• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.18-20
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• 2003

Land cover change detection is one of the most important trends in which remote sensing data could be used to assist strategists and the planners to decide the best land use policy. Two images of NOAA-AVHRR and SPOT vegetation acquired in November 1992 and 2002 were used to assess the changes of Agricultural lands in Egypt. A supervised classification together with two change images derived from classification result and NDVI were used to evaluate the trend and form of the change. It was found that agricultural areas increased by about 14.3 % during the study period in particular around the River Nile Delta and near the Northern Lakes of Egypt. The new cultivated lands were extracted mainly from the desert and from the salt marches areas. At the same time, parts of the agricultural lands were turned into non-cultivated land because of the urban expansion and soil degradation.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.366-369
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• 1998

To get the knowledge of land uses for watersheds, Thematic Mapper image from Landsat 5 satellite was used. The image was classified into land covers/uses by maximum likelihood classification technique. Land uses from the satellite image in this study was compared with those from the topographical map in previous. It was found that Land uses from the satellite image had a good reflection of real situations and more advantage in the reduction of time and cost.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.473-478
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• 1999

The purpose of the study were to detect and evaluate the land use and changes on the Balan Watersheds, located southwest of Suwon, using the Thematic Mapper(TM) data. Three sests of TM taken in 1985 , 1993 and 1996 were used and the changes in the land use analyzed and compared. The suupervised and unsuperivised classification methods were adoppted to classify five land-cover categories ; Paddy , upland , forest , residential , and water. Future ladn use patterns were simulated using a Markow chain method, and the change ratios presented.

• Korean Journal of Environmental Agriculture
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• v.28 no.1
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• pp.1-8
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• 2009

This study was aimed at assess environmental conservation functions by analyzing the change of land use areas in agricultural fields between 1999 and 2006, and comparing land surface temperature distribution between 1994 and 2006 in Yongin city. Land use maps of Yongin city were obtained from soil maps for 1999, Quickbird satellite images(less than 1 m) and parcel map for 2006. The land use area for Yongin city was in the order of forest > paddy field > upland > residence & building in 1999, and forest > residence & building > paddy field > upland in 2006. Decrease of paddy and upland fields reduced 34% and 41% of the capability of agricultural multifunctionality as to environment including flood control, groundwater recharge, and air cooling. Land surface temperature(LST) was derived from Landsat TM thermal infrared band acquired in September of 1994 and 2006 and classified into three grades. The results impplied that green vegetation in agricultural field and forest play an important role to reduce land surface temperature in warm season.

• Korean Journal of Agricultural Science
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• v.22 no.1
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• pp.110-126
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• 1995

Korean economy has been developed successfully in the course of implementing the five year economic development plans since 1962. The gap of incomes and quality of life between rural and urban area has been widened and it made rural farm laborers drain to urban areas. Therefore the prevailing situation of labor shortage and wage hike in rural area has made farm management deteriorate in recent years. Under the internal and international unfavorable economic conditions, marginal farm land of 66.5 thousand ha has been idled as of end of 1993. The total area outside agricultural development zone with bad farming conditions including irrigation and drainage, and land consolidation for mechanization were estimated at 360.4thousand ha equivalent to 17.5% of the total farm land area in Korea. Considering the topographical conditions of marginal lands, the effective use of marginal lands should be studied from the view point of public interest rather than from the view point of individual economic conditions. Considering the present agricultural economic settings, such as price decrease, unfavourable benefits of farm products, labour shrotage, free trade of farm products and poor physical condition of marginal lands, the institutional and realistical measures for the effective utilization of idle and marginal land should be studied as soon as possible. Detail land use pattern should be surveyed in the areas outside agricultural development zone and have to be classified as orchard farms, grass land, fish culture farms, lawn and ornamental tree farm, sight seeing and leisure farms for urban peoples, special crops production farms and common farms to be developed for farm mechanization. According to the surveyed results, the expected utilization patterns of the idle and marginal lands could be considerd as village common use, farm land base development, leisure farm development, mutual complementary utilization between urban and rural areas, G't purchase and management, credit supply and new extension services, improvement of cropping patterns and sight seeing and leisure farm patterns. For the successful and reasonable management of the marginal lands, the actions such as institutional improvement, prohibition of idle marginal land, enforcement of activities of farm management committee members and land banking system of RDC including development and utilization systems should be included.

