• Journal of the Korean Society of Environmental Restoration Technology
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• v.5 no.1
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• pp.35-50
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• 2002

This study aims to understand wetland distribution and type-specific classification features with a focus on Tumen River downstream in China by adjusting and improving the classification system used in Korea with a reference to international wetland classification systems and their criteria & methods. In this study, wetland types were determined based on hydrology, vegetation, and soil conditions, which are the most basic elements of wetlands. Also, topography analytical map, vegetation analytical map, and soil analytical map for wetland classification were developed and used based on currently available topography map, vegetation map, and soil map. In addition, codes were defined based on topography, location, hydrology, and vegetation. The result shows that, in the Tumen River downstream, wetlands are often found near natural revetment and terrace land & river-bed lakes. In the discovered wetlands, riverine, lacustrine, and inland wetlands were mostly found at system level. Riparian and human-made wetlands were also identified. At a sub-system level, perennial and seasonal wetlands were found to a similar degree. At a class level, perennial open water, herbal plants, and shrubs were mostly found and sandy plain, hydrophytes, and forest tree types were also observed. An overall detailed classification shows that a total of 17 wetland types were found and a large distribution of sand dunes and river-bed lakes, which are scarce in Northeast Asia, indicates that other rare wetland types such as palustrine seasonal sand plain wetland and lacustrine seasonal sand plain wetland may be discovered.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.13 no.6
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• pp.117-131
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• 2010

This study was conducted to utilize as basic information for the construction of conservation and estimation system for Palustrine wetland, which was badly managed and imprudently reclaimed, through the analysis of distribution characteristics and the estimation of conservation value for sample sites (eight wetlands) in rural area. As the result of wetland type classification, these wetlands was classified by 4 types (Permanent freshwater marshes/pools, ponds, Aquaculture ponds, and Seasonally flooded agricultural land) by Ramsar system, 3 types (Emergent Wetland, Aquatic Bed, and Scrub-Shrub Wetland) by NWI (Cowardin) System, 5 types (Farm Pond Depression, Under-flow wetland, Man-made Pond Depression, Abandoned Paddy Fields Wetland, and Reservoir Shore) by National Wetland's Categorical System, and 3 types (Aquatic Bed Wetland, Emergent Wetland, and Forested Wetland) by Lee (2000) System. These results suggest us developing the new type classification system for small Palustrine wetland in Korean rural areas. The score of function assessment (The Modified RAM) for small Palustrine wetlands was high at the wetlands nearby hills and rice paddy fields, and low at those nearby upper fields, which was mainly affected by land-use and vegetation. The functions as 'Flood/Storm Water Storage', 'Runoff Attenuation', 'Water Quality Protection' were resulted by the structural difference of inflow and outlet. Some functions as 'Wetland size', 'Wetland to immediate watershed ratio', 'Presence of boat traffic', 'Maximum water depth', 'Fetch of water's body' of RAM were not appropriate in evaluation of small wetlands in rural area. Which suggest us developing the new function assessment system for small Palustirne wetland in Korean rural areas.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.6 no.1
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• pp.65-70
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• 2003

This research aims to classify wetland types and evaluate functions of a wetland created by abandoned rice paddies. The case study area is Ja-un wetland in Daejeon Metropolitan City. In this study, wetland types were classified based on the basic elements of wetlands such as hydrology, vegetation, and soil conditions. This study was carried out based upon field surveys, drawing maps and publication, and modified-RAM which can evaluate the general functions and conservation values of wetlands. The analysis shows that several types of wetlands were identified, such as Palustrine/ Perennial/ Hydrophytes, Palustrine/ Perennial/ Openwater, Palustrine/ Seasonal/Herbal, Palustrine/ Seasonal/ Shrub and Scrub, Palustrine/ Seasonal/ Hydrophye, and Riparian/ Seasonal/ Shrub and Scrub in the Ja-un wetland. The average level of functions of the wetlands is very "HIGH", and it is recommended that prompt conservation measures should be taken.

• Journal of Wetlands Research
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• v.14 no.2
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• pp.303-315
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• 2012

This study developed a wetland inventory describing the characteristics and change of Nakdong estuary wetland ecosystem. The data which are used to develop the inventory are Landsat TM(April 1, 1986; June 23, 1987; June 18, 1997), Kompsat(Jan. 12, 2008) and LiDAR(March 1, 2009) images and published monitoring data of Busan metropolitan city. The developed inventory was utilized for the classification of wetland cover, the spatiotemporal analysis of wetland and landscape pattern, the distribution of benthos species etc. Furthermore, the developed 3 dimensional wetland map showed a better way to delineate wetland boundary and understand wetland dynamics. Considering these results, it's concluded that it is possible to use the similar techniques for the development of wetland inventory in Korea.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.371-379
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• 2018

