World's Best Scientists 2026 revealed!
John R. Miller

John R. Miller

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Environmental Sciences
Canada
2023

D-Index & Metrics

Environmental Sciences

D-Index
59
Citations
18513
World Ranking
3027
National Ranking
129

John R. Miller 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 John R. Miller 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: 178 publications — 55th percentile

55% of scientists in this discipline score the same or lower.

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

John R. Miller 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 John R. Miller 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: 59 D-Index — 69th percentile

69% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2023 - Research.com Environmental Sciences in Canada Leader Award

Overview

John R. Miller is affiliated with York University in Canada and conducts research primarily in Earth and Planetary Sciences as well as Environmental Science. Their work spans topics related to the physical environment and its changes, with special attention to climate-related phenomena and geological aspects.

The scientist's research involves several specialized subfields, including Atmospheric Science, Geology, and Environmental Chemistry. These areas contribute to a multifaceted understanding of environmental processes and their implications, particularly concerning climate and geological systems.

Their scholarly contributions focus on themes such as:

  • Climate change and permafrost
  • Geological Studies and Exploration
  • Methane Hydrates and Related Phenomena

One documented publication by John R. Miller is titled "Elevation-dependent warming in the Eastern Siberian Arctic", published in 2021 in the journal Environmental Research Letters. This work has received citations in subsequent related research, indicating engagement with ongoing scientific discussions in the area of Arctic climate warming.

John R. Miller collaborates with other researchers frequently, including John E. Fuller and Michael J. Puma. Such joint efforts illustrate interdisciplinary and cooperative research dynamics.

Their contributions have appeared in specific publication venues, notably Environmental Research Letters, where they have at least one article to their credit.

Best Publications

  • Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture

    Driss Haboudane;John R. Miller;John R. Miller;Elizabeth Pattey;Pablo J. Zarco-Tejada

  • Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture

    Driss Haboudane;John R. Miller;John R. Miller;Nicolas Tremblay;Pablo J. Zarco-Tejada

  • Scaling-up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data

    P.J. Zarco-Tejada;J.R. Miller;T.L. Noland;G.H. Mohammed

  • Assessing vineyard condition with hyperspectral indices: Leaf and canopy reflectance simulation in a row-structured discontinuous canopy

    P.J. Zarco-Tejada;A. Berjón;R. López-Lozano;J.R. Miller

  • Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress.

    Gina H. Mohammed;Roberto Colombo;Elizabeth M. Middleton;Uwe Rascher

  • Hyperspectral indices and model simulation for chlorophyll estimation in open-canopy tree crops

    Pablo J. Zarco-Tejada;John R. Miller;Arturo Morales;A. Berjón

  • Comparison of in situ and airborne spectral measurements of the blue shift associated with forest decline

    B. N. Rock;T. Hoshizaki;J. R. Miller

  • Determining digital hemispherical photograph exposure for leaf area index estimation

    Yongqin Zhang;Jing M. Chen;John R. Miller

  • Quantitative characterization of the vegetation red edge reflectance 1. An inverted-Gaussian reflectance model

    J. R. Miller;E. W. Hare;J. Wu

  • Remote Estimation of Crop Chlorophyll Content Using Spectral Indices Derived From Hyperspectral Data

    D. Haboudane;N. Tremblay;J.R. Miller;P. Vigneault

  • Imaging chlorophyll fluorescence with an airborne narrow-band multispectral camera for vegetation stress detection

    Pablo J. Zarco-Tejada;J.A.J. Berni;Lola Suarez;G. Sepulcre-Cantó

  • Assessing canopy PRI for water stress detection with diurnal airborne imagery

    L. Suárez;P.J. Zarco-Tejada;G. Sepulcre-Cantó;O. Pérez-Priego

  • Chlorophyll Fluorescence Effects on Vegetation Apparent Reflectance: I. Leaf-Level Measurements and Model Simulation

    Pablo J. Zarco-Tejada;John R. Miller;Gina H. Mohammed;Thomas L. Noland

  • Comparative study between a new nonlinear model and common linear model for analysing laboratory simulated-forest hyperspectral data

    Wenyi Fan;Baoxin Hu;John Miller;Mingze Li

  • Vegetation stress detection through chlorophyll a + b estimation and fluorescence effects on hyperspectral imagery.

    Pablo J. Zarco-Tejada;John R. Miller;G. H. Mohammed;Thomas L. Noland

  • Leaf chlorophyll content retrieval from airborne hyperspectral remote sensing imagery

    Yongqin Zhang;Jing M. Chen;John R. Miller;Thomas L. Noland

  • Needle chlorophyll content estimation through model inversion using hyperspectral data from boreal conifer forest canopies

    Pablo J. Zarco-Tejada;John R. Miller;John R. Miller;John Harron;Baoxin Hu;Baoxin Hu

  • Chlorophyll fluorescence effects on vegetation apparent reflectance: II. laboratory and airborne canopy-level measurements with hyperspectral data.

    Pablo J Zarco-Tejada;John R Miller;Gina H Mohammed;Thomas L Noland

  • Estimating crop stresses, aboveground dry biomass and yield of corn using multi-temporal optical data combined with a radiation use efficiency model

    Jiangui Liu;Elizabeth Pattey;John R. Miller;Heather McNairn

  • Seasonal patterns in leaf reflectance red-edge characteristics

    J.R. Miller;Jiyou Wu;M.G. Boyer;M. Belanger

Frequent Co-Authors

Pablo J. Zarco-Tejada
Pablo J. Zarco-Tejada Spanish National Research Council
Jing M. Chen
Jing M. Chen University of Toronto
Jose Moreno
Jose Moreno University of Valencia
Nicolas Tremblay
Nicolas Tremblay Grain Research Centre
Elizabeth Pattey
Elizabeth Pattey Agriculture and Agriculture-Food Canada
Michael E. Schaepman
Michael E. Schaepman University of Zurich
Massimo Menenti
Massimo Menenti Delft University of Technology
Michel M. Verstraete
Michel M. Verstraete University of the Witwatersrand
Frédéric Baret
Frédéric Baret INRAE : Institut national de recherche pour l'agriculture, l'alimentation et l'environnement
Wolfgang Knorr
Wolfgang Knorr Lund University

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