Mapping threats to agriculture in East Africa: Performance of MODIS derived LST for frost identification in Kenya’s tea plantations

Journal Article · 19 June 2018 · International Journal of Applied Earth Observation and Geoinformation

DOI: https://doi.org/10.1016/j.jag.2018.05.009 · OSTI ID:1471873

Kotikot, Susan M. ^[1]; Flores, Africa ^[2]; Griffin, Robert E. ^[2]; Sedah, Absae ^[3]; Nyaga, James ^[4]; Mugo, Robinson ^[4]; Limaye, Ashutosh ^[5]; Irwin, Daniel E. ^[5]

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1. Univ. of Alabama, Huntsville, AL (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2. Univ. of Alabama, Huntsville, AL (United States). Earth System Science Center
3. Kenya Meteorological Service (KMS), Nairobi (Kenya)
4. Regional Center for Mapping of Resources for Development, Nairobi (Kenya)
5. NASA/SERVIR Global, Huntsville, AL (United States)

Frost is a major threat to crop productivity in the Kenyan highlands. With agriculture being central to the Kenyan economy, every effort needs to be taken to alleviate losses especially on high value crops like tea, the leading foreign exchange earner. Current frost mapping efforts by SERVIR, a joint initiative between National Aeronautics and Space Administration (NASA) and the U.S. Agency for International Development (USAID), and its hub institution in Eastern and Southern Africa, the Regional Center for Mapping of Resources for Development (RCMRD), utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) derived Land Surface Temperature (LST) to probabilistically map areas that have been affected by frost. In this paper, we assessed the accuracy of these frost maps by testing the performance of MYD11A1 MODIS product in indicating areas affected by frost. MODIS derived LST values corresponding to frost and no frost observation locations and dates were reclassified according to 6 predetermined categories representing frost severity levels. The overall accuracy of each threshold category as LST cutoff separating frost and no frost affected areas was determined. An overall performance measure was then estimated using a Receiver Operating Characteristics curve (ROC). Overall accuracies of 67.3%–71.9% among the thresholds were obtained. An area under the ROC curve of 0.69 was obtained, indicating a poor performance of MODIS LST to distinguish frost from no frost areas. This shows that although MODIS derived LST can be used to identify frost-affected areas, it is not on its own sufficient in discriminating these areas with high levels of accuracy. Revision of temperature thresholds is recommended, in addition to improved characterization of frost occurrence in the region to include other factors that may be affecting frost occurrence. These results stand to better prepare the agricultural sector for damaging weather-related events.

• Research Organization: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); NASA/SERVIR Global, Huntsville, AL (United States); Univ. of Alabama, Huntsville, AL (United States); Regional Center for Mapping of Resources for Development, Nairobi (Kenya)
• Sponsoring Organization: USDOE; National Aeronautics and Space Administration (NASA) (United States)
• Grant/Contract Number: AC05-00OR22725
• OSTI ID: 1471873
• Journal Information: International Journal of Applied Earth Observation and Geoinformation, Journal Name: International Journal of Applied Earth Observation and Geoinformation Vol. 72; ISSN 0303-2434
• Publisher: ElsevierCopyright Statement
• Country of Publication: United States
• Language: English