Unlike general VHR (Very-High-Resolution) satellite sensors that are mainly for panchromatic and MS (Multispectral) imaging, Worldview-3 sensor additionally provides eight SWIR (Short Wavelength Infrared) bands in wavelength range from 1198 nm to 2365 nm. This study investigates the effect of informative Worldview-3 SWIR bands for wetland classification performance. Worldview-3 imagery acquired over Sunchon Bay, which is a coastal wetland located in South Korea, is used to implement the classification. Land-cover classes for the scene are determined by referring to national land-cover maps, which are provided by the Ministry of Environment, overlapped with the scene. After that, training data for each determined class are collected. In order to analyze the effect of SWIR bands, classifications with and without SWIR bands are carried out and the results are then compared. In this regard, a SVM (Support Vector Machine) is utilized as their classifier. As a result of the accuracy assessments performed by test data that are independently extracted from training data, it was confirmed that classification performance was improved when the SWIR bands are included as input features for SVM-based classification.

• Korean Journal of Remote Sensing
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• v.20 no.3
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• pp.197-205
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• 2004

Wetlands are lands with a mixture of water, herbaceous or woody vegetation and wet soil. And linear spectral mixture analysis (LSMA) is one of the most often used methods in handling the spectral mixture problem. This study aims to test LSMA is an enhanced routine for classification of wetland land-covers in Paldang reservoir and vicinity (paldang Reservoir) using Landsat TM and ETM+ imagery. In the LSMA process, reference endmembers were driven from scatter-plots of Landsat bands 3, 4 and 5, and a series of endmember models were developed based on green vegetation (GV), soil and water endmembers which are the main indicators of wetlands. To consider phenological characteristics of Paldang Reservoir, a soil endmember was subdivided into bright and dark soil endmembers in spring and a green vegetation (GV) endmember was subdivided into GV tree and GV herbaceous endmembers in fall. We found that LSMA fractions improved the classification accuracy of the wetland land-cover. Four endmember models provided better GV and soil discrimination and the root mean squared (RMS) errors were 0.011 and 0.0039, in spring and fall respectively. Phenologically, a fall image is more appropriate to classify wetland land-cover than spring's. The classification result using 4 endmember fractions of a fall image reached 85.2 and 74.2 percent of the producer's and user's accuracy respectively. This study shows that this routine will be an useful tool for identifying and monitoring the status of wetlands in Paldang Reservoir.

• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.189-211
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• 2005

This paper makes an effort to compare the recently evolved soft classification method based on Linear Spectral Mixture Modeling (LSMM) with the traditional hard classification methods based on Iterative Self-Organizing Data Analysis (ISODATA) and Maximum Likelihood Classification (MLC) algorithms in order to achieve appropriate results for mapping, monitoring and preserving valuable coastal wetland ecosystems of southern India using Indian Remote Sensing Satellite (IRS) 1C/1D LISS-III and Landsat-5 Thematic Mapper image data. ISODATA and MLC methods were attempted on these satellite image data to produce maps of 5, 10, 15 and 20 wetland classes for each of three contrast coastal wetland sites, Pitchavaram, Vedaranniyam and Rameswaram. The accuracy of the derived classes was assessed with the simplest descriptive statistic technique called overall accuracy and a discrete multivariate technique called KAPPA accuracy. ISODATA classification resulted in maps with poor accuracy compared to MLC classification that produced maps with improved accuracy. However, there was a systematic decrease in overall accuracy and KAPPA accuracy, when more number of classes was derived from IRS-1C/1D and Landsat-5 TM imagery by ISODATA and MLC. There were two principal factors for the decreased classification accuracy, namely spectral overlapping/confusion and inadequate spatial resolution of the sensors. Compared to the former, the limited instantaneous field of view (IFOV) of these sensors caused occurrence of number of mixture pixels (mixels) in the image and its effect on the classification process was a major problem to deriving accurate wetland cover types, in spite of the increasing spatial resolution of new generation Earth Observation Sensors (EOS). In order to improve the classification accuracy, a soft classification method based on Linear Spectral Mixture Modeling (LSMM) was described to calculate the spectral mixture and classify IRS-1C/1D LISS-III and Landsat-5 TM Imagery. This method considered number of reflectance end-members that form the scene spectra, followed by the determination of their nature and finally the decomposition of the spectra into their endmembers. To evaluate the LSMM areal estimates, resulted fractional end-members were compared with normalized difference vegetation index (NDVI), ground truth data, as well as those estimates derived from the traditional hard classifier (MLC). The findings revealed that NDVI values and vegetation fractions were positively correlated ($r^2$= 0.96, 0.95 and 0.92 for Rameswaram, Vedaranniyam and Pitchavaram respectively) and NDVI and soil fraction values were negatively correlated ($r^2$ =0.53, 0.39 and 0.13), indicating the reliability of the sub-pixel classification. Comparing with ground truth data, the precision of LSMM for deriving moisture fraction was 92% and 96% for soil fraction. The LSMM in general would seem well suited to locating small wetland habitats which occurred as sub-pixel inclusions, and to representing continuous gradations between different habitat types.

