Research Focal Area and Representative Publications

Low impact development (LID), a comprehensive land use planning and design approach with the goal of mitigating land development impacts to the environment, has received wide attention as an effective approach to lessen runoff and pollutant loadings to streams. The spectrum of LID technology include but are not limited to green roof, bioswale, bioretention basin, stormwater fry and wet basins, pervious pavement, etc.   Validated at the SMA in the past few years, for example, pervious pavements and bioswalws are gaining acceptance for water storage and pollution reduction. An integrated system of pervious pavements, bioswale for stormwater recovery for reuse, and groundwater recharge is possible while maintaining the hydrological functionality. The effectiveness of permeable pavements for the removal of some pollutants is another interdisciplinary area that deserves our attention. In addition, rapid infiltration ponds have received much attention in stormwater management, groundwater recharge, and wastewater disposal in terms of both quantity and quality aspects. Developing the LID technologies for groundwater recharge with water quality control has been the focus recently. However, the hydrology, such as flood attenuation, and hydraulics, such as the mounding effect, have not been well understood yet. The use of rapid infiltration ponds for nutrient control can be an extended focus as well. Some of the publications are listed as below:

• O’Reilly, A., Wanielista, M., Chang, N. B., Xuan, Z. and Harris, W. G. (2012): Biogeochemical assessment of coupled nitrogen and carbon cycle beneath a stormwater infiltration basin with biosorption activated media. Science of the Total Environment, 432, 227-242.
• O’Reilley, A., Wanielista, M., Chang, N. B., Harris, W. G. and Xuan, Z. M. (2012): Soil property control of biogeochemical processes beneath two subtropical stormwater infiltration ponds. Journal of Environmental Quality, 41, 1-18.
• O’Reilley, A., Chang, N. B. and Wanielista, M. (2012): Effects of cyclic biogeochemical processes on nitrogen cycling beneath a subtropical stormwater infiltration pond. Journal of Contaminant Hydrology, 133, 53-75.
• Gogo-Abite, I.*, Chopra, M., and Uju, I. (2013): Evaluation of mechanical properties and structural integrity for pervious concrete pavement systems, Journal of Materials in Civil Engineering (ASCE), 26(6), 06014006.
• Xuan, Z. M.*, Chang, N. B., and Wanielista, M. (2013): System dynamics modeling of nitrogen removal in a stormwater infiltration basin with biosorption activated media. Journal of Environmental Quality, 42, 1086–1099.

Stormwater management at the local or regional level is related to a sustainable low cost drinking water. However, the quality of stormwater frequently has to be improved before it can be discharged or stored. As low cost drinking water becomes limited, there is a need for newer technologies to provide an alternative source of this low cost water. SMA has pioneered green infrastructure methods to improve surface water quality and to protect ground water. While the current 8 US patents in SMA are intimately tied to the smart materials (Biosorption Activated Media) to be in concert with LID technology development; an example of water quality management is to develop a cascade treatment train to fit in different urban landscape and find out a way to reuse the treated stormwater. To carry out systematic assessment, SMA has developed a unique stormwater computer program, called BMPTRAIN, to estimate such treatability in series or in parallel, or both. Given that a suite of component-based LID technologies have been tested and validated by the SMA, such an integrated system of stormwater treatment train methods based on target removals is highly adaptable. On-site wastewater treatment system (i.e., septic tank and drainfield) has been well studied by the research staff in SMA resulting in some extended outreach activities till now. More will also be done especially as a higher water quality is needed before discharging to groundwater aquifers and coastal waters. Some of the publications are listed as below:

• Chang, N. B., Chen, H. W. and Ning, S. K. (2001): Identification of river water quality using the fuzzy synthetic evaluation approach. Journal of Environmental Management, 63(3), 293-305.
• Ning, S. K., Chang, N. B., Yang, L., Chen, H. W. and Hsu, H. Y. (2001): Assessing pollution prevention program by QUAL2E simulation analysis for water quality management in the Kao-Ping river basin, Taiwan,” Journal of Environmental Management, 61(1), 61-76.
• Ning, S. K., Cheng, K. Y. and Chang, N. B. (2002): Evaluation of non-point sources pollution impacts by integrated 3S information technologies and GWLF model in the Kao-ping river basin, Taiwan. Water Science and Technology, 46(6), 217–224.
