Assessing The Environmental Quality of Kirkuk City and Taza District Based on Pressure-State-Response Framework for Winter 2023 Using Remote Sensing and GIS
Article Sidebar
Main Article Content
Abstract
Evaluating a region's Ecological Environment Quality (EEQ) is an essential factor in deciding its urbanization and sustainable development rate. This study aims to find the Ecological Index (EI). It evaluates it using the widely used Pressure-State-Response (PSR) framework based on a set of statistical and remote sensing indices in Kirkuk City and Taza district. Sentinel-2 satellite images were used to obtain 12 indicators that offer a foundation for sustainable development decision-making for Kirkuk City and Taza District during the winter of 2023. The finding reveals that the ecological condition is healthy in winter due to the atmospheric conditions and the social and economic activities. It presents the main relation between environmental health and human activities.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
X. Wang, Y. Cao, X. Zhong, and P. Gao, “A New Method of Regional Eco-environmental Quality Assessment and Its Application,” J. Environ. Qual., vol. 41, no. 5, pp. 1393–1401, 2012, doi: 10.2134/jeq2011.0390.
H. Ma and L. Shi, “Assessment of eco-environmental quality of Western Taiwan Straits Economic Zone,” Environ. Monit. Assess., vol. 188, no. 5, 2016, doi: 10.1007/s10661-016-5312-5.
A. M. Duda and M. T. El-Ashry, “Addressing the global water and environment crises through integrated approaches to the management of land, water and ecological resources,” Water Int., vol. 25, no. 1, pp. 115–126, 2000, doi: 10.1080/02508060008686803.
J. Li, Y. Pei, S. Zhao, R. Xiao, X. Sang, and C. Zhang, “A review of remote sensing for environmental monitoring in China,” Remote Sens., vol. 12, no. 7, pp. 1–25, 2020, doi: 10.3390/rs12071130.
S. Das, B. Pradhan, P. K. Shit, and A. M. Alamri, “Assessment of wetland ecosystem health using the pressure-state-response (PSR) model: A case study of Mursidabad District of West Bengal (India),” Sustain., vol. 12, no. 15, 2020, doi: 10.3390/SU12155932.
J. Xiong, W. Li, H. Zhang, W. Cheng, C. Ye, and Y. Zhao, “Selected environmental assessment model and spatial analysis method to explain correlations in environmental and socio-economic data with possible application for explaining the state of the ecosystem,” Sustain., vol. 11, no. 17, 2019, doi: 10.3390/su11174781.
M. S. Boori, K. Choudhary, R. Paringer, and A. Kupriyanov, “Eco-environmental quality assessment based on pressure-state-response framework by remote sensing and GIS,” Remote Sens. Appl. Soc. Environ., vol. 23, no. April, p. 100530, 2021, doi: 10.1016/j.rsase.2021.100530.
R. Sun et al., “Effects of land-use change on eco-environmental quality in Hainan Island, China,” Ecol. Indic., vol. 109, no. 4, p. 105777, 2020, doi: 10.1016/j.ecolind.2019.105777.
M. A. Shareef, N. D. Hassan, S. F. Hasan, and A. Khenchaf, “Integration of sentinel-1A and sentinel-2B data for land use and land cover mapping of the Kirkuk governorate, Iraq,” Int. J. Geoinformatics, vol. 16, no. 3, pp. 87–96, 2020.
M. Pacione, “Urban environmental quality and human wellbeing - A social geographical perspective,” Landsc. Urban Plan., vol. 65, no. 1–2, pp. 19–30, 2003, doi: 10.1016/S0169-2046(02)00234-7.
V. F. Salahalden, M. A. Shareef, and Q. A. A. Nuaimy, “Red Clay Soil Physical and Chemical Properties Distribution Using Remote Sensing and GIS Techniques in Kirkuk City, Iraq,” Iraqi Geol. J., vol. 57, no. 1, pp. 194–220, 2024, doi: 10.46717/igj.57.1A.16ms-2024-1-27.
A. B. Pinty, M. M. Verstraete, S. Vegetatio, N. Jul, and B. Pinty, “GEMI : A Non-Linear Index to Monitor Global Vegetation from Satellites GEMI : a non-linear index to monitor global vegetation from satellites,” Vegetatio, vol. 101, no. 1, pp. 15–20, 2011.
D. Chu, Fractional vegetation cover, or FVC, is a crucial metric in the study of soil erosion, climate change, and ecosystem balance. It is frequently employed in the assessment and tracking of vegetation degradation and desertification. The only practical method. 2019. doi: 10.1007/978-981-13-7580-4.
H. Fang, F. Baret, S. Plummer, and G. Schaepman-Strub, “An Overview of Global Leaf Area Index (LAI): Methods, Products, Validation, and Applications,” Rev. Geophys., vol. 57, no. 3, pp. 739–799, 2019, doi: 10.1029/2018RG000608.
S. Rahman and V. Mesev, “Change vector analysis, tasseled cap, and NDVI-NDMI for measuring land use/cover changes caused by a sudden short-term severe drought: 2011 Texas event,” Remote Sens., vol. 11, no. 19, 2019, doi: 10.3390/rs11192217.
