Yang-Won Lee

Detecting wildfires with the Korean geostationary meteorological satellite

Satellite remote sensing is a useful tool for monitoring wildfire by analysing the brightness temperature of medium and thermal infrared bands. This letter described a wildfire detection algorithm developed for the COMS (communication, ocean and meteorological satellite) and evaluated the applicability of the proposed method by comparing the detection results with the KFS (Korea Forest Service) wildfire survey data and ASTER (advanced spaceborne thermal emission and reflection radiometer) image. We detected various size of wildfires occurred in South Korea on 9 March 2013, which is a remarkable outcome when considering the limited channels of the COMS. For a more reliable algorithm, the characterization of subpixel fires using Dozier’s method or the multiple endmember spectral mixture analysis will be necessary as future work. In addition, more wildfire cases should be experimented for statistical assessment of the accuracy.

3-D Geovisualization of satellite images on smart devices by the integration of spatial DBMS, RESTful API and WebGL

Recent technological advancements in web-based geographic information systems have enabled access to satellite images on smart devices. The Representational State Transfer (REST) architecture overcomes difficulties that are associated with conventional data communications on the web, and the Web Graphics Library (WebGL) can be used as an alternative to web-based three-dimensional geographic visualization (3-D geovisualization) due to its efficient image processing capabilities. This paper describes a 3-D geovisualization system that was developed for satellite images on smart devices by integrating a spatial database management system (DBMS), a RESTful application programming interface (API), and WebGL. Spatiotemporal objects were constructed for time-series satellite images within a DBMS and a RESTful API was built for spatiotemporal queries to the time-series database so that the requested satellite data could be represented in 3-D on smart devices using WebGL. Satellite images that are represented in WebGL give a more realistic 3-D experience when they are combined with terrain data and provide for intuitive observations of the relationships between pixel values and associated geospatial conditions. This paper shows that a creative combination of existing technologies can be used to enhance and display satellite images on smart devices for 3-D geovisualization.

Assessment of the relationship between thermal-infrared-based temperature−vegetation dryness index and microwave satellite-derived soil moisture

Soil moisture (SM) is an important parameter in terrestrial ecological and hydrological processes, particularly in arid and semi-arid regions. However, a highly accurate SM grid data set, which is used as a reference for the data quality, is not really suitable for the validation of other SM products. Thus, a more effective method may be necessary for evaluation of SM grid data. The temperature−vegetation dryness index (TVDI), which is estimated by the relationship between land surface temperature and vegetation index data, has been developed to assess regional water stress. Based on previous studies, we assumed a negative linear relationship between SM and the TVDI to establish the evaluation method of SM grid data. Although a highly accurate measure of SM obtained by use of microwave sensors may not always exhibit a negative linear correlation with the TVDI, the pixels of strong negative linear correlation between them signifies at least a higher accuracy of the two data at that position. The negative relationships between microwave satellite sensor-derived SM and the TVDI were tested by application of 16-day scaled satellite data in the Sahel. We determined that the correlations differ spatially according to vegetation distribution. That is, when compared with a lower correlation in the arid Sahara to the north, a higher correlation (−0.9 < r < −0.7) was observed in the savannas, shrublands, and grasslands to the south. Our comparison results will be useful in developing validation methodologies for SM grid data in an alternative way under conditions of insufficient in situ measurements.

Satellite-based assessment of large-scale land cover change in Asian arid regions in the period of 2001–2009

Abstract Arid regions in Asia are commonly characterized by rapidly growing populations with limited land resources and varying rainfall frequencies under climatic change. Despite being one of the most important environmental challenges in Asia, the changing aridity in this region, particularly due to large-scale land cover change, has not been well documented. In this study, we used rainfall data and a new land heterogeneity index to identify recent trend in land cover changes in the Asian arid regions. The result indicates a significant decreasing trend of barren lands and an increasing trend of vegetated lands. Although the potential land cover change is commonly believed to be strongly sensitive to rainfall change, such sensitivity has not been observed during the nine-year period (2001–2009) analyzed. Through the analyses of two separate periods (2001–2005 and 2005–2009), the sensitivity of rainfall to land cover change in arid regions is found to be dependent on the initial spatial heterogeneity of vegetated land cover. The approach used and the findings in this study represent an important step toward better understanding of large-scale land cover change in the Asian arid regions, and have the potential to predict future land cover change under various climate change scenarios.

