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Balancing the demand of groundwater resources and the mitigation of land subsidence is particularly important, yet challenging, in populated alluvial fan areas. In this study, we combine multiple monitoring data derived from Multi-Temporal InSAR (MTI), GNSS (Global Navigation Satellite System), precise leveling, groundwater level, and compaction monitoring wells, in order to analyze the relationship between surface displacement and groundwater level change within the alluvial fan of the Choshui River in Taiwan. Our combined time-series analyses suggest, in a yearly time scale, that groundwater level increases with the vertical surface displacement when the effect of pore water pressure dominates. Conversely, this relationship is negative when the effect of water-mass loading predominates over pore water pressure. However, the correlation between the vertical surface displacement and the groundwater level change is consistently positive over the time scale of two decades. It is interpreted that the alluvial fan sequence in the subsurface is not fully elastic, and compaction is greater than rebound in this process. These findings were not well reported and discussed by previous studies because of insufficient monitoring data and analyses. Understanding the combined effect of groundwater level change and vertical surface displacement is very helpful for management of land subsidence and usage of groundwater resources. The spatial and temporal integration of multi-sensors can be applied to overcome the limitations associated with the single technique and provides further insights into land surface changes, particularly in highly populated alluvial fan areas.
Chiao-Yin Lu; Jyr-Ching Hu; Yu-Chang Chan; Yuan-Fong Su; Chih-Hsin Chang. The Relationship between Surface Displacement and Groundwater Level Change and Its Hydrogeological Implications in an Alluvial Fan: Case Study of the Choshui River, Taiwan. Remote Sensing 2020, 12, 3315 .
AMA StyleChiao-Yin Lu, Jyr-Ching Hu, Yu-Chang Chan, Yuan-Fong Su, Chih-Hsin Chang. The Relationship between Surface Displacement and Groundwater Level Change and Its Hydrogeological Implications in an Alluvial Fan: Case Study of the Choshui River, Taiwan. Remote Sensing. 2020; 12 (20):3315.
Chicago/Turabian StyleChiao-Yin Lu; Jyr-Ching Hu; Yu-Chang Chan; Yuan-Fong Su; Chih-Hsin Chang. 2020. "The Relationship between Surface Displacement and Groundwater Level Change and Its Hydrogeological Implications in an Alluvial Fan: Case Study of the Choshui River, Taiwan." Remote Sensing 12, no. 20: 3315.
With the growing concern about the failure risk of river embankments in a rapidly changing climate, this study aims to quantify the overtopping probability of river embankment in Kao-Ping River basin in southern Taiwan. A water level simulation model is calibrated and validated with historical typhoon events and the calibrated model is further used to assess overtopping risk in the future under a climate change scenario. A dynamic downscaled projection dataset, provided by Meteorological Research Institute (MRI) has been further downscaled to 5-km grids and bias-corrected with a quantile mapping method, is used to simulate the water level of Kao-Ping River in the future. Our results highlighted that the overtopping risk of Kao-Ping River increased by a factor of 5.7~8.0 by the end of the 21st century.
Hsiao-Ping Wei; Yuan-Fong Su; Chao-Tzuen Cheng; Keh-Chia Yeh. Levee Overtopping Risk Assessment under Climate Change Scenario in Kao-Ping River, Taiwan. Sustainability 2020, 12, 4511 .
AMA StyleHsiao-Ping Wei, Yuan-Fong Su, Chao-Tzuen Cheng, Keh-Chia Yeh. Levee Overtopping Risk Assessment under Climate Change Scenario in Kao-Ping River, Taiwan. Sustainability. 2020; 12 (11):4511.
Chicago/Turabian StyleHsiao-Ping Wei; Yuan-Fong Su; Chao-Tzuen Cheng; Keh-Chia Yeh. 2020. "Levee Overtopping Risk Assessment under Climate Change Scenario in Kao-Ping River, Taiwan." Sustainability 12, no. 11: 4511.
