Journal of Computer Sciences and Applications
ISSN (Print): 2328-7268 ISSN (Online): 2328-725X Website: Editor-in-chief: Minhua Ma, Patricia Goncalves
Open Access
Journal Browser
Journal of Computer Sciences and Applications. 2019, 7(1), 43-49
DOI: 10.12691/jcsa-7-1-7
Open AccessArticle

Optimizing Photogrammetric Techniques for Wetlands Monitoring: Southeast Texas

Mahdi Safa1, , Alexandra Sokolova2, Parsa Safa3 and Kelly Weeks4

1Engineering Technology, Sam Houston State University, Huntsville, TX 77340, U.S.

2Research Assistant Student, Lamar University, Beaumont, TX 77710, U.S.

3Research Assistant Student, Political Science, Pre Law, Baylor University, Waco, Texas

4Marketing and Management, Baylor University, Waco, Texas

Pub. Date: October 20, 2019

Cite this paper:
Mahdi Safa, Alexandra Sokolova, Parsa Safa and Kelly Weeks. Optimizing Photogrammetric Techniques for Wetlands Monitoring: Southeast Texas. Journal of Computer Sciences and Applications. 2019; 7(1):43-49. doi: 10.12691/jcsa-7-1-7


Environmentalists express concerns about the health of the planet and the vital role of wetlands on Earth. Sufficient knowledge of wetland changes is becoming more crucial as loss of wetland area increases. However, an ability to efficiently map and monitor the wetland topographies requires technology advancement. Producing high resolution and high quality digital elevation models (DEMs) requires substantial investments in personnel time, hardware, and software while increasing accessibility of three-dimensional imaging methods, such as digital photogrammetry. Further refinements have highly improved the method while preserving its convenience. This study introduces unmanned aerial system (UAS) coupled with with structure-from-motion (SfM) technology as a new method in wetland mapping. The contributions of this study are aimed at maximizing the efficiency and accuracy of the data collection process for mapping the Southeast Texas wetlands and other related applications. This paper serves as a summary and evaluation of various photogrammetric and data extraction techniques.

Unmanned Aerial System (UAS) Unmanned Aerial Vehicle (UAV) Structure-from-Motion (SfM) Wetland Mapping Digital Photogrammetry

