Abhirup Dikshit is a geospatial ecohydrologist using advanced remote sensing tools and machine learning models to monitor vegetation health and function in the face of climate change, land use, and other major disturbance events.
Abhirup’s Ph.D. was on examining large-scale soil-vegetation-climate interactions and processes with remotely sensed measurements from satellites under the mentorship of Prof. Biswajeet Pradhan & Prof. Alfredo Huete. Here, he received valuable professional mentoring in ecology, machine learning applications, and remote sensing to conduct research on ecological resilience, geospatial modeling, and environmental monitoring. He specializes in the use of next-generation geostationary satellites to examine extreme dry events, vegetation dynamics, and flash droughts to better understand Australia's ecosystems.
Dorji L; Sarkar R; Lhachey U; Sharma V; Tshewang ; Dikshit A; Kurar R, 2020, 'An Evaluation of Hydrological Modeling Using SCS-CN Method in Ungauged Om Chhu River Basin of Phuentsholing, Bhutan', in Disaster Risk Reduction, Springer Singapore, pp. 111 - 121, http://dx.doi.org/10.1007/978-981-32-9527-8_7
Book Chapters | 2020
Sarkar R; Narang K; Sharma P; Pal I; Dikshit A, 2020, 'Risk Identification, Assessment, and Disaster Risk Reduction of a Building Information Modeling (BIM)-Implemented Project', in Disaster Risk Reduction, Springer Singapore, pp. 289 - 309, http://dx.doi.org/10.1007/978-981-32-9527-8_17
Journal articles | 2025
Dikshit A; Davis C, 2025, 'Finding the link between flash drought and bushfires', Nature Reviews Earth and Environment, 6, pp. 322, http://dx.doi.org/10.1038/s43017-025-00675-w
Journal articles | 2025
Dikshit A; Evans JP, 2025, 'Characterization of the Australia’s 2019 megafires: a remote-sensing perspective', International Journal of Remote Sensing, 46, pp. 8152 - 8174, http://dx.doi.org/10.1080/01431161.2025.2564909
Journal articles | 2025
Jacob PE; Choudhary N; Dikshit A; Evans JP; Pradhan B; Huete AR, 2025, 'Flash drought prediction using deep learning', Environmental Research Letters, 20, pp. 074006, http://dx.doi.org/10.1088/1748-9326/addb65
Journal articles | 2024
Dikshit A; Evans JP, 2024, 'Quantifying vegetation recovery after fire considering post-fire rainfall', Environmental Research Communications, 6, http://dx.doi.org/10.1088/2515-7620/ad9dbd
Journal articles | 2024
Dikshit A; Pradhan B; Matin SS; Beydoun G; Santosh M; Park HJ; Maulud KNA, 2024, 'Artificial Intelligence: A new era for spatial modelling and interpreting climate-induced hazard assessment', Geoscience Frontiers, 15, http://dx.doi.org/10.1016/j.gsf.2024.101815
Journal articles | 2023
Pradhan B; Dikshit A; Lee S; Kim H, 2023, 'An explainable AI (XAI) model for landslide susceptibility modeling', Applied Soft Computing, 142, http://dx.doi.org/10.1016/j.asoc.2023.110324
Journal articles | 2023
Pradhan B; Lee S; Dikshit A; Kim H, 2023, 'Spatial flood susceptibility mapping using an explainable artificial intelligence (XAI) model', Geoscience Frontiers, 14, http://dx.doi.org/10.1016/j.gsf.2023.101625
Journal articles | 2022
Abdollahi A; Liu Y; Pradhan B; Huete A; Dikshit A; Nguyen Tran N, 2022, 'Short-time-series grassland mapping using Sentinel-2 imagery and deep learning-based architecture', Egyptian Journal of Remote Sensing and Space Science, 25, pp. 673 - 685, http://dx.doi.org/10.1016/j.ejrs.2022.06.002
Journal articles | 2022
Dikshit A; Pradhan B; Assiri ME; Almazroui M; Park HJ, 2022, 'Solving transparency in drought forecasting using attention models', Science of the Total Environment, 837, http://dx.doi.org/10.1016/j.scitotenv.2022.155856
Journal articles | 2022
Dikshit A; Pradhan B; Huete A; Park HJ, 2022, 'Spatial based drought assessment: Where are we heading? A review on the current status and future', Science of the Total Environment, 844, http://dx.doi.org/10.1016/j.scitotenv.2022.157239
Journal articles | 2022
Dikshit A; Pradhan B; Santosh M, 2022, 'Artificial neural networks in drought prediction in the 21st century–A scientometric analysis', Applied Soft Computing, 114, http://dx.doi.org/10.1016/j.asoc.2021.108080
Journal articles | 2022
Serbouti I; Raji M; Hakdaoui M; El Kamel F; Pradhan B; Gite S; Alamri A; Maulud KNA; Dikshit A, 2022, 'Improved Lithological Map of Large Complex Semi-Arid Regions Using Spectral and Textural Datasets within Google Earth Engine and Fused Machine Learning Multi-Classifiers', Remote Sensing, 14, http://dx.doi.org/10.3390/rs14215498