Many people use smartphone cameras to record their living environments through captured images, and share aspects of their daily lives on social networks, such as Facebook, Instagram, and Twitter. These platforms provide volunteered geographic information (VGI), which enables the public to know where and when events occur. At the same time, image-based VGI can also indicate environmental changes and disaster conditions, such as flooding ranges and relative water levels. However, little image-based VGI has been applied for the quantification of flooding water levels because of the difficulty of identifying water lines in image-based VGI and linking them to detailed terrain models. In this study, flood detection has been achieved through image-based VGI obtained by smartphone cameras. Digital image processing and a photogrammetric method were presented to determine the water levels. In digital image processing, the random forest classification was applied to simplify ambient complexity and highlight certain aspects of flooding regions, and the HT-Canny method was used to detect the flooding line of the classified image-based VGI. Through the photogrammetric method and a fine-resolution digital elevation model based on the unmanned aerial vehicle mapping technique, the detected flooding lines were employed to determine water levels. Based on the results of image-based VGI experiments, the proposed approach identified water levels during an urban flood event in Taipei City for demonstration. Notably, classified images were produced using random forest supervised classification for a total of three classes with an average overall accuracy of 88.05%. The quantified water levels with a resolution of centimeters (
Yan-Ting Lin; Ming-Der Yang; Jen-Yu Han; Yuan-Fong Su; Jiun-Huei Jang. Quantifying Flood Water Levels Using Image-Based Volunteered Geographic Information. Remote Sensing 2020, 12, 706 .
AMA StyleYan-Ting Lin, Ming-Der Yang, Jen-Yu Han, Yuan-Fong Su, Jiun-Huei Jang. Quantifying Flood Water Levels Using Image-Based Volunteered Geographic Information. Remote Sensing. 2020; 12 (4):706.
Chicago/Turabian StyleYan-Ting Lin; Ming-Der Yang; Jen-Yu Han; Yuan-Fong Su; Jiun-Huei Jang. 2020. "Quantifying Flood Water Levels Using Image-Based Volunteered Geographic Information." Remote Sensing 12, no. 4: 706.
Super-resolution mapping (SRM) is a potential technique to improve image pattern recognition by predicting the spatial distribution of class composition at a sub-pixel scale. A number of SRM techniques have been reported in the past two decades. Most of the techniques are based on the assumption of spatial dependence. In this paper, a scale-invariant concept of fractal geometry is taking into account in the original Hopfield neural network (HNN) algorithm and a self-similar Hopfield neural network (SSHNN) is proposed which based on both spatial dependence and self-similarity in the fractal geometry. Both synthetic and real satellite images are used to test the performance of the SSHNN. The results show that by taking self-similarity into consideration, with a single image and no other additional data needed, the mapping accuracy of the SSHNN increases by up to 20% compared to the HNN.
Yuan-Fong Su. Integrating a scale-invariant feature of fractal geometry into the Hopfield neural network for super-resolution mapping. International Journal of Remote Sensing 2019, 1 -22.
AMA StyleYuan-Fong Su. Integrating a scale-invariant feature of fractal geometry into the Hopfield neural network for super-resolution mapping. International Journal of Remote Sensing. 2019; ():1-22.
Chicago/Turabian StyleYuan-Fong Su. 2019. "Integrating a scale-invariant feature of fractal geometry into the Hopfield neural network for super-resolution mapping." International Journal of Remote Sensing , no. : 1-22.
Yen-Ching Chen; Hao-Wei Chiu; Yuan-Fong Su; Yii-Chen Wu; Ke-Sheng Cheng. Does urbanization increase diurnal land surface temperature variation? Evidence and implications. Landscape and Urban Planning 2017, 157, 247 -258.
AMA StyleYen-Ching Chen, Hao-Wei Chiu, Yuan-Fong Su, Yii-Chen Wu, Ke-Sheng Cheng. Does urbanization increase diurnal land surface temperature variation? Evidence and implications. Landscape and Urban Planning. 2017; 157 ():247-258.
Chicago/Turabian StyleYen-Ching Chen; Hao-Wei Chiu; Yuan-Fong Su; Yii-Chen Wu; Ke-Sheng Cheng. 2017. "Does urbanization increase diurnal land surface temperature variation? Evidence and implications." Landscape and Urban Planning 157, no. : 247-258.
