• Korean Journal of Remote Sensing
• /
• v.36 no.5_1
• /
• pp.807-821
• /
• 2020

The objective of this study is to evaluate the applicability of representative spatio-temporal fusion models developed for the fusion of mid- and low-resolution satellite images in order to construct a set of time-series high-resolution images for crop monitoring. Particularly, the effects of the characteristics of input image pairs on the prediction performance are investigated by considering the principle of spatio-temporal fusion. An experiment on the fusion of multi-temporal Sentinel-2 and RapidEye images in agricultural fields was conducted to evaluate the prediction performance. Three representative fusion models, including Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), SParse-representation-based SpatioTemporal reflectance Fusion Model (SPSTFM), and Flexible Spatiotemporal DAta Fusion (FSDAF), were applied to this comparative experiment. The three spatio-temporal fusion models exhibited different prediction performance in terms of prediction errors and spatial similarity. However, regardless of the model types, the correlation between coarse resolution images acquired on the pair dates and the prediction date was more significant than the difference between the pair dates and the prediction date to improve the prediction performance. In addition, using vegetation index as input for spatio-temporal fusion showed better prediction performance by alleviating error propagation problems, compared with using fused reflectance values in the calculation of vegetation index. These experimental results can be used as basic information for both the selection of optimal image pairs and input types, and the development of an advanced model in spatio-temporal fusion for crop monitoring.

• Korean Journal of Remote Sensing
• /
• v.26 no.2
• /
• pp.143-151
• /
• 2010

We carried out studies on InSAR techniques for time-series deformation monitoring using multi-temporal SAR. The PSInSAR method using permanent scatterer is much more complicate than the SBAS because it includes many non-linear equation due to the input of wrapped phase. It is conformed the PS algorithm is very sensitive to even PSC selection. On the other hand, the SBAS method using interferogram of small baseline subset is simple but sensitive to the accuracy of unwrapped phase. The SBAS is better method for expecting not significant unwrapping error while PSInSAR is more proper method for expecting local deformation within very limited area. We used 51 ERS-1/2 SAR data during 1992-2000 over Las Vegas, USA for the comparison between PSInSAR and SBAS. Both PSInSAR and SBAS show similar ground deformation value although local deformation seems to be detected in the PSInSAR method only.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.15 no.3
• /
• pp.66-80
• /
• 2012

It is necessary to normalize spectral image values derived from multi-temporal satellite data to a common scale in order to apply remote sensing methods for change detection, disaster mapping, crop monitoring and etc. There are two main approaches: absolute radiometric normalization and relative radiometric normalization. This study focuses on the multi-temporal satellite image processing by the use of relative radiometric normalization. Three scenes of KOMPSAT-2 imagery were processed using the Multivariate Alteration Detection(MAD) method, which has a particular advantage of selecting PIFs(Pseudo Invariant Features) automatically by canonical correlation analysis. The scenes were then applied to detect disaster areas over Sendai, Japan, which was hit by a tsunami on 11 March 2011. The case study showed that the automatic extraction of changed areas after the tsunami using relatively normalized satellite data via the MAD method was done within a high accuracy level. In addition, the relative normalization of multi-temporal satellite imagery produced better results to rapidly map disaster-affected areas with an increased confidence level.

• Aerospace Engineering and Technology
• /
• v.3 no.2
• /
• pp.141-148
• /
• 2004

The importance of satellite data for numerous applications is stressed by the fact that many countries have given the development of space technologies very high priority. Among these, Korea has established a medium-term space development strategy to promote space development both on a scientific as well as commercial level. As part of this strategy, the first operational earth-observation, multi-purpose satellite(KOMPSAT-1) was launched successfully in December, 1999. The Electro-Optical Camera (EOC) on board of KOMPSAT-1 supplies panchromatic images with a spatial resolution of 6.6m Until April, 2004, it collected over 150.000 images of the Korean Peninsula and the rest of the world. This paper examines the use of remote sensing data to analyze urban growth in the city of Daejeon from 1960 to 2003. By using visual interpretation, land use maps are created.

• Journal of Korean Society for Geospatial Information Science
• /
• v.18 no.2
• /
• pp.87-92
• /
• 2010

Large pressure on the growing population has increased rapid change in the LULC (land use/land cover) patterns in the watershed area. Spatial distribution of LULC information and its changes are desirable for any effective planning, managing and monitoring activities. The aim of the study is to produce the 1,50,000 scaled LULC change map for the sub-watershed, Western Moyar, India using the multi-temporal satellite image dataset of IRS LISS III images for the year 1989, 1999, and 2002. About 9 classes are extracted using onscreen visual interpretation techniques for all the three years. The change detection analysis was performed using matrix method for period I (1989-1999) and period II (1999-2002). The study reveals that the changes noticed in period II (1999-2002) is comparatively more than period I (1989-1999), which is dynamic information to protect the sub-watershed area from the deterioration and paves the way to for the sustainable development.

