The use of small unmanned aircraft systems (sUAS) to acquire very high-resolution multispectral imagery has attracted growing attention recently; however, no systematic, feasible, and convenient radiometric calibration method has been specifically developed for sUAS remote sensing. In this research, we used a modified color infrared (CIR) digital single-lens reflex (DSLR) camera as the sensor and the DJI S800 hexacopter sUAS as the platform to collect imagery. Results show that the relationship between the natural logarithm of measured surface reflectance and image raw, unprocessed digital numbers (DNs) is linear and the y-intercept of the linear equation can be theoretically interpreted as the minimal possible surface reflectance that can be detected by each sensor waveband. The empirical line calibration equation for every single band image can be built using the y-intercept as one data point, and the natural log-transformed measured reflectance and image DNs of a gray calibration target as another point in the coordinate system. Image raw DNs are therefore converted to reflectance using the calibration equation. The Mann-Whitney U test results suggest that the difference between the measured and the predicted reflectance values of 13 tallgrass sampling quadrats is not statistically significant. The method theory developed in this study can be employed for other sUAS-based remote sensing applications.

This study examines the spatial and temporal patterns of the surface urban heat island (SUHI) intensity in the Phoenix metropolitan area and the relationship with land use land cover (LULC) change between 2000 and 2014. The objective is to identify specific regions in Phoenix that have been increasingly heated and cooled to further understand how LULC change influences the SUHI intensity. The data employed include MODerate-resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) 8-day composite June imagery, and classified LULC maps generated using 2000 and 2014 Landsat imagery. Results show that the regions that experienced the most significant LST changes during the study period are primarily on the outskirts of the Phoenix metropolitan area for both daytime and nighttime. The conversion to urban, residential, and impervious surfaces from all other LULC types has been identified as the primary cause of the UHI effect in Phoenix. Vegetation cover has been shown to significantly lower LST for both daytime and nighttime due to its strong cooling effect by producing more latent heat flux and less sensible heat flux. We suggest that urban planners, decision-makers, and city managers formulate new policies and regulations that encourage residential, commercial, and industrial developers to include more vegetation when planning new construction.