• Journal of Wetlands Research
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• v.6 no.3
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• pp.55-70
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• 2004

The wetland ecosystem is a complex products of various erosion force, accumulation as water flows, hydrogeomorphic units, seasonal changes, the amount of rainfalls, and other essential element. There is no single, correct, ecologically sound definition for wetlands because of the diversity of wetlands and the demarcation between dry and wet environments occurs along a continuum, but wetland plays various ecosystem functions. Despite comprehensive integration through classification and impact factors there is still lacking in systematic management of wetlands. Classification system developed by the USFWS(1979) is hierarchical progresses from systems and subsystems at general levels to classes, subclasses, dominance types, and habitat modifiers. Systems and subsystems are delineated according to major physical attributes such as tidal flushing, ocean-derived salts, and the energy of flowing water or waves. Classes and subclasses describe the type of substrate and habitat or the physiognomy of the vegetation or faunal assemblage. Wetland classes are divided into physical types and biotic types. For the wise management of wetlands in Korea, this study was carried out to examine methodology of USFWS classification system and discuss its application for Korean wetland hydrogeomorphic units already known. Seven wetland types were chosen as study sites in Korea divided into some different types based on USFWS system. Three wetland types belonging to palustrine system showed no difference between Wangdungjae wetland and Mujechi wetland, but Youngnup of Mt. Daeam was different from the former two types at the level of dominant types. This fact means that setting of classification system for management of wetland is needed. Although we may never know much about the wetland resources that have been lost, there are opportunities to conserve the riches that remain. Extensive inventory of all wetland types and documentation of their ecosystem functions are vital. Unique and vulnerable examples in particular need to be identified and protected. Furthermore, a framework with which to demonstrate wetland characteristics and relationships is needed that is sufficiently detailed to achieve the identification of the integrity and salient features of an enormous range of wetland types.

• Journal of Ecology and Environment
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• v.48 no.3
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• pp.395-404
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• 2024

Background: In this study, citizen scientists gathered survey data by monitoring inland wetlands, recognized as carbon sinks, and verified the accuracy of the data for incorporation into ecosystem management policies. Results: In October 2022, citizen scientists conducted surveys on three taxonomical groups (plants, mammals, terrestrial insects) in three wetland protection areas. After capturing photographs with location information, these images were uploaded to a national ecological information bank (EcoBank) managed in Korea. The information collected by citizen scientists underwent cross-validation through two expert methods, involving ecology field experts. First, experts conducted a survey of invasive alien plants in the designated areas and compared their findings with those of citizen scientists. The choice of survey locations by citizen scientists was influenced by their proximity to their residences. Second, an expert scrutinized the accuracy of species names collected and uploaded to EcoBank by citizen scientists, presenting their findings. The classification accuracy for species names was 98.8% for vegetation (n = 83), 21.6% for terrestrial insects (n = 21), and 66.7% for mammals (n = 8). These results indicate that citizen scientists may lack detailed classification ability at the species level. Conclusions: Moving forward, it will be imperative to offer diverse forms of education to strengthen the capabilities of the citizen scientists, including sharing wetland survey results to enhance expertise in species identification, creating and distributing educational materials, and providing on-site education through professional surveyors.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.17 no.2
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• pp.15-30
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• 2014

Systematic management of wetlands should be a priority to build the data for the extent and distribution of wetlands all over the country. However there are no clear guidelines for the wetland boundary delineation, so researchers have to determine the boundary of wetlands in each different way. As a result, it is very difficult to identify the extent and distribution of wetlands. This study proposes applicable criteria of setting boundary of wetlands which consider their wetland vegetation and geographical characteristics, according to wetland classification. The proposed site in this study is selected wetlands that represent each wetland type and have been ecologically well preserved like the wetland protected areas. GIS data for setting the boundary of wetlands selected were land-cover maps, aerial photographs, high resolution satellite images, and digital topographic maps. In this study, 'wetland unit determination' of the Washington State Wetlands Rating System(WSDE, 1993) and the concept of 'Wetland and Deep-water Habitats' was suggested by Wetland Delineation Manual(USACE, 1987) were used as criteria for setting the boundary of wetlands. As a result, it was found that the boundary of wetlands could be, in general, set consistently. Also, it seemed possible to set systematic and standardized boundary of wetlands and to provide more objective data for establishing national wetland policies, if maps of wetlands are made and an investigation of wetlands is implemented according to the criteria.