Land Use and Land Cover Change Detection for Water Yield Estimation using Remote Sensing Data in Batu Pahat, Johor

Hong Ziexin, Amal Najihah, Sunisa Suchat, Siwipa Pruitikanee, ๋Jinda Kongcharoen, Supattra Puttinaovarat


Globally, the accelerating urbanization led by industrialization and population growth causes severe environmental degradation. The urban expansion particularly to the conversion of land activities affects the ecosystem services critically. This study helps to fill in the gap of determining water yield in the urban area to reduce water stress due to the spatial land use change. The research objectives are to quantify the spatial land use change in Batu Pahat, Johor in the year 1999, 2010, and 2018. Second, to identify the water yield of Batu Pahat in the years 1999, 2010, and 2018. Third, to determine the relationship between water yield, vegetation, and urban expansion. The methods used are landscape change, water yield simulation, and statistical analysis by using the software included ENVI, ArcGIS, FRAGSTAT, Annual Water Yield InVEST Model, and Microsoft Excel. Raw satellite images were extracted for the year 1999, 2010, and 2018. The supervised classification of LULC (Land Use and Land Cover) was done based on the region created which are built-up area, cleared land, vegetation, and water bodies. This study generates results for the changes in percentage area for each LULC class. The highest percentage of area in Batu Pahat is vegetation while the cleared land ranked lowest. In conclusion, this study will aid in understanding and provided empirical data result for the urban expansion and water yield in Batu Pahat, Johor by using GIS and remote sensing applications to produce land use and water yield map as final output.


Water yield; LULC classification and change detection; InVest model; landsat.

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C. Grislain-Letrémy, and B. Villeneuve, “Natural disasters, land-use, and insurance.” Geneva Risk Ins Rev, vol. 44, no. 1, pp. 54-86, 2019.

S. Puttinaovarat, and P. Horkaew, “Flood Forecasting System Based on Integrated Big and Crowdsource Data by Using Machine Learning Techniques.” IEEE Access, vol. 8, pp. 5885-5905, 2020.

D. Dodman, “Environment and Urbanization. International Encyclopedia of Geography: People,” the Earth, Environment and Technology, pp. 1–9, 2017.

S. Li, H. Yang, M. Lacayo, J. Liu, and G. Lei, “Impacts of land-use and land-cover changes on water yield: A case study in Jing-Jin-Ji,” China. Sustainability, vol.10, no. 4, pp. 960, 2018.

Y. Zhou et al., “Simulation of the Impact of Urban Forest Scale on PM2. 5 and PM10 based on System Dynamics.” Sustainability, vol. 11, pp. 5998, 2019.

M. Camara, N. R. Jamil, and A. F. B, Abdullah, “Impact of land uses on water quality in Malaysia: a review.” Ecological Processes, vol. 8, no. 1, pp. 1-10, 2019.

S. Puttinaovarat, and P. Horkaew, “Internetworking flood disaster mitigation system based on remote sensing and mobile GIS.” Geomat Nat Haz Risk, vol. 11, no. 1, pp. 1886-1911, 2020.

A. M. Hersperger et al., "Urban land-use change: The role of strategic spatial planning." Global Environ Chang, vol. 51, pp. 32-42, 2018.

S. Puttinaovarat, and P. Horkaew, "Multi-spectral and Topographic Fusion for Automated Road Extraction." Open Geosci, vol. 10, no. 1, pp. 461-473, 2018.

G. Yin et al., "InVEST model-based estimation of water yield in North China and its sensitivities to climate variables." Water, vol. 12, no. 6, pp. 1692, 2020.

F. Scordo et al., “Modeling water yield: Assessing the role of site and region-specific attributes in determining model performance of the InVEST seasonal water yield model,” water, vol.10 no. 11, pp. 1496, 2018.

J. R. Irons, J. L. Dwyer, and J. A. Barsi, “The next Landsat satellite: The Landsat data continuity mission,” Remote Sens Environ, vol.122, pp. 11-21, 2012.

J. Sinha et al., “Assessment of the impacts of climatic variability and anthropogenic stress on hydrologic resilience to warming shifts in Peninsular India.” Sci Rep-Uk, vol. 8, no. 1, pp. 1-14, 2018.

H. Bandi Hermawan, I. Agustian, and B. G. Murcitro, "A Model to Predict Plant-available Water Content of Soils at Different Land Units in Bengkulu, Indonesia." Terra, vol. 3, no. 1, pp. 10-14, 2020.

S. Lamine et al., “Quantifying land use/land cover spatio-temporal landscape pattern dynamics from Hyperion using SVMs classifier and FRAGSTATS®.” Geocarto Int, vol. 33, no. 8, pp. 862-878, 2018.

L. Hou, F. Wu, and X. Xie, “The spatial characteristics and relationships between landscape pattern and ecosystem service value along an urban-rural gradient in Xi’an city, China,” Ecol Indic, vol. 108, pp. 105720, 2020.

J. Yang, L. Shimei, and L. Huicui, "Quantitative influence of land-use changes and urban expansion intensity on landscape pattern in Qingdao, China: Implications for urban sustainability." Sustainability, vol. 11, pp. 6174, 2019.

D. V. Spracklen et al., “The effects of tropical vegetation on rainfall,” Annu Rev Env Resour, vol.43, pp. 193-218, 2018.

C. Yang et al., “Effects of Vegetation Cover on Hydrological Processes in a Large Region: Huaihe River Basin, China,” J Hydrol Eng, vol. 18 no. 11, pp. 1477-1483, 2011.

G. Zhao et al., “Evidence and causes of spatiotemporal changes in runoff and sediment yield on the Chinese Loess Plateau,” Land Degrad Dev, vol. 28 no. 2, pp. 579-590, 2017.



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