{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T03:37:24Z","timestamp":1770349044562,"version":"3.49.0"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031510229","type":"print"},{"value":"9783031510236","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-51023-6_33","type":"book-chapter","created":{"date-parts":[[2024,1,23]],"date-time":"2024-01-23T07:02:36Z","timestamp":1705993356000},"page":"395-405","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Assessing Machine Learning Algorithms for Land Use and Land Cover Classification in Morocco Using Google Earth Engine"],"prefix":"10.1007","author":[{"given":"Hafsa","family":"Ouchra","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdessamad","family":"Belangour","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Allae","family":"Erraissi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mouad","family":"Banane","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,1,24]]},"reference":[{"key":"33_CR1","doi-asserted-by":"publisher","unstructured":"Tamiminia, H., Salehi, B., Mahdianpari, M., Quackenbush, L., Adeli, S., Brisco, B.: Google earth engine for geo-big data applications: a meta-analysis and systematic review. ISPRS J. Photogrammetry Remote Sens. 164, 152\u2013170 (2020). https:\/\/doi.org\/10.1016\/j.isprsjprs.2020.04.001","DOI":"10.1016\/j.isprsjprs.2020.04.001"},{"issue":"22","key":"33_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/rs12223776","volume":"12","author":"A Tassi","year":"2020","unstructured":"Tassi, A., Vizzari, M.: Object-oriented LULC classification in google earth engine combining SNIC, GLCM, and machine learning algorithms. Remote Sens (Basel) 12(22), 1\u201317 (2020). https:\/\/doi.org\/10.3390\/rs12223776","journal-title":"Remote Sens (Basel)"},{"key":"33_CR3","doi-asserted-by":"publisher","unstructured":"P\u00e9rez-Cutillas, P., P\u00e9rez-Navarro, A., Conesa-Garc\u00eda, C., Zema, D.A., Amado-\u00c1lvarez, J.P.: What is going on within google earth engine? A systematic review and meta-analysis. Remote Sens. Appl. Soc. Environ. 29 (2023). https:\/\/doi.org\/10.1016\/j.rsase.2022.100907","DOI":"10.1016\/j.rsase.2022.100907"},{"key":"33_CR4","doi-asserted-by":"publisher","unstructured":"Magidi, J., Nhamo, L., Mpandeli, S., Mabhaudhi, T.: Application of the random forest classifier to map irrigated areas using google earth engine. Remote Sens. 13(5), 876 (2021). https:\/\/doi.org\/10.3390\/RS13050876","DOI":"10.3390\/RS13050876"},{"key":"33_CR5","doi-asserted-by":"publisher","unstructured":"Awad, M.: Google earth engine (GEE) cloud computing based crop classification using radar , optical images and support vector machine algorithm (SVM). In: 2021 IEEE 3rd International Multidisciplinary Conference on Engineering Technology, IMCET 2021, pp. 71\u201376 (2021). https:\/\/doi.org\/10.1109\/IMCET53404.2021.9665519","DOI":"10.1109\/IMCET53404.2021.9665519"},{"key":"33_CR6","doi-asserted-by":"publisher","first-page":"103138","DOI":"10.1016\/J.PCE.2022.103138","volume":"126","author":"H Chen","year":"2022","unstructured":"Chen, H., Yunus, A.P., Nukapothula, S., Avtar, R.: Modelling arctic coastal plain lake depths using machine learning and google earth engine. Phys. Chem. Earth, Parts A\/B\/C 126, 103138 (2022). https:\/\/doi.org\/10.1016\/J.PCE.2022.103138","journal-title":"Phys. Chem. Earth, Parts A\/B\/C"},{"key":"33_CR7","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/J.RSE.2017.06.031","volume":"202","author":"N Gorelick","year":"2017","unstructured":"Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., Moore, R.: Google earth engine: planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202, 18\u201327 (2017). https:\/\/doi.org\/10.1016\/J.RSE.2017.06.031","journal-title":"Remote Sens. Environ."