Sitthisak Moukomla

Dr. Sitthisak Moukomla

orcid

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 March 2016 in Remote Sensing
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Sitthisak MoukomlaSitthisak Moukomla
Sitthisak Moukomla
PBPeter Blanken
Peter Blanken
The Great Lakes Surface Temperature (GLST) is the key to understanding the effects of climate change on the Great Lakes (GL). This study provides the first techniques to retrieve pixel-based GLST under all sky conditions by merging skin temperature derived from the MODIS Land Surface Temperature (MOD11L2) and the MODIS Cloud product (MOD06L2) from 6 July 2001 to 31 December 2014, resulting in 18,807 scenes in total 9373 (9434) scenes for MOD11L2 (MOD06L2). The pixel-based GLST under all sky conditions was well-correlated with the in situ observations (R2 = 0.9102) with a cool bias of −1.10 °C and a root mean square error (RMSE) of 1.39 °C. The study also presents the long-term trends of GLST. Contrary to expectations, it decreased slightly due to the impact of an anomalously cold winter in 2013–2014.

19 April 2019 in Water
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RLRui Li
Rui Li
JSJiancheng Shi
Jiancheng Shi
Dabin JiDabin Ji
Dabin Ji
Tianjie ZhaoTianjie Zhao
Tianjie Zhao
VPVichian Plermkamon
Vichian Plermkamon
JKJiratiwan Kruasilp
Jiratiwan Kruasilp
Watershed runoff is essential for water management. However, runoff materials are lacking in poorly gauged catchments and not always accessible. Microwave remote sensing offers emerging capabilities for hydrological simulation. In this study based on multi-satellite retrievals for Global Precipitation Measurement (IMERG), Tropical Rainfall Measuring Mission (TRMM) products, and World Meteorological Organization (WMO) interpolated precipitation data, we simulated runoff using a variable infiltration capacity (VIC) model and studied the differences among the results. Then, we analyzed the impacts of the runoff on a moderate-resolution imaging spectroradiometer vegetation leaf area index (LAI) during dry seasons. The results showed that (1) IMERG V5 and TRMM products are capable of monitoring the night-day rainfall diurnal cycle and have higher correlations than the WMO daily observation interpolations. However, the WMO shows less overestimation of total precipitation than remote-sensing precipitation; (2) in the downstream, the TRMM shows better runoff simulation accuracy in the tributaries, and the WMO shows better results in the mainstreams. Therefore, at basin outlets in mainstreams, the Nash–Sutcliffe efficiency coefficients of monthly runoff by the WMO are higher than the simulations by the TRMM; (3) for the whole basin during dry seasons, the LAI variation is correlated with the outlet runoff, which is similar to the correlation with three- to six-month accumulated precipitation. TRMM products can be used to depict both precipitation deficit and runoff deficit, which cause vegetation variations. Our research suggests the potential of microwave precipitation products for detailed watershed runoff simulations and water management.

8 February 2017 in Remote Sensing
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Sitthisak MoukomlaSitthisak Moukomla
Sitthisak Moukomla
PBPeter Blanken
Peter Blanken
This study provides the first technique to investigate the turbulent fluxes over the Great Lakes from July 2001 to December 2014 using a combination of data from satellite remote sensing, reanalysis data sets, and direct measurements. Turbulent fluxes including latent heat flux (QE) and sensible heat flux (QH) were estimated using the bulk aerodynamic approach, then compared with the direct eddy covariance measurements from the rooftop of three lighthouses—Stannard Rock Lighthouse (SR) in Lake Superior, White Shoal Lighthouse (WS) in Lake Michigan, and Spectacle Reef Lighthouse (SP) in Lake Huron. The relationship between modeled and measured QE and QH were in a good statistical agreement, for QE, R2 varied from 0.41 (WS), 0.74 (SR), and 0.87 (SP) with RMSE of 5.68, 6.93, and 4.67 W·m−2, respectively, while QH, R2 ranged from 0.002 (WS), 0.8030 (SP) and 0.94 (SR) with RMSE of 6.97, 4.39 and 4.90 W·m−2 respectively. Both monthly mean QE and QH were highest in January for all lakes except Lake Ontario, which was highest in early December. The turbulent fluxes then sharply drop in March and are negligible during June and July. The evaporation processes continue again in August.

24 March 2021 in IEEE Geoscience and Remote Sensing Letters
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Dong FanDong Fan
Dong Fan
Tianjie ZhaoTianjie Zhao
Tianjie Zhao
XJXiaoguang Jiang
Xiaoguang Jiang
HXHuazhu Xue
Huazhu Xue
Sitthisak MoukomlaSitthisak Moukomla
Sitthisak Moukomla
JSJiancheng Shi
Jiancheng Shi
In this letter, we propose a dual-temporal dual-channel (DTDC) algorithm for soil moisture retrieval by using time-series observations from the Sentinel-1 C-band synthetic aperture radar. This algorithm utilizes the ancillary information of vegetation water content derived from optical images and assumes no variation on the surface roughness during the two consecutive radar measurements. Therefore, with the DTDC backscatter observations, four equations could be established using forward models, while three unknowns (the two consecutive soil moisture values and one roughness parameter) could be solved simultaneously by minimizing a cost function. The algorithm was tested with a series of Sentinel-1 dual-channel (VV + VH) data over croplands (sugarcane and cassava) of Northeast Thailand with an upscaling resolution of 1 km. Results show that the proposed algorithm could well capture the temporal change of soil moisture with root-mean-square errors within 0.06 m 3 /m 3 when ignoring days with precipitation, and could achieve a similar spatial pattern of soil moisture as detected from the Soil Moisture Active Passive mission, indicating the Sentinel-1 might be a proper tool for agricultural water management.

20 February 2025 in Urban Science
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Sitthisak MoukomlaSitthisak Moukomla
Sitthisak Moukomla
Wijitbusaba (Ann) MaromeWijitbusaba (Ann) Marome
Wijitbusaba (Ann) Marome
Historically known for its tin mining industry, Phuket Island has undergone significant transformation into a global tourism hub. This study aims at analyzing the evolutionary dynamics of Phuket Island from the years 1987 to 2024. We integrate Landsat satellite images and sophisticated analytical methods to assess the effects of tourism and economic policies on changes in land use and land cover using Google Earth Engine (GEE) for cloud-based data processing and Random Forest (RF) models for classification, and the Urban Expansion Intensity Index (UEII) and Shannon Entropy metrics for measuring the intensity of urban expansion and diversity, respectively. The results show that there has been a dynamic change in the patterns of land use which was brought about by the economic and environmental forces. Some of the major events that have had a great effect on Phuket’s landscape include the 1997 Asian Financial Crisis, the 2004 Indian Ocean Tsunami, and the COVID-19 pandemic; this highlights how the island is fragile and can be affected easily by events happening around the world. This work reveals a dramatic reduction in forest and mangrove cover, which calls for increased conservation measures to prevent the loss of biodiversity and to preserve the natural balance.

10 June 2025 in Geography and Sustainability
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Nattapong PuttanapongNattapong Puttanapong
Nattapong Puttanapong
NNNithima Nuengjumnong
Nithima Nuengjumnong
JSJoJinda SaeJung
JoJinda SaeJung
Sitthisak MoukomlaSitthisak Moukomla
Sitthisak Moukomla