Assessment of a Spatially and Temporally Consistent MODIS Derived NDVI Product for Application in Index-Based Drought Insurance
In arid and semi-arid regions of Eastern and Southern Africa, drought can be devastating to pastoralists who depend on healthy vegetation for their herds. The Kenya Livestock Insurance Program (KLIP) addresses this challenge through its insurance program that relies on a vegetation index product der...
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-09-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/12/18/3031 |
| _version_ | 1797553473064009728 |
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| author | Sara E. Miller Emily C. Adams Kel N. Markert Lilian Ndungu W. Lee Ellenburg Eric R. Anderson Richard Kyuma Ashutosh Limaye Robert Griffin Daniel Irwin |
| author_facet | Sara E. Miller Emily C. Adams Kel N. Markert Lilian Ndungu W. Lee Ellenburg Eric R. Anderson Richard Kyuma Ashutosh Limaye Robert Griffin Daniel Irwin |
| author_sort | Sara E. Miller |
| collection | DOAJ |
| description | In arid and semi-arid regions of Eastern and Southern Africa, drought can be devastating to pastoralists who depend on healthy vegetation for their herds. The Kenya Livestock Insurance Program (KLIP) addresses this challenge through its insurance program that relies on a vegetation index product derived from eMODIS NDVI (enhanced Normalized Difference Vegetation Index). Insurance payouts are triggered when index values fall below a certain threshold for a Unit Area of Insurance (UAI). The objective of this study is to produce an updated, cloud-based NDVI product, potentially allowing for earlier payouts that may help herders to prevent, minimize, or offset drought-induced losses. The new product, named reNDVI (rapid enhanced NDVI), provides an updated cloud filtering algorithm and brings the entire processing chain to the cloud. Access to the scripts used for the processing described and resulting data is openly available. To test the performance of the new product, we provide a robust evaluation of reNDVI and eMODIS NDVI and their derived payout indices against historical drought, payouts provided, and mortality data. The implications of potential payout differences are also discussed. The products show good comparability; the monthly average NDVI per UAI has correlation values over 0.95 and MAPD under 5% for most UAIs. However, there are moderate differences when assessing year-to-year payout amounts triggered. Because the payouts are currently calculated based on the 20th and first percentile of index values from 2003–2016, payouts are very sensitive to even small changes in NDVI. Where livestock mortality was available, payouts for reNDVI and eMODIS had similar correlations (r = 0.453 and r = 0.478, respectively) with mortality rates. Therefore, with the potential reduced latency and updated cloud filtering, the reNDVI product could be a suitable replacement for eMODIS in the Kenya Livestock Insurance Program. The updated reNDVI product shows promise as a vegetation index that could address a pressing drought insurance challenge. |
| first_indexed | 2024-03-10T16:15:59Z |
| format | Article |
| id | doaj.art-c0dfcd4a35374d8ba4407ca0aa6715a0 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T16:15:59Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-c0dfcd4a35374d8ba4407ca0aa6715a02023-11-20T14:03:19ZengMDPI AGRemote Sensing2072-42922020-09-011218303110.3390/rs12183031Assessment of a Spatially and Temporally Consistent MODIS Derived NDVI Product for Application in Index-Based Drought InsuranceSara E. Miller0Emily C. Adams1Kel N. Markert2Lilian Ndungu3W. Lee Ellenburg4Eric R. Anderson5Richard Kyuma6Ashutosh Limaye7Robert Griffin8Daniel Irwin9Department of Atmospheric Science, The University of Alabama in Huntsville, 320 Sparkman Dr., Huntsville, AL 35805, USANASA SERVIR Science Coordination Office, Marshall Space Flight Center, 320 Sparkman Dr., Huntsville, AL 35805, USANASA SERVIR Science Coordination Office, Marshall Space Flight Center, 320 Sparkman Dr., Huntsville, AL 35805, USAThe Regional Centre for Mapping of Resources for Development, Kasarani, Nairobi 00618, KenyaNASA SERVIR