Korean Journal of Remote Sensing

Quick links

Most View Most Download Archives Go to e-Submission

Automated Updates of Coordinates of Ground Control Points Through Tiepoints from Multiple Satellite Images

For utilization of satellite images, enhancing the geometric accuracy and the provision of accurate ground control points (GCPs) are essential. However, maintaining and updating numerous GCPs is time-consuming and costly, presenting considerable limitations. To improve these challenges, this study proposes an automated method to accurately adjust GCP height values using rational function model (RFM) bundle block adjustment with multiple satellite images. Tiepoints over multiple images were constructed through automated matching between satellite images and GCP chips. We converted true GCP heig...

Korean J. Remote Sens. 2024; 40(5): 419-429

An Active Subglacial Lake near Vostok Subglacial Lake in East Antarctica Discovered Using ALOS-2 Interferometry

Subglacial lakes, located beneath ice sheets, significantly influence ice dynamics, making the detection of their distribution and the monitoring of their fill and drain activities essential. This study focuses on the high-latitude regions near the Vostok subglacial lake in East Antarctica, an area highly probable for the presence of undiscovered subglacial lakes. We constructed two interferometric pairs of Advanced Land Observing Satellite-2 (ALOS-2) Phased-Array L-band Synthetic Aperture Radar-2 (PALSAR-2) Scanning SAR (ScanSAR) images with a 140-day temporal baseline and applied differentia...

Korean J. Remote Sens. 2024; 40(5): 431-444

Multi-Sensor Satellite Image Classification Using Random Forest Algorithm in Google Earth Engine: Application of CAS500-1 Image Sets

This study conducted multi-sensor image classification by utilizing Google Earth Engine (GEE) and applying satellite imagery from Compact Advanced Satellite 500-1 (CAS500-1), Sentinel-1, and Sentinel-2. The Land Use and Land Cover classification was performed using the Random Forest algorithm provided by GEE. The study experimented with various combinations of input data, integrating CAS500-1, Sentinel-1, and Sentinel-2 imagery with Normalized Difference Vegetation Index (NDVI) data from CAS500-1. The study area focused on the Goryeong County region in Gyeongsangbuk-do, and the satellite image...

Korean J. Remote Sens. 2024; 40(5): 445-453

Accuracy Assessment of Coastal Aquaculture Facility Detection Using Deep Learning Techniques

Due to declining fish catches caused by rapid climate change and advancements in aquaculture technology, the global demand for aquaculture products is continuously increasing. However, since the reckless expansion of facilities adversely affects the coastal ecosystem and fish stock prices, managing aquaculture facilities through periodic coastal environment monitoring is essential. This study analyzed the detection accuracy of shellfish aquaculture facilities in Gyeongsangnam-do using Sentinel-2 optical imageries and deep learning-based detection methodology. The DeepLabv3+, ResUNet++, and Att...

Korean J. Remote Sens. 2024; 40(5): 455-464

Study on Automated Forest Change Detection Using Medium-Resolution Satellites: The Case Study of Dogyemyeon, Samcheok City

Land use constantly changes due to climate change and human activities. Above all else, monitoring forests is crucial for global carbon management, particularly in the context of climate change. Land use changes in forested areas occur due to various factors such as development projects or natural disasters; forest fires are one of the primary drivers of large-scale forest loss. Therefore, it is essential to detect forest changes including forest fires accurately and to develop an automated system for periodic monitoring. In response, this study proposes a machine learning-based method for aut...

Korean J. Remote Sens. 2024; 40(5): 465-478

Generation of CAS500-4 Orthoimages Using Automatic GCP Extraction Method Based on Sentinel-2 Images

The Korean government plans to launch the CAS500-4 specialized for efficient management of the land. The CAS500-4 enables periodic monitoring of the Korean Peninsula with a spatial resolution of 5m along a 120 km swath width and a short revisit cycle of 3 days. To increase the usability of the CAS500-4, a process of removing geometric distortion is necessary. For this process, ground control points (GCPs) are used as key data. Acquiring GCPs through a field survey takes time and cost and cannot be achieved for inaccessible and overseas areas. In this study, we propose a method to automatically...

