Keunchang Jang

Retrievals of All-Weather Daily Air Temperature Using MODIS and AMSR-E Data

Satellite optical-infrared remote sensing from the Moderate Resolution Imaging Spectroradiometer (MODIS) provides effective air temperature (Ta) retrieval at a spatial resolution of 5 km. However, frequent cloud cover can result in substantial signal loss and remote sensing retrieval error in MODIS Ta. We presented a simple pixel-wise empirical regression method combining synergistic information from MODIS Ta and 37 GHz frequency brightness temperature (Tb) retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) for estimating surface level Ta under both clear and cloudy sky conditions in the United States for 2006. The instantaneous Ta retrievals showed favorable agreement with in situ air temperature records from 40 AmeriFlux tower sites; mean R2 correspondence was 86.5 and 82.7 percent, while root mean square errors (RMSE) for the Ta retrievals were 4.58 K and 4.99 K for clear and cloudy sky conditions, respectively. Daily mean Ta was estimated using the instantaneous Ta retrievals from day/night overpasses, and showed favorable agreement with local tower measurements (R2 = 0.88; RMSE = 3.48 K). The results of this study indicate that the combination of MODIS and AMSR-E sensor data can produce Ta retrievals with reasonable accuracy and relatively fine spatial resolution (~5 km) for clear and cloudy sky conditions.

Evaluation of MODIS-derived Evapotranspiration at the Flux Tower Sites in East Asia

Evapotranspiration (ET) is one of the major hydrologic processes in terrestrial ecosystems. A reliable estimation of spatially representavtive ET is necessary for deriving regional water budget, primary productivity of vegetation, and feedbacks of land surface to regional climate. Moderate resolution imaging spectroradiometer (MODIS) provides an opportunity to monitor ET for wide area at daily time scale. In this study, we applied a MODIS-based ET algorithm and tested its reliability for nine flux tower sites in East Asia. This is a stand-alone MODIS algorithm based on the Penman-Monteith equation and uses input data derived from MODIS. Instantaneous ET was estimated and scaled up to daily ET. For six flux sites, the MODIS-derived instantaneous ET showed a good agreement with the measured data (

Characterizing regional precipitation-driven lake area change in Mongolia

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Status of Rice Paddy Field and Weather Anomaly in the Spring of 2015 in DPRK

Lake area is an important indicator for climate change and its relationship with climatic factors is critical for understanding the mechanisms that control lake level changes. In this study, lake area changes and their relations to precipitation were investigated using multi-temporal Landsat Thermatic Mapper (TM) and Enhanced Thermatic Mapper plus (ETM+) images collected from 10 different regions of Mongolia since the late 1980s. A linear-regression analysis was applied to examine the relationship between precipitation and lake area change for each region and across different regions of Mongolia. The relationships were interpreted in terms of regional climate regime and hydromorphological characteristics. A total of 165 lakes with areas greater than 10 hm2 were identified from the Landsat images, which were aggregated for each region to estimate the regional lake area. Temporal lake area variability was larger in the Gobi regions, where small lakes are densely distributed. The regression analyses indicated that the regional patterns of precipitation-driven lake area changes varied considerably (R2=0.028–0.950), depending on regional climate regime and hydromorphological characteristics. Generally, the lake area change in the hot-and-dry Gobi regions showed higher correlations with precipitation change. The precedent two-month precipitation was the best determining factor of lake area change across Mongolia. Our results indicate the usefulness of regression analysis based on satellite-derived multi-temporal lake area data to identify regions where factors other than precipitation might play important roles in determining lake area change.

Estimation of evapotranspiration over northeast Asia using modis products and MM5 FDDA data

To understand the impact of 2015 spring drought on crop production of DPRK (Democratic People’s Republic of Korea), we analyzed satellite and weather data to produce 2015 spring outlook of rice paddy field and rice growth in relation to weather anomaly. We defined anomaly of 2015 for weather and NDVI in comparison to past 5 year-average data. Weather anomaly layers for rainfall and mean temperature were calculated based on 27 weather station data. Rainfall in late April, early May, and late May in 2015 was much lower than those in average years. NDVI values as an indicator of rice growth in early June of 2015 was much lower than in 2014 and the average years. RapidEye and Radarsat-2 images were used to monitor status of rice paddy irrigation and transplanting. Due to rainfall shortage from late April to May, rice paddy irrigation was not favorable and rice planting was not progressed in large portion of paddy fields until early June near Pyongyang. Satellite images taken in late June showed rice paddy fields which were not irrigated until early June were flooded, assuming that rice was transplanted after rainfall in June. Weather and NDVI anomaly data in regular basis and timely acquired satellite data can be useful for grasping the crop and land status of DPRK, which is in high demand.

Mapping evapotranspiration using MODIS and MM5 Four-Dimensional Data Assimilation

Evapotranspiraiton (ET) is significant and necessary to understand the hydrological cycle and to assess water resource at any region. The Moderate Resolution Imaging Spectroradiometer (MODIS) offers promising techniques to monitor regional or global ET patterns. Under cloudy conditions, however, some pixels contain missing data that hamper the continuous monitoring of ET. In this study, MODIS atmospheric and land products were used ET estimates under clear and partial clear sky condition, and atmospheric data produced by the Four-Dimensional Data Assimilation (FDDA) between MODIS products and the Fifth Generation Meso-scale Meteorological Model (MM5) and MODIS land products were used ET estimates under cloudy sky condition. MODIS ET under clear and cloudy sky conditions showed a good agreement with nine flux tower observations in Northeast Asia. These results indicate that MODIS can be applied to monitor ET with reasonable accuracy.