Photographic and videographic observations for determining and mapping the response of cotton to soil salinity

Better ways are needed to assess the extent and severity of soil salinity in fields in terms of economic impact on crop production and effectiveness of reclamation efforts. Procedures to help meet these needs were developed from soil salinity, plant height and boll counts, and digitized color infrared aerial photography and videography acquired during midboll set development stage for four salt-affected cotton (Gossypium hirsutum, L. ) fields in the San Joaquin Valley of California. Unsupervised classification procedures were used to produce seven-category spectral maps by field. Regression equations were developed from salinity measurements in the surface 30 cm (EC1) at 100–200 sample sites per field and the photography and videography digital counts at those same sites. The equations were used to estimate the salinity of each of the approximately 100,000 pixels per field, and the salinity categories corresponding to the spectral ones were mapped. The spectral classification maps and the estimated salinity maps corresponded well. Boll counts, made at about 20 sites per field, were converted to lint yield and regressed on NDVI from both the photography and videography; the correlation coefficient (r ) was 0.72 for video and 0.73 for the photographic data. Lint yields decreased by 43 ± 10 kg ha −1 per dS m −1 increase in EC1, or $52 ± 12 ha −1 at current market prices. Our results illustrate very practical ways to combine image analysis capability, spectral observations, and ground truth to map and quantify the severity of soil salinity and its effects on crops.