Model performance evaluation for real-time flood forecasting has been conducted using various criteria. Although the coefficient of efficiency () is most widely used, we demonstrate that a model achieving good model efficiency may actually be inferior to the naïve (or persistence) forecasting, if the flow series has a high lag-1 autocorrelation coefficient. We derived sample-dependent and AR model-dependent asymptotic relationships between the coefficient of efficiency and the coefficient of persistence () which form the basis of a proposed – coupled model performance evaluation criterion. Considering the flow persistence and the model simplicity, the AR(2) model is suggested to be the benchmark model for performance evaluation of real-time flood forecasting models. We emphasize that performance evaluation of flood forecasting models using the proposed – coupled criterion should be carried out with respect to individual flood events. A single or value derived from a multi-event artifactual series by no means provides a multi-event overall evaluation and may actually disguise the real capability of the proposed model.
Ke-Sheng Cheng; Yi-Ting Lien; Yii-Chen Wu; Yuan-Fong Su. On the criteria of model performance evaluation for real-time flood forecasting. Stochastic Environmental Research and Risk Assessment 2016, 31, 1123 -1146.
AMA StyleKe-Sheng Cheng, Yi-Ting Lien, Yii-Chen Wu, Yuan-Fong Su. On the criteria of model performance evaluation for real-time flood forecasting. Stochastic Environmental Research and Risk Assessment. 2016; 31 (5):1123-1146.
Chicago/Turabian StyleKe-Sheng Cheng; Yi-Ting Lien; Yii-Chen Wu; Yuan-Fong Su. 2016. "On the criteria of model performance evaluation for real-time flood forecasting." Stochastic Environmental Research and Risk Assessment 31, no. 5: 1123-1146.
This study ascertains the disaster impacts of extreme rainfall events at the river basin scale. Several numerical models were employed, including TRIGRS for shallow landslide, Flo-2D for debris flow, SOBEK for flooding, and FVCOM for coastline disasters. The connection between numerical models was determined by the input and output data of the scenario. The worst case was selected as the extreme event, i.e. the typhoon event with the most rainfall at the end of the century (2074–2099). Climate change data, including rainfall data, the return period of rainfall events, air pressure, tide data, and sea level were generated after bias correction for the disaster assessment. A river basin with a reservoir was selected as the study area and disaster potential was separately shown for upstream and downstream areas. All disaster impacts are represented on a river basin scale. The result shows that more sediment will affect mountain ways and a large volume of sediment will enter the reservoir. The reservoir is not affected because it has sufficient capacity. The most severe flooding will occur at parts where the main river curves, which are also key areas of mitigation. Finally, the coastline area is at low risk due to the far typhoon track. This result highlights key areas where disaster prevention measures should be implemented during a severe rainfall event.
TingYeh Wu; Hsin-Chi Li; Shaio-Pin Wei; Wei-Bo Chen; Yung-Ming Chen; Yuan-Fong Su; Jen-Jih Liu; Hung-Ju Shih. A comprehensive disaster impact assessment of extreme rainfall events under climate change: a case study in Zheng-wen river basin, Taiwan. Environmental Earth Sciences 2016, 75, 1 -17.
AMA StyleTingYeh Wu, Hsin-Chi Li, Shaio-Pin Wei, Wei-Bo Chen, Yung-Ming Chen, Yuan-Fong Su, Jen-Jih Liu, Hung-Ju Shih. A comprehensive disaster impact assessment of extreme rainfall events under climate change: a case study in Zheng-wen river basin, Taiwan. Environmental Earth Sciences. 2016; 75 (7):1-17.
Chicago/Turabian StyleTingYeh Wu; Hsin-Chi Li; Shaio-Pin Wei; Wei-Bo Chen; Yung-Ming Chen; Yuan-Fong Su; Jen-Jih Liu; Hung-Ju Shih. 2016. "A comprehensive disaster impact assessment of extreme rainfall events under climate change: a case study in Zheng-wen river basin, Taiwan." Environmental Earth Sciences 75, no. 7: 1-17.
