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

Abstract

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 undermore » 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.« less

Authors:
 [1];  [2];  [2];  [3];  [4];  [4];  [5];  [5]
  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)
Publication Date:
Research Org.:
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 Org.:
USDOE; National Aeronautic and Space Administration (NASA)
OSTI Identifier:
1471873
Grant/Contract Number:  
AC05-00OR22725; NNM11AA01A
Resource Type:
Accepted Manuscript
Journal Name:
International Journal of Applied Earth Observation and Geoinformation
Additional Journal Information:
Journal Volume: 72; Journal ID: ISSN 0303-2434
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; frost; crop damage; MODIS derived LST; tea crops; SERVIR

Citation Formats

Kotikot, Susan M., Flores, Africa, Griffin, Robert E., Sedah, Absae, Nyaga, James, Mugo, Robinson, Limaye, Ashutosh, and Irwin, Daniel E. Mapping threats to agriculture in East Africa: Performance of MODIS derived LST for frost identification in Kenya’s tea plantations. United States: N. p., 2018. Web. doi:10.1016/j.jag.2018.05.009.
Kotikot, Susan M., Flores, Africa, Griffin, Robert E., Sedah, Absae, Nyaga, James, Mugo, Robinson, Limaye, Ashutosh, & Irwin, Daniel E. Mapping threats to agriculture in East Africa: Performance of MODIS derived LST for frost identification in Kenya’s tea plantations. United States. doi:10.1016/j.jag.2018.05.009.
Kotikot, Susan M., Flores, Africa, Griffin, Robert E., Sedah, Absae, Nyaga, James, Mugo, Robinson, Limaye, Ashutosh, and Irwin, Daniel E. Tue . "Mapping threats to agriculture in East Africa: Performance of MODIS derived LST for frost identification in Kenya’s tea plantations". United States. doi:10.1016/j.jag.2018.05.009. https://www.osti.gov/servlets/purl/1471873.
@article{osti_1471873,
title = {Mapping threats to agriculture in East Africa: Performance of MODIS derived LST for frost identification in Kenya’s tea plantations},
author = {Kotikot, Susan M. and Flores, Africa and Griffin, Robert E. and Sedah, Absae and Nyaga, James and Mugo, Robinson and Limaye, Ashutosh and Irwin, Daniel E.},
abstractNote = {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.},
doi = {10.1016/j.jag.2018.05.009},
journal = {International Journal of Applied Earth Observation and Geoinformation},
number = ,
volume = 72,
place = {United States},
year = {2018},
month = {6}
}

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