Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Scaling-up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data
2001582 citationsPablo J. Zarco‐Tejada, John R. Miller et al.IEEE Transactions on Geoscience and Remote Sensingprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by G. H. Mohammed
Since
Specialization
Citations
This map shows the geographic impact of G. H. Mohammed's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by G. H. Mohammed with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. H. Mohammed more than expected).
This network shows the impact of papers produced by G. H. Mohammed. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by G. H. Mohammed. The network helps show where G. H. Mohammed may publish in the future.
Co-authorship network of co-authors of G. H. Mohammed
This figure shows the co-authorship network connecting the top 25 collaborators of G. H. Mohammed.
A scholar is included among the top collaborators of G. H. Mohammed based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with G. H. Mohammed. G. H. Mohammed is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Noland, Thomas L., John R. Miller, Pablo J. Zarco‐Tejada, et al.. (2003). Bioindicators of Forest Sustainability: Using Remote Sensing to Monitor Forest Condition. DIGITAL.CSIC (Spanish National Research Council (CSIC)).4 indexed citations
Zarco‐Tejada, Pablo J., John R. Miller, Thomas L. Noland, G. H. Mohammed, & P. H. Sampson. (2001). Scaling-up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data. IEEE Transactions on Geoscience and Remote Sensing. 39(7). 1491–1507.582 indexed citations breakdown →
Zarco‐Tejada, Pablo J., John R. Miller, G. H. Mohammed, Thomas L. Noland, & P. H. Sampson. (2000). Optical Indices as Bioindicators of Forest Condition from Hyperspectral CASI data. DIGITAL.CSIC (Spanish National Research Council (CSIC)).21 indexed citations
7.
Mohammed, G. H., et al.. (2000). Natural and stress-induced effects on leaf spectral reflectance in Ontario species. DIGITAL.CSIC (Spanish National Research Council (CSIC)).25 indexed citations
Zarco‐Tejada, Pablo J., John R. Miller, G. H. Mohammed, Thomas L. Noland, & P. H. Sampson. (1999). Indices Opticos obtenidos mediante datos Hiperspectrales del sensor CASI como Indicadores de Estres en Zonas Forestales. DIGITAL.CSIC (Spanish National Research Council (CSIC)).1 indexed citations
Mohammed, G. H.. (1999). Non-timber forest products in Ontario: an overview..12 indexed citations
12.
Sampson, P. H., G. H. Mohammed, S. J. Colombo, et al.. (1998). Bioindicators of Forest Sustainability: Progress Report. DIGITAL.CSIC (Spanish National Research Council (CSIC)).4 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.