• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.57-81
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• 2019

Satellite images can be integrated into a crop model to strengthen the advantages of each technique for crop monitoring and to compensate for weaknesses of each other, which can be systematically applied for monitoring inaccessible croplands. The objective of this study was to outline the productivity of paddy rice based on simulation of the yield of all paddy fields in North Korea, using a grid crop model combined with optical satellite imagery. The grid GRAMI-rice model was used to simulate paddy rice yields for inaccessible North Korea based on the bidirectional reflectance distribution function-adjusted vegetation indices (VIs) and the solar insolation. VIs and solar insolation for the model simulation were obtained from the Geostationary Ocean Color Imager (GOCI) and the Meteorological Imager (MI) sensors of the Communication Ocean and Meteorological Satellite (COMS). Reanalysis data of air temperature were achieved from the Korea Local Analysis and Prediction System (KLAPS). Study results showed that the yields of paddy rice were reproduced with a statistically significant range of accuracy. The regional characteristics of crops for all of the sites in North Korea were successfully defined into four clusters through a spatial analysis using the K-means clustering approach. The current study has demonstrated the potential effectiveness of characterization of crop productivity based on incorporation of a crop model with satellite images, which is a proven consistent technique for monitoring of crop productivity in inaccessible regions.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.15-17
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• 2003

One of the most serious problems that the world is facing is the loss of biodiversity and habitats as a result of environmental degradation. There are several strategies to protect the habitats and biodiversity within a certain region such as establishing protected areas; monitoring the remaining forests and managing the landscape within limits have been employed. In this study, Predicted Habitat Distribution Model (simple spatial modeling) was developed using vegetation types, land use and land cover, DEM, slope, drainage, roads, human settlement areas and minimum habitat requirements of each species. Then, based on the checklist of presence and absence of each species, the final habitat maps for selected endangered species are generated. Integration of Remote Sensing (RS) and Geographical Information System (GIS) has proven a very effective tool to generate wildlife habitat maps at various levels. An effecting mapping could be performed based on satellite remote sensing and modeling biodiversity indicators in GIS.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.76-78
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• 2005

When the data from the artificial satellite is analyzed, recent years it is perceived to vegetation index using BRF(Bidirectional Reflectance Factor) of the observation target. To make the BRF models, it is important to measure the 3D structure of the observation target actually. In this study, it is proposed to the observation technique by using laser scanning data. Also, our team has been operating the radio controlled helicopter which can fly over the tall forest canopy and it can be equipped the measurement system.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.549-552
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• 2004

Since open-cut mining excavates gradually from the top of the mountain, vegetation planting is needed to reduce negative environmental impact on the surrounding environment. Accordingly, this study aimed at performing the environmental monitoring of the open-cut mining ground using the satellite remote sensing technique. As the research technique, in order to grasp the environmental change around the open-cut mining ground, NDVI (normalized difference vegetation index) was calculated, and every year change of the vegetation activity was analyzed. The results of the study showed lower vegetation activity in the open-cut mining ground compared to the surrounding areas and suggested the need for closed monitoring by remote sensing techniques.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.170-173
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• 2004

When the data from the artificial satellite is analyzed, recent years it is perceived to vegetation index using BRF(Bi-directional Reflectance Factor) of the observation target. To make the BRF models, it is important to measure the 3D structure of the observation target actually. In this study, it is proposed to the observation technique by using multi-angle stereo pair image, and shown the observation result in grassland area. Also, our team has been operating the radio controlled helicopter which can fly over the tall forest canopy and it can be equipped the measurement system.

• Proceedings of the KSRS Conference
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• v.1
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• pp.239-242
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• 2006

Impervious surface is an important index for the estimation of urbanization and environmental change. In addition, impervious surface has an influence on the parameters of rainfall-runoff model during rainy season. The increase of impervious surface causes peak discharge increasing and fast concentration time in urban area. Accordingly, impervious surface estimation is an important factor of urban rainfall-runoff model development and calibration. In this study, impervious surface estimation is performed by using remote sensing images such as landsat-7 ETM+ and high resolution satellite image and regression tree algorithm based on case study area ? Jungnang-cheon basin in Korea.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.317-319
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• 2008

Traditionally, it is measured by using basin or empirical formula with meteorology data, while it does not represent the evaportransporation over a regional area. With the advent of improved remote sensing technology, it becomes feasible to assess the ET over a regional scale. Firstly, the IMAGINE ATCOR atmospheric module is used to preprocess for the MODIS imagery. Then MODIS satellite images which have been corrected by radiation and geometry in conjunction with the in-situ surface meteorological measurement are used to estimate the surface heat fluxes such as soil heat flux, sensible heat flux, and latent heat flux. In addition, the correlation coefficient between the derived latent heat and the in-situ measurement is found to be over 0.76. In the future, we will continue to monitor the surface heat fluxes of paddy rice field in Chiayi area.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.26-28
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• 2008

Soil moisture plays an important role in the land-atmosphere energy balance because it governs the partitioning of energy through latent heat fluxes or evapotranspiration. From the numerous studies, it is evident that the L-band radiometer is a useful and effective tool to measure soil moisture. The objective of the study is to develop and to verify the soil moisture retrieval algorithms for the L-band radiometer system. Through the radiometer-observed brightness temperature, surface emissivity and reflectivity can be derived, and, hence, soil moisture. We collect field and L-band airborne radiometer data from washita92, SGP97 and SGP99 experiments to assist the development of the retrieval algorithms. Upon launching the satellite L-band radiometer such as ESA-sponsored SMOS (Soil Moisture and Ocean Salinity) mission, the developed algorithms may be used to study and monitor globe soil moisture change.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.329-332
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• 2002

In this study, we reviews the application of GIS(Geographic Information system) and RS(Remote sensing) for many fields of the fisheries and ocean science. GIS and RS plays an important role as a advanced science and technology, and becomes a powerful tool of the study and research in various fields of Earth Science. In future, GIS and RS will be greatly used to observed and predict various phenomena associated with the fisheries and ocean environments.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1039-1041
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• 2003

Ocean color products derived from remote sensing satellite data are useful for monitoring the sea water quality such as the concentrations of chlorophyll, sediments and dissolved organic matter. Currently, ocean color products derived from MODIS data can be requested from NASA over the internet. However, due to the bandwidth limitation of most users in this region, and the time delay in data delivery, the products cannot be use for near-real time monitoring of sea water chlorophyll. CRISP operates a MODIS data receiving station for environmental monitoring purposes. MODIS data have been routinely received and processed to level 1B. We have adapted the higher level processing algorithms from the Institutional Algorithms provided by NASA to run in a standalone environment. The implemented algorithms include the MODIS ocean color algorithms. Seasonal chlorophyll concentration composite can be compiled for the region. By comparing the near-real time chlorophyll product with the seasonal composite, anomaly in chlorophyll concentration can be detected.