• Journal of the Korean earth science society
• /
• v.34 no.7
• /
• pp.727-737
• /
• 2013

The purpose of this study was to investigate the middle school students' perception and their learning satisfaction in SMART learning based science instruction. Three types of modules on the solar system and lunar phases unit at the middle school level were developed and lessons on each module were taught to 207 student participants. All participants were provided with tabletPC(iPad2) with iOS5 installed, and using astronomy app Solar Walk, mirroring function, QR code, and Google Presentation, the lessons were carried out both in classroom and at home. The instrument for assessing students' perception on the SMART learning-based instruction was developed based on 4 factors including Self-directed, Motivation, Adaptiveness, and Technology Embedded, with a Likert scale from 1-5 on 20 items. The learning satisfaction survey instrument was originally from Keller's work (1987), and its test items were adapted and modified. To reveal the perception and learning satisfaction about SMART learning-based science lessons, the participants were comparatively analyzed by gender and science achievement levels. Results indicated that male students showed positive perception for the SMART learning-based instruction. Group with higher science achievement scores showed more positive perception of the SMART learning-based instruction in terms of Self-directed and Motivation factor. Also, the learning satisfaction of male students was higher than female students and group with higher academic ability more satisfied with the SMART learning-based instruction than the low group. The results provide implications for future development of programs and help set a direction of increasing the use of a SMART learning-based science in school.

• Korean Journal of Remote Sensing
• /
• v.37 no.3
• /
• pp.449-461
• /
• 2021

Analysis Ready Data (ARD) for optical satellite images represents a pre-processed product by applying spectral characteristics and viewing parameters for each sensor. The atmospheric correction is one of the fundamental and complicated topics, which helps to produce Top-of-Atmosphere (TOA) and Top-of-Canopy (TOC) reflectance from multi-spectral image sets. Most remote sensing software provides algorithms or processing schemes dedicated to those corrections of the Landsat-8 OLI sensors. Furthermore, Google Earth Engine (GEE), provides direct access to Landsat reflectance products, USGS-based ARD (USGS-ARD), on the cloud environment. We implemented the Orfeo ToolBox (OTB) atmospheric correction extension, an open-source remote sensing software for manipulating and analyzing high-resolution satellite images. This is the first tool because OTB has not provided calibration modules for any Landsat sensors. Using this extension software, we conducted the absolute atmospheric correction on the Landsat-8 OLI images of Railroad Valley, United States (RVUS) to validate their reflectance products using reflectance data sets of RVUS in the RadCalNet portal. The results showed that the reflectance products using the OTB extension for Landsat revealed a difference by less than 5% compared to RadCalNet RVUS data. In addition, we performed a comparative analysis with reflectance products obtained from other open-source tools such as a QGIS semi-automatic classification plugin and SAGA, besides USGS-ARD products. The reflectance products by the OTB extension showed a high consistency to those of USGS-ARD within the acceptable level in the measurement data range of the RadCalNet RVUS, compared to those of the other two open-source tools. In this study, the verification of the atmospheric calibration processor in OTB extension was carried out, and it proved the application possibility for other satellite sensors in the Compact Advanced Satellite (CAS)-500 or new optical satellites.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.6-7
• /
• 2021

Vegetation development in rivers is one of the important issues not only in academic fields such as geomorphology, ecology, hydraulics, etc., but also in river management practices. The problem of river vegetation is directly connected to the harmony of conflicting values of flood management and ecosystem conservation. In Korea, since the 2000s, the issue of river vegetation and land formation has been continuously raised under various conditions, such as the regulating rivers downstream of the dams, the small eutrophicated tributary rivers, and the floodplain sites for the four major river projects. In this background, this study proposes a method for classifying the distribution of vegetation in rivers based on remote sensing data, and presents the results of applying this to the Naeseong Stream. The Naeseong Stream is a representative example of the river landscape that has changed due to vegetation development from 2014 to the latest. The remote sensing data used in the study are images of Sentinel 1 and 2 satellites, which is operated by the European Aerospace Administration (ESA), and provided by Google Earth Engine. For the ground truth, manually classified dataset on the surface of the Naeseong Stream in 2016 were used, where the area is divided into eight types including water, sand and herbaceous and woody vegetation. The classification method used a random forest classification technique, one of the machine learning algorithms. 1,000 samples were extracted from 10 pre-selected polygon regions, each half of them were used as training and verification data. The accuracy based on the verification data was found to be 82~85%. The model established through training was also applied to images from 2016 to 2020, and the process of changes in vegetation zones according to the year was presented. The technical limitations and improvement measures of this paper were considered. By providing quantitative information of the vegetation distribution, this technique is expected to be useful in practical management of vegetation such as thinning and rejuvenation of river vegetation as well as technical fields such as flood level calculation and flow-vegetation coupled modeling in rivers.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_1
• /
• pp.481-493
• /
• 2023

In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.36 no.3
• /
• pp.26-36
• /
• 2018