Self-similarity of fractal geometry refers to that a part of an object is similar to the whole. This scale-invariant feature has a certain role to play in super-resolution mapping which is a mapping technique across scale aiming at enhancing spatial resolution of remote-sensing imagery. Unlike other super-resolution mapping methods depending solely on spatial continuity, a self-similar pixel swapping (SSPS) method combining spatial continuity and self-similarity of fractal geometry into original pixel swapping (PS) algorithm is presented here. A self-similar weight function defined from the composition information at pixel scale within a predetermined window is added to the calculation of attractiveness in the standard PS method. The self-similar weight function guides the subpixels within a pixel to arrange spatially similar to the appearance of the composition information at pixel scale. Evaluating with synthetic images and satellite image, the performance of the SSPS is particularly obvious in reproducing objects with sharp corners, linear features and adjacent small objects.
Yuan-Fong Su. Spatial continuity and self-similarity in super-resolution mapping: self-similar pixel swapping. Remote Sensing Letters 2016, 7, 338 -347.
AMA StyleYuan-Fong Su. Spatial continuity and self-similarity in super-resolution mapping: self-similar pixel swapping. Remote Sensing Letters. 2016; 7 (4):338-347.
Chicago/Turabian StyleYuan-Fong Su. 2016. "Spatial continuity and self-similarity in super-resolution mapping: self-similar pixel swapping." Remote Sensing Letters 7, no. 4: 338-347.
Yuan-Fong Su; Chao-Tzuen Cheng; Jun-Jih Liou; Yung-Ming Chen; Akio Kitoh. Bias Correction of MRI-WRF Dynamic Downscaling Datasets. Terrestrial, Atmospheric and Oceanic Sciences 2016, 27, 649 -657.
AMA StyleYuan-Fong Su, Chao-Tzuen Cheng, Jun-Jih Liou, Yung-Ming Chen, Akio Kitoh. Bias Correction of MRI-WRF Dynamic Downscaling Datasets. Terrestrial, Atmospheric and Oceanic Sciences. 2016; 27 (5):649-657.
Chicago/Turabian StyleYuan-Fong Su; Chao-Tzuen Cheng; Jun-Jih Liou; Yung-Ming Chen; Akio Kitoh. 2016. "Bias Correction of MRI-WRF Dynamic Downscaling Datasets." Terrestrial, Atmospheric and Oceanic Sciences 27, no. 5: 649-657.
Landslide impact variation under climate change scenario Landslide impact assessment model for Gaoping river basin by TRIGRS model Sensitivity of rain...
TingYeh Wu; Hung-Ju Shih; Hsin-Chi Li; Yuan-Fong Su; Yung-Ming Chen. Landslide Impact Assessment Using Projection Rainfall Data from Climate Change Scenario. Terrestrial, Atmospheric and Oceanic Sciences 2016, 27, 729 -740.
AMA StyleTingYeh Wu, Hung-Ju Shih, Hsin-Chi Li, Yuan-Fong Su, Yung-Ming Chen. Landslide Impact Assessment Using Projection Rainfall Data from Climate Change Scenario. Terrestrial, Atmospheric and Oceanic Sciences. 2016; 27 (5):729-740.
Chicago/Turabian StyleTingYeh Wu; Hung-Ju Shih; Hsin-Chi Li; Yuan-Fong Su; Yung-Ming Chen. 2016. "Landslide Impact Assessment Using Projection Rainfall Data from Climate Change Scenario." Terrestrial, Atmospheric and Oceanic Sciences 27, no. 5: 729-740.
To understand the characteristics of severe floods under global climate change, we created a design hyetograph for a 100-year return period. This incorporates a modified ranking method using the top 10 extreme rainfall events for present, near-future, and far-future periods. The rainfall data sets were projected with a general circulation model with high spatial and temporal resolution and used with a flood model to simulate the higher discharge peaks for the top 10 events of each term in a local watershed. The conventional-like ranking method, in which only a dimensionless shape is considered for the creation of a design hyetograph for a temporal distribution of rainfall, likely results in overestimates of discharge peaks because, even with a lower peak of rainfall intensity and a smaller amount of cumulative rainfall, the distribution shape is the only the factor for the design hyetograph. However, the modified ranking method, which considers amounts of cumulative rainfalls, provides a discharge peak from the design hyetograph less affected by a smaller cumulative rainfall depth for extreme rainfall. Furthermore, the effects of global climate change indicate that future discharge peaks will increase by up to three times of those of Present-term peaks, which may result in difficult flood control for the downstream river reaches.
