A bibliometric review of geospatial analyses and artificial intelligence literature in agriculture

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[2]  A. Karmaoui.  Ordovician-Cambrian Palaeontological Heritage of Zagora Province: A Bibliometric Analysis from 1984 to 2020 (Anti-Atlas, Morocco) , 2022, Geoheritage.

[3]  Shahfahad,et al.  Coupling geographic information system integrated fuzzy logic-analytical hierarchy process with global and machine learning based sensitivity analysis for agricultural suitability mapping , 2022, Agricultural Systems.

[4]  Vishal A. Meshram,et al.  Machine learning in agriculture domain: A state-of-art survey , 2021, Artificial Intelligence in the Life Sciences.

[5]  Hassan Chaachouay,et al.  The socio-ecological system of the pre-Sahara zone of Morocco: a conceptual framework to analyse the impact of drought and desertification , 2021, GeoJournal.

[6]  Biswajeet Pradhan,et al.  A Meta-Learning Approach of Optimisation for Spatial Prediction of Landslides , 2021, Remote. Sens..

[7]  A. Karmaoui,et al.  Monitoring spatiotemporal variation of groundwater level and salinity under land use change using integrated field measurements, GIS, geostatistical, and remote-sensing approach: case study of the Feija aquifer, Middle Draa watershed, Moroccan Sahara , 2021, Environmental Monitoring and Assessment.

[8]  Biswajeet Pradhan,et al.  Orthorectification of WorldView-3 Satellite Image Using Airborne Laser Scanning Data , 2021, J. Sensors.

[9]  Houssam Ayt Ougougdal,et al.  A new mountain flood vulnerability index (MFVI) for the assessment of flood vulnerability , 2021, Sustainable Water Resources Management.

[10]  A. Taloor,et al.  Climate vulnerability and economic determinants: Linkages and risk reduction in Sagar Island, India; A geospatial approach , 2021 .

[11]  Joost C. B. Hoedjes,et al.  Quantifying water storage within the north of Lake Naivasha using sonar remote sensing and Landsat satellite data , 2021, International Journal of Ecohydrology and Hydrobiology.

[12]  Yi Wang,et al.  An industrial-grade solution for agricultural image classification tasks , 2021, Comput. Electron. Agric..

[13]  Ahmed El-Shafie,et al.  Groundwater quality forecasting modelling using artificial intelligence: A review , 2021, Groundwater for Sustainable Development.

[14]  Javed Mallick,et al.  Modeling fragmentation probability of land-use and land-cover using the bagging, random forest and random subspace in the Teesta River Basin, Bangladesh , 2021, Ecological Indicators.

[15]  Elfatih M. Abdel-Rahman,et al.  Cropping Pattern Mapping in an Agro-Natural Heterogeneous Landscape Using Sentinel-2 and Sentinel-1 Satellite Datasets , 2021 .

[16]  Remigio Berruto,et al.  Machine Learning in Agriculture: A Comprehensive Updated Review , 2021, Sensors.

[17]  Juan Pablo Garcia Vazquez,et al.  Scientometric Analysis of the Application of Artificial Intelligence in Agriculture , 2021, Journal of Scientometric Research.

[18]  Javier Garzás,et al.  Research Trends in Career Success: A Bibliometric Review , 2021, Sustainability.

[19]  E. Scudiero,et al.  Multitemporal satellite imagery analysis for soil organic carbon assessment in an agricultural farm in southeastern Brazil. , 2021, The Science of the total environment.

[20]  Yuan Rao,et al.  Identification of cucumber leaf diseases using deep learning and small sample size for agricultural Internet of Things , 2021, Int. J. Distributed Sens. Networks.

[21]  Alexandros A. Taflanidis,et al.  Storm hazard analysis over extended geospatial grids utilizing surrogate models , 2021 .

[22]  Neeru Jindal,et al.  Machine Learning and Deep Learning Applications-A Vision , 2021, Global Transitions Proceedings.

[23]  R. Ranjith Kumar,et al.  Application of artificial intelligence techniques in irrigation and crop health management for crop yield enhancement , 2020 .

[24]  J. Ruiz-Real,et al.  A Look at the Past, Present and Future Research Trends of Artificial Intelligence in Agriculture , 2020, Agronomy.

[25]  B. Dedieu,et al.  Mapping the research domains on work in agriculture. A bibliometric review from Scopus database , 2020 .

[26]  L. Bounoua,et al.  Delineation of vulnerable areas to water erosion in a mountain region using SDR-InVEST model: A case study of the Ourika watershed, Morocco , 2020 .

[27]  Bruno Henrique Groenner Barbosa,et al.  Artificially intelligent soil quality and health indices for ‘next generation’ food production systems. , 2020 .

[28]  Mutiara Syifa,et al.  Detection of the Pine Wilt Disease Tree Candidates for Drone Remote Sensing Using Artificial Intelligence Techniques , 2020 .

[29]  Biswajeet Pradhan,et al.  Unseen Land Cover Classification from High-Resolution Orthophotos Using Integration of Zero-Shot Learning and Convolutional Neural Networks , 2020, Remote. Sens..

[30]  Yuei-An Liou,et al.  Land-Use Land-Cover Classification by Machine Learning Classifiers for Satellite Observations - A Review , 2020, Remote. Sens..

[31]  Christopher S. Applegate,et al.  Combining computer vision and deep learning to enable ultra-scale aerial phenotyping and precision agriculture: A case study of lettuce production , 2019, Horticulture Research.

[32]  Sha Zhang,et al.  NDVI anomaly for drought monitoring and its correlation with climate factors over Mongolia from 2000 to 2016 , 2019, Journal of Arid Environments.

[33]  S. Balica,et al.  A new flood vulnerability index adapted for the pre-Saharan region , 2019, International Journal of River Basin Management.

[34]  Andreas Kamilaris,et al.  Deep learning in agriculture: A survey , 2018, Comput. Electron. Agric..

[35]  Carlos Granell,et al.  Conceptual Architecture and Service-Oriented Implementation of a Regional Geoportal for Rice Monitoring , 2017, ISPRS Int. J. Geo Inf..

[36]  Daniele Rotolo,et al.  Bibliometric perspectives on medical innovation using the medical subject Headings of PubMed , 2012, J. Assoc. Inf. Sci. Technol..

[37]  Ludo Waltman,et al.  Software survey: VOSviewer, a computer program for bibliometric mapping , 2009, Scientometrics.

[38]  Liguo Weng,et al.  DFFAN: Dual Function Feature Aggregation Network for Semantic Segmentation of Land Cover , 2021, ISPRS Int. J. Geo Inf..

[39]  S. Saha,et al.  Integration of artificial intelligence with meta classifiers for the gully erosion susceptibility assessment in Hinglo river basin, Eastern India , 2021, Advances in Space Research.

[40]  Qiong Li,et al.  Urban water resource management for sustainable environment planning using artificial intelligence techniques , 2021 .

[41]  B. Pham,et al.  Flood risk assessment using hybrid artificial intelligence models integrated with multi-criteria decision analysis in Quang Nam Province, Vietnam , 2021, Journal of Hydrology.

[42]  Dharam J. Shah,et al.  Implementation of artificial intelligence in agriculture for optimisation of irrigation and application of pesticides and herbicides , 2020, Artificial Intelligence in Agriculture.