O. Strashok, M. Ziemiańska, and V. Strashok, “Evaluation and Correlation of Sentinel-2 NDVI and NDMI in Kyiv (2017-2021),” J. Ecol. Eng., vol. 23, no. 9, pp. 212–218, 2022, doi: 10.12911/22998993/151884.
S. K. McFeeters, “NDWI BY McFEETERS,” Remote Sens. Environ., vol. 25, no. 3, pp. 687–711, 1996.
X. Wang, Y. Yan, and Y. Cao, “Impact of historic grazing on steppe soils on the northern Tibetan Plateau,” Plant Soil, vol. 354, no. 1–2, pp. 173–183, 2012, doi: 10.1007/s11104-011-1053-y.
A. C. Neri, P. Dupin, and L. E. Sánchez, “A pressure-state-response approach to cumulative impact assessment,” J. Clean. Prod., vol. 126, no. April, pp. 288–298, 2016, doi: 10.1016/j.jclepro.2016.02.134.
S. F. Hasan, M. A. Shareef, and N. D. Hassan, “Speckle filtering impact on land use/land cover classification area using the combination of Sentinel-1A and Sentinel-2B (a case study of Kirkuk city, Iraq),” Arab. J. Geosci., vol. 14, no. 4, 2021, doi: 10.1007/s12517-021-06494-9.
M. A. Shareef, M. H. Ameen, and Q. M. Ajaj, “Change detection and gis-based fuzzy ahp to evaluate the degradation and reclamation land of tikrit city, Iraq,” Geod. Cartogr., vol. 46, no. 4, pp. 194–203, 2020, doi: 10.3846/gac.2020.11616.
A. Comber and M. Wulder, “Considering spatiotemporal processes in big data analysis: Insights from remote sensing of land cover and land use,” Trans. GIS, vol. 23, no. 5, pp. 879–891, 2019, doi: 10.1111/tgis.12559.
P. P. Rhyma, K. Norizah, O. Hamdan, I. Faridah-Hanum, and A. W. Zulfa, “Integration of normalised different vegetation index and Soil-Adjusted Vegetation Index for mangrove vegetation delineation,” Remote Sens. Appl. Soc. Environ., vol. 17, no. December 2019, p. 100280, 2020, doi: 10.1016/j.rsase.2019.100280.
A. R. Huete, “A soil-adjusted vegetation index (SAVI),” Remote Sens. Environ., vol. 25, no. 3, pp. 295–309, 1988, doi: 10.1016/0034-4257(88)90106-X.
Q. Zhou, “Digital Elevation Model and Digital Surface Model,” Int. Encycl. Geogr., no. March, pp. 1–17, 2017, doi: 10.1002/9781118786352.wbieg0768.
J. Vaze, J. Teng, and G. Spencer, “Impact of DEM accuracy and resolution on topographic indices,” Environ. Model. Softw., vol. 25, no. 10, pp. 1086–1098, 2010, doi: 10.1016/j.envsoft.2010.03.014.
M. Neteler, “Estimating daily land surface temperatures in mountainous environments by reconstructed MODIS LST data,” Remote Sens., vol. 2, no. 1, pp. 333–351, 2010, doi: 10.3390/rs1020333.
G. C. Hulley, D. Ghent, F. M. Göttsche, P. C. Guillevic, D. J. Mildrexler, and C. Coll, Land Surface Temperature. 2019. doi: 10.1016/B978-0-12-814458-9.00003-4.
W. Ren, X. Zhang, and H. Peng, “Evaluation of Temporal and Spatial Changes in Ecological Environmental Quality on Jianghan Plain From 1990 to 2021,” Front. Environ. Sci., vol. 10, no. May, pp. 1–14, 2022, doi: 10.3389/fenvs.2022.884440.
B. Wolfslehner and H. Vacik, “Evaluating sustainable forest management strategies with the Analytic Network Process in a Pressure-State-Response framework,” J. Environ. Manage., vol. 88, no. 1, pp. 1–10, 2008, doi: 10.1016/j.jenvman.2007.01.027.
J. Ji and J. Chen, “Urban flood resilience assessment using RAGA-PP and KL-TOPSIS model based on PSR framework: A case study of Jiangsu province, China,” Water Sci. Technol., vol. 86, no. 12, pp. 3264–3280, 2022, doi: 10.2166/wst.2022.404.
H. F. Huang, J. Kuo, and S. L. Lo, “Review of PSR framework and development of a DPSIR model to assess greenhouse effect in Taiwan,” Environ. Monit. Assess., vol. 177, no. 1–4, pp. 623–635, 2011, doi: 10.1007/s10661-010-1661-7.
D. Liu and S. Hao, “Ecosystem health assessment at county-scale using the pressure-state-response framework on the loess plateau, China,” Int. J. Environ. Res. Public Health, vol. 14, no. 1, 2017, doi: 10.3390/ijerph14010002.
R. Sensing and E. Index, “Evaluation of the Spatiotemporal Variations in the Eco-environmental Quality in China Based on the Remote Sensing Ecological Index,” Remote Sens., 2020.