Korean J. Remote Sens. 2024; 40(5): 479-493

Parcel-Based Crop Type Classification in UAV Imagery with SAM for Smallholder Farms

Estimation of crop-specific cultivation area is a fundamental indicator in agricultural policy decision-making, as it helps to determine the production volume for a given year. For efficient surveying of large areas, remote sensing technologies using satellite imagery and unmanned aerial vehicle (UAV) imagery are increasingly being utilized for crop-type classification. In South Korea, where smallholder farms with small fields are predominant, the low spatial resolution of satellite images poses challenges, prompting the use of UAV imagery with higher spatial resolution. Deep learning-based cr...

Korean J. Remote Sens. 2024; 40(5): 495-506

Performance Comparison of Water Body Detection from Sentinel-1 SAR and Sentinel-2 Optical Imagery Using Attention U-Net Model

As global warming accelerates greenhouse gas emissions, the frequency and severity of abnormal weather events such as floods and droughts are increasing, complicating disaster management and amplifying socio-economic damage. In response, effective strategies for mitigating water-related disasters and proactively addressing climate change are essential, which can be achieved through the use of satellite imagery. This study aims to compare the water body detection performance of Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 optical imagery using the Attention U-Net model. Through this...

Korean J. Remote Sens. 2024; 40(5): 507-523

Comparative Analysis of Heatwave Mitigation Strategies Using UAV and Thermal Infrared Sensors according to Spatial and Temporal Conditions – For the Cool Roof of Case Study Jangyu Mugye-dong –

The purpose of this study is to quantitatively and spatiotemporally analyze the effects of cool roof installations on mitigating urban heat island (UHI) phenomena. By utilizing unmanned aerial vehicle (UAV) and thermal infrared sensor (TIR), the reduction in land surface temperature (LST) due to cool roofs, a key heat mitigation measure, was analyzed across different times of the day. The research was conducted in Jangyu Mugye-dong, Gimhae-si, Gyeongsangnam-do, where cool roofs were implemented as part of a pilot project aimed at mitigating UHI effects. High-resolution thermal images were capt...

Korean J. Remote Sens. 2024; 40(5): 525-537

Diagnosis of Chinese Cabbage Growth and Water Stress Using Time-Series Drone Imagery

The importance of growth and water management for open-field crops is increasing due to climate change. Although automatic irrigation systems based on soil moisture sensors are effective for water management, they have limitations in spatially representing the entire field. To supplement this, drone imagery can be utilized. In this study, we evaluated the response of outputs based on RGB, multispectral, and thermal imagery according to the growth stages and water status of Chinese cabbage. The normalized difference vegetation index (NDVI) was useful for monitoring the initial growth stage of c...

Korean J. Remote Sens. 2024; 40(5): 539-549

Optimal Hyperparameter Analysis of Segment Anything Model for Building Extraction Using KOMPSAT-3/3A Images

Extracting building information from Very-High-Resolution (VHR) satellite images is critical for urban mapping and monitoring. Traditional manual annotation methods are labor-intensive and costly, making automated solutions highly desirable. Segment Anything Model (SAM), a foundation model trained mostly on natural images, has recently shown high performance on diverse segmentation tasks. However, due to differences in perspective and the average size of objects in the images, SAM exhibits lower performance when extracting buildings from satellite imagery. These limitations, derived from diffe...

Korean J. Remote Sens. 2024; 40(5): 551-568

Atmospheric Correction Effects on the NDSI: Snow Detection Characteristics across Land Cover Types

The normalized difference snow index (NDSI) is a key indicator used to identify and map snow-covered areas by normalizing the reflectance difference between visible and shortwave infrared bands detected by satellite sensors. This study analyzed the effects of atmospheric correction on NDSI and snow cover detection characteristics according to land cover types. The study used data from the geostationary satellite (GK-2A/AMI) from November 2022 to April 2023. Comparing top-of-atmosphere (TOA) reflectance-based NDSI (NDSITOA) and top-of-canopy (TOC) reflectance-based NDSI (NDSITOC), NDSITOC gener...

Korean J. Remote Sens. 2024; 40(5): 569-577

Seasonal Variability of Solar-Induced Fluorescence and Correlation with Greenhouse Gas across Different Land Cover in East Asia

Climate change is a significant global issue recognized as being primarily caused by greenhouse gases, making it essential to understand the various factors affecting the carbon cycle for effective problem-solving. This study uses satellite data to analyze Solar-Induced Fluorescence (SIF), a key indicator of photosynthetic activity. It investigates differences across various land types based on Moderate Resolution Imaging Spectroradiometer (MODIS) data. The analysis revealed seasonal variations and higher photosynthetic indices in forested areas, suggesting the presence of robust photosyntheti...

