The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
An overview of current and potential applications of thermal remote sensing in precision agriculture
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Citations
Cites
Overview of the radiometric and biophysical performance of the MODIS vegetation indices
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., & Ferreira, L. G. (2002) · Remote Sensing of Environment · doi:10.1016/s0034-4257(02)00096-2 · Cited by 9,869
Pimentel, D., Zuniga, R., & Morrison, D. (2005) · Ecological Economics · doi:10.1016/j.ecolecon.2004.10.002 · Cited by 4,771
Managing nitrogen for sustainable development.
Zhang, X., Davidson, E. A., Mauzerall, D. L., Searchinger, T. D., Dumas, P., & Shen, Y. (2015) · Nature · doi:10.1038/nature15743 · Cited by 3,054
Derivation of Leaf‐Area Index from Quality of Light on the Forest Floor
Jordan, C. F. (1969) · Ecology · doi:10.2307/1936256 · Cited by 2,694
Gitelson, A. A., Gritz †, Y., & Merzlyak, M. N. (2003) · Journal of Plant Physiology · doi:10.1078/0176-1617-00887 · Cited by 2,683
The application of small unmanned aerial systems for precision agriculture: a review
Zhang, C., & Kovacs, J. M. (2012) · Precision Agriculture · doi:10.1007/s11119-012-9274-5 · Cited by 2,012
Precision Agriculture and Food Security
Gebbers, R., & Adamchuk, V. I. (2010) · Science · doi:10.1126/science.1183899 · Cited by 1,595
Weng, Q. (2009) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2009.03.007 · Cited by 1,446
Berni, J., Zarco-Tejada, P. J., Suarez, L., & Fereres, E. (2009) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2008.2010457 · Cited by 1,308
Irrigation scheduling: advantages and pitfalls of plant-based methods
Jones, H. G. (2004) · Journal of Experimental Botany · doi:10.1093/jxb/erh213 · Cited by 1,111
Cited by
Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges
Shakhatreh, H., Sawalmeh, A. H., Al-Fuqaha, A., Dou, Z., Almaita, E., Khalil, I., Othman, N. S., Khreishah, A., & Guizani, M. (2019) · IEEE Access · doi:10.1109/access.2019.2909530 · Cited by 2,529
A compilation of UAV applications for precision agriculture
Radoglou-Grammatikis, P., Sarigiannidis, P., Lagkas, T., & Moscholios, I. (2020) · Computer Networks · doi:10.1016/j.comnet.2020.107148 · Cited by 957
A novel surface energy balance-based approach to land surface temperature downscaling
Firozjaei, M. K., Mijani, N., Kiavarz, M., Duan, S.-B., Atkinson, P. M., & Alavipanah, S. K. (2024) · Remote Sensing of Environment · doi:10.1016/j.rse.2024.114087 · Cited by 42
DeepG2P: fusing multi-modal data to improve crop production
Sharma, S., Partap, A., Balaguer, M. A. D. L., Malvar, S., & Chandra, R. (2022) · arXiv · doi:10.48550/arxiv.2211.05986 · Cited by 11
“It helps enhancing crop production, increasing yield, reducing water and nutrient losses and environmental impacts [8, 9, 10, 11].”
Background
Metadata
- Authors
- Khanal, S., Fulton, J., & Shearer, S.
- Venue
- Computers and Electronics in Agriculture
- Publisher
- Elsevier BV
- Published
- 2017-06
- Volume
- 139
- Pages
- 22-32
- ISSN
- 0168-1699 (ISSN-L)
- OpenAlex
- W2615516218
- Cited by
- 614
- References
- 55
- FWCI
- 34.07
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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- CoChat. (2026). Citation check: An overview of current and potential applications of thermal remote sensing in precision agriculture. https://app.cochat.ai/papers/10.1016/j.compag.2017.05.001
- The paper
- Khanal, S., Fulton, J., & Shearer, S. (2017). An overview of current and potential applications of thermal remote sensing in precision agriculture. Computers and Electronics in Agriculture. https://doi.org/10.1016/j.compag.2017.05.001
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
