A New Remote-Sensing Indicator for Measuring Degree of Crop Damage due to Natural Disasters

Natural disasters, such as flood and drought, can significantly damage crops, resulting in significant yield loss. A number of remote sensing-based methods have been proposed to assess the degree of crop damage due to natural disasters. Many of them rely on the NDVI temporal curve of entire season to assess the crop damage. However, such methods cannot be used to assess the crop damage immediately after a natural disaster since the seasonal NDVI temporal curve is not available. To overcome this problem, an alternative indicator has been proposed to measure the degree of crop damage. The indictor, called Disaster Vegetation Damage Index (DVDI), is based on measuring the difference of vegetation condition before and after a disaster. There are two steps to calculate DVDI: 1). A modified VCI, mVCI = (NDVI – NDVIm)/(NDVImax-NDVIm), is proposed, where NDVIm is the median value of NDVI for the pixel from the historic records of NDVI, NDVImax is the max NDVI value for the pixel from the historic records, and NDVI is the current value for the pixel. mVCI > 0 indicates the vegetation growth is better than historical normal, and <0 indicates growth is worse than the normal. The reasons to modify the normal VCI equation are: a) NDVImin are often contaminated by clouds etc., while NDVIm is more reliable and stable; b) the daily median NDVI value based on past 17-year records of MODIS NDVI are easy to be calculated; 2) Disaster Vegetation Damage Index (DVDI) is proposed: DVDI = mVCIa – mVCIb, where, mVCIa is the mVCI value immediately after a disaster, and mVCIb is mVCI value immediately before the disaster. DVDI value > 0 indicates no damage to the crops, and <0 indicates the degree of damage. Since the DVDI is calculated just for the disaster period, any change can reasonably be attributed to the disaster. Immediately here means 1-2, or maybe 3 weeks before and after the flood events. In order to further identify the degree of damage, the DVDI values can be further categorized into the following categories: 0: no damage; 1: slight damage; 2: moderate damage; 3: Severe damage; 4: Extreme damage; 5: Exceptional Damage. Historical yield data can be used to establish the relationship between DVDI values and percentage of crop loss. In return, this also helps in defining the range of values for crop damage categories based on DVDI. With the assumption that disasters of the same type and magnitude will cause the same degree of damages to same type of crops at same phonological stages, regardless where the disasters happen, flood-induced crop yield loss models of corn and soybean have been established based on historic flood events in the past 17 years. The models have been applied to the 2011 Missouri River flood in Iowa and the 2016 Louisiana flood to examine the method. Results indicate that the DVDI method can reach to 95% accuracy in estimating crop loss at county level. The drought-induced crop loss models are being established. In conclusion, it is found that the proposed DVDI is an effective and easily implementable method for the rapid assessment of crop damage due to natural disasters.