First retrieval of fire radiative power from COMS data using the mid-infrared radiance method

ABSTRACT Fire radiative power (FRP), which is the power radiated by fire within a unit area, is a fundamental component for estimation of fire emissions. Successive information of FRP is provided by instruments on geostationary satellites, such as the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat, and the Imager on board Geostationary Operational Environmental Satellite (GOES) for Europe, Africa and America. In East Asia, however, the geostationary satellites such as Multifunctional Transport Satellite, Himawari, Fengyun, and Communication, Ocean and Meteorological Satellite (COMS) do not provide official FRP products yet. This article describes the first retrieval of COMS FRP using the mid-infrared radiance method with an optimal sensor coefficient derived from our experimental simulations. The COMS FRP retrievals were compared with Moderate Resolution Imaging Spectroradiometer (MODIS) FRP products in East Asia for each April during 2011–2014. The mean absolute percentage difference was approximately 17%, which is comparable with the results of SEVIRI (30%) and GOES (17%) against MODIS FRP even if their experiment conditions were slightly different. The retrieval accuracies of the COMS FRP had almost no dependence on land-cover types and the size of fire, which can be interpreted a stable outcome covering most wildfire situations, although parts of the pixels showed somewhat low accuracies according to viewing and solar zenith angles. The results of our study can be useful to understand spatiotemporal variations of wildfire emissions. Furthermore, it can be a reference for FRP retrievals of the next-generation geostationary satellites such as the latest Himawari-8 and the forthcoming Geostationary Korean Multipurpose Satellite 2A.

Satellite-based assessment of Amazonian surface dryness due to deforestation

ABSTRACT Intensive deforestation due to human activities has been occurring in the Amazon over the last several decades, leading to a projected decrease in precipitation due to reduced evapotranspiration (ET) according to the prediction by climate model experiments. Such hydrological and climatic changes are closely related to the drying of soil moisture (SM) as a source of atmospheric water vapour via evaporation. We used a satellite-observed index, temperature-vegetation dryness index (TVDI), to assess the impact of deforestation on SM during the dry season. Thirteen-year (2002-2014) data for three representative areas (forest, deforesting and deforested) in the Rondônia, southwest (SW) of Amazon were used to evaluate the relative changes in SM corresponding to the extent of deforestation. We found the increase in dryness in the deforested Amazon using the moderate resolution imaging spectroradiometer (MODIS) satellite sensor. Furthermore, given that the impact of forest removal on surface SM can be distinguished from the associated changes in precipitation and vegetation conditions, it is found that the relative proportion of deforested areas is linearly correlated with that of SM. The results from this study are useful to validate climate model simulations of deforestation and to improve our understanding on the biophysical controls of Amazon deforestation.

On the relationships between satellite-based drought index and gross primary production in the North Korean croplands, 2000–2012

ABSTRACT Drought is one of the main constraints on vegetation growth and crop yields, although land ecosystems differ in their sensitivity to drought. Satellite-based vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), have been used in many drought studies, but they may not sufficiently represent the water content of vegetated land. Alternatively, the Normalized Difference Drought Index (NDDI) has been developed by integrating the NDVI and Normalized Difference Water Index (NDWI). In this letter, we examine how drought affects crop growth by quantifying the relationships between NDDI and the Gross Primary Production (GPP) derived from the moderate-resolution imaging spectroradiometer. In the North Korean croplands, NDDI had a strong negative correlation with GPP during 2000–2012. The relationships were more significant under relatively dry conditions (e.g., dry seasons or dry regions). The impacts of NDDI on GPP was greater in summer than in spring, which indirectly shows summer drought may be more critical to crop productivity. The NDDI–GPP relationship was slightly time-lagged in spring, which indicates that vegetation productivity may not always respond instantly to surface dryness. The NDDI can be a viable option for measuring the impacts of drought on vegetation and agriculture over a wide area.

