Change detection and GIS-based fuzzy AHP to evaluate the degradation and reclamation land of Tikrit City, Iraq

    Muntadher Aidi Shareef   Affiliation
    ; Mohammed Hashim Ameen Affiliation
    ; Qayssar Mahmood Ajaj Affiliation


LULC factors in Tikrit city (Iraq) and the neighboring municipalities are studied among 1989, 2002 and 2015 using various techniques of remote sensing, geographical information system (GIS), and fuzzy analytical hierarchy process (FAHP). Satellite imagery with GIS helped to assess the standard LULC changes in the long term period. FAHP permitted estimating the importance of various LULC by determination of the suitable weight for used factors and then producing the evaluating models. Using different techniques, two models were created (1) to estimate the degradation of the land (2) is generated to determine the reclamation of the area. The finding reveals that the a overall accuracy of 97.0939%, 98.9199% and 99.5817% or 1989, 2002 and 2015 respectively. The outcomes also revealed that urban, vegetation, and water features area are developed in the long term (1989–2015) about 4.35%, 4.28%, and 1.49%, respectively, while barren area is reduced about 5.57%.The degradation map index showed that the lands strongly debased are these converted from vegetation to barren, followed by moderate to high these changed from water areas to urban, while moderate degradation is noticed of urban transformed to barren soil. Contrary, the reclamation map index illustrated that the lands are powerfully transformed from barren to the vegetation and followed by those converted from barren to the water, while barren transformed to the urban is marked as moderate reclamation. The transformation from urban to vegetation or water was classified as the low and deficient class to evaluate the area. The study is also revealed that the integration of remote sensing and GIS produces a successful method for LULC monitoring and managing the environment.

First published online 05 January 2021

Keyword : LULC, FAHP, GIS, degradation map index, reclamation map index

How to Cite
Shareef, M. A., Ameen, M. H., & Ajaj, Q. M. (2020). Change detection and GIS-based fuzzy AHP to evaluate the degradation and reclamation land of Tikrit City, Iraq. Geodesy and Cartography, 46(4), 194-203.
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Dec 31, 2020
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Aburas, M. M., Ahamad, M. S. S., & Omar, N. Q. (2019). Spatiotemporal simulation and prediction of land-use change using conventional and machine learning models: A review. Environmental Monitoring and Assessment, 191(4), 205.

Ajaj, Q. M., Pradhan, B., Noori, A. M., & Jebur, M. N. (2017). Spatial monitoring of desertification extent in western Iraq using Landsat images and GIS. Land Degradation & Development, 28(8), 2418–2431.

An, R., Wang, H.-L., Feng, X.-Z., Wu, H., Wang, Z., Wang, Y., Shen, X.-J., Lu, C.-H., Quaye-Ballard, J. A., Chen, Y.-H., & Zhao, Y.-H. (2017). Monitoring rangeland degradation using a novel local NPP scaling based scheme over the “Three-River Headwaters” region, hinterland of the Qinghai-Tibetan Plateau. Quaternary International, 444(Part A), 97–114.

Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems, 17(3), 233–247.

Feizizadeh, B., Roodposhti, M. S., Jankowski, P., & Blaschke, T. (2014). A GIS-based extended fuzzy multi-criteria evaluation for landslide susceptibility mapping. Computers & Geosciences, 73, 208–221.

Foody, G. M. (2002). Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80(1), 185–201.

Gao, J., & Liu, Y. (2008). Mapping of land degradation from space: A comparative study of Landsat ETM+ and ASTER data. International Journal of Remote Sensing, 29(14), 4029–4043.

Gao, J., & Liu, Y. (2010). Determination of land degradation causes in Tongyu County, Northeast China via land cover change detection. International Journal of Applied Earth Observation and Geoinformation, 12(1), 9–16.

Hadi, S. J., Shafri, H. Z., & Mahir, M. D. (2014). Factors affecting the eco-environment identification through change detection analysis by using remote sensing and GIS: A case study of Tikrit, Iraq. Arabian Journal for Science and Engineering, 39(1), 395–405.

