS for updates. Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  7. Title: Bed Capacity for Major Tourist Hotels on the Eastern Coast of Kenya, 2003

    Contributors:

    Summary: This point shapefile depicts the capacity, or number of beds, for major tourist hotels on the eastern coast of Kenya. These data were caluclated by the International Livestock Research Institute based on data sources from the United National Environmental Programme and the Republic of Kenya. This data was used in Map 6.4 and Map 6.5 in Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. International Livestock Research Institute. (2007). Bed Capacity for Major Tourist Hotels on the Eastern Coast of Kenya, 2003. World Resources Institute. Available at: http://purl.stanford.edu/rc618qh5215. Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  8. Title: Giraffe Distribution: Kenya, 1994-1996

    Contributors:

    Summary: This polygon shapefile portrays the spatial distribution of giraffe numbers observed in Kenya from 1994 to 1996. Wildlife counts came from a rangeland census using low altitude flights. Animals are aggregated to squares of 5 kilometers by 5 kilometers. This data was used in Map 6.2 in Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. International Livestock Research Institute. (2007). Giraffe Distribution: Kenya, 1994-1996. ILRI. Available at: http://purl.stanford.edu/hp304xd1616 Wildlife counts come from a rangeland census using low-altitude flights in Kenya. Numbers of animals observed were aggregated to 5km grid cells. Note: A number of giraffes nul should be interpreted as "No observation of giraffes". Please refer to DRSRS for updates. Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  9. Title: Zebra Distribution: Kenya, 1994-1996

    Contributors:

    Summary: This polygon shapefile portrays the spatial distribution of zebra numbers observed in Kenya from 1994 to 1996. Wildlife counts came from a rangeland census using low altitude flights. Animals are aggregated to squares of 5 kilometers by 5 kilometers. This data was used in Map 6.2 in Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. International Livestock Research Institute. (2007). Zebra Distribution: Kenya, 1994-1996. ILRI. Available at: http://purl.stanford.edu/sy389gp2436 Wildlife counts come from a rangeland census using low-altitude flights in Kenya. Numbers of animals observed were aggregated to 5km grid cells. Note: A number of zebra nul should be interpreted as "No observation of zebra". Please refer to DRSRS for updates. Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  10. Title: Wildebeest Distribution: Kenya, 1994-1996

    Contributors:

    Summary: This polygon shapefile portrays the spatial distribution of wildebeest numbers observed in Kenya from 1994 to 1996. Wildlife counts came from a rangeland census using low altitude flights. Animals are aggregated to squares of 5 kilometers by 5 kilometers. This data was used in Map 6.2 in Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. International Livestock Research Institute. (2007). Wildebeest Distribution: Kenya, 1994-1996. ILRI. Available at: http://purl.stanford.edu/kg342gc4695 Wildlife counts come from a rangeland census using low-altitude flights in Kenya. Numbers of animals observed were aggregated to 5km grid cells. Note: A number of wildebeest nul should be interpreted as "No observation of wildebeest". Please refer to DRSRS for updates. Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  11. Title: Buffalo Distribution: Kenya, 1994-1996

    Contributors:

    Summary: This polygon shapefile portrays the spatial distribution of buffalo numbers observed in Kenya from 1994 to 1996. Wildlife counts came from a rangeland census using low altitude flights. Animals are aggregated to squares of 5 kilometers by 5 kilometers. This data was used in Map 6.2 in Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. International Livestock Research Institute. (2007). Buffalo Distribution: Kenya, 1994-1996. ILRI. Available at: http://purl.stanford.edu/jh904mn9840 Wildlife counts come from a rangeland census using low-altitude flights in Kenya. Numbers of animals observed were aggregated to 5km grid cells. Note: A number of buffalo nul should be interpreted as "No observation of buffalos". Please refer to DRSRS for updates. Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  12. Title: Milk Production in Central and Western Kenya, 2005

    Contributors:

    Summary: This polygon shapefile portrays milk production per square kilometer in central and western Kenya, 1997. Calculations of milk production were done by assessing the number of dairy cattle in an administrative area, and extrapolating out liters of milk per area. This data was used in Map 4.5 in Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. Baltenweck I., Staal, L. Njoroge, F. Wanyoike, Ochungo, P., Kariuki, E and International Livestock Research Institute. (2005). Milk Production in Central and Western Kenya, 2005. ILRI. Available at: http://purl.stanford.edu/mk366pr6303 Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  13. Title: Milk Surplus and Deficit in Central and Western Kenya, 1997

    Contributors:

    Summary: This polygon shapefile portrays areas of milk surplus and deficit in central and western Kenya, 1997. Calculations of milk production were done by assessing the number of dairy cattle in an administrative area, and extrapolating out liters of milk per area. Demand for milk was calculated by estimating the milk needs per person, and applying that number to the population density of each area. Areas with more milk produced than needed by the population are considered "surplus" areas, while those with more demand than can be met by current production are considered to be in "deficit." Many areas of the country produce more milk than they need locally. Hence, establishing good transportation and marketing systems for dairy could go a long way toward increasing the availability of milk in deficit areas. This data was used in Map 4.6 in Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. Baltenweck I., Staal, L. Njoroge, F. Wanyoike, Ochungo, P., Kariuki, E and International Livestock Research Institute. (2005). Milk Surplus and Deficit in Central and Western Kenya, 1997. ILRI. Available at: http://purl.stanford.edu/jf184vq4069 Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  14. Title: Major Cities: Kenya, 2000

    Contributors:

    Summary: This point shapefile identifies major cities in Kenya for 2000. Data from 1:50,000 and 250,000 topographic maps originally created by the Geological Survey of Kenya were digitized by the International Livestoack Research Institute and the Japan International Cooperation Agency. This data was used in maps throughout Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. Geological Survey of Kenya, Japanese International Cooperation Agency, and International Livestock Research Institute. (2000). Major Cities: Kenya, 2000. World Resources Institute. Available at: http://purl.stanford.edu/mb999xf7048 Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty.

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  15. Title: Market Centers in Western Kenya, 2000

    Contributors:

    Summary: This point shapefile shows locations of market centers in western Kenya. This data was used in Map 3.15 in Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. Geological Survey of Kenya and International Livestock Research Institute. (2000). Market Centers in Western Kenya, 2000. Geological Survey of Kenya. Available at: http://purl.stanford.edu/sb710sh4558 Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty.

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  16. Title: Major Roads: Kenya, 1997

    Contributors:

    Summary: This line shapefile shows major roads in Kenya. These data were originally produced as a 1:250,000 topographic map by the Geological Survey of Kenya. This data was used in maps throughout Nature's Benefits in Kenya: An Atlas of Ecosystems and Human Well-Being. Geological Survey of Kenya, Japanese International Cooperation Agency, and International Livestock Research Institute. (1997). Major Roads: Kenya, 1997. World Resources Institute. Available at: http://purl.stanford.edu/hd634cg4363 Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, WRI, cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. WRI makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty. This layer is presented in the WGS84 coordinate system for web display purposes. Downloadable data are provided in native coordinate system or projection.

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  17. Title: Minnesota Natural Resource Atlas

    Contributors:

    Summary: The Interactive Map provides a basic set of GIS tools for viewing, searching, and manipulating mapped data. These tools allows users to measure, access attribute data, conduct basic summaries, query features, and view different combinations of spatial data. Information can be shared by exporting results and map images.

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  18. Title: Coastal Social Vulnerability Index, Wisconsin 2006-2010

    Contributors:

    Summary: This data depicts the lake-level change of the social vulnerability of Wisconsin census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

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  19. Title: Canada Postal Points, 2008

    Contributors:

    Summary: Canada Postal Points is a point theme representing the centroids of the three-character Forward Sortation Areas (FSA) of Canada.

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  20. Title: Canada Postal Areas, 2008

    Contributors:

    Summary: Canada Postal Areas is a polygon theme representing the three-character Forward Sortation Areas (FSA) of Canada. This data set provides six levels of generalization for displaying the data at different scales. Everything about the levels is the same but the level of generalization and its name. The least generalized level is called <data set name>. The next more generalized level is called <data set name>_1, and so on. For best performance, use the most appropriate generalized level when displaying or printing.

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