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit


[1]  Mitsch, W, J., and Gosselink, J.G. (2000). The values of wetlands: Landscapes and institutional perspectives, Ecological Economics, Vol. 35 No. 200, pp. 25-33.
[2]  Ramani Bai, G. and Tamjis, M.R. (2008). Water quality in healthcare, Int. J. Environmental Technology and Management, Vol. 9, No. 1, pp.125-140.
[3]  Perera, R. and Kantawanichkul, S. (2011). Constructed wetland system for treating wastewater of scattered small industries: a case study of fermented fish production industry in Phayao City, Thailand, Int. J. Environmental Technology and Management, Vol. 14, Nos. 1/2/3/4, pp.103-114.
[4]  Dahl, T. E. (2000). Status and trends of wetlands in the conterminous United States 1986 to 1997. [online] Washington, DC: U.S. Department of the Interior, Fish and Wildlife. (Accessed 3 June 2017).
[5]  Anderson, K. and Gaston K.J. (2013). Lightweight unmanned aerial vehicles will revolutionize spatial ecology, Frontiers in Ecology and the Environment. Vol. 11 No. 3, pp.138-146.
[6]  Colomina, I. and Molina, P. (2014). Unmanned aerial systems for photogrammetry and remote sensing: A review, ISPRS Journal of Photogrammetry and Remote Sensing. Vol. 92, pp. 79-97.
[7]  Aelion, C.M. and Tuerk, K. (2005). Technology development for environmental problems of the Southeastern United States, Int. J. Environmental Technology and Management, Vol. 5, Nos. 2/3, pp.183-202.
[8]  El-Gafy M., Abdelhamid T., AbdelRazig Y. (2010). Environmental impact analysis using hybrid decision support framework: a transportation project case study, International Journal of Construction Education and Research, 6:3, pp. 219-237.
[9]  Allenby, B. (2007) Creating economic, social and environmental value: an information infrastructure perspective, Int. J. Environmental Technology and Management, Vol. 7, Nos. 5/6, pp.618-631.
[10]  Greb, S. F., DiMichele, W. A., Gastaldo, R. A. (2006). Evolution and importance of wetlands in earth history, Geological Society of America Special Papers, Vol. 399, pp. 1-40
[11]  Bullock A. and Acreman M. (2003). The role of wetlands in the hydrological cycle, Hydrology and Earth System Sciences Discussions. Vol. 7 No.3, pp. 358-389.
[12]  Smith, E.D. and Bishop, B.S. (2005). Benefits to groundwater quality by diverting construction and demolition wastes from landfills, Int. J. Environmental Technology and Management, Vol. 5, Nos. 2/3, pp.230-245.
[13]  Dugan, P.J. (1990). Wetland Conservation: A Review of Current Issues and Required Action. IUCN, Gland, Switzerland.
[14]  Žalakevičius, M., & Švažas, S. (2005). Global climate change and its impact on wetlands and waterbird polulations, Acta Zoologica Lithuanica, 15(3), pp. 211-217.
[15]  Ruth, M. (2007). Integrative environmental research and education, Int. J. Environmental Technology and Management, Vol. 7, Nos. 5/6, pp.632-643.
[16]  U.S. Environmental Protection Agency (EPA) (2010). Guidelines for Preparing Economic Analysis [online]. EPA, Washington. (240-R-10-001). (Accessed 27 May 2017).
[17]  Ventura Victoria, J., Marbella Sánchez, F. and Fernández Gago, R. (2003). The impact of environmental intervention on business management: an empirical survey of its presence in the packaging sector in Spain and of results achieved, Int. J. Environmental Technology and Management, Vol. 3, Nos. 3/4, pp.312-335.
[18]  WWF Global (2017). The value of wetlands. [online] (Accessed 3 June 2017).
[19]  Gordon, S. J., & Lichti, D. D. (2007). Modeling terrestrial laser scanner data for precise structural deformation measurement, Journal of Surveying Engineering, Vol. 133 No. 2, pp. 72-80.
[20]  Scherer, M. and Lerma, J. L. (2009). From the conventional total station to the prospective image assisted photogrammetric scanning total station: comprehensive review, Journal of Surveying Engineering, Vol. 135 No. 4, pp. 173-178.
[21]  Dai, F., Feng, Y., & Hough, R. (2014). Photogrammetric error sources and impacts on modelling and surveying in construction engineering applications, Visualization in Engineering, Vol. 2 No. 2, pp. 1-14.
[22]  Teza, G., Pesci, A., & Ninfo, A. (2016). Morphological Analysis for Architectural Applications: Comparison between Laser Scanning and Structure-from-Motion Photogrammetry, Journal of Surveying Engineering, Vol. 142 No. 3, pp. 1-10.
[23]  Böhner, C. (2006). Decision support systems for sustainable urban planning, Int. J. Environmental Technology and Management, Vol. 6, Nos. 1/2, pp.193-205.
[24]  Azhar, S. and Brown, J. (2009). BIM for Sustainability Analyses. International Journal of Construction Education and Research, 5(4), pp. 276-292.
[25]  Rigby, E.T., McCoy, A.P., Garvin, M.J. (2012). Toward aligning academic and industry understanding of innovation in the construction industry, International Journal of Construction Education and Research, 8(4), pp. 243-259.
[26]  Safa, M., Sabet, A., Ghahremani, K., Haas, C., & Walbridge, S. (2015). Rail corrosion forensics using 3D imaging and finite element analysis. International Journal of Rail Transportation, 3(3), 164-178.
[27]  Rutchey, K., and Vilchek, L. (1999). Air photointerpretation and satellite imagery analysis techniques for mapping cattail coverage in a northern Everglades impoundment, Photogrammetric Engineering and Remote Sensing, Vol. 65 No. 2, pp. 185-191.
[28]  Fonstad, M. A., Dietrich, J.T., Courville, B.C., Jensen, J.L., Carbonneau, P.E. (2013). Topographic structure from motion: a new development in photogrammetric measurement, Earth Surface Processes and Landforms, Vol. 38 No. 4, pp. 421-430.
[29]  Fabris Massimo and Arianna Pesci (2005). Automated DEM extraction in digital aerial photogrammetry: precisions and validation for mass movement monitoring, Annals of Geophysics, Vol. 48 No. 6, pp. 973-988.
[30]  Jenson, S. K. and Domingue J.O. (1988). Extracting topographic structure from digital elevation data for geographic information system analysis, Photogrammetric engineering and remote sensing, Vol. 54 No.11, pp. 1593-1600.
[31]  Safa, M., Shahi, A., Nahangi, M., Haas, C., Noori, H. (2015) Automating measurement process to improve quality management for piping fabrication, Structures, Vol. 3, pp. 71-80.
[32]  Sesli, F.A. (2010) Mapping and monitoring temporal changes for coastline and coastal area by using aerial data images and digital photogrammetry: A case study from Samsun, Turkey, International Journal of the Physical Sciences, Vol. 5 No. 10, pp. 1567-1575.
[33]  Jenkins, D. and Vasigh, B. (2013). The Economic Impact of Unmanned Aircraft Systems Integration in the United States, Arlington, VA: AUVSI Economic Report.
[34]  Gasperini, D., Allemand, P., Delacourt, C. and Grandjean, P. (2014) Potential and limitation of UAV for monitoring subsidence in municipal landfills, Int. J. Environmental Technology and Management, Vol. 17, No. 1, pp.1-13.
[35]  Frayer, W.E. (1983) Status and Trends of Wetlands and Deepwater Habitats in the Conterminous United States, 1950’s to 1970’s. Fort Collins, CO: Department of Forest and Wood Sciences, Colorado State University.
[36]  Tiner, R.W. (1984). Wetlands of the United States: Current Status and Recent Trends. Washington, DC: U.S. Fish and Wildlife Service. Technical Report.
[37]  Safa, M., Shahi, A., & Weeks, K. (2018). Advancing Measurement Process to Improve Inspection of Construction Heavy Equipment Using State-of-the-Art Technologies. In Construction Research Congress 2018. (pp. 562-571).
[38]  James, M. R., & Robson, S. (2012). Straightforward reconstruction of 3D surfaces and topography with a camera: Accuracy and geoscience application. Journal of Geophysical Research: Earth Surface, 117(F3).
[39]  Texas Commission on Environmental Quality (2017). Texas Drought Information [online]. (Accessed 30 May 2017).