SACRA – a method for the estimation of global high-resolution crop calendars from a satellite-sensed NDVI

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ID: 102668
2015
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Abstract
To date, many studies have performed numerical estimations of biomass production and agricultural water demand to understand the present and future supply–demand relationship. A crop calendar (CC), which defines the date or month when farmers sow and harvest crops, is an essential input for the numerical estimations. This study aims to present a new global data set, the SAtellite-derived CRop calendar for Agricultural simulations (SACRA), and to discuss advantages and disadvantages compared to existing census-based and model-derived products. We estimate global CC at a spatial resolution of 5 arcmin using satellite-sensed normalized difference vegetation index (NDVI) data, which corresponds to vegetation vitality and senescence on the land surface. Using the time series of the NDVI averaged from three consecutive years (2004–2006), sowing/harvesting dates are estimated for six crops (temperate-wheat, snow-wheat, maize, rice, soybean and cotton). We assume time series of the NDVI represent the phenology of one dominant crop and estimate CCs of the dominant crop in each grid. The dominant crops are determined using harvested areas based on census-based data. The cultivation period of SACRA is identified from the time series of the NDVI; therefore, SACRA considers current effects of human decisions and natural disasters. The difference between the estimated sowing dates and other existing products is less than 2 months (< 62 days) in most of the areas. A major disadvantage of our method is that the mixture of several crops in a grid is not considered in SACRA. The assumption of one dominant crop in each grid is a major source of discrepancy in crop calendars between SACRA and other products. The disadvantages of our approach may be reduced with future improvements based on finer satellite sensors and crop-type classification studies to consider several dominant crops in each grid. The comparison of the CC also demonstrates that identification of wheat type (sowing in spring or fall) is a major source of error in global CC estimations.
Reference Key
kotsuki2015sacrahydrology Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Kotsuki, S.;Tanaka, K.;
Journal hydrology and earth system sciences
Year 2015
DOI
DOI not found
URL
http://www.hydrol-earth-syst-sci.net/19/4441/2015/hess-19-4441-2015.pdf
Keywords
Technology Science environmental sciences agriculture water supply for domestic and industrial purposes geography. anthropology. recreation hydraulic engineering environmental technology. sanitary engineering anthropology recreationenvironmental sciences sanitary engineeringgeography technologyenvironmental technology

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