• Chen, H. W., Chang, N. B. and Shaw, D. G. (2005): Valuation of in-stream water quality improvement via fuzzy contingent valuation method. Stochastic Environmental Research and Risk Assessment, 19(2), 158-171.
• Chang, N. B., Srilakshmi Kanth, R. and Parvathinathan, G. (2008): Comparison of models of Simazine transport and fate in subsurface environment in a citrus farm. Journal of Environmental Management, 86, 27-43.
• Chang, N. B., Mani, S., Gomathishanker, G. and Srilakshmi Kanth, R. (2009): Pesticide impact assessment via using Enzyme-linked Immunosorbent Assay (ELISA) technique in the Lower Rio Grande River Basin, Texas. Journal of Water Quality, Exposure and Health, 1(3), 145-158.
• Hossain, F., Chang, N. B., Wanielista, M., Xuan, Z. M. and Makkeasorn, A. (2009): Nitrification and denitrification effect in a passive on-site wastewater treatment system with a recirculation filtration tank. Journal of Water Quality, Exposure and Health, 1(3-4), 31-46.
• Xuan, Z. M., Chang, N. B., Makkeasorn, A. and Wanielista, M. (2009): Initial test of a subsurface constructed wetland with green sorption media for nutrient removal in on-site wastewater treatment systems. Journal of Water Quality, Exposure and Health, 1(3), 159–169.
• Chang, N. B., Hossain, F. and Wanielista, M. (2010): Use of filter media for nutrient removal in natural systems and built environments (I): previous trends and perspectives. Environmental Engineering Science, 27(9), 689-706.
• Chang, N. B., Wanielista, M. and Makkeasorn, A. (2010): Use of filter media for nutrient removal in natural systems and built environments (II): design challenges and application potentials. Environmental Engineering Science, 27(9), 707-720.
• Xuan, Z., Chang, N. B., Wanielista, M. and Hossain, F. (2010): Laboratory-scale characterization of the green sorption medium for wastewater treatment to improve nutrient removal. Environmental Engineering Science, 27(4), 301-312.
• Chang, N. B., Wanielista, M., Daranpob, A., Hossain, F. and Xuan, Z. (2010): New performance-based passive septic tank underground drainfield for nutrient and pathogen removal using sorption medium. Environmental Engineering Science, 27(6), 469-482.
• Xuan, Z. M., Chang, N. B., Daranpob, A. and Wanielista, M. (2010): Modeling the Subsurface Upflow Wetlands (SUW) systems for wastewater effluent treatment. Environmental Engineering Science, 27(10), 879-888.
• Hossain, F., Chang, N. B. and Wanielista, M. (2010): Modeling kinetics and isotherm of functionalized filter medium for nutrient removal in stormwater dry ponds. Environmental Progress and Sustainable Energy, 29(3), 319–333.
• Chang, N. B., Xuan, Z. M., Daranpob, A. and Wanielista, M. (2011): A subsurface upflow wetland system for nutrient and pathogen removal in on-site sewage treatment and disposal systems. Environmental Engineering Science, 28(1), 11-24.
• Chang, N. B., Wanielista, M. and Henderson, D. (2011): Temperature effects on functionalized filter media for nutrient removal in stormwater treatment. Environmental Progress and Sustainable Energy, 30(3), 309-317.
• Ryan, P., Wanielista, M. and Chang, N. B. (2010): Reducing nutrient concentrations from a stormwater wet pond using a Chamber Upflow Filter and Skimmer (CUFS) with green sorption media. Water, Air and Soil Pollution, 208(1), 385-400.  
• Xuan, Z. M., Chang, N. B. and Wanielista, M. (2012): Modeling the system dynamics for nutrient removal in an innovative septic tank media filter. Bioprocess and Biosystems Engineering, 35(4), 545-552.
• Chang, N. B., Xuan, Z. M. and Wanielista, M. (2012): A tracer study for addressing the interactions between hydraulic retention time and transport processes in a subsurface wetland system for nutrient removal. Bioprocess and Biosystems Engineering, 35(3), 399-406.