Korean J. Remote Sens. 2024; 40(5): 579-588

Satellite-Based Coral Reef Habitat Mapping in Weno Island Using Water Column Corrected High Spatial Resolution Image

Coral reefs play significant roles in marine ecosystems, and recently, they have been experiencing degradation primarily due to global warming. Monitoring the coral reef ecosystem is crucial to rehabilitation and preventing further degradation. Here, we used high spatial resolution multispectral image data from the QuickBird sensor and in-situ measurements acquired around 2011 to derive a benthic habitat map around the coral reef ecosystem in Weno Island, Micronesia. Water column correction was performed to eliminate the effect of the light attenuation within the water column from the satellit...

Korean J. Remote Sens. 2024; 40(5): 589-600

Trend Analysis of Vegetation Index Anomaly in the Korean Peninsula Using Sentinel-2 and Definition of a Visualization Color Scheme

This study aims to analyze the vegetation index anomaly in the Korean Peninsula using Sentinel-2 satellite data from 2017 to 2023 and to define a visualization color scheme for vegetation index anomaly products of the CAS500-4. The study compared the impact of climate factors and local changes on vegetation index anomalies for 2022 and 2023, across different countries and land cover types. It was shown that the spring drought and abnormal temperatures of 2022 significantly impacted vegetation conditions. Additionally, the vegetation index anomaly data were statistically analyzed, and 11 color ...

Korean J. Remote Sens. 2024; 40(5): 601-615

Evaluation of Deep Learning-Based Water Bodies and Flooded Area Detection with Nanosatellites: The PlanetScope Satellite Imageries and HRNet Model

The continuous monitoring of water body is essential for efficient water resource management and the prevention of water-related disasters. Microsatellite and nanosatellite imageries provide a tool for continuous and accurate monitoring of water bodies at high spatial and temporal resolution. In this study, PlanetScope imagery with a resolution of 3.7 m and High-Resolution Network (HRNet) model were used to detect water bodies at dams and rivers in Korea, with the objective of evaluating the utility of water surface area monitoring. The HRNet model and the optimal band combinations of PlanetSc...

Korean J. Remote Sens. 2024; 40(5): 617-627

Application of GOCI to the Estimate of Habitat for Mackerel in the South Korea Exclusive Economic Zone

We estimated the habitat suitability index (HSI) for mackerel to examine the spatial distribution of mackerel catches within the Exclusive Economic Zone (EEZ) of South Korea from 2011 to 2019, using satellite-based environmental data and the amount of catch data information provided by the government. The HSI is well-regarded for its effectiveness in identifying and predicting fishing grounds. By integrating mackerel catch data with satellite-derived environmental variables including chlorophyll-a concentration (CHL), sea surface temperature (SST), sea surface height (SSH) and primary producti...

Korean J. Remote Sens. 2024; 40(5): 629-641

Reservoir Water Surface Area Estimation Using Sentinel-1 and Sentinel-2 Imagery

There are approximately 17,080 agricultural reservoirs distributed across South Korea, and maintaining these reservoirs requires significant costs and time. Accordingly, time series tracking of water surface area changes using satellite imagery has been proposed as a more efficient and economical method for managing reservoirs. This study analyzes reservoir surface areas using Sentinel-1 Synthetic Aperture Radar (SAR) and Sentinel-2 Multispectral Instrument (MSI) imagery and assesses the applicability of satellite data for reservoir maintenance. Sentinel-1 SAR analysis results show that except...

Korean J. Remote Sens. 2024; 40(5): 643-656

Evaluation of Surface Reflectance and Vegetation Indices Measured by Sentinel-2 Satellite Using Drone Considering Crop Type and Surface Heterogeneity

Satellite data are used in precision agriculture to optimize crop management. Thus, the planting pattern (e.g., flat and ridge-furrow) and crop type should be accurately reflected in the data. The purpose of this study was to identify the spatial characteristics of errors in the surface reflectance (SR) and vegetation index (VI) obtained from the Sentinel-2 satellite. Drone data were used to evaluate the suitability of the Sentinel-2 satellite for precision agriculture applications in agricultural fields. Four VIs (normalized difference vegetation index, green normalized difference vegetation ...

