Ground-Based NDVI Network: Early Validation Practice with Sentinel-2 in South Korea.

As satellite launching increases worldwide, uncertainty quantification for satellite data becomes essential. Misunderstanding satellite data uncertainties can lead to misinterpretations of natural phenomena, emphasizing the importance of validation. In this study, we established a tower-based network equipped with multispectral sensors, SD-500 and SD-600, to validate the satellite-derived NDVI product. Multispectral sensors were installed at eight long-term ecological monitoring sites managed by NIFoS. High correlations were observed between both multispectral sensors and a hyperspectral sensor, with correlations of 0.76 and 0.92, respectively, indicating that the calibration between SD-500 and SD-600 was unnecessary. High correlations, 0.8 to 0.96, between the tower-based NDVI with Sentinel-2 NDVI, were observed at most sites, while lower correlations at Anmyeon-do, Jeju, and Wando highlighting challenges in evergreen forests, likely due to shadows in complex canopy structures. In future research, we aim to analyze the uncertainties of surface reflectance in evergreen forests and develop a biome-specific validation protocol starting from site selection. Especially, the integration of tower, drone, and satellite data is expected to provide insights into the effect of complex forest structures on different spatial scales. This study could offer insights for CAS500-4 and other satellite validations, thereby enhancing our understanding of diverse ecological conditions.

Calibration of BRDF Based on the Field Goniometer System Using a UAV Multispectral Camera.

The bidirectional reflectance distribution function (BRDF) is important for estimating the physical properties of a surface in remote sensing. In the laboratory, the BRDF can be estimated quickly and accurately using a goniometer, but it is very difficult to operate in the field. The purpose of this study was to evaluate whether estimating the BRDF with reasonable accuracy using an unmanned aerial vehicle (UAV) with a multispectral camera is possible in the field. Hemispherical reflectance was created from images taken using an UAV multispectral camera. The ground targets were four calibrated reference tarps (CRTs) of different reflectance, and the UAV was operated five times. Down-welling irradiance for reflectance calculation was measured in two ways: a sunlight sensor was mounted on a UAV, and a spectroradiometer with a remote cosine receptor (RCR) was installed on the ground. The BRDF was assessed through the anisotropy factor (ANIF) of the CRT reflectance derived from the collected data. As a result, the irradiance data for the reflectance calculation were more effective from the spectroradiometer with RCR on the ground than from the sunlight sensor mounted on an UAV. Furthermore, the high reflectance CRTs, ANIF, and BRDF had similar results. Therefore, when analyzing the BRDF, the effectiveness can be guaranteed when the reflectance of the target is over 21~46%, because a low reflectance tendency differs due to the adjacency effect. In addition, weather affects irradiance, so it is more effective to conduct fieldwork in clear weather.

Spatial and temporal characteristics of tropical nights in Seoul.

We examined the spatial and temporal characteristics of tropical nights (TNs) in Seoul to determine whether land use factors increase the frequency of TN. The number of TN was derived using data from 23 Automatic Weathering Stations (AWS) in Seoul for 1998-2006, and 26 AWS in Seoul and nine Gangnam-gu stations for 2007-2013. The results show that the number of TN recorded in the Seoul Automatic Synoptic Observation System (ASOS) gradually increased from 1971 to 2013. TN occurred most frequently in early August, followed by mid-August, late July, late August, mid-July, early July, early September, and mid-September. The largest annual average difference occurred between Gangnam Station and Yeomgokdong, in spite of the short physical distance (4.5 km) between two stations at Gangnam-gu. There were more TNs at high-rise buildings and commercial business district (CBD) areas with low sky view factors (SVF) than in mountain foothill areas.

Investigation of drought-vulnerable regions in North Korea using remote sensing and cloud computing climate data.

Drought is one of the most severe natural disasters in the world and leads to serious challenges that affect both the natural environment and human societies. North Korea (NK) has frequently suffered from severe and prolonged droughts since the second half of the twentieth century. These droughts affect the growing conditions of agricultural crops, which have led to food shortages in NK. However, it is not easy to obtain ground data because NK is one of the most closed-off societies in the world. In this situation, remote sensing (RS) techniques and cloud computing climate data (CCCD) can be used for drought monitoring in NK. RS-derived drought indices and CCCD were used to determine the drought-vulnerable regions in the spring season in NK. After the results were compared and discussed, the following conclusions were derived: (1) 10.0% of the total area of NK is estimated to be a drought-vulnerable region. The most susceptible regions to drought appear in the eastern and western coastal regions, far from BaekDu-DaeGan (BDDG), while fewer drought regions are found near BDDG and the Nahngrim Mountains. The drought-vulnerable regions are the coastal regions of South Hamgyong Province, North Hamgyong Province, South Pyongan Province, and South Hwanghae Province. The latter region is the food basket of NK. (2) In terms of land cover, the drought-vulnerable regions mainly consisted of croplands and mixed forest.

Investigating flood susceptible areas in inaccessible regions using remote sensing and geographic information systems.

Every summer, North Korea (NK) suffers from floods, resulting in decreased agricultural production and huge economic loss. Besides meteorological reasons, several factors can accelerate flood damage. Environmental studies about NK are difficult because NK is inaccessible due to the division of Korea. Remote sensing (RS) can be used to delineate flood inundated areas in inaccessible regions such as NK. The objective of this study was to investigate the spatial characteristics of flood susceptible areas (FSAs) using multi-temporal RS data and digital elevation model data. Such study will provide basic information to restore FSAs after reunification. Defining FSAs at the study site revealed that rice paddies with low elevation and low slope were the most susceptible areas to flood in NK. Numerous sediments from upper streams, especially streams through crop field areas on steeply sloped hills, might have been transported and deposited into stream channels, thus disturbing water flow. In conclusion, NK floods may have occurred not only due to meteorological factors but also due to inappropriate land use for flood management. In order to mitigate NK flood damage, reforestation is needed for terraced crop fields. In addition, drainage capacity for middle stream channel near rice paddies should be improved.