World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
7251
World Ranking
10591
National Ranking
114

Manoj K. Arora publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Manoj K. Arora sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 118 publications — 14th percentile

14% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Manoj K. Arora D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Manoj K. Arora sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Manoj K. Arora is affiliated with the Indian Institute of Technology Roorkee in India. Their research work primarily spans the fields of Earth and Planetary Sciences, Environmental Science, and Energy. The scientist has contributed extensively to subfields such as Atmospheric Science, Renewable Energy, Sustainability and the Environment, Management, Monitoring, Policy and Law, Environmental Engineering, and Global and Planetary Change.

The main topics of Manoj K. Arora's research include:

  • Cryospheric studies and observations
  • Climate change and permafrost
  • Solar Thermal and Photovoltaic Systems
  • Landslides and related hazards
  • Solar-Powered Water Purification Methods
  • Photovoltaic System Optimization Techniques
  • Urban Stormwater Management Solutions

The scientist has published research in several venues, with frequent publications in:

  • Research Square (Research Square)
  • Environmental Monitoring and Assessment
  • ShodhKosh Journal of Visual and Performing Arts
  • Desalination
  • Remote Sensing

Some of the notable recent papers authored or co-authored by Manoj K. Arora include:

  • What drives e-hailing apps adoption? An analysis of behavioral factors through fuzzy AHP, 2021, Journal of Science and Technology Policy Management
  • Performance and cost analysis of photovoltaic thermal (PVT)-compound parabolic concentrator (CPC) collector integrated solar still using CNT-water based nanofluids, 2020, Desalination
  • Large-Scale Debris Cover Glacier Mapping Using Multisource Object-Based Image Analysis Approach, 2022, Remote Sensing
  • On Drivers of Subpixel Classification Accuracy-An Example From Glacier Facies, 2020, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • Evaluation of the performance parameters of a PVT system: Case study of composite environmental conditions for different Indian cities, 2021, Materials Today Proceedings

Frequent collaborators in these research efforts include Swati Arora, Harendra Pal Singh, Lovedeep Sahota, Kavita Vaijanath Mitkari, and Reet Kamal Tiwari.

Best Publications

  • A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas

    D.P. Kanungo;M.K. Arora;S. Sarkar;R.P. Gupta

  • Decision tree regression for soft classification of remote sensing data

    Min Xu;Pakorn Watanachaturaporn;Pramod K. Varshney;Manoj K. Arora

  • GIS-based Landslide Hazard Zonation in the Bhagirathi (Ganga) Valley, Himalayas

    A. K. Saha;R. P. Gupta;M. K. Arora

  • An evaluation of some factors affecting the accuracy of classification by an artificial neural network

    G. M. Foody;M. K. Arora

  • Super-resolution land cover mapping using a Markov random field based approach

    Teerasit Kasetkasem;Manoj K. Arora;Pramod K. Varshney

  • Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data

    Manoj K. Arora;Pramod K. Varshney

  • Performance of mutual information similarity measure for registration of multitemporal remote sensing images

    Hua-Mei Chen;P.K. Varshney;M.K. Arora

  • Mutual information based image registration for remote sensing data

    Hua-mei Chen;Manoj K. Arora;Pramod K. Varshney

  • An artificial neural network approach for landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas

    M. K. Arora;A. S. Das Gupta;R. P. Gupta

  • Landslide susceptibility zonation of the Chamoli region, Garhwal Himalayas, using logistic regression model.

    Shivani Chauhan;Mukta Sharma;Manoj K. Arora

  • Landslide Susceptibility Zonation through ratings derived from Artificial Neural Network

    Shivani Chauhan;Mukta Sharma;M.K. Arora;N.K. Gupta

  • Logistic Regression for Feature Selection and Soft Classification of Remote Sensing Data

    Qi Cheng;P.K. Varshney;M.K. Arora

  • Synergistic approach for mapping debris-covered glaciers using optical–thermal remote sensing data with inputs from geomorphometric parameters

    A. Shukla;M.K. Arora;R.P. Gupta

  • An assessment of independent component analysis for detection of military targets from hyperspectral images

    K. C. Tiwari;Manoj K. Arora;Dharmendra Singh

  • Incorporating mixed pixels in the training, allocation and testing stages of supervised classifications

    Giles M. Foody;Manoj K. Arora

  • Landslide Susceptibility Zonation (LSZ) Mapping - A Review

    D. P. Kanungo;M. K. Arora;S. Sarkar;R. P. Gupta

  • Land Cover Classification Using IRS LISS III Image and DEM in a Rugged Terrain: A Case Study in Himalayas

    A. K. Saha;M. K. Arora;E. Csaplovics;R. P. Gupta

  • Landslide risk assessment using concepts of danger pixels and fuzzy set theory in Darjeeling Himalayas

    D. P. Kanungo;M. K. Arora;R. P. Gupta;S. Sarkar

  • Estimation of debris cover and its temporal variation using optical satellite sensor data: a case study in Chenab basin, Himalaya

    A. Shukla;R.P. Gupta;M.K. Arora

  • GIS‐based route planning in landslide‐prone areas

    Ashis Kumar Saha;Manoj K. Arora;Ravi Prakash Gupta;M. L. Virdi

  • Unsupervised classification of hyperspectral data: an ICA mixture model based approach

    Chintan A. Shah;Manoj K. Arora;Pramod K. Varshney

Frequent Co-Authors

Pramod K. Varshney
Pramod K. Varshney Syracuse University
Umesh C. Kothyari
Umesh C. Kothyari Indian Institute of Technology Roorkee
Giles M. Foody
Giles M. Foody University of Nottingham
Stephen V. Stehman
Stephen V. Stehman SUNY College of Environmental Science and Forestry
Balasubramanian Raman
Balasubramanian Raman Indian Institute of Technology Roorkee

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