Nobuaki Kimura; Akira Tai; Shen Chiang; Hsiao-Ping Wei; Yuan-Fong Su; Chao-Tzuen Cheng; Akio Kitoh. Hydrological Flood Simulation Using a Design Hyetograph Created from Extreme Weather Data of a High-Resolution Atmospheric General Circulation Model. Water 2014, 6, 345 -366.
AMA StyleNobuaki Kimura, Akira Tai, Shen Chiang, Hsiao-Ping Wei, Yuan-Fong Su, Chao-Tzuen Cheng, Akio Kitoh. Hydrological Flood Simulation Using a Design Hyetograph Created from Extreme Weather Data of a High-Resolution Atmospheric General Circulation Model. Water. 2014; 6 (2):345-366.
Chicago/Turabian StyleNobuaki Kimura; Akira Tai; Shen Chiang; Hsiao-Ping Wei; Yuan-Fong Su; Chao-Tzuen Cheng; Akio Kitoh. 2014. "Hydrological Flood Simulation Using a Design Hyetograph Created from Extreme Weather Data of a High-Resolution Atmospheric General Circulation Model." Water 6, no. 2: 345-366.
Severe rainstorms have occurred more frequently in Taiwan over the last decade. To understand the flood characteristics of a local region under climate change, a hydrological model simulation was conducted for the Tsengwen Reservoir watershed. The model employed was the Integrated Flood Analysis System (IFAS), which has a conceptual, distributed rainfall-runoff analysis module and a GIS data-input function. The high-resolution rainfall data for flood simulation was categorized into three terms: 1979 - 2003 (Present), 2015 - 2039 (Near-future), and 2075 - 2099 (Future), provided by the Meteorological Research Institute atmospheric general circulation model (MRI-AGCM). Ten extreme rainfall (top ten) events were selected for each term in descending order of total precipitation volume. Due to the small watershed area the MRI-AGCM3.2S data was downsized into higher resolution data using the Weather Research and Forecasting Model. The simulated discharges revealed that most of the Near-future and Future peaks caused by extreme rainfall increased compared to the Present peak. These ratios were 0.8 - 1.6 (Near-future/Present) and 0.9 - 2.2 (Future/Present), respectively. Additionally, we evaluated how these future discharges would affect the reservoir¡¦s flood control capacity, specifically the excess water volume required to be stored while maintaining dam releases up to the dam¡¦s spillway capacity or the discharge peak design for flood prevention. The results for the top ten events show that the excess water for the Future term exceeded the reservoir¡¦s flood control capacity and was approximately 79.6 - 87.5% of the total reservoir maximum capacity for the discharge peak design scenario
Nobuaki Kimura; Shen Chiang; Hsiao-Ping Wei; Yuan-Fong Su; Jung-Lien Chu; Chao-Tzuen Cheng; Jun-Jih Liou; Yung-Ming Chen; Lee-Yaw Lin. Tsengwen Reservoir Watershed Hydrological Flood Simulation Under Global Climate Change Using the 20 km Mesh Meteorological Research Institute Atmospheric General Circulation Model (MRI-AGCM). Terrestrial, Atmospheric and Oceanic Sciences 2014, 25, 449 .
AMA StyleNobuaki Kimura, Shen Chiang, Hsiao-Ping Wei, Yuan-Fong Su, Jung-Lien Chu, Chao-Tzuen Cheng, Jun-Jih Liou, Yung-Ming Chen, Lee-Yaw Lin. Tsengwen Reservoir Watershed Hydrological Flood Simulation Under Global Climate Change Using the 20 km Mesh Meteorological Research Institute Atmospheric General Circulation Model (MRI-AGCM). Terrestrial, Atmospheric and Oceanic Sciences. 2014; 25 (3):449.