Journal articles | 2022
Youssef AM; Pradhan B; Dikshit A; Al-Katheri MM; Matar SS; Mahdi AM, 2022, 'Landslide susceptibility mapping using CNN-1D and 2D deep learning algorithms: comparison of their performance at Asir Region, KSA', Bulletin of Engineering Geology and the Environment, 81, http://dx.doi.org/10.1007/s10064-022-02657-4
Journal articles | 2022
Youssef AM; Pradhan B; Dikshit A; Mahdi AM, 2022, 'Comparative study of convolutional neural network (CNN) and support vector machine (SVM) for flood susceptibility mapping: a case study at Ras Gharib, Red Sea, Egypt', Geocarto International, 37, pp. 11088 - 11115, http://dx.doi.org/10.1080/10106049.2022.2046866
Journal articles | 2021
Dikshit A; Pradhan B; Alamri AM, 2021, 'Long lead time drought forecasting using lagged climate variables and a stacked long short-term memory model', Science of the Total Environment, 755, http://dx.doi.org/10.1016/j.scitotenv.2020.142638
Journal articles | 2021
Dikshit A; Pradhan B; Alamri AM, 2021, 'Pathways and challenges of the application of artificial intelligence to geohazards modelling', Gondwana Research, 100, pp. 290 - 301, http://dx.doi.org/10.1016/j.gr.2020.08.007
Journal articles | 2021
Dikshit A; Pradhan B; Huete A, 2021, 'An improved SPEI drought forecasting approach using the long short-term memory neural network', Journal of Environmental Management, 283, http://dx.doi.org/10.1016/j.jenvman.2021.111979
Saha S; Kundu B; Paul GC; Mukherjee K; Pradhan B; Dikshit A; Abdul Maulud KN; Alamri AM, 2021, 'Spatial assessment of drought vulnerability using fuzzy-analytical hierarchical process: a case study at the Indian state of Odisha', Geomatics Natural Hazards and Risk, 12, pp. 123 - 153, http://dx.doi.org/10.1080/19475705.2020.1861114
Journal articles | 2021
Saha S; Roy J; Hembram TK; Pradhan B; Dikshit A; Abdul Maulud KN; Alamri AM, 2021, 'Comparison between deep learning and tree‐based machine learning approaches for landslide susceptibility mapping', Water Switzerland, 13, http://dx.doi.org/10.3390/w13192664
Journal articles | 2020
Dikshit A; Pradhan B; Alamri AM, 2020, 'Short-term spatio-temporal drought forecasting using random forests model at New South Wales, Australia', Applied Sciences Switzerland, 10, http://dx.doi.org/10.3390/app10124254
Journal articles | 2020
Dikshit A; Pradhan B; Alamri AM, 2020, 'Temporal hydrological drought index forecasting for New South Wales, Australia using machine learning approaches', Atmosphere, 11, http://dx.doi.org/10.3390/atmos11060585
Dikshit A; Sarkar R; Pradhan B; Jena R; Drukpa D; Alamri AM, 2020, 'Temporal probability assessment and its use in landslide susceptibility mapping for Eastern Bhutan', Water Switzerland, 12, http://dx.doi.org/10.3390/w12010267
Journal articles | 2020
Dikshit A; Sarkar R; Pradhan B; Segoni S; Alamri AM, 2020, 'Rainfall induced landslide studies in indian himalayan region: A critical review', Applied Sciences Switzerland, 10, http://dx.doi.org/10.3390/app10072466
Journal articles | 2020
Dikshit A; Satyam N; Pradhan B; Kushal S, 2020, 'Estimating rainfall threshold and temporal probability for landslide occurrences in Darjeeling Himalayas', Geosciences Journal, 24, pp. 225 - 233, http://dx.doi.org/10.1007/s12303-020-0001-3
Journal articles | 2020
Shukla N; Pradhan B; Dikshit A; Chakraborty S; Alamri AM, 2020, 'A review of models used for investigating barriers to healthcare access in Australia', International Journal of Environmental Research and Public Health, 17, pp. 1 - 19, http://dx.doi.org/10.3390/ijerph17114087
Journal articles | 2020
Tempa K; Sarkar R; Dikshit A; Pradhan B; Simonelli AL; Acharya S; Alamri AM, 2020, 'Parametric study of local site response for bedrock ground motion to earthquake in Phuentsholing, Bhutan', Sustainability Switzerland, 12, http://dx.doi.org/10.3390/su12135273
Journal articles | 2019
Dikshit A; Sarkar R; Pradhan B; Acharya S; Dorji K, 2019, 'Estimating rainfall thresholds for landslide occurrence in the Bhutan Himalayas', Water Switzerland, 11, http://dx.doi.org/10.3390/w11081616
Journal articles | 2019
Dikshit A; Satyam N; Pradhan B, 2019, 'Estimation of Rainfall-Induced Landslides Using the TRIGRS Model', Earth Systems and Environment, 3, pp. 575 - 584, http://dx.doi.org/10.1007/s41748-019-00125-w
Journal articles | 2019