Hailemariam, S., Soromessa, T., & Teketay, D. (2016). Land use and land cover change in the Bale Mountain Eco-Region of Ethiopia during 1985 to 2015. Land, 5(4), 41.

Higginbottom, T. P., & Symeonakis, E. (2014). Assessing land degradation and desertification using vegetation index data: Current frameworks and future directions. Remote Sensing, 6(10), 9552–9575.

Huang, J.-H., & Peng, K.-H. (2012). Fuzzy Rasch model in TOPSIS: A new approach for generating fuzzy numbers to assess the competitiveness of the tourism industries in Asian countries. Tourism Management, 33(2), 456–465.

Metternicht, G. (1999). Change detection assessment using fuzzy sets and remotely sensed data: An application of topographic map revision. ISPRS Journal of Photogrammetry and Remote Sensing, 54(4), 221–233.

Olofsson, P., Foody, G. M., Stehman, S. V., & Woodcock, C. E. (2013). Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation. Remote Sensing of Environment, 129, 122–131.

Pourghasemi, H. R., Beheshtirad, M., & Pradhan, B. (2016). A comparative assessment of prediction capabilities of modified analytical hierarchy process (M-AHP) and Mamdani fuzzy logic models using Netcad-GIS for forest fire susceptibility mapping. Geomatics, Natural Hazards and Risk, 7(2), 861–885.

Rawat, J., & Kumar, M. (2015). Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India. The Egyptian Journal of Remote Sensing and Space Science, 18(1), 77–84.

Rocchini, D., Boyd, D. S., Féret, J. B., Foody, G. M., He, K. S., Lausch, A., Nagendra, H., Wegmann, M., & Pettorelli, N. (2016). Satellite remote sensing to monitor species diversity: Potential and pitfalls. Remote Sensing in Ecology and Conservation, 2(1), 25–36.

Saaty, T. L. (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48(1), 9–26.

Shareef, M. A., Hasan, S. F., & Ajaj, Q. M. (2018, October). Estimation and mapping of dates palm using Landsat-8 images: A case study in Baghdad city. In 2018 International Conference on Advanced Science and Engineering (ICOASE). Duhok, Iraq.

Shareef, M. A., Hassan, N. D., Hasan, S. F., & Noori, A. M. (2019). Integrating of GIS and fuzzy multi-criteria method to evaluate land degradation and their impact on the urban growth of Kirkuk city, Iraq. International Journal of Advanced Science and Technology, 28(15), 800–815.

Shareef, M. A., Toumi, A., & Khenchaf, A. (2014). Estimation of water quality parameters using the regression model with fuzzy K-means clustering. International Journal of Advanced Computer Science and Applications (IJACSA), 5(6), 151–157.

Wang, L., Chu, J., & Wu, J. (2007). Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process. International Journal of Production Economics, 107(1), 151–163.

Weng, Q. (2001). A remote sensing? GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China. International Journal of Remote Sensing, 22(10), 1999–2014.

Werner, A., Storie, C. D., & Storie, J. (2014). Evaluating SARoptical image fusions for urban LULC classification in Vancouver Canada. Canadian Journal of Remote Sensing, 40(4), 278–290.

Wu, C.-R., Lin, C.-T., & Chen, H.-C. (2007). Optimal selection of location for Taiwanese hospitals to ensure a competitive advantage by using the analytic hierarchy process and sensitivity analysis. Building and Environment, 42(3), 1431–1444.

Xiao, J., Shen, Y., Ge, J., Tateishi, R., Tang, C., Liang, Y., & Huang, Z. (2006). Evaluating urban expansion and land use change in Shijiazhuang, China, by using GIS and remote sensing. Landscape and Urban Planning, 75(1–2), 69–80.

Zamani-Sabzi, H., King, J. P, Gard, C. C., & Abudu, S. (2016). Statistical and analytical comparison of multi-criteria decision-making techniques under fuzzy environment. Operations Research Perspectives, 3, 92–117.