Chicago/Turabian StyleNobuaki Kimura; Shen Chiang; Hsiao-Ping Wei; Yuan-Fong Su; Jung-Lien Chu; Chao-Tzuen Cheng; Jun-Jih Liou; Yung-Ming Chen; Lee-Yaw Lin. 2014. "Tsengwen Reservoir Watershed Hydrological Flood Simulation Under Global Climate Change Using the 20 km Mesh Meteorological Research Institute Atmospheric General Circulation Model (MRI-AGCM)." Terrestrial, Atmospheric and Oceanic Sciences 25, no. 3: 449.
The mixed pixel problem may be reduced through the use of a soft image classification and super-resolution mapping analyses. Here, the positive attributes of two popular super-resolution mapping methods, based on contouring and the Hopfield neural network, are combined. For a binary classification scenario, the method is based on fitting a contour of equal class membership to a pre-final output of a standard Hopfield neural network. Analyses of simulated and real image data sets show that the proposed method is more accurate than the standard contouring and Hopfield neural network based methods, with error typically reduced by a factor of two or more. The sensitivity of the Hopfield neural network based approaches to the setting of a gain function is also explored.
Yuan-Fong Su; Giles M. Foody; Anuar Mikdad Muad; Ke-Sheng Cheng. Combining Hopfield Neural Network and Contouring Methods to Enhance Super-Resolution Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2012, 5, 1403 -1417.
AMA StyleYuan-Fong Su, Giles M. Foody, Anuar Mikdad Muad, Ke-Sheng Cheng. Combining Hopfield Neural Network and Contouring Methods to Enhance Super-Resolution Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2012; 5 (5):1403-1417.
Chicago/Turabian StyleYuan-Fong Su; Giles M. Foody; Anuar Mikdad Muad; Ke-Sheng Cheng. 2012. "Combining Hopfield Neural Network and Contouring Methods to Enhance Super-Resolution Mapping." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 5, no. 5: 1403-1417.
Combining super-resolution techniques can increase the accuracy with which the shape of objects may be characterised from imagery. This is illustrated with two approaches to combining the contouring and pixel swapping methods of super-resolution mapping for binary classification applications. In both approaches, the output of the pixel swapping method is softened to allow a contour of equal class membership to be fitted to it to represent the inter-class boundary. The accuracy of super-resolution mapping with the individual and combined techniques is explored, including an assessment of the effect of variation in the number of neighbors and zoom factor on pixel swapping based analyses. When combined, the error with which objects of varying shape were represented was typically greatly reduced relative to that observed from the application of the methods individually. For example, the root mean square error in mapping the boundary of an aeroplane represented in relatively fine spatial resolution imagery decreased from 14.41 m with contouring and 4.35 m with pixel swapping to 3.07 m when the approaches were combined.
Yuan-Fong Su; Giles M. Foody; Anuar Mikdad Muad; Ke-Sheng Cheng. Combining Pixel Swapping and Contouring Methods to Enhance Super-Resolution Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2012, 5, 1428 -1437.
AMA StyleYuan-Fong Su, Giles M. Foody, Anuar Mikdad Muad, Ke-Sheng Cheng. Combining Pixel Swapping and Contouring Methods to Enhance Super-Resolution Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2012; 5 (5):1428-1437.
Chicago/Turabian StyleYuan-Fong Su; Giles M. Foody; Anuar Mikdad Muad; Ke-Sheng Cheng. 2012. "Combining Pixel Swapping and Contouring Methods to Enhance Super-Resolution Mapping." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 5, no. 5: 1428-1437.
Yuan-Fong Su; Giles M. Foody; Ke-Sheng Cheng. Spatial non-stationarity in the relationships between land cover and surface temperature in an urban heat island and its impacts on thermally sensitive populations. Landscape and Urban Planning 2012, 107, 172 -180.
AMA StyleYuan-Fong Su, Giles M. Foody, Ke-Sheng Cheng. Spatial non-stationarity in the relationships between land cover and surface temperature in an urban heat island and its impacts on thermally sensitive populations. Landscape and Urban Planning. 2012; 107 (2):172-180.
Chicago/Turabian StyleYuan-Fong Su; Giles M. Foody; Ke-Sheng Cheng. 2012. "Spatial non-stationarity in the relationships between land cover and surface temperature in an urban heat island and its impacts on thermally sensitive populations." Landscape and Urban Planning 107, no. 2: 172-180.