Dikshit A; Satyam N, 2019, 'Probabilistic rainfall thresholds in Chibo, India: estimation and validation using monitoring system', Journal of Mountain Science, 16, pp. 870 - 883, http://dx.doi.org/10.1007/s11629-018-5189-6
Journal articles | 2019
Gariano SL; Sarkar R; Dikshit A; Dorji K; Brunetti MT; Peruccacci S; Melillo M, 2019, 'Automatic calculation of rainfall thresholds for landslide occurrence in Chukha Dzongkhag, Bhutan', Bulletin of Engineering Geology and the Environment, 78, pp. 4325 - 4332, http://dx.doi.org/10.1007/s10064-018-1415-2
Journal articles | 2019
Sarkar R; Dikshit A; Hazarika H; Yamada K; Subba K, 2019, 'Probabilistic rainfall thresholds for landslide occurrences in Bhutan', International Journal of Recent Technology and Engineering, 8, pp. 737 - 742, http://dx.doi.org/10.35940/ijrte.B1132.0982S1019
Journal articles | 2019
Teja TS; Dikshit A; Satyam N, 2019, 'Determination of rainfall thresholds for landslide prediction using an algorithm-based approach: Case study in the Darjeeling Himalayas, India', Geosciences Switzerland, 9, http://dx.doi.org/10.3390/geosciences9070302
Journal articles | 2018
Dikshit A; Sarkar R; Satyam N, 2018, 'Probabilistic approach toward Darjeeling Himalayas landslides-A case study', Cogent Engineering, 5, pp. 1 - 11, http://dx.doi.org/10.1080/23311916.2018.1537539
Journal articles | 2018
Dikshit A; Satyam DN; Towhata I, 2018, 'Early warning system using tilt sensors in Chibo, Kalimpong, Darjeeling Himalayas, India', Natural Hazards, 94, pp. 727 - 741, http://dx.doi.org/10.1007/s11069-018-3417-6
Journal articles | 2018
Dikshit A; Satyam DN, 2018, 'Estimation of rainfall thresholds for landslide occurrences in Kalimpong, India', Innovative Infrastructure Solutions, 3, http://dx.doi.org/10.1007/s41062-018-0132-9
Conference Papers | 2019
Dikshit A; Satyam N, 2019, 'Monitoring of Unstable Slopes with Low Cost Sensor Network in Chibo, Kalimpong, Darjeeling Himalayas, India', in LopezAcosta NP; MartinezHernandez E; EspinosaSantiago AL; MendozaPromotor JA; Lopez AO(eds.), GEOTECHNICAL ENGINEERING IN THE XXI CENTURY: LESSONS LEARNED AND FUTURE CHALLENGES, IOS PRESS, MEXICO, Cancun, pp. 1710 - 1715, presented at 16th Pan-American Conference on Soil Mechanics and Geotechnical Engineering (PCSMGE), MEXICO, Cancun, 17 November 2019 - 20 November 2019, http://dx.doi.org/10.3233/STAL190225
Preprints | 2017
Dikshit A; Satyam N, 2017, Application of FLaIR model for early warning system in Chibo Pashyor, Kalimpong, India for rainfall-induced landslides, http://dx.doi.org/10.5194/nhess-2017-295
2025 - Recipient of Discovery Early Career Researcher Award (DECRA), Australian Research Council (ARC).
2021 - Recipient of the Cross-Faculty Project funded by the School of Information Systems and Modelling, UTS.
2020 - Recipient of the ISM Research Incentivisation by the School of Information Systems and Modelling, UTS.
2019 - Recipient of the International Research Training Program Scholarship (IRTP) funded by the Australian Government under the Department of Education and Training.
2019 - Co-CI - Impact of climate change, Land use land cover, and socio-economic dynamics on landslides in South and East Asia. (Granted by International Science Council (ICSU).
2022 - HDR Excellence Awards - UTS Faculty of Engineering & IT (Commendation)
2021 - Best Paper Award in Gondwana Research, Elsevier for the article titled ’Pathways and challenges of the application of artificial intelligence to geohazards modelling’. This article has been recognized as a 'Highly Cited Paper' by Clarivate Analytics, Web of Science. Link: https://doi.org/10.1016/j.gr.2022.11.009
2020 - Best Paper Award in Atmosphere, MDPI for the article titled ’Temporal Hydrological Drought Index Forecasting for New South Wales, Australia Using Machine Learning Approaches’. Link: https://www.mdpi.com/journal/atmosphere/awards/1600
2020 - Won 2nd prize in the IEEE NSW Chapter computational Challenge Competition, 2020, presenting work on Drought Forecasting.
2020 - Won 2nd prize in the Urban MAXAR Challenge, 2020 a national challenge competition addressing solutions to Australia's biggest challenges.
Understanding vegetation response during extreme dry events.
Analysing ecosystems function by tracking important sub-daily and daily processes.
Improve our understanding and modelling of unusual bushfire behaviour.
Analyzing the land-atmosphere feedback mechanism post bushfires.
Empirical modeling of of rainfall-induced landslides.
