World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
70
Citations
19018
World Ranking
1667
National Ranking
701

Prasad S. Thenkabail 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 Prasad S. Thenkabail 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: 244 publications — 76th percentile

76% of scientists in this discipline score the same or lower.

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

Prasad S. Thenkabail 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 Prasad S. Thenkabail 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: 70 D-Index — 83rd percentile

83% of scientists in this discipline score the same or lower.

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

Overview

Prasad S. Thenkabail is affiliated with the United States Geological Survey in the United States. Their research focuses primarily on environmental science with an emphasis on remote sensing applications in agriculture and land use. The scientist works extensively on combining satellite data with machine learning techniques to improve crop classification and mapping.

The primary fields of study for Thenkabail include Environmental Science, with significant contributions in subfields such as Ecology, Global and Planetary Change, Atmospheric Science, Media Technology, and Plant Science.

The main research topics include:

  • Remote Sensing in Agriculture
  • Remote Sensing and Land Use
  • Remote-Sensing Image Classification
  • Plant Water Relations and Carbon Dynamics
  • Smart Agriculture and AI
  • Solar Radiation and Photovoltaics
  • Land Use and Ecosystem Services

Recent papers include:

  • "Mapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat, Random Forest, and Google Earth Engine," 2020, ISPRS Journal of Photogrammetry and Remote Sensing
  • "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
  • "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
  • "Classifying Crop Types Using Two Generations of Hyperspectral Sensors (Hyperion and DESIS) with Machine Learning on the Cloud," 2021, Remote Sensing
  • "New Generation Hyperspectral Sensors DESIS and PRISMA Provide Improved Agricultural Crop Classifications," 2022, Photogrammetric Engineering & Remote Sensing

Thenkabail frequently publishes in prominent venues such as:

  • Photogrammetric Engineering & Remote Sensing
  • Remote Sensing
  • ISPRS Journal of Photogrammetry and Remote Sensing
  • GIScience & Remote Sensing
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

They have collaborated frequently with several co-authors, including:

  • Pardhasaradhi Teluguntla
  • Itiya Aneece
  • Adam Oliphant
  • Daniel J. Foley
  • Richard L. McCormick

The research of Prasad S. Thenkabail integrates satellite remote sensing technologies such as Landsat and hyperspectral sensors with machine learning approaches implemented on cloud platforms like Google Earth Engine. This work supports food and water security by improving the accuracy of cropland classification and monitoring on regional and global scales.

Best Publications

  • Hyperspectral Vegetation Indices and Their Relationships with Agricultural Crop Characteristics

    Prasad S Thenkabail;Ronald B Smith;Eddy De Pauw

  • Free access to Landsat imagery.

    Curtis E. Woodcock;Richard Allen;Martha Anderson;Alan Belward

  • Hyperspectral Remote Sensing of Vegetation

    Prasad Srinivasa Thenkabail;John Grimson Lyon;Alfredo Huete

  • Accuracy assessments of hyperspectral waveband performance for vegetation analysis applications

    Prasad S. Thenkabail;Eden A. Enclona;Mark S. Ashton;Bauke Van Der Meer

  • 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

  • Hyperion, IKONOS, ALI, and ETM+ sensors in the study of African rainforests

    Prasad S Thenkabail;Eden A Enclona;Mark S Ashton;Christopher Legg

  • 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

  • Evaluation of Narrowband and Broadband Vegetation Indices for Determining Optimal Hyperspectral Wavebands for Agricultural Crop Characterization

    P. S. Thenkabail

  • Remote Sensing Sensors and Applications in Environmental Resources Mapping and Modelling.

    Assefa M Melesse;Qihao Weng;Prasad S Thenkabail;Gabriel B Senay

  • A support vector machine to identify irrigated crop types using time-series Landsat NDVI data

    Baojuan Zheng;Soe W. Myint;Prasad S. Thenkabail;Rimjhim M. Aggarwal

  • Global Land Cover Mapping: A Review and Uncertainty Analysis

    Russell G. Congalton;Jianyu Gu;Kamini Yadav;Prasad S. Thenkabail

  • Ganges and Indus river basin land use/land cover (LULC) and irrigated area mapping using continuous streams of MODIS data

    Prasad S. Thenkabail;Mitchell Schull;Hugh Turral

  • 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

  • Biomass estimations and carbon stock calculations in the oil palm plantations of African derived savannas using IKONOS data

    Prasad S. Thenkabail;N. Stucky;B. W. Griscom;M. S. Ashton

  • 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

  • Hyperspectral versus multispectral crop-productivity modeling and type discrimination for the HyspIRI mission

    Isabella Mariotto;Isabella Mariotto;Prasad S. Thenkabail;Alfredo Huete;E. Terrence Slonecker

Frequent Co-Authors

Murali Krishna Gumma
Murali Krishna Gumma International Crops Research Institute for the Semi-Arid Tropics
Chandrashekhar Biradar
Chandrashekhar Biradar International Center for Agricultural Research in the Dry Areas, Egypt
Russell G. Congalton
Russell G. Congalton University of New Hampshire
Hugh Turral
Hugh Turral International Water Management Institute
Alfredo Huete
Alfredo Huete University of Technology Sydney
Mutlu Ozdogan
Mutlu Ozdogan University of Wisconsin–Madison
Andrew Nelson
Andrew Nelson University of Twente
Trent W. Biggs
Trent W. Biggs San Diego State University
Mark S. Ashton
Mark S. Ashton Yale University
Jerry W. Knox
Jerry W. Knox Cranfield University

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