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Fractional green canopy cover (FGCC) is a key diagnostic variable that can be used to estimate canopy development, light interception, and evapotranspiration partitioning. Available image analysis tools for quantifying FGCC are time-consuming or expensive and cannot analyze video. Our objective was to develop a simple, accurate, and rapid tool to analyze FGCC from images and videos. Th is tool, called Canopeo, was developed using Matlab and is based on color ratios of red to green (R/G) and blue to green (B/G) and an excess green index (2G-R-B). Th e output from this tool was compared to that from two soft ware packages widely used to analyze FGCC, SamplePoint, and SigmaScan Pro. Canopeo's image processing speed was 20 to 130 times faster than SigmaScan and 75 to 2500 times faster than SamplePoint. Canopeo correctly classifi ed 90% of pixels when compared to SamplePoint. Root mean squared diff erence

The soil thermal properties—heat capacity (C), thermal diffusivity (α), and thermal conductivity (λ)—are important in many agricultural, engineering, and meteorological applications. Soil thermal properties are largely dependent on the volume fraction of water (θ), volume fraction of solids (vs), and volume fraction of air (na) in the soil. In many natural settings θ, vs, and na vary greatly over time and space, but data showing the effects of these variations on thermal properties are not readily available. We used a heat‐pulse method to measure the thermal properties of 59 packed columns of four medium‐textured soils covering large ranges of θ, vs, and na The measured data reveal the commonly overlooked but dominant influence of na on soil thermal properties. Notably, the measurements show that the λ of these soils at 20°C can be accurately described as a decreasing linear function of na Good agreement exists between the measured data and common models for λ and C