},{"key":"33_CR8","doi-asserted-by":"publisher","first-page":"5326","DOI":"10.1109\/JSTARS.2020.3021052","volume":"13","author":"M Amani","year":"2020","unstructured":"Amani, M., et al.: Google earth engine cloud computing platform for remote sensing big data applications: a comprehensive review. IEEE J. Sel. Top. Appl. Earth. Obs. Remote Sens 13, 5326\u20135350 (2020). https:\/\/doi.org\/10.1109\/JSTARS.2020.3021052","journal-title":"IEEE J. Sel. Top. Appl. Earth. Obs. Remote Sens"},{"key":"33_CR9","doi-asserted-by":"publisher","unstructured":"Ouchra, H., Belangour, A.: Satellite image classification methods and techniques: a survey. In: Proceedings of IEEE International Conference on Imaging Systems and Techniques, IST 2021 (2021). https:\/\/doi.org\/10.1109\/IST50367.2021.9651454","DOI":"10.1109\/IST50367.2021.9651454"},{"key":"33_CR10","doi-asserted-by":"publisher","unstructured":"Ouchra, H., Belangour, A., Erraissi, A.: Machine learning for satellite image classification: a comprehensive review. In: 2022 International Conference on Data Analytics for Business and Industry (ICDABI), pp. 1\u20135, October 2022. https:\/\/doi.org\/10.1109\/ICDABI56818.2022.10041606","DOI":"10.1109\/ICDABI56818.2022.10041606"},{"key":"33_CR11","doi-asserted-by":"publisher","unstructured":"Nelson, P.R., et al.: Satellite remote sensing. An introduction. J. Geophys. Res. Biogeosci. 127(2) (1987). https:\/\/doi.org\/10.1029\/2021JG006697","DOI":"10.1029\/2021JG006697"},{"key":"33_CR12","doi-asserted-by":"publisher","unstructured":"Ouchra, H., Belangour, A., Erraissi, A.: Spatial data mining technology for GIS: a review. In: 2022 International Conference on Data Analytics for Business and Industry (ICDABI), pp. 655\u2013659, October 2022. https:\/\/doi.org\/10.1109\/ICDABI56818.2022.10041574","DOI":"10.1109\/ICDABI56818.2022.10041574"},{"key":"33_CR13","doi-asserted-by":"publisher","first-page":"206","DOI":"10.14445\/22315381\/IJETT-V70I8P221","volume":"70","author":"H Ouchra","year":"2022","unstructured":"Ouchra, H., Belangour, A., Erraissi, A.: A comparative study on pixel-based classification and object-oriented classification of satellite image. Int. J. Eng. Trends Technol. 70, 206\u2013215 (2022). https:\/\/doi.org\/10.14445\/22315381\/IJETT-V70I8P221","journal-title":"Int. J. Eng. Trends Technol."},{"key":"33_CR14","doi-asserted-by":"publisher","unstructured":"Ouchra, H., Belangour, A., Erraissi, A.: Satellite data analysis and geographic information system for urban planning: a systematic review. In: 2022 International Conference on Data Analytics for Business and Industry (ICDABI), pp. 558\u2013564, October 2022. https:\/\/doi.org\/10.1109\/ICDABI56818.2022.10041487","DOI":"10.1109\/ICDABI56818.2022.10041487"},{"key":"33_CR15","doi-asserted-by":"publisher","unstructured":"Ouchra, H., Belangour, A.: Object detection approaches in images: a survey. vol. 11878, pp. 132\u2013141, June 2021, https:\/\/doi.org\/10.1117\/12.2601452","DOI":"10.1117\/12.2601452"},{"key":"33_CR16","unstructured":"Ouchra, H., Belangour, A.: Object detection approaches in images: a weighted scoring model based comparative study. www.ijacsa.thesai.org"},{"key":"33_CR17","doi-asserted-by":"publisher","unstructured":"Ouchra, H., Belangour, A., Erraissi, A.: An overview of GeoSpatial artificial intelligence technologies for city planning and development. In: 2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT), pp. 1\u20137, February 2023, https:\/\/doi.org\/10.1109\/ICECCT56650.2023.10179796","DOI":"10.1109\/ICECCT56650.2023.10179796"},{"key":"33_CR18","doi-asserted-by":"crossref","unstructured":"Borra, S., Thanki, R., Dey, N.: Satellite image analysis\u202f: clustering and classification (2019)","DOI":"10.1007\/978-981-13-6424-2"},{"key":"33_CR19","doi-asserted-by":"publisher","unstructured":"Venkatappa, M., Sasaki, N., Shrestha, R.P., Tripathi, N.K., Ma, H.O.: Determination of vegetation thresholds for assessing land use and land use changes in Cambodia using the google earth engine cloud-computing platform. Remote Sens (Basel) 11(13) (2019). https:\/\/doi.org\/10.3390\/rs11131514","DOI":"10.3390\/rs11131514"},{"key":"33_CR20","doi-asserted-by":"publisher","unstructured":"Bouzekri, S., Lasbet, A.A., Lachehab, A.: A new spectral index for extraction of built-up area using landsat-8 data. J. Indian Soc. Remote Sens. 43(4), 867\u2013873 (2015). https:\/\/doi.org\/10.1007\/S12524-015-0460-6","DOI":"10.1007\/S12524-015-0460-6"},{"key":"33_CR21","unstructured":"Landsat 8 | Landsat Science. https:\/\/landsat.gsfc.nasa.gov\/satellites\/landsat-8\/. Accessed 30 Jan 2023"},{"key":"33_CR22","unstructured":"LSIB 2017: large scale international boundary polygons, Simplified | Earth Engine Data Catalog | Google for Developers. https:\/\/developers.google.com\/earth-engine\/datasets\/catalog\/USDOS_LSIB_SIMPLE_2017. Accessed 24 Aug 