Korean J. Remote Sens. 2024; 40(5): 657-673

Evaluation of the Potential Use of Multimodal Models for Land Cover Classification

This study was conducted to evaluate the potential of a multimodal model for land cover classification. The performance of the Clipseg multimodal model was compared with two unimodal models including Convolutional Neural Network (CNN)-based Unet and Transformer-based Segformer for land cover classification. Using orthophotos of two areas (Area1 and Area2) in Wonju City, Gangwon Province, classification was performed for seven land cover categories (Forest, Cropland, Grassland, Wetland, Settlement, Bare Land, and Forestry-managed Land). The results showed that the Clipseg model demonstrated the...

Korean J. Remote Sens. 2024; 40(5): 675-689

History, Status, and Prospects of Remote Sensing in Korea

The Korean Society of Remote Sensing (KSRS) has reached the 40th year since its establishment. This special issue on ‘history, status, and prospects of remote sensing in Korea’ was published to review the achievement of the KSRS and remote sensing research in Korea at the milestone of 40 years. Eleven invited papers covered major segments of remote sensing in Korea. They reviewed the development of remote sensing science and technologies over the 40 years, summarized current activities, and suggested future plans for remote sensing in Korea. We hope to provide reach backgrounds and...

Korean J. Remote Sens. 2024; 40(5): 691-694

Current Status of Satellite Development and Application

Science and technology are advancing at an unprecedented pace, particularly space technology, where private sector-led innovations, including Earth Observation (EO) satellites, are driving rapid growth in the New Space era. The Korean Society of Remote Sensing (KSRS) has been pivotal in developing domestic remote sensing technology over the past 40 years publishing numerous high-quality research papers in the Korean Journal of Remote Sensing (KJRS). The Korea Multi-Purpose Satellite (KOMPSAT) series, developed under the Master Plan for the Promotion of Space Development, acquires high-resoluti...

Korean J. Remote Sens. 2024; 40(5): 695-712

History, Status, and Prospects of Remote Sensing in the Field of Meteorological Satellite in Korea

Remote sensing through meteorological satellites plays an essential role in monitoring hazardous weather conditions, providing critical data for numerical weather prediction, and contributing to climate change studies. In Korea, research in this field began in the 1980s, with early efforts focused on utilizing foreign satellite data for weather forecasting. Significant advancements were made in the 2000s with the development of Korea’s first geostationary meteorological satellite, the Communication, Ocean, and Meteorological Satellite (COMS). This satellite marked a milestone in Korea&rs...

Korean J. Remote Sens. 2024; 40(5): 713-726

Progress in Current Research and Applications of the Geostationary Ocean Color Imager Series (GOCI and GOCI-II): A Bibliometric Analysis

Since the launch of the Geostationary Ocean Color Imager (GOCI), the world’s first geostationary ocean color satellite, in 2010, and its successor, GOCI-II, in 2020, these satellites have made substantial contributions to advancing ocean color monitoring through hourly observations, enabling real-time environmental surveillance. The GOCI series has advanced ocean color satellite missions from the research level to the operational level, supporting a range of applications in marine and atmospheric monitoring. In this study, we systematically collected and analyzed 578 research papers rela...

Korean J. Remote Sens. 2024; 40(5): 727-739

Pioneering Air Quality Monitoring over East and Southeast Asia with the Geostationary Environment Monitoring Spectrometer (GEMS)

The Geostationary Environment Monitoring Spectrometer (GEMS) onboard the Geostationary Korea Multi-Purpose Satellite-2B (GEO-KOMPSAT-2B) satellite, launched in February 2020, represents a pioneering milestone in air quality monitoring across East and Southeast Asia. GEMS provides hourly data on atmospheric pollutants, including nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), volatile organic compounds such as formaldehyde (HCHO) and glyoxal (CHOCHO), as well as aerosols, all with high spatial resolution. The Environmental Satellite Center (ESC) of the National Institute of Environmen...

Korean J. Remote Sens. 2024; 40(5): 741-752

National Spatial Data Policy and Remote Sensing: Technological Advancements, Policy Implications, and Future Prospects

This paper provides a comprehensive review of the development of Korea’s national spatial data policy and the evolution of remote sensing technology, analyzing how their interrelationship has influenced land management and public policy formulation. Beginning with aerial photography-based national mapping in the 1960s, remote sensing technology has rapidly advanced to satellite-based data acquisition since the 1990s. This progression has been a key factor in promoting the development of spatial data infrastructure at each stage of the national spatial data policy. The study reviews the i...

