Historical extension of operational NDVI products for livestock insurance in Kenya

International Journal of Applied Earth Observation and Geoinformation

Volumn 28, Issue 1, 2014, Pages 238-251

  Vrieling, Anton ^a   Meroni, Michele ^b   Shee, Apurba ^c   Mude, Andrew G ^c   Woodard, Joshua ^d   de Bie, C A J M ^a   Rembold, Felix ^b  

^a UNIVERSITY OF TWENTE   (Netherlands)

^b JOINT RESEARCH CENTRE   (Italy)

^c INTERNATIONAL LIVESTOCK RESEARCH INSTITUTE   (Kenya)

^d Department of Obstetrics Gynecology   (United States)

Author keywords

AVHRR; Index insurance; Intercalibration; MODIS; NDVI; SPOT

Indexed keywords

ARID ENVIRONMENT; AVHRR; DROUGHT; INSURANCE SYSTEM; LIVESTOCK; MODIS; MORTALITY; NDVI; SPOT;

KENYA;

EID: 84897401040     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2013.12.010     Document Type: Article

References (60)

1. Anyamba, A., Chretien, J.-P., Small, J., Tucker, C.J., Formenty, P.B., Richardson, J.H., Britch, S.C., Schnabelf, D.C., Erickson, R.L., Linthicum, K.J., 2009. Prediction of a Rift Valley fever outbreak. Proceedings of the National Academy of Sciences of the United States of America 106, 955-959.
2. Atzberger, C., Eilers, P.H.C., 2011. A time series for monitoring vegetation activity and phenology at 10-daily time steps covering large parts of South America. International Journal of Digital Earth 4, 365-386.
3. Atzberger, C., Klisch, A., Mattiuzzi, M., Vuolo, F., 2014. Phenological metrics derived over the European continent from NDVI3g data and MODIS time series. Remote Sensing 6, 257-284.
4. Baltagi, B.H., 2008. Econometric Analysis of Panel Data, fourth ed. John Wiley & Sons Ltd., Chichester, West Sussex, UK.
5. Barnett, B.J., Barrett, C.B., Skees, J.R., 2008. Poverty traps and index-based risk transfer products. World Development 36, 1766-1785.
6. Barrett, C.B., Barnett, B.J., Carter, M.R., Chantarat, S., Hansen, J.W., Mude, A.G., Osgood, D., Skees, J.R., Turvey, C.G., Ward, M.N., 2007. Poverty Traps and Climate Risk: Limitations and Opportunities of Index-Based Risk Financing. IRI Technical Report No. 07-02.
7. Barrett, C.B., Marenya, P.P., McPeak, J., Minten, B., Murithi, F., Oluoch-Kosura, W., Place, F., Randrianarisoa, J.C., Rasambainarivo, J., Wangila, J., 2006. Welfare dynamics in rural Kenya and Madagascar. Journal of Development Studies 42, 248-277.
8. Bell, A.R., Osgood, D.E., Cook, B.I., Anchukaitis, K.J., McCarney, G.R., Greene, A.M., Buckley, B.M., Cook, E.R., 2013. Paleoclimate histories improve access and sustainability in index insurance programs. Global Environmental Change 23, 774-781.
9. Biener, C., 2013. Pricing in microinsurance markets. World Development 41, 132-144.
10. Binswanger-Mkhize, H.P., 2012. Is there too much hype about index-based agricultural insurance? The Journal of Development Studies 48, 187-200.
11. Bonifacio, R., Dugdale, G., Milford, J.R., 1993. Sahelian rangeland production in relation to rainfall estimates from Meteosat. International Journal of Remote Sensing 14, 2695-2711.
12. Brink, A.B., Eva, H.D., 2009. Monitoring 25 years of land cover change dynamics in Africa: a sample based remote sensing approach. Applied Geography 29, 501-512.
13. Brown, M.E., Lary, D.J., Vrieling, A., Stathakis, D., Mussa, H., 2008. Neural networks as a tool for constructing continuous NDVI time series from AVHRR and MODIS. International Journal of Remote Sensing 29, 7141-7158.
14. Brown, M.E., Osgood, D.E., Carriquiry, M.A., 2011. Science-based insurance. Nature Geoscience 4, 213-214.
15. Brown, M.E., Pinzón, J.E., Didan, K., Morisette, J.T., Tucker, C.J., 2006. Evaluation of the consistency of long-term NDVI time series derived from AVHRR, SPOTvegetation, SeaWiFS, MODIS, and Landsat ETM+ sensors. IEEE Transactions on Geoscience and Remote Sensing 44, 1787-1793.
16. Chantarat, S., Mude, A.G., Barrett, C.B., Carter, M.R., 2013. Designing index-based livestock insurance for managing asset risk in northern Kenya. Journal of Risk and Insurance 80, 205-237.
17. Chen, J., Jönsson, P., Tamura, M., Gu, Z.H., Matsushita, B., Eklundh, L., 2004. A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter. Remote Sensing of Environment 91, 332-344.
18. Coe, R., Stern, R.D., 2011. Assessing and addressing climate-induced risk in sub-Saharan rainfed agriculture: lessons learned. Experimental Agriculture 47, 395-410.
