World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
44
Citations
7420
World Ranking
6743
National Ranking
69

Murali Krishna Gumma publication distribution in Environmental Sciences in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Environmental Sciences in 2026. The highlighted bar marks where Murali Krishna Gumma sits on this spectrum.

41–50 publications: 21 scientists 51–60 publications: 62 scientists 61–70 publications: 133 scientists 71–80 publications: 257 scientists 81–90 publications: 361 scientists 91–100 publications: 440 scientists 101–110 publications: 492 scientists 111–120 publications: 541 scientists 121–130 publications: 617 scientists 131–140 publications: 544 scientists 141–150 publications: 541 scientists 151–160 publications: 539 scientists 161–170 publications: 444 scientists 171–180 publications: 444 scientists 181–190 publications: 400 scientists 191–200 publications: 377 scientists 201–210 publications: 318 scientists 211–220 publications: 283 scientists 221–230 publications: 263 scientists 231–240 publications: 220 scientists 241–250 publications: 217 scientists 251–260 publications: 180 scientists 261–270 publications: 181 scientists 271–280 publications: 155 scientists 281–290 publications: 130 scientists 291–300 publications: 127 scientists 301–310 publications: 130 scientists 311–320 publications: 85 scientists 321–330 publications: 106 scientists 331–340 publications: 80 scientists 341–350 publications: 83 scientists 351–360 publications: 75 scientists 361–370 publications: 69 scientists 371–380 publications: 52 scientists 381–390 publications: 54 scientists 391–400 publications: 56 scientists 401–410 publications: 44 scientists 411–420 publications: 40 scientists 421–430 publications: 36 scientists 431–440 publications: 25 scientists 441–450 publications: 25 scientists 451–460 publications: 32 scientists 461–470 publications: 29 scientists 471–480 publications: 21 scientists 481–490 publications: 26 scientists 491–500 publications: 25 scientists 501–510 publications: 17 scientists 511–520 publications: 18 scientists 521–530 publications: 15 scientists 531–540 publications: 22 scientists 541–550 publications: 12 scientists 551–560 publications: 15 scientists 561–570 publications: 11 scientists 571–580 publications: 19 scientists 581–590 publications: 9 scientists 591–600 publications: 9 scientists 601–610 publications: 7 scientists 611–620 publications: 11 scientists 621–630 publications: 5 scientists 631–640 publications: 5 scientists 641–650 publications: 6 scientists 651–660 publications: 3 scientists 661–670 publications: 3 scientists 671–680 publications: 4 scientists 681–686 publications: 3 scientists 687+ publications: 100 scientists
41 publications 687+

This scientist: 133 publications — 32nd percentile

32% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 687 publications or more.

Murali Krishna Gumma D-index placement in Environmental Sciences in 2026

The chart shows the D-index (discipline H-index) distribution of Environmental Sciences scientists ranked by Research.com in 2026. The highlighted bar marks where Murali Krishna Gumma sits on this spectrum.