• Lian, J., Xu, S., Chang, N. B., Han, C. and Liu, J. (2013): Removal of molybdate from mine tailing effluents with the aid of loessial soil and slag waste. Environmental Engineering Science, 30(5), 213-220.
• Chang, N. B., Jones, J., and Wanielista, M. (2015): Reliability analysis of phosphorus removal efficiencies of stormwater runoff with green sorption media under varying Influent conditions. Science of the Total Environment, 502(1), 434–447.
• Hood, A., Chopra, M., and Wanielista, M., (2013): Assessment of biosorption activated media under roadside swales for the removal of phosphorus from stormwater. Water, 5(1), 53-66.
• Chang, N. B., Xuan, Z., Marimon, Z., Islam, K., and Wanielista, M. P. (2013): Exploring hydrobiogeochemical processes of floating treatment wetlands in a subtropical stormwater wet pond. Ecological Engineering, 54, 66-76.
• Imen, S., Chang, N. B., and Yang, J. (2015): Developing a remote sensing-based early warning system for monitoring TSS concentrations in Lake Mead, Journal of Environmental Management, 160, 73-89.
• Chang, N. B., Houmann, C., and Wanielista, M. (2015): Scaling up the Sorption Media Reactors for Copper Removal with the aid of Dimensionless Numbers. Chemosphere, in press.

Soil erosion and sediment controls are measures developed for reducing the amount of soil particles that might be carried out of a land area and deposited in a receiving water body. Ongoing efforts in using the state-of-the-art Rainfall Simulator with tilting test beds for studying erosion and sediment control measures at SMA will be enhanced using smart sensors and new materials, such as embedded nanomaterials. Erosion and sediment control analysis may get started by using watershed modeling with the aid of remote sensing, geographical information system, and global positioning system at the basin scale. Once the critical location of an erosion hazard is identified in a river basin, local scale erosion and sediment control efforts may be implemented. In addition, coastal erosion control will become a necessity due to storm tides and surge under the impact of extreme weather and sea level rise. SMA will look into possible research opportunities along this line too. Some of the publications are listed as below:

• Ning, S. K., Chang, N. B., Jeng, K. Y. and Tseng, Y. H. (2006): Soil erosion and non-point sources pollution impacts assessment with the aid of remote sensing. Journal of Environmental Management, 79(1), 88-101.
• Makkeasorn, A., Chang, N. B., Beaman, M., Wyatt, C. and Slater, C. (2006): Soil moisture prediction in a semi-arid reservoir watershed using RADARSAT satellite images and genetic programming. Water Resources Research, 42, 1-15.
• Ning, S. K. and Chang, N. B. (2007): Watershed-based point sources permitting strategy and dynamic permit trading analysis. Journal of Environmental Management, 84(4), 427-446.
• Lin, K. S., Chang, N. B. and Chuang, T. D. (2008): Fine structure characterization of zero-valent Iron nanoparticles for decontamination of nitrites and nitrates in wastewater. Science and Technology for Advanced Materials, 9, 025105 (9pp).
• Gogo-Abite, I., Chopra, M., and Wanielista, M. (2013): Performance evaluation of two silt fence fabrics using a tilting test-bed with simulated rainfall, geotextiles and geomembranes, Journal of Hydrologic Engineering, ASCE, 39, 30-38, .
• Kakuturu, S., Chopra, M., Hardin, M., and Wanielista, M. (2013): Runoff curve numbers for simulated highway slopes under different slope, soil-turf, and rainfall conditions, Journal of Hydrologic Engineering, ASCE, 18(3), 299–306.
• Chang, N. B., Crawford, A. J., and Mohiuddin, G. (2015): Low flow regime measurements with an automatic pulse tracer velocimeter (APTV) in heterogeneous aquatic environments, Flow Measurement and Instrumentation, 42, 98–112.
• Crawford, A. J. and Chang, N. B. (2015): Developing the Groundwater Variability Probes (GVP) and wireless sensor networks for characterizing the low flow field, IEEE Sensors Journal, in press.

