Dr. Jin-Ki Park Profile

Dr. Jin-Ki Park

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Publications (2)

Proceedings Article | 22 October 2018 Paper

Paddy rice inventory studies using drone imagery on a small town area in South Korea

Jin-Ki Park, Dong-Ho Lee, Heong-Seup Shin, Jong-Hwa Park

Proceedings Volume 10777, 1077718 (2018) https://doi.org/10.1117/12.2324963

KEYWORDS: Vegetation, Agriculture, Remote sensing, Near infrared, Atomic force microscopy, Sensors, Geographic information systems, RGB color model, Associative arrays, Global Positioning System

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Remote sensing (RS) and geographic information system (GIS) could be very efficiently used for precise paddy field area estimation and provision of paddy field crop maps. The study on drone RS based paddy field estimation and inventory studies at small town-level was taken up in Chungbuk. The major objective of this study was to attempt small town-level paddy rice inventory during rice growing season using drone mounted sensors. The methodology adopted for small townlevel paddy field crop inventory consisted of: a) geo-referencing of Smart Farm Map data, b) rectification of cadastral maps, c) Ground data collection, d) drone data collection and e) accuracy assessment. The data obtained from RGB and NIR sensors onboard the drone are described. Approaches for preprocessing, transferring, and modeling these data for understanding the relationship between their spatial and temporal behavior and rice growth states are discussed. Finally, techniques for rice identification and area and inventory are briefly described. The results indicate that paddy field discrimination at small town-level is possible using drone with accuracy ranging from 95 to 97 per cent depending upon plot size. In most of the paddy field, an amount of heterogeneity was found due to growing state differences and varying management practices resulting in different vigor conditions. As expected it was observed that the accuracy with drone imagery data was better in comparison to National Statistical Office data since plot sizes are very small in the study area. The drone data of the paddy field was also available due to various reasons, it was observed that, for better rice growing condition discrimination and achieving higher accuracy, therefore, Combination drone imagery with Smart Farm Map data is very important. This study brings out the potentials and limitations of combined GIS based small town-level paddy field inventory using drone imagery data. Thus drone data and the information derived from it, is attractive to agricultural management system in the South Korea. It is concluded that, in addition to the GIS combined technology, the use of many other techniques such as ground observations, GPS and meteorological data is highly appreciable.

Proceedings Article | 22 October 2018 Paper

Using the UAV-derived NDVI to evaluate spatial and temporal variation of crop phenology at crop growing season in South Korea

Dong-Ho Lee, Jin-Ki Park, Kyong-Ho Shin, Jong-Hwa Park

Proceedings Volume 10777, 107770R (2018) https://doi.org/10.1117/12.2324959

KEYWORDS: Unmanned aerial vehicles, Vegetation, Agriculture, Satellites, Atomic force microscopy, Associative arrays, Sensors, Global Positioning System, Satellite imaging, Earth observing sensors

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