• Journal of Cadastre & Land InformatiX
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• v.54 no.1
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• pp.19-32
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• 2024

This study examined the feasibility of image-based surveys by detecting objects in facilities and agricultural land using the YOLO algorithm based on drone images and comparing them with the land category by law. As a result of detecting objects through the YOLO algorithm, buildings showed a performance of detecting objects corresponding to 96.3% of the buildings provided in the existing digital map. In addition, the YOLO algorithm developed in this study detected 136 additional buildings that were not located in the digital map. Plastic greenhouses detected a total of 297 objects, but the detection rate was low for some plastic greenhouses for fruit trees. Also, agricultural land had the lowest detection rate. This result is because agricultural land has a larger area and irregular shape than buildings, so the accuracy is lower than buildings due to the inconsistency of training data. Therefore, segmentation detection, rather than box-shaped detection, is likely to be more effective for agricultural fields. Comparing the detected objects with the land category by law, it was analyzed that some buildings exist in agricultural and forest areas where it is difficult to locate buildings. It seems that it is necessary to link with administrative information to understand that these buildings are used illegally. Therefore, at the current level, it is possible to objectively determine the existence of buildings in fields where it is difficult to locate buildings.

• Journal of Agricultural Extension & Community Development
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• v.25 no.2
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• pp.57-70
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• 2018

Farm succession is one of the most important events that substantially influence the viability of a farm business not only for a family farm operation, but also for a farm industry as a whole. This study aims to analyze the factors which affect the probability of existence of a successor, using the nationwide survey data. The probability of having a successor increases with the age of operator, the number of sons, the area under cultivation, organic farming, farm expansion plan, main crop and operator's attitude towards farm succession. Also this study investigates the succession plans of family farms having a successor and land disposal plans of family farms without a successor. 40% of farms having a successor have only vague succession plans and 34.7% of farms without a successor have a plan to apportion their land among their children. Based on these results, this study suggests the necessity of planning for farm succession and successors' agricultural training. In addition, measures for preventing from land fragmentation are needed for realization of effective usage of agricultural land.

• Korean Journal of Soil Science and Fertilizer
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• v.46 no.6
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• pp.426-433
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• 2013

This study was aimed to classify soil desalination area for cultivation using NDVI (Normalized difference vegetation index) of high-resolution satellite image because the soil salinity affects the change of plant community in reclaimed lands. We measured the soil salinity and NDVI at 28 sites in the Saemangeum reclaimed land in June 2013. In halophyte and non-vegetation sites, no relation was found between NDVI and soil salinity. In glycophyte sites, however, we found that the soil salinity was below 0.1% and NDVI ranged from 0.11 to 0.57 which was greater than the other sites. So, we could distinguish the glycophyte sites from the halophyte sites and non-vegetation, and classify the area that soil salinty was below 0.1%. This technique could save the time and labor to measure the soil salinity in large area for agricultural utilization.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.6
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• pp.826-831
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• 2016

he land use, land-use change, and forestry (LULUCF) is one of the greenhouse gas inventory sectors that cover emission and removals of greenhouse gases resulting from land use such as agricultural activities and land use change. Particularly, LULUCF-Cropland sector consists of carbon stock changes in soil, $N_2O$ emissions from disturbance associated with land use conversion to cropland, and $CO_2$ emission from agricultural lime application. In this paper, we conducted the study to calculate the greenhouse gases emission of LULUCF-Cropland sector in South Korea from 1990 to 2014. The emission by carbon stock changes, conversion to cropland and lime application in 2014 was 4424, 32, and 125 Gg $CO_2$-eq, respectively. Total emission from the LULUCF-Cropland sector in 2014 was 4,582 Gg $CO_2$-eq, increased by 508% since 1990 and decreased by 0.7% compared to the previous year. Total emission from this sector showed that the largest sink was the soil carbon and its increase trend in total emission in recent years was largely due to loss of cropland area.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.6
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• pp.15-22
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• 2023

In this study, We conduct a comparative study of deep learning-based classification of agricultural field attributes using Tagged Image File (TIF) and Enhanced Compression Wavelet (ECW) images. The goal is to interpret and classify the attributes of agricultural fields by analyzing the differences between these two image formats. "FarmMap," initiated by the Ministry of Agriculture, Food and Rural Affairs in 2014, serves as the first digital map of agricultural land in South Korea. It comprises attributes such as paddy, field, orchard, agricultural facility and ginseng cultivation areas. For the purpose of comparing deep learning-based agricultural attribute classification, we consider the location and class information of objects, as well as the attribute information of FarmMap. We utilize the ResNet-50 instance segmentation model, which is suitable for this task, to conduct simulated experiments. The comparison of agricultural attribute classification between the two images is measured in terms of accuracy. The experimental results indicate that the accuracy of TIF images is 90.44%, while that of ECW images is 91.72%. The ECW image model demonstrates approximately 1.28% higher accuracy. However, statistical validation, specifically Wilcoxon rank-sum tests, did not reveal a significant difference in accuracy between the two images.