Urbanization often increases the impervious surface that results in larger runoff in populated areas and greater flooding risk. Worse of all, the extreme rainfall events are likely to occur more violently and frequently due to the climate change impact. The sea level rise also poses threats to coastal cities. Under such hybrid impact, an integrated approach is required to evaluate the flood impact of the combinations of urban growth and climate change. Future socio-economic trends also need to be accounted for such that authorities can set up effective measures to improve the infrastructure resilience of cities and reduce the flood risk. Options to harvest clean water co-exist in parallel with flood proofing resulting in many extended research initiatives in the future. SMA is developing an integrated modelling framework for assessing the current and future flood impact under changing climate and urban land use patterns simultaneously. Such approach will result in the new planning and design strategies of smart stormwater management grid in highly urbanized regions in which the LID technologies can be an integral part of the smart stormwater management grid. Some of the publications are listed as below:

• Zhou, X. B., Chang, N. B. and Li, S. S. (2007): Detection of coastal region sea ice decay from orthorectified RADARSAT-1 ScanSAR imagery: a case study of Bering Strait and Norton Sound, Alaska. Journal of Environmental Informatics, 10(1), 37-46.
• Ernest, A., Bokhim, B., Chang N. B. and Huang, I. J. (2007): Fluvial geomorphologic and hydrodynamic assessment in the tidal portion of the Lower Rio Grande River, US-Mexico Borderland. Journal of Environmental Informatics, 10(1), 10-21.
• Makkeasorn, A., Chang, N. B. and Zhou, X. (2008): Short-term stream flow forecasting with global climate change implications – A comparative study between genetic programming and neural network models. Journal of Hydrology, 352, 336-354.
• Wang, C., Chang, N. B. and Yeh, G. (2009): Copula-based Flood Frequency (COFF) analysis at the confluences of river systems. Hydrological Processes, 23, 1471-1486.
• Makkeasorn, A. and Chang, N. B. (2009): Seasonal change detection of riparian zones with remote sensing images and genetic programming in a semi-arid watershed. Journal of Environmental Management, 90, 1069–1080.
• Chen, H. W., Chang, N. B., Yu, R. F. and Huang, Y. W. (2009): Urban land use and land cover classification using the neural-fuzzy inference approach with Formosat-2 Data. Journal of Applied Remote Sensing, 3, 033558.
• Gao, W., Zhang, W., Gao, Z. and Chang, N. B. (2009): Modeling the land surface heat exchange process with the aid of moderate resolution imaging spectroradiometer images. Journal of Applied Remote Sensing, 3, 033573.
• Chang, N. B., Han, M., Yao, W., Xu, S. G. and Chen, L. C. (2010): Change detection of land use and land cover in a fast growing urban region with SPOT-5 images and partial Lanczos extreme learning machine. Journal of Applied Remote Sensing, 4, 043551.
• Xie, H., Chang, N. B., Makkeasorn, A. and Prado, D. (2010): Assessing the long-term urban heat island in San Antonio, Texas based on MODIS/Aqua Data. Journal of Applied Remote Sensing, 4, 043508.
• Chang, N. B., Yang, J. and Daranpob, A. (2010): Medium-term Metropolitan Water Availability Index (MWAI) assessment based on synergistic potentials of multi-sensor data. Journal of Applied Remote Sensing, 4, 043519.
• Sun, Z., Chang, N. B. and Opp, C. (2010): Using SPOT-VGT NDVI as successive ecological indicators of for understanding the environmental implications in the Tarim River Basin, China. Journal of Applied Remote Sensing, 4, 043554.
• Sun, Z., Chang, N. B., Opp, C. and Hennig, T. (2011): Evaluation of ecological restoration through vegetation patterns in the Lower Tarim River, China with MODIS NDVI Data. Ecological Informatics, 6, 156-163.
• Gao, Z., Gao, W. and Chang, N. B. (2011): Integrating Temperature Vegetation Dryness Index (TVDI) and Regional Water Stress Index (RWSI) for drought assessment with the aid of landsat TM/ETM+ images. International Journal of Applied Earth Observation and Geoinformation, 13(3), 495-503.
• Gao, Z., Xie, X., Gao, W. and Chang, N. B. (2011): Spatial analysis of terrain-impacted Photosynthetic Active Radiation (PAR) using MODIS data. GIScience & Remote Sensing, 48(4), 1-21.