2023"},{"key":"33_CR23","doi-asserted-by":"publisher","unstructured":"Yang, L., Driscol, J., Sarigai, S., Wu, Q., Chen, H., Lippitt, C.D.: Google earth engine and artificial intelligence (AI): a comprehensive review. Remote Sens. 14(14) MDPI (2022). https:\/\/doi.org\/10.3390\/rs14143253","DOI":"10.3390\/rs14143253"},{"key":"33_CR24","doi-asserted-by":"publisher","unstructured":"Ouchra, H., Belangour, A., Erraissi, A.: Machine learning algorithms for satellite image classification using google earth engine and landsat satellite data: Morocco case study. IEEE Access (2023). https:\/\/doi.org\/10.1109\/ACCESS.2023.3293828","DOI":"10.1109\/ACCESS.2023.3293828"},{"key":"33_CR25","doi-asserted-by":"publisher","unstructured":"Yengoh, G.T., Dent, D., Olsson, L., Tengberg, A.E., Tucker III, C.J.: Use of the normalized difference vegetation index (NDVI) to assess land degradation at multiple scales, Springer. in SpringerBriefs in Environmental Science. Cham: Springer International Publishing (2016). https:\/\/doi.org\/10.1007\/978-3-319-24112-8","DOI":"10.1007\/978-3-319-24112-8"},{"key":"33_CR26","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/J.UFUG.2016.07.001","volume":"19","author":"M Gascon","year":"2016","unstructured":"Gascon, M., et al.: Normalized difference vegetation index (NDVI) as a marker of surrounding greenness in epidemiological studies: the case of Barcelona city. Urban For Urban Green 19, 88\u201394 (2016). https:\/\/doi.org\/10.1016\/J.UFUG.2016.07.001","journal-title":"Urban For Urban Green"},{"key":"33_CR27","unstructured":"NDBI\u2014ArcGIS Pro | Documentation. https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/arcpy\/spatial-analyst\/ndbi.htm. Accessed 19 May 2023"},{"issue":"1","key":"33_CR28","doi-asserted-by":"publisher","first-page":"35","DOI":"10.4236\/ARS.2015.41004","volume":"4","author":"K Abutaleb","year":"2015","unstructured":"Abutaleb, K., et al.: Assessment of urban heat island using remotely sensed imagery over greater Cairo, Egypt. Adv. Remote Sens. 4(1), 35\u201347 (2015). https:\/\/doi.org\/10.4236\/ARS.2015.41004","journal-title":"Adv. Remote Sens."},{"key":"33_CR29","doi-asserted-by":"publisher","unstructured":"Ngandam Mfondoum, A.H., Etouna, J., Nongsi, B.K., Mvogo Moto, F.A., Noulaquape Deussieu, F.G.: Assessment of land degradation status and its impact in arid and semi-arid areas by correlating spectral and principal component analysis neo-bands. Int. J. Adv. Remote Sens. GIS 5(1), 1539\u20131560 (2016). https:\/\/doi.org\/10.23953\/CLOUD.IJARSG.77","DOI":"10.23953\/CLOUD.IJARSG.77"},{"key":"33_CR30","doi-asserted-by":"crossref","unstructured":"Abburu, S., Golla, S.B.: Satellite image classification methods and techniques: a review (2015)","DOI":"10.5120\/21088-3779"},{"issue":"1","key":"33_CR31","first-page":"15","volume":"14","author":"H Ouchra","year":"2022","unstructured":"Ouchra, H., Belangour, A., Erraissi, A.: A comprehensive study of using remote sensing and geographical information systems for urban planning. Internetworking Indonesia J. 14(1), 15\u201320 (2022)","journal-title":"Internetworking Indonesia J."}],"container-title":["Lecture Notes in Computer Science","Image Analysis and Processing - ICIAP 2023 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-51023-6_33","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,23]],"date-time":"2024-01-23T07:07:55Z","timestamp":1705993675000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-51023-6_33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031510229","9783031510236"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-51023-6_33","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"24 January 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIAP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Image Analysis and Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Udine","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iciap2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.iciap2023.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"144","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"82","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"13","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"57% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"https:\/\/iciap2023.org\/satellite-event\/workshops\/","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}