19. de Bie, C.A.J.M., Khan, M.R., Smakhtin, V.U., Venus, V., Weir, M.J.C., Smaling, E.M.A., 2011. Analysis of multi-temporal SPOT NDVI images for small-scale land-use mapping. International Journal of Remote Sensing 32, 6673-6693.
20. Funk, C., Budde, M.E., 2009. Phenologically-tuned MODIS NDVI-based production anomaly estimates for Zimbabwe. Remote Sensing of Environment 113, 115-125.
21. Gallo, K., Li, L., Reed, B., Eidenshink, J., Dwyer, J., 2005. Multi-platform comparisons of MODIS and AVHRR normalized difference vegetation index data. Remote Sensing of Environment 99, 221-231.
22. Gao, B.C., 2000. A practical method for simulating AVHRR-consistent NDVI data series using narrow MODIS channels in the 0.5-1.0 μm spectral range. IEEE Transactions on Geoscience and Remote Sensing 38, 1969-1975.
23. Gebrekirstos, A., Worbes, M., Teketay, D., Fetene, M., Mitloehner, R., 2009. Stable carbon isotope ratios in tree rings of co-occurring species from semi-arid tropics in Africa: patterns and climatic signals. Global and Planetary Change 66, 253-260.
24. Genovese, G., Vignolles, C., Nègre, T., Passera, G., 2001. A methodology for a combined use of normalised difference vegetation index and CORINE land cover data for crop yield monitoring and forecasting. A case study on Spain. Agronomie 21, 91-111.
25. Gutman, G., Masek, J.G., 2012. Long-term time series of the Earth's landsurface observations from space. International Journal of Remote Sensing 33, 4700-4719.
26. Hazell, P.R., Hess, U., 2010. Drought insurance for agricultural development and food security in dryland areas. Food Security 2, 395-405.
27. Homewood, K., Trench, P., Randall, S., Lynen, G., Bishop, B., 2006. Livestock health and socio-economic impacts of a veterinary intervention in Maasailand: infection-and-treatment vaccine against East Coast fever. Agricultural Systems 89, 248-271.
28. Huete, A., Didan, K., Miura, T., Rodriguez, E.P., Gao, X., Ferreira, L.G., 2002. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment 83, 195-213.
29. Jacobs, T., Borstlap, G., Bartholomé, E., Maathuis, B.H.P., 2008. DevCoCast in support of environmental management and sustainable development in Africa. In: Proceedings of the 7th AARSE Conference, Accra, Ghana, 6 pp.
30. James, M.E., Kalluri, S.N.V., 1994. The Pathfinder AVHRR land data set: an improved coarse resolution data set for terrestrial monitoring. International Journal of Remote Sensing 15, 3347-3363.
31. Jenkerson, C.B., Maiersperger, T., Schmidt, G., 2010. eMODIS: A User-Friendly Data Source. Open-File Report 2010-1055. USGS, 10 pp.
32. Leblois, A., Quirion, P., 2013. Agricultural insurances based on meteorological indices: realizations, methods and research challenges. Meteorological Applications 20, 1-9.
33. Little, P.D., Smith, K., Cellarius, B.A., Coppock, D.L., Barrett, C.B., 2001. Avoiding disaster: diversification and risk management among east African herders. Development and Change 32, 401-433.
34. Mahul, O., Skees, J., 2007. Managing Agricultural Risk at the Country Level: The Case of Index-Based Livestock Insurance in Mongolia. Policy Research Working Paper 4325, Washington, DC., pp. 37.
35. Meroni, M., Verstraete, M.M., Rembold, F., Urbano, F., Kayitakire, F., 2014. A phenology-based method to derive biomass production anomaly for food security monitoring in the Horn of Africa. International Journal of Remote Sensing (in press).
36. Miura, T., Huete, A., Yoshioka, H., 2006. An empirical investigation of cross-sensor relationships of NDVI and red/near-infrared reflectance using EO-1 hyperion data. Remote Sensing of Environment 100, 223-236.
37. Myneni, R.B., Asrar, G., 1994. Atmospheric effects and spectral vegetation indexes. Remote Sensing of Environment 47, 390-402.
38. Nkedianye, D., de Leeuw, J., Ogutu, J.O., Said, M.Y., Saidimu, T.L., Kifugo, S.C., Kaelo, D.S., Reid, R.S., 2011. Mobility and livestock mortality in communally used pastoral areas: the impact of the 2005-2006 drought on livestock mortality in Maasailand. Pastoralism 1, 17.
39. Norval, R.A.I., Perry, B.D., Gebreab, F., Lessard, P., 1991. East Coast fever: a problem of the future for the Horn of Africa. Preventive Veterinary Medicine 10, 163-172.
