طريقة كائنية الاعتماد للاستخلاص الحضري باستخدام صور للقمر الصناعي كوك بيرد وبيانات ليدار وتقنيات الجيوماتيك الحضرية الرقمي ة

Weng Q, Quattrochi D, Gamba P. Urban remote sensing. 2018. DOI: https://doi.org/10.1201/9781315166612

Sun Z, Xu R, Du W, Wang L, and Lu D. High-resolution urban land mapping in China from sentinel 1A/2 imagery based on Google Earth Engine. Remote Sensing 2019; 11: 1-22 MdpiCom.doi:10.3390/rs11070752. DOI: https://doi.org/10.3390/rs11070752

Mohammed Albayati MA, Hashim Hamed N, Al any SJ. Detect irregularities of master plan by comparison with land use, using GIS and remote sensing techniques for Falujah city. Iraqi Journal for Civil Engineering 2017; vol.2.

Jasim OZ, Hasoon KI, Sadiqe NE. Mapping LCLU Using Python Scripting. Eng Technol J 2019; 37:140–7. https://doi.org/10.30684/etj.37.4A.5. DOI: https://doi.org/10.30684/etj.37.4A.5

Rizeei HM, Pradhan B. Urban Mapping Accuracy Enhancement in High-Rise Built-Up Areas Deployed by 3D-Orthorectification Correction from WorldView-3 and LiDAR Imageries. Remote Sensing2019. MdpiCom. https://doi.org/10.3390/rs11060692. DOI: https://doi.org/10.3390/rs11060692

Hashim Hameed N. On the use of GIS Technique to Analyze the Distribution of Primary Schools in Holy Karbala City. Eng. &Tech. Journal 2016: Vol.34: 2816-2827.

Mohammed HR, Hamed NH, Al Bayati MM. Building of a Spatial Database to Identify Areas of Contamination by Mines and Hazardous Remnants of War by Using GIS (Analyti-cal Study / Basra Governorate). Anbar Journal of Engineering Science. 2018; vol.7.

Zakariya Jasim O. Using of machines learning in extraction of urban roads from DEM of LIDAR data: Case study at Baghdad expressways, Iraq. Periodicals of Engineering and Natural Sciences .2019; vol.7:1710–21. DOI: https://doi.org/10.21533/pen.v7i4.914

Singh KK, Chen G, Ozelkan E, Zhou J, Brown MR, Meentemeyer RK. Uncertainties in mapping forest carbon in urban ecosystems. Artic J Environ Manag 2017. https://doi.org/10.1016/j.jenvman.2016.11.062. DOI: https://doi.org/10.1016/j.jenvman.2016.11.062

Näsi R, Honkavaara E, Blomqvist M.and Saarenmaa P. Remote sensing of bark beetle damage in urban forests at individual tree level using a novel hyperspectral camera from UAV and aircraft. Elsevier2018;vol. 30:72-83 DOI: https://doi.org/10.1016/j.ufug.2018.01.010

Abdelkarim A, Gaber AFD, Youssef AM, Pradhan B. Flood Hazard Assessment of the Urban Area of Tabuk City, Kingdom of Saudi Arabia by Integrating Spatial-Based Hydrologic and Hydrodynamic Modeling. Sensors2019; 19. https://doi.org/10.3390/s19051024. DOI: https://doi.org/10.3390/s19051024

Rizaludin Mahmud M, Hosaka T, Rizaludin Mahmud M, Numata S. Mapping an invasive goldenrod of Solidago altissima in urban landscape of Japan using multi-scale remote sensing and knowledge-based classification Satellite-based water yield mapping View project Spatial Hydroanalytics Research View project Original Articles Mapping an invasive goldenrod of Solidago altissima in urban landscape of Japan using multi-scale remote sensing and knowledge-based classification. Elsevier 2019. https://doi.org/10.1016/j.ecolind.2019.105975. DOI: https://doi.org/10.1016/j.ecolind.2019.105975