30 D-Index: 12 scientists 31 D-Index: 26 scientists 32 D-Index: 51 scientists 33 D-Index: 88 scientists 34 D-Index: 123 scientists 35 D-Index: 163 scientists 36 D-Index: 206 scientists 37 D-Index: 267 scientists 38 D-Index: 265 scientists 39 D-Index: 275 scientists 40 D-Index: 321 scientists 41 D-Index: 343 scientists 42 D-Index: 305 scientists 43 D-Index: 336 scientists 44 D-Index: 330 scientists 45 D-Index: 348 scientists 46 D-Index: 291 scientists 47 D-Index: 275 scientists 48 D-Index: 272 scientists 49 D-Index: 273 scientists 50 D-Index: 263 scientists 51 D-Index: 232 scientists 52 D-Index: 266 scientists 53 D-Index: 217 scientists 54 D-Index: 199 scientists 55 D-Index: 177 scientists 56 D-Index: 202 scientists 57 D-Index: 204 scientists 58 D-Index: 166 scientists 59 D-Index: 177 scientists 60 D-Index: 166 scientists 61 D-Index: 152 scientists 62 D-Index: 143 scientists 63 D-Index: 150 scientists 64 D-Index: 124 scientists 65 D-Index: 119 scientists 66 D-Index: 120 scientists 67 D-Index: 118 scientists 68 D-Index: 82 scientists 69 D-Index: 98 scientists 70 D-Index: 94 scientists 71 D-Index: 105 scientists 72 D-Index: 74 scientists 73 D-Index: 84 scientists 74 D-Index: 70 scientists 75 D-Index: 67 scientists 76 D-Index: 78 scientists 77 D-Index: 60 scientists 78 D-Index: 59 scientists 79 D-Index: 52 scientists 80 D-Index: 47 scientists 81 D-Index: 38 scientists 82 D-Index: 48 scientists 83 D-Index: 42 scientists 84 D-Index: 42 scientists 85 D-Index: 43 scientists 86 D-Index: 29 scientists 87 D-Index: 37 scientists 88 D-Index: 29 scientists 89 D-Index: 30 scientists 90 D-Index: 34 scientists 91 D-Index: 20 scientists 92 D-Index: 22 scientists 93 D-Index: 17 scientists 94 D-Index: 19 scientists 95 D-Index: 24 scientists 96 D-Index: 21 scientists 97 D-Index: 20 scientists 98 D-Index: 24 scientists 99 D-Index: 17 scientists 100 D-Index: 17 scientists 101 D-Index: 21 scientists 102 D-Index: 25 scientists 103 D-Index: 18 scientists 104 D-Index: 26 scientists 105 D-Index: 19 scientists 106 D-Index: 15 scientists 107 D-Index: 10 scientists 108 D-Index: 13 scientists 109 D-Index: 15 scientists 110 D-Index: 12 scientists 111 D-Index: 8 scientists 112 D-Index: 7 scientists 113 D-Index: 9 scientists 114 D-Index: 6 scientists 115 D-Index: 12 scientists 116 D-Index: 7 scientists 117 D-Index: 8 scientists 118 D-Index: 3 scientists 119 D-Index: 5 scientists 120 D-Index: 7 scientists 121 D-Index: 2 scientists 122 D-Index: 4 scientists 123 D-Index: 8 scientists 124 D-Index: 7 scientists 125+ D-Index: 99 scientists
30 D-Index 125+

This scientist: 44 D-Index — 32nd percentile

32% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 125 D-Index or more.

Overview

Murali Krishna Gumma is affiliated with the International Crops Research Institute for the Semi-Arid Tropics in India. Their research primarily spans the fields of Environmental Science and Agricultural and Biological Sciences, with a focus on subfields such as Global and Planetary Change, Ecology, Plant Science, Ecology, Evolution, Behavior and Systematics, and Environmental Engineering.

Gumma's scholarly work covers several main topics, including Remote Sensing in Agriculture, Land Use and Ecosystem Services, Climate Change Impacts on Agriculture, Flood Risk Assessment and Management, Smart Agriculture and AI, Leaf Properties and Growth Measurement, and Agricultural Economics and Practices.

Frequent co-authors in their publications include:

  • Pranay Panjala
  • Pavan Kumar Bellam
  • Anthony Whitbread
  • Kumara Charyulu Deevi
  • Pardhasaradhi Teluguntla

Gumma has published multiple papers in prominent venues, with frequent contributions to AgriEngineering, Geocarto International, Sustainability, Communications Earth & Environment, and Renewable Agriculture and Food Systems.

Recent papers by Murali Krishna Gumma include:

  • Crop type identification and spatial mapping using Sentinel-2 satellite data with focus on field-level information, 2020, Geocarto International
  • Multiple agricultural cropland products of South Asia developed using Landsat-8 30 m and MODIS 250 m data using machine learning on the Google Earth Engine (GEE) cloud and spectral matching techniques (SMTs) in support of food and water security, 2022, GIScience & Remote Sensing

Additional notable papers in which Gumma was involved are:

  • Dynamics and drivers of land use and land cover changes in Bangladesh, 2020, Regional Environmental Change
  • Global cropland-extent product at 30-m resolution (GCEP30) derived from Landsat satellite time-series data for the year 2015 using multiple machine-learning algorithms on Google Earth Engine cloud, 2021, USGS professional paper
  • Characterizing and mapping cropping patterns in a complex agro-ecosystem: An iterative participatory mapping procedure using machine learning algorithms and MODIS vegetation indices, 2020, Computers and Electronics in Agriculture

Best Publications

  • A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform

    Pardhasaradhi Teluguntla;Pardhasaradhi Teluguntla;Prasad S. Thenkabail;Adam Oliphant;Jun N. Xiong

  • Global irrigated area map (GIAM), derived from remote sensing, for the end of the last millennium

    Prasad S. Thenkabail;Chandrashekhar M. Biradar;Praveen Noojipady;Venkateswarlu Dheeravath

  • Automated cropland mapping of continental Africa using Google Earth Engine cloud computing

    Jun N. Xiong;Prasad S. Thenkabail;Murali Krishna Gumma;Pardhasaradhi G. Teluguntla

  • Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

    Jun N. Xiong;Prasad S. Thenkabail;James C. Tilton;Murali Krishna Gumma

  • Mapping rice areas of South Asia using MODIS multitemporal data

    Murali Krishna Gumma;Andrew Nelson;Prasad S. Thenkabail;Amrendra N. Singh

  • Selection of Hyperspectral Narrowbands (HNBs) and Composition of Hyperspectral Twoband Vegetation Indices (HVIs) for Biophysical Characterization and Discrimination of Crop Types Using Field Reflectance and Hyperion/EO-1 Data

    P. S. Thenkabail;I. Mariotto;M. K. Gumma;E. M. Middleton

  • A global map of rainfed cropland areas (GMRCA) at the end of last millennium using remote sensing

    Chandrashekhar M. Biradar;Prasad S. Thenkabail;Praveen Noojipady;Yuanjie Li

  • Mapping seasonal rice cropland extent and area in the high cropping intensity environment of Bangladesh using MODIS 500 m data for the year 2010

    Murali Krishna Gumma;Murali Krishna Gumma;Prasad S. Thenkabail;Aileen Maunahan;Saidul Islam;Saidul Islam

  • Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using a random forest classifier on the Google Earth Engine Cloud

    Adam J. Oliphant;Prasad S. Thenkabail;Pardhasaradhi Teluguntla;Pardhasaradhi Teluguntla;Jun Xiong;Jun Xiong

  • Irrigated area mapping in heterogeneous landscapes with MODIS time series, ground truth and census data, Krishna Basin, India

    Trent W. Biggs;Prasad S. Thenkabail;Murali K. Gumma;Christopher A. Scott

  • Mapping of groundwater potential zones across Ghana using remote sensing, geographic information systems, and spatial modeling.

    Murali Krishna Gumma;Paul Pavelic

  • Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data

    Murali Krishna Gumma;Prasad S. Thenkabail;Pardhasaradhi G. Teluguntla;Mahesh N. Rao

  • Hyperspectral Remote Sensing of Vegetation and Agricultural Crops

    P S Thenkabail;M K Gumma;P Teluguntla;I A Mohammed

  • Mapping Irrigated Areas of Ghana Using Fusion of 30 m and 250 m Resolution Remote-Sensing Data

    Muralikrishna Gumma;Prasad S. Thenkabail;Fujii Hideto;Andrew Nelson

  • Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud

    Murali Krishna Gumma;Prasad S. Thenkabail;Pardhasaradhi G. Teluguntla;Adam Oliphant

  • Assessing future risks to agricultural productivity, water resources and food security: How can remote sensing help?

    P. S. Thenkabail;J. W. Knox;M. Ozdogan;M. K. Gumma

  • A Holistic View of Global Croplands and Their Water Use for Ensuring Global Food Security in the 21st Century through Advanced Remote Sensing and Non-remote Sensing Approaches

    Prasad S. Thenkabail;Munir A. Hanjra;Venkateswarlu Dheeravath;Muralikrishna Gumma

  • Irrigated areas of India derived using MODIS 500 m time series for the years 2001–2003

    Venkateswarlu Dheeravath;Prasad S. Thenkabail;G. Chandrakantha;P. Noojipady

  • Influence of Resolution in Irrigated Area Mapping and Area Estimation

    N. M. Velpuri;Prasad S. Thenkabail;Murali K. Gumma;Chandrashekhar M. Biradar

  • Temporal changes in rice-growing area and their impact on livelihood over a decade: A case study of Nepal

    Murali Krishna Gumma;Devendra Gauchan;Andrew Nelson;Sushil Pandey

  • Assessing Future Risks to Agricultural Productivity, Water Resources and Food Security

    P.S. Thenkabail;J.w. Knox;M. Ozdogan;M.K. Gumma

Frequent Co-Authors

Prasad S. Thenkabail
Prasad S. Thenkabail United States Geological Survey
Russell G. Congalton
Russell G. Congalton University of New Hampshire
Andrew Nelson
Andrew Nelson University of Twente
Chandrashekhar Biradar
Chandrashekhar Biradar International Center for Agricultural Research in the Dry Areas, Egypt
Hugh Turral
Hugh Turral International Water Management Institute
Hari D. Upadhyaya
Hari D. Upadhyaya International Crops Research Institute for the Semi-Arid Tropics
Trent W. Biggs
Trent W. Biggs San Diego State University
Mutlu Ozdogan
Mutlu Ozdogan University of Wisconsin–Madison
Christopher A. Scott
Christopher A. Scott University of Arizona
Rajeev K. Varshney
Rajeev K. Varshney Murdoch University

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