Science Coordination Office, Marshall Space Flight Center, 320 Sparkman Dr., Huntsville, AL 35805, USANASA SERVIR Science Coordination Office, Marshall Space Flight Center, 320 Sparkman Dr., Huntsville, AL 35805, USAKenya Ministry of Agriculture, Livestock, Fisheries, and Irrigation, P.O. Box 30028-00100, Cathedral Road, Nairobi 00100, KenyaEarth Science Branch, Marshall Space Flight Center, 320 Sparkman Dr., Huntsville, AL 35805, USADepartment of Atmospheric Science, The University of Alabama in Huntsville, 320 Sparkman Dr., Huntsville, AL 35805, USAEarth Science Branch, Marshall Space Flight Center, 320 Sparkman Dr., Huntsville, AL 35805, USAIn arid and semi-arid regions of Eastern and Southern Africa, drought can be devastating to pastoralists who depend on healthy vegetation for their herds. The Kenya Livestock Insurance Program (KLIP) addresses this challenge through its insurance program that relies on a vegetation index product derived from eMODIS NDVI (enhanced Normalized Difference Vegetation Index). Insurance payouts are triggered when index values fall below a certain threshold for a Unit Area of Insurance (UAI). The objective of this study is to produce an updated, cloud-based NDVI product, potentially allowing for earlier payouts that may help herders to prevent, minimize, or offset drought-induced losses. The new product, named reNDVI (rapid enhanced NDVI), provides an updated cloud filtering algorithm and brings the entire processing chain to the cloud. Access to the scripts used for the processing described and resulting data is openly available. To test the performance of the new product, we provide a robust evaluation of reNDVI and eMODIS NDVI and their derived payout indices against historical drought, payouts provided, and mortality data. The implications of potential payout differences are also discussed. The products show good comparability; the monthly average NDVI per UAI has correlation values over 0.95 and MAPD under 5% for most UAIs. However, there are moderate differences when assessing year-to-year payout amounts triggered. Because the payouts are currently calculated based on the 20th and first percentile of index values from 2003–2016, payouts are very sensitive to even small changes in NDVI. Where livestock mortality was available, payouts for reNDVI and eMODIS had similar correlations (r = 0.453 and r = 0.478, respectively) with mortality rates. Therefore, with the potential reduced latency and updated cloud filtering, the reNDVI product could be a suitable replacement for eMODIS in the Kenya Livestock Insurance Program. The updated reNDVI product shows promise as a vegetation index that could address a pressing drought insurance challenge.https://www.mdpi.com/2072-4292/12/18/3031NDVIKenyaindex-based insurancelivestock |
| spellingShingle | Sara E. Miller Emily C. Adams Kel N. Markert Lilian Ndungu W. Lee Ellenburg Eric R. Anderson Richard Kyuma Ashutosh Limaye Robert Griffin Daniel Irwin Assessment of a Spatially and Temporally Consistent MODIS Derived NDVI Product for Application in Index-Based Drought Insurance Remote Sensing NDVI Kenya index-based insurance livestock |
| title | Assessment of a Spatially and Temporally Consistent MODIS Derived NDVI Product for Application in Index-Based Drought Insurance |
| title_full | Assessment of a Spatially and Temporally Consistent MODIS Derived NDVI Product for Application in Index-Based Drought Insurance |
| title_fullStr | Assessment of a Spatially and Temporally Consistent MODIS Derived NDVI Product for Application in Index-Based Drought Insurance |
| title_full_unstemmed | Assessment of a Spatially and Temporally Consistent MODIS Derived NDVI Product for Application in Index-Based Drought Insurance |
| title_short | Assessment of a Spatially and Temporally Consistent MODIS Derived NDVI Product for Application in Index-Based Drought Insurance |
| title_sort | assessment of a spatially and temporally consistent modis derived ndvi product for application in index based drought insurance |
| topic | NDVI Kenya index-based insurance livestock |
| url | https://www.mdpi.com/2072-4292/12/18/3031 |
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