Atli Benediktsson J, Pesaresi M, Arnason K. Classification and Feature Extraction for Remote Sensing Images From Urban Areas Based on Morphological Transformations. IEEE Trans Geosci Remote Sensing 2003; vol.41. https://doi.org/10.1109/TGRS.2003.814625. DOI: https://doi.org/10.1109/TGRS.2003.814625

Sensing HX-PE& R, 2007 undefined. 06-012.qxd. 2007. DOI: https://doi.org/10.1088/1475-7516/2007/06/012

Myint SW, Gober P, Brazel A, Grossman-Clarke S, Weng Q. Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery. Elsevier 2010. https://doi.org/10.1016/j.rse.2010.12.017. DOI: https://doi.org/10.1016/j.rse.2010.12.017

Abdulkareem A, Aldulaimi A, Pradhan B, Mansor S, Ahmed AA, Kalantar B, et al. Land Use and Land Cover Mapping Using Rule-Based Classification in Karbala City, Iraq deepgeo: Automated Classification of Remote Sensing Data with Deep Learning in Python View project LTA-UAV View project Land Use and Land Cover Mapping Using Rule-Based Classification in Karbala City, Iraq. Springer 2019; vol.9:1019–27. https://doi.org/10.1007/978-981-10-8016-6_71. DOI: https://doi.org/10.1007/978-981-10-8016-6_71

Abdulkareem A, Aldulaimi A, Pradhan B, Al-Zuhairi M. An optimized object-based analysis for vegetation mapping using integration of Quickbird and Sentinel-1 data Flood Monitoring Mapping View project Application of fuzzy logic and GIS to provide geospatial solutions for displaced people in Al-Anbar province , Iraq View project. Artic Arab J Geosci 2018; vol.11 https://doi.org/10.1007/s12517-018-3632-1. DOI: https://doi.org/10.1007/s12517-018-3632-1

Chen Y, Fan R, Yang X, Wang J, Latif A. Extraction of Urban Water Bodies from High-Resolution Remote-SensingImageryUsingDeepLearning.JournalWater2018;vol.10.MdpiCom. https://doi.org/10.3390/w10050585. DOI: https://doi.org/10.3390/w10050585

Priem F, Canters F, Yu B, Myint SW, Atzberger C, Thenkabail PS. Synergistic Use of LiDAR and APEX Hyperspectral Data for High-Resolution Urban Land Cover Mapping. Remote Sensing.2016; vol.8 MdpiCom. https://doi.org/10.3390/rs8100787. DOI: https://doi.org/10.3390/rs8100787

Zhang W, Li W, Zhang C, Hanink DM, Li X, Wang W. Parcel-based urban land use classification in megacity using airborne LiDAR, high resolution orthoimagery, and Google Street View Remote sensing View project Markov chain geostatistical modeling View project Parcel-based urban land use classification in megacity using airborne LiDAR, high resolution orthoimagery, and Google Street View. Elsevier 2017; vol. 64. https://doi.org/10.1016/j.compenvurbsys.2017.03.001. DOI: https://doi.org/10.1016/j.compenvurbsys.2017.03.001

Ibrahim Sameen M, Pradhan B. A Two-Stage Optimization Strategy for Fuzzy Object-Based Analysis Using Airborne LiDAR and High-Resolution Orthophotos for Urban Road Extraction. Journal of Sensors2017. HindawiCom . DOI: https://doi.org/10.1155/2017/6431519

Li Q, Lu L, Jiang H, … JH-2018 FI,. Object-based urban land cover mapping using high-resolution airborne imagery and LiDAR data. IeeexploreIeeeOrg n.d 2018 undefined. DOI: https://doi.org/10.1109/EORSA.2018.8598566

Degerickx J, Roberts D,. Enhancing the performance of Multiple Endmember Spectral Mixture Analysis (MESMA) for urban land cover mapping using airborne lidar data and band. Elsevier2019 undefined. DOI: https://doi.org/10.1016/j.rse.2018.11.026