• Gao, Z., Liu, C., Gao, W. and Chang, N. B. (2011): A coupled remote sensing and the surface energy balance with Topography Algorithm (SEBTA) to estimate actual evapotranspiration over heterogeneous terrain. Hydrology and Earth System Sciences, 15, 119-139.
• Jin, K. R., Chang, N. B., Ji, J. and Thomas, J. R. (2011): Hurricanes affect sediment and environments in Lake Okeechobee. Critical Reviews in Environmental Science and Technology, 41(S1), 382-394.
• Kao, S. C. and Chang, N. B. (2012): Copula-based flood frequency analysis at ungaged basin confluences: a case study for Nashville, TN. Journal of Hydrologic Engineering, ASCE, 17(7), 790-800.
• Chang, N. B. and Jin, K. R. (2012): Ecodynamic assessment of the submerged aquatic vegetation in Lake Okeechobee, Florida under natural and anthropogenic stress. International Journal of Design & Nature and Ecodynamics, 7(2), 140-154.
• Gao, Z., Gao, W. and Chang, N. B. (2012): Evaluation of dynamic linkages between evapotranspiration and land use/land cover changes with Landsat TM and ETM+ data. International Journal of Remote Sensing, 33(12), 3733-3750.
• Sadeghi, Z., Zouj, M. J. V., Dehghani, M. and Chang, N. B. (2012): An enhanced algorithm based on persistent scatterer interferometry for high-rate land subsidence estimation. Journal of Applied Remote Sensing, 6(1), 063573.
• Sun, Z. and Chang, N. B., Huang, Q. and Opp, C. (2012): Precipitation patterns and associated summer extreme flow analyses in the Yangtze River, China using TRMM/PR data. Hydrologic Sciences Journal, 57(7), 1-10.
• Liu, S. and Chang, N. B. (2013): Geochemical impact of aquifer storage and recovery operation on fate and transport of sediment phosphorus in a large shallow lake. Environmental Earth Sciences, 68(1), 189-201.
• Chen, C. F., Son, N. T., Chang, N. B., Chen, C. R., Chang, L. U., Valdez, M., Centeno, G., Thompson, C., and Aceituno, J. L. (2013): Multi-decadal mangrove forest change detection and prediction in Honduras, Central America with Landsat imageries and Markov chain model. Remote Sensing, 5(12), 6408-6426.
• Mullon, L., Chang, N. B., Yang, J. and Weiss, J. (2013): Integrated remote sensing and wavelet analyses for short-term teleconnection pattern identification between sea surface temperature and greenness in northeast America. Journal of Hydrology, 499, 247-264.
• Chen, C. F., Valdez, M. C., Chang, N. B., Chang, L. Y., and Yuan, P. Y. (2014): Monitoring spatiotemporal surface soil moisture variations during dry seasons in Central America with multi-sensor cascade data fusion. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, DOI: 10.1109/JSTARS.2014.2347313.
• Son, N. T., Chen, C. F., Chang, N. B., and Chen, C. R. (2014): Mangrove mapping and change detection in Ca Mau Peninsula, Vietnam using Landsat data and object-based image analysis. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, in press, Sept., 2014.
• Chang, N. B., Valdez, M., Chen, J. F., Imen, S., and Mollun, L. (2014): Nonlinear and nonstationary global climate change effect on regional precipitation and forest phenology in Panama, Central America, Hydrological Processes, DOI: 10.1002/hyp.10151
• Chang, N. B., Valdez, M., Chen, J. F., Imen, S., and Mollun, L. (2015):  Global nonlinear and nonstationary climate change effects on regional precipitation and forest phenology in Panama, Central America. Hydrological Processes, 29(3), 339-355.