Korean J. Remote Sens. 2024; 40(5): 753-767

History, Status, and Prospects of Remote Sensing in Agriculture in Republic of Korea

Remote sensing technology has emerged as a vital tool in the agricultural sector, offering capabilities for real-time crop monitoring, yield prediction, and resource management optimization. This paper reviews the historical development, current state, and future prospects of remote sensing in agriculture, with a focus on technological advancements and their impact on agricultural productivity and sustainability. The evolution of remote sensing technology, from its initial stages of soil and geographic data collection to its integration with high-resolution satellite imagery and drone technolo...

Korean J. Remote Sens. 2024; 40(5): 769-781

Advancement and Applications of Forest Remote Sensing in Korea: Past, Present, and Future Perspectives

Korea’s forest remote sensing began in the 1970s with the nationwide forest resource survey using aerial photographs, during which forest-type map and national forest resource data were produced for the first time. This data served as a crucial foundation for forest restoration and management at that time. In the 1990s, Landsat Multispectral Scanner (MSS) and Landsat Thematic Mapper (TM) were used to survey forest resources across North Korea, revealing for the first time the extent of forest degradation. Since then, satellite imagery has been regularly used to monitor North Korean fores...

Korean J. Remote Sens. 2024; 40(5): 783-812

National Disaster Management and Monitoring Using Satellite Remote Sensing and Geo-Information

As disasters become more diverse and widespread, disaster management at the national level is increasingly important. Since satellite remote sensing technology is capable of observing a wide range of areas on a regular basis, it can be effectively utilized to monitor a massive scale of disaster conditions and preemptively respond to urgent disasters. Disasters that can be managed through satellite remote sensing technology include forest fires, drought, floods, landslides, and earthquakes. This study introduces a variety of studies using satellite remote sensing and Geographic Information Syst...

Korean J. Remote Sens. 2024; 40(5): 813-832

A Comprehensive Review of Remote Sensing for Water-Related Disaster Management in South Korea: Focus on Floods and Droughts

This review analyzes the application of remote sensing technologies in managing water-related disasters, specifically floods and droughts, in South Korea. As climate change increases the frequency and intensity of these disasters, effective monitoring and response systems are crucial. Remote sensing, through satellites such as optical sensors and Synthetic Aperture Radar (SAR), has become essential for disaster management, providing large-scale, real-time data. In flood management, optical satellites provide high-resolution images for assessing damage and land changes, while SAR enables all-we...

Korean J. Remote Sens. 2024; 40(5): 833-847

Geological Remote Sensing of Korea

This review paper provides a comprehensive overview of advancements in geological remote sensing in Korea, based on the research published in the Korean Journal of Remote Sensing (KJRS). The review encompasses critical geological domains, including lineament analysis, rock and mineral remote sensing, landslide detection, volcanic activity monitoring, earthquake assessment, and gravity studies. The content is organized chronologically, allowing for a detailed examination of the evolution of remote sensing techniques and their applications by KJRS authors. This review emphasizes significant cont...

Korean J. Remote Sens. 2024; 40(5): 849-865

Four Decades of Polar Research in Remote Sensing: A Comprehensive Review

This review analyzes the progress of polar science, emphasizing the scientific and technological achievements reflected in research papers published in the Korean Journal of Remote Sensing over the last 40 years. Polar research, particularly in the context of climate change, is a relatively young but rapidly expanding field. This review includes approximately 40 studies highlighting the application of advanced remote sensing technologies such as Synthetic Aperture Radar, multispectral, and hyperspectral imaging, LiDAR, alongside machine learning and deep learning techniques. These technologies...

Korean J. Remote Sens. 2024; 40(5): 867-879

KSRS

Archives

October 31, 2024

Vol. 40, No. 5, pp. 419-879

Aims and Scope
Korean Journal of Remote Sensing serves the remote sensing community with the publication of results based on theory, technology and applications of remote sensing fields. Thoroughly interdisciplinary, this journal focuses on the research and development of remote sensing science and technologies and promotes the exchange of expert knowledge among remote sensing researchers as well.

More +

Current Issue Vol. 40, No. 5, October 2024

Research Article
Automated Updates of Coordinates of Ground Control Points Through Tiepoints from Multiple Satellite Images

Seunghyeok Choi, Seunghwan Ban, Taejung Kim

Korean Journal of Remote Sensing 2024; 40(5): 419-429

PDF Cite Share
Research Article
An Active Subglacial Lake near Vostok Subglacial Lake in East Antarctica Discovered Using ALOS-2 Interferometry

Hyunjin Shin, Hyangsun Han

Korean Journal of Remote Sensing 2024; 40(5): 431-444

PDF Cite Share
Research Article
Multi-Sensor Satellite Image Classification Using Random Forest Algorithm in Google Earth Engine: Application of CAS500-1 Image Sets

Jeonghee Lee, Kwangseob Kim, Kiwon Lee

Korean Journal of Remote Sensing 2024; 40(5): 445-453

PDF Cite Share
Research Article
Accuracy Assessment of Coastal Aquaculture Facility Detection Using Deep Learning Techniques

Seo Jin Kim, Hahn Chul Jung, Do-Hyun Hwang

Korean Journal of Remote Sensing 2024; 40(5): 455-464

PDF Cite Share

Online First Articles

There is no article data yet.

