Desertification Hazard for Kenya (Model Result) from UNEP/GRID-Geneva
Entry ID:
GNVd0137_104
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Summary
Abstract:
Conceptual models were developed by FAO staff to assess global soils in relation to the processes of desertification and to conduct a full desertification hazards evaluation in Africa. The map sheet for NE Africa was established as a test base for applying both the World and Africa models. Preliminary versions of the models were presented at ESRI in October 1983. Todor Boyadgiev provided ... direction for model iteration and review over a period of three months, being present at ESRI for four weeks in January - February and two weeks in April 1984. Models were programmed using INFO software and involved both logical and arithmetic operations. All coordinate and attribute manipulations were effected by means of INFO and ARC software respectively. The World models were programmed by ESRI staff to operate on the expansion file of FAO soils for Africa. Thus, with each run, all of the soils on the continent were evaluated. The results, however, were initially presented in a map form only for the NE sheet. Elsewhere, the results were represented by computer listings only. Following iteration and review, the World models were also run on the expansion file of FAO soils for the World outside of Africa. The resulting model values were added to the expansion files and served as the basis for the spatial patterning and values displayed on the final maps. The Africa models were programmed to operate in the expansion files wherever possible. Final results were resolved to the attribute components of the overlay files which were created for each of the three original Africa sheets. As part of the modeling effort, interpretive values for each of the FAO soil unit components were developed by FAO staff. These values, involving ratings for grassland productivity, soil constraints and agricultural productivity, soil K-values and wind erodibility ratings, were automated and were used in the modeling process through a relational data base operation which tied them to the pertinent soil type. Some of these values were modified during the process of model iteration. The soil interpretive values used in the final models for Africa are included in the code listings accompanying the final data files. The concepts and definitions concerning desertification analysis are detailed in the FAO report entitled, Provisional Methodology for Assessment and Mapping of Desertification. The definitions, criteria, and class values employed for both the Africa models and the World models are outlined in the Map of Desertification Hazards: Explanatory Note, which accompanied the maps prepared for presentation in May 1984. A seven-stage evaluation of desertification hazards in Africa was conducted. Six component analyses were programmed and iterated, each iteration involving a review of the maps and statistical outputs from the computer analysis. The full results of each of the component analyses were used in the final analysis. Thus, it was necessary to resolve all of the component analyses prior to generating a final hazards map for iteration and review. Based upon a review of the resulting spatial and statistical distributions from each of the analyses, summation criteria for each of the models were specified and iterated. new results of each of the component analyses were classed in four levels: slight, moderate, severe, and very severe. The class limits were based upon percentages of the highest numeric value for each model. The final sunmry values were built using the raw numeric values from each of the component analyses. These were normalized by use of the factors listed below. Each component analysis contributed a maximum value of 100 to the summary. Soil Constraints 2.5 Wind Action 3.368 water Action 5.321 Salinization 0.772 Population 2.5 Animal 6.25 The class limits for the summary model were established as follows: Summary None to Slight <= 42.5 Moderate 42.51-85.0 Severe 85.1-127.5 Very Severe > 127.5 The final model was programmed to track the relative contribution of each component of the summary value. The two most significant components were identified in the summary statement for the model and were displayed on the resulting map. For final presentation, the hazard ratings and factors were eliminated in areas with greater than 180 days growing period or with cold temperatures, and were discriminated in areas with zero and with 0-180 growing periods.
Geographic Coverage
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Spatial coordinates
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N: 5.07
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S: -5.3
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E: 42.44
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W: 33.0
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Access Constraints
Public
Distribution
Distribution Media:
8 mm tape or ftp
Distribution Size:
approximately 16 Megabytes
Personnel
Role:
INVESTIGATOR
Email:
cneale at cc.usu.edu
Contact Address:
Biological & Irrigation Engineering Department
Room EC 329
Utah State University
City:
Logan
Province or State:
Utah
Postal Code:
84322-4105
Country:
USA
Role:
INVESTIGATOR
Contact Address:
Utah State University
Civil and Environmental Engineering
4110 Old Main Hill
City:
Logan
Province or State:
UT
Postal Code:
84322-4110
Country:
USA
Role:
TECHNICAL CONTACT
Phone:
+1 (303) 492-6199
Fax:
+1 (303) 492-2468
Email:
nsidc at nsidc.org
Contact Address:
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
City:
Boulder
Province or State:
CO
Postal Code:
80309-0449
Country:
USA
Publications/References
Satellite/Instrument/Data Processing Documentation Hollinger, J. P., R. Lo, G. Poe, R. Savage, and J. Peirce. 1987. Special Sensor Microwave/Imager User's Guide. Hollinger, J. P., ed. 1989.DMSP Special Sensor Microwave/Imager Calibration/Validation - Final Report - Volume I, Naval Research Laboratory, Washington, DC. Hollinger, J. P. 1991. DMSP Special Sensor Microwave/Imager ... Calibration/Validation Final Report - Volume II, Naval Research Laboratory, Washington, DC. Wentz, F.J. 1991. Revision-1 User's Manual SSM/I Antenna Temperature Tapes, Remote Sensing Systems, Santa Rosa, CA, 70 pp. Journal Articles and Study Reports McFarland, M. J., and C. Neale. 1991. Land Parameter Algorithm Validation and Calibration. DMSP Special Sensor Microwave/Imager Calibration/Validation - Final Report, Volume II, Naval Research Laboratory, Washington, DC, chap 9, pp 1-64. McFarland, M.J., R. L. Miller, and C. M. U. Neale. 1990.Land Surface Temperature Derived From the SSM/I Passive Microwave Brightness Temperatures. IEEE Transactions on Geoscience and Remote Sensing, 28(5):839-845. Neale, C.M.U., M.J. McFarland, and K. Chang. 1990.Land Surface-Type Classification Using Microwave Brightness Temperatures From The Special Sensor Microwave/Imager. IEEE Transactions on Geoscience and Remote Sensing, 28(5):829-838. Hollinger, J. P., J. L. Peirce, and G. A. Poe. 1990. SSM/I Instrument Evaluation. IEEE Transactions on Geoscience and Remote Sensing, 28(5):781-790.
Extended Metadata Properties
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Creation and Review Dates
Last DIF Revision Date:
2012-05-14
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