Ecological engineering technologies, such as floating treatment wetland in stormwater wet ponds, may polish water quality in stormwater runoff and enhance ecosystem service design contributing to urban sustainability. There are a variety of opportunities to integrate treatment methods and ecological engineering technologies with infrastructure system engineering approaches at different scales. Constructed wetland located at the Stormwater Treatment Area (STA) north to the Everglades has been sampled and monitored by SMA for developing a better retrofit strategies. SMA has also conducted various ecosystem restoration case studies across Florida. Optimal planning and design of stormwater treatment and reuse that are deemed as an integral part of basin-scale treatment strategies requires a series of innovative treatment train design. Stormwater impacts on transportation grids may be harmonized by using ecological engineering approach to improve aesthetic value of the total environment. Some of the publications are listed as below:

• Chang, N. B., Islam, K., Marimon, Z., Xuan, Z. M. and Wanielista, M. (2012): Assessing chemical and biological signatures of nutrient removal via the use of floating islands in stormwater mesocosms. Chemosphere, 88(6), 736-743.
• Chang, N. B., Islam, K. and Wanielista, M. (2012): Floating wetland mesocosm assessment of nutrient removal to reduce ecotoxicity in stormwater ponds. International Journal of Environmental Science and Technology, 9(3), 453-462.
• Xuan, Z. M., Chang, N. B., and Wanielista, M. (2013): System dynamics modeling of nitrogen removal in a stormwater infiltration basin with biosorption activated media. Journal of Environmental Quality, 42, 1086–1099.
• Chang, N. B., Xuan, Z., Marimon, Z., Islam, K., and Wanielista, M. P. (2013): Exploring hydrobiogeochemical processes of floating treatment wetlands in a subtropical stormwater wet pond. Ecological Engineering, 54, 66-76.
• Marimon, Z. A., Xuan, Z., and Chang, N. B. (2013): System dynamics modeling with sensitivity analysis for floating treatment wetlands in a stormwater wet pond. Ecological Modelling, 267, 66– 79.
• Chang, N. B., Mohiuddin, G., Crawford, A. J., and Jin, K. R. Diagnosis of the AI-based predictions of flow regimes in a constructed wetland for stormwater pollution control. Ecological Informatics, 28, 42-60, 2015.
• Xuan, Z. and Chang, N. B. (2014): Modeling the climate-induced changes of lake ecosystem structure under the cascade impacts of hurricanes and droughts, Ecological Modelling, 288, 79-93.

To ensure the efficiency and effectiveness of stormwater management that contributes to the restoration of aquatic environments and ecosystem integrity, a wealth of Best Management Practices (BMPs) can be woven together for improving the water quality and ecosystem integrity in lakes, wetlands, and coastal estuary and bayou at the same time. To monitor the efficacy and effectiveness of those BMPs, advanced remote sensing techniques, such as Integrated Data Fusion and Machine-Learning (IDFM) developed for near real-time environmental monitoring by the SMA, may be upgraded to meet the field requirements in due course. This effort leads to the development of early warning systems for drinking water infrastructure impact assessment. All of these efforts may be assessed based on a system of systems engineering approach. Stormwater impacts on transportation grids may be investigated and monitored with integrated structural health monitoring to identify target improvement areas via coupling traffic incidents, flooding and structure risk assessment. Some of the publications are listed as below:

• Chang, Y. C. and Chang, N. B. (2002): The design of a web-based decision support system for the sustainable management of an urban river system. Water Science and Technology, 46(6), 131-139.
• Chen, J. C., Chang, N. B., Chang, Y. C. and Lee, M. T. (2003): Mitigating the impacts of combined sewer overflow in an urban river system via web-based share-vision modeling analysis. Journal of Civil Engineering and Environmental Systems, 20(4), 213-230.
• Chen, J. C., Chang, N. B., Fen, C. S. and Chen, C. Y. (2004): Assessing the stormwater impact to an urban river ecological system using an estuarine water quality simulation model. Journal of Civil Engineering and Environmental Systems, 21(1), 33-50.
• Chen, J. C., Chang, N. B. and Chen, C. Y. (2004): Minimizing the ecological risk of combined-sewer overflow in an urban river system by a system-based approach. Journal of Environmental Engineering, ASCE, 130(10), 1-16.
• Ning, S. K. and Chang, N. B. (2004): Optimal expansion of water quality monitoring network by fuzzy optimization approach. Environmental Monitoring and Assessment, 91(1-3), 145-170.
• Chang, N. B. and Hernandez, E. A. (2008): Optimal expansion strategies for a sanitary sewer system under uncertainty. Environmental Modeling and Assessment, 13(1), 93-113.