40. Onono, J.O., Wieland, B., Rushton, J., 2013. Productivity in different cattle production systems in Kenya. Tropical Animal Health and Production 45, 423-430.
41. Pedelty, J., Devadiga, S., Masuoka, E., Brown, M., Pinzon, J., Tucker, C., Roy, D., Junchang, J., Vermote, E., Prince, S., Nagol, J., Justice, C., Schaaf, C., Jicheng, L., Privette, J., Pinheiro, A., 2007. Generating a long-term land data record from the AVHRR and MODIS instruments. In: IEEE International on Geoscience and Remote Sensing Symposium, 2007 (IGARSS 2007), pp. 1021-1025.
42. Peel, M.C., Finlayson, B.L., McMahon, T.A., 2007. Updated world map of the Köppen-Geiger climate classification. Hydrology and Earth System Sciences 11, 1633-1644.
43. Pinzón, J.E., Tucker, C.J., 2014. A non-stationary 1981-2012 AVHRR NDVI3g time series. Remote Sensing (submitted for publication).
44. Rahman, H., Dedieu, G., 1994. SMAC: a simplified method for the atmospheric correction of satellite measurements in the solar spectrum. International Journal of Remote Sensing 15, 123-143.
45. Rojas, O., Vrieling, A., Rembold, F., 2011. Assessing drought probability for agricultural areas in Africa with coarse resolution remote sensing imagery. Remote Sensing of Environment 115, 343-352.
46. Sandmeier, S., Muller, C., Hosgood, B., Andreoli, G., 1998. Physical mechanisms in hyperspectral BRDF data of grass and watercress. Remote Sensing of Environment 66, 222-233.
47. Savitzky, A., Golay, M.J.E., 1964. Smoothing and differentiation of data by simplified least squares procedures. Analytical Chemistry 36, 1627-1639.
48. Song, Y., Ma, M., Veroustraete, F., 2010. Comparison and conversion of AVHRR GIMMS and SPOT VEGETATION NDVI data in China. International Journal of Remote Sensing 31, 2377-2392.
49. Steven, M.D., Malthus, T.J., Baret, F., Xu, H., Chopping, M.J., 2003. Intercalibration of vegetation indices from different sensor systems. Remote Sensing of Environment 88, 412-422.
50. Swets, D.L., Reed, B.C., Rowland, J.D., Marko, S.E.,1999. A weighted least-squares approach to temporal NDVI smoothing. In: Proceedings of the 1999 ASPRS Annual Conference. American Society of Photogrammetric Remote Sensing, Portland, OR, pp. 526-536.
51. Swinnen, E., Veroustraete, F., 2008. Extending the SPOT-VEGETATION NDVI time series (1998-2006) back in time with NOAA-AVHRR data (1985-1998) for southern Africa. IEEE Transactions on Geoscience and Remote Sensing 46, 558-572.
52. Trevennec, C., Pittiglio, C., Wainwright, S., Plee, L., Pinto, J., Lubroth, J., Martin, V., 2012. Rift Valley fever: vigilance needed in the coming months. EMPRES Watch 27, 1-8.
53. Trishchenko, A.P., 2009. Effects of spectral response function on surface reflectance and NDVI measured with moderate resolution satellite sensors: extension to AVHRR NOAA-17,18 and METOP-A. Remote Sensing of Environment 113, 335-341.
54. Trishchenko, A.P., Cihlar, J., Li, Z.Q., 2002. Effects of spectral response function on surface reflectance and NDVI measured with moderate resolution satellite sensors. Remote Sensing of Environment 81, 1-18.
55. Tucker, C.J., Pinzón, J.E., Brown, M.E., Slayback, D.A., Pak, E.W., Mahoney, R., Vermote, E.F., El Saleous, N., 2005. An extended AVHRR 8-km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data. International Journal of Remote Sensing 26, 4485-4498.
56. Turvey, C.G., McLaurin, M.K., 2012. Applicability of the normalized difference vegetation index (NDVI) in index-based crop insurance design. Weather, Climate, and Society 4, 271-284.
57. Vrieling, A., de Beurs, K.M., Brown, M.E., 2011. Variability of African farming systems from phenological analysis of NDVI time series. Climatic Change 109, 455-477.
58. Vrieling, A., de Leeuw, J., Said, M.Y., 2013. Length of growing period over Africa: variability and trends from 30 years of NDVI time series. Remote Sensing 5, 982-1000.
59. Vuolo, F., Mattiuzzi, M., Klisch, A., Atzberger, C., 2012. Data service platform for MODIS NDVI time series pre-processing at BOKU Vienna: current status and future perspectives. Earth Resources and Environmental Remote Sensing/GIS Applications III. Proceedings of SPIE 8538, 85380A.
60. Woodard, J., Shee, A., Mude, A.G., 2014. A spatial econometric approach to scalable index insurance against drought related livestock mortality in Kenya (in preparation).