Most View (2021 - 2023)

578

Effects of Environmental Conditions on Vegetation Indices from Multispectral Images: A Review

Md Asrakul Haque, Md Nasim Reza, Mohammod Ali, Md Rejaul Karim, Shahriar Ahmed, Kyung-Do Lee, Young Ho Khang, Sun-Ok Chung
Review Korean Journal of Remote Sensing 2024; 40(4): 319-341
408

Application of Geo-Segment Anything Model (SAM) Scheme to Water Body Segmentation: An Experiment Study Using CAS500-1 Images

Hayoung Lee, Kwangseob Kim, Kiwon Lee
Research Article Korean Journal of Remote Sensing 2024; 40(4): 343-350
388

National Disaster Management and Monitoring Using Satellite Remote Sensing and Geo-Information

Jongsoo Park, Hagyu Jeong, Junwoo Lee
Review Korean Journal of Remote Sensing 2024; 40(5): 813-832
307

Analysis of Waterbody Changes in Small and Medium-Sized Reservoirs Using Optical Satellite Imagery Based on Google Earth Engine

Younghyun Cho, Joonwoo Noh
Research Article Korean Journal of Remote Sensing 2024; 40(4): 363-375

View More +

Most Downloaded (2021 - 2023)

135

Effects of Environmental Conditions on Vegetation Indices from Multispectral Images: A Review

Md Asrakul Haque, Md Nasim Reza, Mohammod Ali, Md Rejaul Karim, Shahriar Ahmed, Kyung-Do Lee, Young Ho Khang, Sun-Ok Chung
Review Korean Journal of Remote Sensing 2024; 40(4): 319-341
103

Application of Geo-Segment Anything Model (SAM) Scheme to Water Body Segmentation: An Experiment Study Using CAS500-1 Images

Hayoung Lee, Kwangseob Kim, Kiwon Lee
Research Article Korean Journal of Remote Sensing 2024; 40(4): 343-350
90

Assessing the Geometric Integrity of Cylindrical Storage Tanks: A Comparative Study Using Static Terrestrial Laser Scanning and Total Station

Mansour Alghamdi, Jinha Jung
Research Article Korean Journal of Remote Sensing 2024; 40(3): 243-255
75

Analysis of Waterbody Changes in Small and Medium-Sized Reservoirs Using Optical Satellite Imagery Based on Google Earth Engine

Younghyun Cho, Joonwoo Noh
Research Article Korean Journal of Remote Sensing 2024; 40(4): 363-375

View More +

Announcement

View More +

Call for Papers for December 2024 Issue (Early Submission Deadline)

October 9, 2024
Call for Papers - Special Issue on KOMPSAT Image Processing and Applications

[Call for Papers]

Special Issue on KOMPSAT Image Processing and Applications

Over the past several deca...

September 20, 2024
Call for Papers for October 2024 Issue (Submission Closed)

Dear Authors,

We are now accepting submissions for the October 2024 issue of the Korean Journal of Remote Sensing (KJRS). Please note that starting ...

September 20, 2024
Renewal of the KJRS Journal Website

We are pleased to announce that the website of the Korean Journal of Remote Sensing (KJRS) has been updated in 2024 to commemorate the 40th anniversary of the Korean So...

September 20, 2024

About the Journal

KSRS Journal

Aims and Scope

Korean Journal of Remote Sensing serves the remote sensing community with the publication of results based on theory, technology and applications of remote sensing fields. Thoroughly interdisciplinary, this journal focuses on the research and development of remote sensing science and technologies and promotes the exchange of expert knowledge among remote sensing researchers as well.

Areas of interest include, but are not necessarily restricted to:
– Remote Sensor Technology
– Novel Sensor Design and Platforms Development ...

More +

Editorial Office

VISITORS

Since August 10, 2024

TODAY	126
TOTAL	17,567