• Chang, N. B. and Makkeasorn, A. (2010): Optimal site selection of watershed hydrological monitoring stations using remote sensing and grey integer programming. Environmental Modeling and Assessment, 15(6), 469-486.
• Chang, N. B., Pongsanone, N. P. and Ernest, A. (2011): Comparisons between a rule-based expert system and optimization models for sensor deployment in a small-scale drinking water distribution network. Expert System with Applications, 38, 10685–10695.
• Chang, N. B., Yang, J., Daranpob, A., Jin, K. R. and James, T. (2012): Spatiotemporal pattern validation of Chlorophyll-a concentrations in Lake Okeechobee, Florida using a comparative MODIS image mining approach. International Journal of Remote Sensing, 33(7), 2233-2260.
• Chang, N. B., Wimberly, B. and Xuan, Z. M. (2012): Identification of spatiotemporal nutrient patterns in a coastal bay via an integrated K-means clustering and gravity model. Journal of Environmental Monitoring, 14, 992-1005.
• Chang, N. B., Ernest, A. and Pongsanone, N. P. (2012): A rule-based decision support system for sensor deployment in small drinking water networks. Journal of Cleaner Production, 29, 28-37.
• Chang, N. B., Pongsanone, N. P. and Ernest, A. (2012): Optimal sensor deployment in a large-scale complex drinking water distribution network: comparisons between a rule-based decision support system and optimization models. Computers and Chemical Engineering, 43, 191-199.
• Chang, N. B., Xuan, Z. M. and Wimberly, B. (2012): Remote sensing spatiotemporal assessment of nitrogen concentrations in Tampa Bay, Florida due to a drought. Journal of Terrestrial, Atmospheric and Oceanic Sciences, 23(5), 467-479.
• Chang, N. B., Xuan, Z., and Yang, J. (2013): Exploring spatiotemporal patterns of nutrient concentrations in a coastal bay with MODIS images and machine learning models. Remote Sensing of Environment, 134, 100-110.
• Chang, N. B., Vannah, B., Yang, Y. J., and Elovitz, M. (2014): Integrated data fusion and mining techniques for monitoring total organic carbon concentrations in a lake. International Journal of Remote Sensing, 35(3), 1064-1093.
• Chang, N. B. and Vannah, B., and Yang, J. (2014): Comparative sensor fusion between hyperspectral and multispectral remote sensing data for monitoring microcystin distribution in Lake Erie. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(6), 2426-2442.
• Doña-Monzó, C., Chang, N. B., Vannah, B. W., Sánchez-Tomás, J. M., Delegido-Gómez, J., Camacho-González, A., and Caselles-Miralles, (2015): Integrated satellite data fusion and mining for monitoring lake water quality status of the Albufera de Valencia in Spain, Journal of Environmental Management, 151, 416-426
• Chen, C. F., Son, N. T., Chang, N. B., Chen, C. R., Chang, L. U., Valdez, M., Centeno, G., Thompson, C., and Aceituno, J. L. (2013): Multi-decadal mangrove forest change detection and prediction in Honduras, Central America with Landsat imageries and Markov chain model. Remote Sensing, 5(12), 6408-6426.
• Chang, N. B., Imen, S., and Vannah, B. (2015): Remote sensing for monitoring surface water quality status and ecosystem state in relation to the nutrient cycle: a 40-year perspective. Critical Reviews of Environmental Science and Technology, 45(2), 101-166.
• Son, N. T., Chen, C. F., Chang, N. B., and Chen, C. R. (2105): Mangrove mapping and change detection in Ca Mau Peninsula, Vietnam using Landsat data and object-based image analysis.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8(2), 530-510.
• Chang, N. B., Bai, K. X., and Chen, C. F. (2105): Smart information reconstruction via time-space-spectrum continuum for cloud removal in satellite images, IEEE Journal of Selected Topics in Applied Earth Observations, 99, 1-15, 2015.
• Bai, K. X., Chang, N. B., and Chen. C. F. (2015): Spectral Information Adaptation and Synthesis Scheme (SIASS) for merging cross-mission consistent ocean color reflectance observations from MODIS and VIIRS. IEEE Transactions on Geoscience and Remote Sensing, 99, 1-19.