This study aims to examine the characteristics of landscape through the analysis of location and the landscape of Gugok while also conducting the empirical study through the literature review, field study, and digital analysis of the Okgung Gugok. Oksan Gugok is a set of songs set in Ogsan Creek(玉山川)or Jagyese Creek(紫溪川, 紫玉山), which flows in front of the Oksan Memorial Hall(李彦迪), which is dedicated to the Lee Eong-jeok (李彦迪). We first ascertained the location and configuration of Oksan Gogok. Second, we confirmed the accurate location of Oksan Gogok by utilizing the digital topographic map of Oksan Gogok which was submitted by Google Earth Pro and Geographic Information Center as well as the length of the longitude of the gravel measured by the Trimble Juno SB GPS. Through the study of the literature and the field investigation, The results of the study are as follows. First, Yi Eonjeok was not a direct composer of Oksan Gugok, nor did he produce "Oksan Gugokha(Music)". Lee Ia-sung(李野淳), the ninth Youngest Son of Tweo-Kye, Hwang Lee, visited the "Oksan Gugokha" in the spring of 1823(Sunjo 23), which was the 270th years after the reign of Yi Eonjeok. At this time, receiving the proposal of Ian Sung, Lee Jung-eom(李鼎儼), Lee Jung-gi(李鼎基), and Lee Jung-byeong(李鼎秉), the descendants of Ian Sung set up a song and created Oksan Gugok Music. And the Essay of Oksan Travel Companions writted by Lee Jung-gi turns out being a crucial data to describe the situation when setting up the Ok-San Gugok. Second, In the majority of cases, Gogok Forest is a forest managed by a Confucian Scholar, not run by ordinary people. The creation of "Oksan Bugok Music" can be regarded as an expression of pride that the descendants of Yi Eonjeok and Lee Hwang, and next generation of several Confucian scholars had inherited traditional Neo-Confucian. Third, Lee Jung-eom's "Oksan Donghaengki" contains a detailed description of the "Oksan Gugokha" process and the process of creating a song. Fourth, We examined the location of one to nine Oksan songs again. In particular, eight songs and nine songs were located at irregular intervals, and eight songs were identified as $36^{\circ}01^{\prime}08.60^{{\prime}{\prime}}N$, $129^{\circ}09^{\prime}31.20^{{\prime}{\prime}}E$. Referring to the ancient kingdom of Taojam, the nine-stringed Sainam was unbiased as a lower rock where the two valleys of the East West congregate. The location was estimated at $36^{\circ}01^{\prime}19.79^{{\prime}{\prime}}N$, $129^{\circ}09^{\prime}30.26^{{\prime}{\prime}}E$. Fifth, The landscape elements and landscapes presented in Lee Jung-eom's "Oksan Gugokha" were divided into form, semantic and climatic elements. As a result, Lee Jung-eom's Cho Young-gwan was able to see the ideal of mountain water and the feeling of being idle in nature as well as the sense of freedom. Sixth, After examining the appearance of the elements and the frequency of the appearance of the landscape, 'water' and 'mountain' were the absolute factors that emphasized the original curved environment at the mouth of Lee Jung-eom. Therefore, there was gugokga can gauge the fresh ideas(神仙思想)and retreat ever(隱居思想). This inherent harmony between the landscape as well as through the mulah any ideas that one with nature and meditation, Confucian tube.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.14 no.2
• /
• pp.905-910
• /
• 2013

Road facility has the high possibility of being damaged or destroyed due to continuous pass of the vehicles, overloaded vehicles, traffic accidents and so on and stormwater manhole, sewerage manhole that are installed on the road may cause the functional degradation in case of periodic pavement of the road. So management through establishing DB of road facility and efficient updating plan are required. Thus, this study used DGPS camera for efficient establishment and improvement of road facility DB. Applicability of DGPS camera could be suggested by satisfying the allowable accuracy required for establishing DB of road facility through the comparative analysis with the result of establishment of existing road facility DB and the process of DB establishment by existing total solution could be improved through process analysis. And the existing DB of road facility was improved so that the present conditions of surrounding topography and road facility can be grasped by developing the module that can add the images of road facility to digital map and Google Earth-based KML Builder. It is expected that road facility service that provides various information can be available if the spatial data of each local self-governing body and study of automation that utilizes DGPS camera images are accomplished hereafter.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.24 no.2
• /
• pp.91-101
• /
• 2021