A new algorithm of path radiance estimation based on measurements of surface reflectance at radiometric control areas (RCAs) is proposed. Path radiance estimates of the proposed RCA-based method were compared against estimates of other methods including the dark object subtraction (DOS) method, the multi-band regression (MBR) technique and the covariance matrix method (CMM). The RCA-based method is superior to other methods based on three qualitative assessment criteria and a quantitative assessment based on measurements of molecule and aerosol optical depths (AODs) available from the Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) data archive. Asphalt-paved surface, which could be easily identified in most images, was also found to be a good choice for RCAs. The DOS method and the CMM tend to overestimate path radiances. Although in our study the MBR technique and the RCA-based method seem to perform equally well, estimates of the MBR technique may be less reliable.
Ke-Sheng Cheng; Yuan-Fong Su; H. C. Yeh; J. H. Chang; W. C. Hung. A path radiance estimation algorithm using reflectance measurements in radiometric control areas. International Journal of Remote Sensing 2011, 33, 1543 -1566.
AMA StyleKe-Sheng Cheng, Yuan-Fong Su, H. C. Yeh, J. H. Chang, W. C. Hung. A path radiance estimation algorithm using reflectance measurements in radiometric control areas. International Journal of Remote Sensing. 2011; 33 (5):1543-1566.
Chicago/Turabian StyleKe-Sheng Cheng; Yuan-Fong Su; H. C. Yeh; J. H. Chang; W. C. Hung. 2011. "A path radiance estimation algorithm using reflectance measurements in radiometric control areas." International Journal of Remote Sensing 33, no. 5: 1543-1566.
Goodness-of-fit tests based on the -moment-ratio diagram for selection of appropriate distributions for hydrological variables have had many applications in recent years. For such applications, sample-size-dependent acceptance regions need to be established in order to take into account the uncertainties induced by sample -skewness and -kurtosis. Acceptance regions of two-parameter distributions such as the normal and Gumbel distributions have been developed. However, many hydrological variables are better characterized by three-parameter distributions such as the Pearson type III and generalized extreme value distributions. Establishing acceptance regions for these three-parameter distributions is more complicated since their -moment-ratio diagrams plot as curves, instead of unique points for two-parameter distributions. Through stochastic simulation we established sample-size-dependent 95% acceptance regions for the Pearson type III distribution. The proposed approach involves two key elements—the conditional distribution of population -skewness given a sample -skewness and the conditional distribution of sample -kurtosis given a sample -skewness. The established 95% acceptance regions of the Pearson type III distribution were further validated through two types of validity check, and were found to be applicable for goodness-of-fit tests for random samples of any sample size between 20 and 300 and coefficient of skewness not exceeding 3.0.
Yii-Chen Wu; Jun-Jih Liou; Yuan-Fong Su; Ke-Sheng Cheng. Establishing acceptance regions for L-moments based goodness-of-fit tests for the Pearson type III distribution. Stochastic Environmental Research and Risk Assessment 2011, 26, 873 -885.
AMA StyleYii-Chen Wu, Jun-Jih Liou, Yuan-Fong Su, Ke-Sheng Cheng. Establishing acceptance regions for L-moments based goodness-of-fit tests for the Pearson type III distribution. Stochastic Environmental Research and Risk Assessment. 2011; 26 (6):873-885.
Chicago/Turabian StyleYii-Chen Wu; Jun-Jih Liou; Yuan-Fong Su; Ke-Sheng Cheng. 2011. "Establishing acceptance regions for L-moments based goodness-of-fit tests for the Pearson type III distribution." Stochastic Environmental Research and Risk Assessment 26, no. 6: 873-885.
In studies involving environmental risk assessment, Gaussian random field generators are often used to yield realizations of a Gaussian random field, and then realizations of the non-Gaussian target random field are obtained by an inverse-normal transformation. Such simulation process requires a set of observed data for estimation of the empirical cumulative distribution function (ECDF) and covariance function of the random field under investigation. However, if realizations of a non-Gaussian random field with specific probability density and covariance function are needed, such observed-data-based simulation process will not work when no observed data are available. In this paper we present details of a gamma random field simulation approach which does not require a set of observed data. A key element of the approach lies on the theoretical relationship between the covariance functions of a gamma random field and its corresponding standard normal random field. Through a set of devised simulation scenarios, the proposed technique is shown to be capable of generating realizations of the given gamma random fields.