The effect of fractional vegetation cover on the relationship between EVI and soil moisture in non-forest regions

Surface soil moisture (SM) is critical for terrestrial ecological and hydrological processes, particularly in non-forested arid and semi-arid regions. On the large scale, the relationship of vegetation greenness to SM is often considered to be a reflection of spatiotemporal changes in SM. In this study, we investigated the empirical relationship between the remotely sensed enhanced vegetation index (EVI) and in situ SM, using observations from 16 Ameriflux sites in non-forest regions. The linear relationship between SM and EVI could be classified by the fractional vegetation cover (FVC), and the ratio of EVI to SM became higher as the FVC increased. In addition, multiple regressions for SM using both EVI and FVC showed a higher correlation than that of the single regressions using EVI or FVC separately. We found that EVI and FVC were critical parameters in representing the SM variations related with the surface vegetation changes, but further studies are necessary before the relationship can be applied.

Statistical Modeling of Sea Ice Concentration Using Satellite Imagery and Climate Reanalysis Data in the Barents and Kara Seas, 1979–2012

Abstract: Extensive sea ice over Arctic regions is largely involved in heat, moisture, and momentum exchanges between the atmosphere and ocean. Some previous studies have been conducted to develop statistical models for the status of Arctic sea ice and showed considerable possibilities to explain the impacts of climate changes on the sea ice extent. However, the statistical models require improvements to achieve better predictions by incorporating techniques that can deal with temporal variation of the relationships between sea ice concentration and climate factors. In this paper, we describe the statistical approaches by ordinary least squares (OLS) regression and a time-series method for modeling sea ice concentration using satellite imagery and climate reanalysis data for the Barents and Kara Seas during 1979–2012. The OLS regression model could summarize the overall climatological characteristics in the relationships between sea ice concentration and climate variables. We also introduced autoregressive integrated moving average (ARIMA) models because the sea ice concentration is such a long-range dataset that the relationships may not be explained by a single equation of the OLS regression. Temporally varying

A scattering-based over-land rainfall retrieval algorithm for South Korea using GCOM-W1/AMSR-2 data

Heavy summer rainfall is a primary natural disaster affecting lives and properties in the Korean Peninsula. This study presents a satellite-based rainfall rate retrieval algorithm for the South Korea combining polarization-corrected temperature (PCT) and scattering index (SI) data from the 36.5 and 89.0 GHz channels of the Advanced microwave Scanning Radiometer 2 (AMSR-2) onboard the Global Change Observation Mission (GCOM)-W1 satellite. The coefficients for the algorithm were obtained from spatial and temporal collocation data from the AMSR-2 and groundbased automatic weather station rain gauges from 1 July - 30 August during the years, 2012-2015. There were time delays of about 25 minutes between the AMSR-2 observations and the ground raingauge measurements. A new linearly-combined rainfall retrieval algorithm focused on heavy rain for the PCT and SI was validated using ground-based rainfall observations for the South Korea from 1 July - 30 August, 2016. The validation presented PCT and SI methods showed slightly improved results for rainfall > 5 mm h-1 compared to the current ASMR-2 level 2 data. The best bias and root mean square error (RMSE) for the PCT method at AMSR-2 36.5 GHz were 2.09 mm h-1 and 7.29 mm h-1, respectively, while the current official AMSR-2 rainfall rates show a larger bias and RMSE (4.80 mm h-1 and 9.35 mm h-1, respectively). This study provides a scatteringbased over-land rainfall retrieval algorithm for South Korea affected by stationary front rain and typhoons with the advantages of the previous PCT and SI methods to be applied to a variety of spaceborne passive microwave radiometers.