• Proceedings of the KSRS Conference
• /
• 2008.03a
• /
• pp.119-124
• /
• 2008

2000년대 들어 주기적으로 발생하고 있는 봄 가뭄에 대한 적절한 대책 마련을 위해서는 가뭄을 모니터링 할 수 있는 감시체계가 필요하며 가뭄의 심도를 정량적으로 나타내기 위한 지표가 요구된다. 또한, 가뭄의 거동 및 지역적인 심도 분석을 위해서는 면 단위의 공간적인 분석이 요구된다. 위성영상은 공간정보를 신속하고 주기적으로 제공할 수 있는 도구로 위성영상의 밴드 조합을 통해 제작된 식생지수는 1990년대 중반 이후 건조지역을 중심으로 가뭄 모니터링을 위한 도구로 활용 중이다. 본 연구에서는 MODIS 영상으로부터 제작된 정규식생지수(NDVI)를 이용하여 식생상태지수(VCI)와 정규화된 식생지수(SVI)를 제작하였으며 2000년$\sim$2007년을 대상으로 가뭄발생연도, 각 가뭄사상에 대한 심도, 가뭄다발 시기 및 다발지역을 분석하였다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2004.03a
• /
• pp.203-208
• /
• 2004

NDVI (Normalized Difference Vegetation Index)는 식생의 건강상태 및 농작물 생산량 추정등에 효과적인 식생지수로, 20년 이상 축적된 MOAA NDVI data의 경우, 식생의 시기적, 계절적 변화탐지가 가능해져 이를 바탕으로 한 가뭄지수들이 개발되어 가뭄 모니터링에 사용되어지고 있다 지난 2001년, 한반도는 기상관측 이래 90년만의 강수량 최저치를 기록하여 전국적인 대 가뭄의 피해를 입었으며, 특히 북한은 유엔이 선정한 가뭄에 가장 취약한 국가로 그로 인한 식량난이 더욱 악화되고 있어 가뭄에 대한 정보는 필수적이라 할 수 있다. 이에 본 연구에서는 1994～2002년의 식물 생장기(growing season : 3～10월)동안 NDVI 10일 최대값 합성영상 (10-day maximum composite data)을 사용하여 남북한으로 나누어진 한반도를 대상으로 각각의 식생현황을 파악 및 비교하고, 산림, 농지, 도시지역별로 NDVI와 가뭄의 주원인인 강수량과의 상관관계로 그 효용성을 분석하였다. 그 결과, NDVI는 1～2개월 전 강수량의 영향이 가장 컸으며, 특히 농지지역에서의 상관계수가 높게 나타났다.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.9 no.4
• /
• pp.176-192
• /
• 2006

The need for a systematic drought management has increased since last countrywide drought in 2001. Naturally various studies for establishing drought plan and preventing drought disaster have been conducted. MODIS image provided by Terra satellite has effective spatial and temporal resolutions to observe spatial and temporal characteristics of a region. MODIS data products are easy for preprocessing and correcting geometrically and provide various data set in regular which are applicable for drought monitoring. In this study, Ansung river and the upstream of South Han river basin was chosen for case study to identify and assess spring drought. The multi-period MODIS image and accumulated precipitation were used to detect not only the drought year but also the vegetation change of normal year and the result were compared with various spatial data. The result shows NDVI and LSWI with is more appropriate than LST for assesing spring drought in Korea and two month cumulative precipitation has moderate relationship with drought. It is necessary to use MODIS image which has same period and same space for effective drought analysis because drought is also affected by landover and altitude.

• Journal of Environmental Science International
• /
• v.15 no.4
• /
• pp.373-378
• /
• 2006

The western coast of South Korea is famous for its large and broad tidal lands. Nevertheless, land reclamation, which has been conducted on a large scale, such as Sihwa embankment construction project has accelerated coastal environmental changes in the embankment inland. For monitoring of environmental change, vegetation change detecting of the embankment inland were carried out and field survey data compared with Landsat TM, ETM+, IKONOS, and EOC satellite remotely sensed data. In order to utilize multi-temporal remotely sensed images effectively, all data set with pixel size were analyzed by same geometric correction method. To detect the tidal land vegetation change, the spectral characteristics and spatial resolution of Landsat TM and ETM+ images were analyzed by SMA(spectral mixture analysis). We obtained the 78.96% classification accuracy and Kappa index 0.2376 using March 2000 Landsat data. The SMA(spectral mixture analysis) results were considered with comparing of vegetation seasonal change detection method.

• Journal of Korean Society for Geospatial Information Science
• /
• v.21 no.3
• /
• pp.11-17
• /
• 2013

With high social demands for the diverse utilizations of forest lands, the illegal forest land use changes have increased. We studied change detection technique to detect changes in forest land use using an object-oriented segmentation of RED bands differencing in multi-temporal aerial photographs. The new object-oriented segmentation method consists of the 5 steps, "Image Composite - Segmentation - Reshaping - Noise Remover - Change Detection". The method enabled extraction of deforested objects by selecting a suitable threshold to determine whether the objects was divided or merged, based on the relations between the objects, spectral characteristics and contextual information from multi-temporal aerial photographs. The results found that the object-oriented segmentation method detected 12% of changes in forest land use, with 96% of the average detection accuracy compared by visual interpretation. Therefore this research showed that the spatial data by the object-oriented segmentation method can be complementary to the one by a visual interpretation method, and proved the possibility of automatically detecting and extracting changes in forest land use from multi-temporal aerial photographs.