Jun-Jih Liou; Yuan-Fong Su; Jie-Lun Chiang; Ke-Sheng Cheng. Gamma random field simulation by a covariance matrix transformation method. Stochastic Environmental Research and Risk Assessment 2010, 25, 235 -251.
AMA StyleJun-Jih Liou, Yuan-Fong Su, Jie-Lun Chiang, Ke-Sheng Cheng. Gamma random field simulation by a covariance matrix transformation method. Stochastic Environmental Research and Risk Assessment. 2010; 25 (2):235-251.
Chicago/Turabian StyleJun-Jih Liou; Yuan-Fong Su; Jie-Lun Chiang; Ke-Sheng Cheng. 2010. "Gamma random field simulation by a covariance matrix transformation method." Stochastic Environmental Research and Risk Assessment 25, no. 2: 235-251.
His study demonstrates the feasibility of coastal water quality mapping using satellite remote sensing images. Water quality sampling campaigns were conducted over a coastal area in northern Taiwan for measurements of three water quality variables including Secchi disk depth, turbidity, and total suspended solids. SPOT satellite images nearly concurrent with the water quality sampling campaigns were also acquired. A spectral reflectance estimation scheme proposed in this study was applied to SPOT multispectral images for estimation of the sea surface reflectance. Two models, univariate and multivariate, for water quality estimation using the sea surface reflectance derived from SPOT images were established. The multivariate model takes into consideration the wavelength-dependent combined effect of individual seawater constituents on the sea surface reflectance and is superior over the univariate model. Finally, quantitative coastal water quality mapping was accomplished by substituting the pixel-specific spectral reflectance into the multivariate water quality estimation model.
Yuan-Fong Su; Jun-Jih Liou; Ju-Chen Hou; Wei-Chun Hung; Shu-Mei Hsu; Yi-Ting Lien; Ming-Daw Su; Ke-Sheng Cheng; Yeng-Fung Wang. A Multivariate Model for Coastal Water Quality Mapping Using Satellite Remote Sensing Images. Sensors 2008, 8, 6321 -6339.
AMA StyleYuan-Fong Su, Jun-Jih Liou, Ju-Chen Hou, Wei-Chun Hung, Shu-Mei Hsu, Yi-Ting Lien, Ming-Daw Su, Ke-Sheng Cheng, Yeng-Fung Wang. A Multivariate Model for Coastal Water Quality Mapping Using Satellite Remote Sensing Images. Sensors. 2008; 8 (10):6321-6339.
Chicago/Turabian StyleYuan-Fong Su; Jun-Jih Liou; Ju-Chen Hou; Wei-Chun Hung; Shu-Mei Hsu; Yi-Ting Lien; Ming-Daw Su; Ke-Sheng Cheng; Yeng-Fung Wang. 2008. "A Multivariate Model for Coastal Water Quality Mapping Using Satellite Remote Sensing Images." Sensors 8, no. 10: 6321-6339.
Ke-Sheng Cheng; Yuan-Fong Su; Fang-Tzu Kuo; Wei-Chun Hung; Jie-Lung Chiang. Assessing the effect of landcover changes on air temperatu×re using remote sensing images—A pilot study in northern Taiwan. Landscape and Urban Planning 2008, 85, 85 -96.
AMA StyleKe-Sheng Cheng, Yuan-Fong Su, Fang-Tzu Kuo, Wei-Chun Hung, Jie-Lung Chiang. Assessing the effect of landcover changes on air temperatu×re using remote sensing images—A pilot study in northern Taiwan. Landscape and Urban Planning. 2008; 85 (2):85-96.
Chicago/Turabian StyleKe-Sheng Cheng; Yuan-Fong Su; Fang-Tzu Kuo; Wei-Chun Hung; Jie-Lung Chiang. 2008. "Assessing the effect of landcover changes on air temperatu×re using remote sensing images—A pilot study in northern Taiwan." Landscape and Urban Planning 85, no. 2: 85-96.