This study attempted to conduct the study from a macro perspective more specifically through the temporal and spatial analysis of Minbuk villages according to a change in a Civilian Control Line, such as a social and spatial distribution and a change of the existing Minbuk villages. To this end, this study conducted the spatial analysis for the change in the Minbuk villages according to the adjustment of the Civilian Control Line in time series by using a map of the Armistice Agreement Vol. 2, Google Earth, a digital cadastral map, an administrative district map, and the like are used as spatial data, and summarizing and constructing, as attribute data, a statistical yearbook, Ministry of Defense and Cheorwon-Gun notification data, a Land Use Regulation Information System, and cadastral map attribute information. After the enactment of the Military Facility Protection Act, the analysis was performed on a 20-year basis based on the 1976 statistical yearbook of which the Civilian Control Line was drawn. As a result, the total area of the Civilian Control Zone in Cheorwon from 1975 to 2015 decreased by 105.8 km², and 9 of 14 Minbuk villages were released and only 6 villages existed. The unoccupied villages were analyzed as 14 villages, 10 fewer than the existing surveyed or statistical villages. The movement of the Civilian Control Line to the north may disappear the unique characteristics of the Minbuk villages but should be done carefully as it is closely related to the lives of the current residents, and policies should be established in terms of sustainable development and conservation of the villages. This study is significant in conducting the temporal and spatial analysis, which is the basis of the Minbuk regions and the Minbuk villages, and may be used as basic data necessary for subsequent analysis study.

• Journal of Korean Society of Forest Science
• /
• v.111 no.4
• /
• pp.667-675
• /
• 2022

Agroforestry is an ecological and economic land-use system that enables sustainable agriculture by combining forestry, agriculture, and livestock industries. North Korea chose agroforestry as a strategy for the restoration of sloping land and deforested land. Agroforestry was proposed for the inter-Korean forest cooperation subcommittee meeting and is currently highlighting carbon removal and promoting the '2050 Carbon Neutral Strategy' and 'Korea Peninsula Green Détente.' The study area, Suan-gun, Hwanghaebuk-do, is a constant deforestation monitoring area and a pilot site for management by the International Center for Research in Agroforestry. The requirements for agroforestry were analyzed through literature analysis. The agroforestry site-suitability map was visualized by applying GIS overlap analysis. Approximately 8,839 ha of sloping area was selected as suitable for agroforestry management, which is about 15% of Suan. We compared the map with Google Earth images and visually detected the land use status, such as agroforestry in Suan, to verify the results. As a future study, we will consider both natural-environment and socioeconomic factors and evaluate the relative importance of the factors to produce a high-accuracy agroforestry sitesuitability map at the national scale with the goal of producing basic data for the inter-Korea forest cooperation policy for long-term goals.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.25 no.3
• /
• pp.182-196
• /
• 2023

Accurate and timely estimation of crop yields is crucial for various purposes, including global food security planning and agricultural policy development. Remote sensing techniques, particularly using vegetation indices (VIs), have show n promise in monitoring and predicting crop conditions. However, traditional VIs such as the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) have limitations in capturing rapid changes in vegetation photosynthesis and may not accurately represent crop productivity. An alternative vegetation index, the near-infrared reflectance of vegetation (NIRv), has been proposed as a better predictor of crop yield due to its strong correlation with gross primary productivity (GPP) and its ability to untangle confounding effects in canopies. In this study, we investigated the potential of NIRv in estimating crop yield, specifically for corn and soybean crops in major crop-producing regions in 14 states of the United States. Our results demonstrated a significant correlation between the peak value of NIRv and crop yield/area for both corn and soybean. The correlation w as slightly stronger for soybean than for corn. Moreover, most of the target states exhibited a notable relationship between NIRv peak and yield, with consistent slopes across different states. Furthermore, we observed a distinct pattern in the yearly data, where most values were closely clustered together. However, the year 2012 stood out as an outlier in several states, suggesting unique crop conditions during that period. Based on the established relationships between NIRv peak and yield, we predicted crop yield data for 2022 and evaluated the accuracy of the predictions using the Root Mean Square Percentage Error (RMSPE). Our findings indicate the potential of NIRv peak in estimating crop yield at the county level, with varying accuracy across different counties.

• Journal of the Korean earth science society
• /
• v.34 no.6
• /
• pp.515-523
• /
• 2013

The eastern coast of South Korea is expected to be damaged by volcanic ash when Mt. Baekdusan volcano erupts. Even if the amount of volcanic ash is small, it can be fatal on the agricultural sector withering many plants and causing soil acidification. Thus, in this paper, we aim to estimate agricultural losses caused by the volcanic ash and to visualize them with Google map. To estimate the volcanic ash losses, a damage assessment model is needed. As the volcanic ash hazard depends on the kind of a crops and the ash thickness, the fragility function of damage assessment model should represent the relation between ash thickness and damage rate of crops. Thus, we model the fragility function using the damage rate for each crop of RiskScape. The volcanic ash losses can be calculated with the agricultural output and the price of each crop using the fragility function. This paper also represents the estimated result of the losses in Gangwon province, which is most likely to get damaged by volcanic ashes in Korea. According to the result with gross agricultural output of Gangwon province in 2010, the amount of volcanic ash losses runs nearly 635,124 million wons in Korean currency if volcanic ash is accumulated over four millimeters. This amount represents about 50% of the gross agricultural output of Gangwon province. We consider the damage only for the crops in this paper. However, a volcanic ash fall has the potential to damage the assets for a farm, including the soil fertility and installations. Thus, to estimate the total amount of volcanic ash damage for the whole agricultural sectors, these collateral damages should also be considered.