João Valente

3.0k total citations · 1 hit paper
89 papers, 2.0k citations indexed

About

João Valente is a scholar working on Plant Science, Environmental Engineering and Ecology. According to data from OpenAlex, João Valente has authored 89 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Plant Science, 31 papers in Environmental Engineering and 30 papers in Ecology. Recurrent topics in João Valente's work include Remote Sensing in Agriculture (28 papers), Remote Sensing and LiDAR Applications (28 papers) and Smart Agriculture and AI (25 papers). João Valente is often cited by papers focused on Remote Sensing in Agriculture (28 papers), Remote Sensing and LiDAR Applications (28 papers) and Smart Agriculture and AI (25 papers). João Valente collaborates with scholars based in Netherlands, Spain and China. João Valente's co-authors include Antonio Barrientos, Jaime del Cerro, David Sanz, Lammert Kooistra, Mar Ariza-Sentís, Sergio Vélez, Cláudio Rossi, Julian D. Colorado, A. Martínez and Mariska van der Voort and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.

In The Last Decade

João Valente

82 papers receiving 1.9k citations

Hit Papers

Object detection and trac... 2024 2026 2024 20 40 60

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
João Valente Netherlands 24 689 634 586 442 396 89 2.0k
Inkyu Sa Australia 19 1.4k 2.0× 500 0.8× 647 1.1× 448 1.0× 225 0.6× 41 2.3k
Annalisa Milella Italy 21 472 0.7× 416 0.7× 493 0.8× 166 0.4× 174 0.4× 88 1.6k
Cunjia Liu United Kingdom 33 580 0.8× 745 1.2× 472 0.8× 479 1.1× 270 0.7× 124 2.9k
Lei Tian United States 25 917 1.3× 232 0.4× 290 0.5× 708 1.6× 493 1.2× 98 2.3k
Noboru Noguchi Japan 27 1.3k 2.0× 341 0.5× 458 0.8× 251 0.6× 255 0.6× 208 2.6k
Stamatia Bibi Greece 15 501 0.7× 342 0.5× 214 0.4× 307 0.7× 221 0.6× 59 1.7k
Raghav Khanna Switzerland 11 627 0.9× 292 0.5× 309 0.5× 381 0.9× 195 0.5× 18 1.2k
Grzegorz Cielniak United Kingdom 22 511 0.7× 380 0.6× 677 1.2× 128 0.3× 166 0.4× 90 1.6k
Jinya Su United Kingdom 33 832 1.2× 338 0.5× 243 0.4× 603 1.4× 289 0.7× 91 3.1k
Rasmus Nyholm Jørgensen Denmark 28 1.4k 2.0× 178 0.3× 221 0.4× 658 1.5× 289 0.7× 111 2.2k

Countries citing papers authored by João Valente

Since Specialization
Citations

This map shows the geographic impact of João Valente'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 João Valente with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites João Valente more than expected).

Fields of papers citing papers by João Valente

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by João Valente. 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 João Valente. The network helps show where João Valente may publish in the future.

Co-authorship network of co-authors of João Valente

This figure shows the co-authorship network connecting the top 25 collaborators of João Valente. A scholar is included among the top collaborators of João Valente 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 João Valente. João Valente is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ariza-Sentís, Mar, et al.. (2025). Comparative analysis of single-view and multiple-view data collection strategies for detecting partially-occluded grape bunches: Field trials. Journal of Agriculture and Food Research. 19. 101736–101736. 1 indexed citations
2.
Valente, João, et al.. (2025). Fields2Benchmark: An open-source benchmark for coverage path planning methods in agriculture. Smart Agricultural Technology. 12. 101156–101156.
3.
Valente, João, et al.. (2025). AI-Powered Augmented Reality for Satellite Assembly, Integration and Test. 1–9. 2 indexed citations
4.
Vélez, Sergio, et al.. (2024). Integrated framework for multipurpose UAV Path Planning in hedgerow systems considering the biophysical environment. Crop Protection. 187. 106992–106992. 6 indexed citations
5.
Ariza-Sentís, Mar, et al.. (2024). Object detection and tracking in Precision Farming: a systematic review. Computers and Electronics in Agriculture. 219. 108757–108757. 61 indexed citations breakdown →
6.
Valente, João, et al.. (2024). Continuous Curvature Path Planning for Headland Coverage With Agricultural Robots. Journal of Field Robotics. 42(3). 641–656. 3 indexed citations
7.
Vélez, