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Accurate measurement of the tree height and canopy cover density is important for forest biomass and management. Recently, Light Detection and Ranging (LIDAR) and Unmanned Aerial Vehicle (UAV) images have been used to estimate the tree height and canopy cover density for a forest stands. More so, UAV systems with autopilot functions, affordable Global Navigation Satellite System (GNSS) and Inertial Measurement Unit (IMU) have created new possibilities, aided by available photogrammetric programs. In this study, we investigated the possibility of data collection methods using an Aerial LIDAR Scanner (ALS) and an UAV together with a fieldworks to evaluate accurate the tree standard metrics in Singyeri, Gyeongjusi, and Gyeongsangbukdo province. The derived metrics via statistical analyses of the ALS and UAV data and validated by field measurements were compared to a published forest type map (scale 1:5000) by the Korea Forest Service; geared towards improving the forest attributes. We collected data and analyzed and compared them with existent the forest type map produced from an aerial photographs and a digital stereo plotter. The ALS data of around 19.5 points·m–2 were collected by an airplane, then processed and classified using the LAStools; while about 362 images of the UAV were processed via Structure from Motion algorithm in the Agisoft Metashape Pro. Thus, we calculated the metrics using the point clouds of both an ALS and an UAV, and then verified their similarity. The fieldwork was manually done on 110 sampled trees. Calculated heights of the UAV were 3.8~5.8 m greater than those for the ALS; and when correlated with the fieldwork, the UAV data overestimated, while the maximum height of the ALS data was more accurate. For the canopy cover, the ALS computed canopy cover was 10%~30% less than that of the UAV. However, the canopy cover above 2 m by an UAV was the best measurement for a forest canopy. Therefore, these results assert that the examined techniques are robust and can significantly complement methods of the conventional data acquisition for the forest type map.

& Many countries are increasing their research on monitoring technology to identify and systematically manage various domestic changes. In particular, the need for remote monitoring is increasing in response to climatic disasters, such as flooding, storms, and rising tides caused by global warming. We developed a smartphone-based environmental monitoring system that enables remote monitoring in any place and at any time. The overall system is composed of a 24-hour smartphonebased imaging system, a monitoring information management system to receive the monitoring information, and stereo image rectification software that provides lens distortion correction, geometric correction, and stereo matching of the monitoring images. The system was developed using the Samsung Galaxy S with the Android OS, as well as open source-based software and other hardware. It is easy to install, control remotely, and monitor the status of imaging devices. We assessed the accuracy of the micro-electro-mechanical system (MEMS) sensors of the smartphone to evaluate the applicability of our environmental monitoring system. The assessment was conducted via survey using metric cameras, a global positioning system receiver, a three-dimensional laser scanner and total station, geometric correction, and digital elevation models generated with camera internal elements, external elements, and ground control points. We demonstrated the effectiveness of the system, and showed that the accuracy of the MEMS sensor and camera calibration have a significant effect on image analysis.

This paper presents absolute radiometric calibration coefficients (gains) that explain the relationship between the digital number (DN) and at-sensor radiance for the multispectral camera (MSC) on Korea's first high-resolution satellite (KOMPSAT-2). Absolute radiometric calibration was performed using a reflectance-based method. In addition, the suitability of vicarious results from radiance-and reflectance-based validations was analyzed with reference to IKONOS and QuickBird images. The latter are spectrally similar to KOMPSAT-2 images and have been validated in a large number of studies. For all bands, the R 2 values of fitted lines for the gain ranged from 0.82 to 0.94, representing an improvement compared to previous findings for the KOMPSAT-2 MSC. To analyze the suitability of the vicarious results, same-pixel at-sensor radiances across different spectral bands were compared. In all bands, except the red band of QuickBird, the at-sensor radiances of KOMPSAT-2 MSC were highly correlated with those of IKONOS and QuickBird. In addition, same-pixel comparisons of reflectance across different spectral bands showed that the slopes of the least-squares lines for each band were similar to the results of the radiance comparison. The standard deviation among top of atmosphere (TOA) reflectances was within 0.019 for all bands. To calculate the tasseled cap transformation (TCT) coefficients for the KOMPSAT-2 MSC, an empirical method was applied using radiometric normalization. The results were similar to those obtained using the TCT coefficients for IKONOS and QuickBird in the brightness, greenness, and wetness components. The TCT images showed similar patterns. The absolute radiometric calibration coefficients presented here appear to be a good standard for maintaining the optical quality of the KOMPSAT-2 MSC, for which prelaunch, on-board, and vicarious calibration data are lacking.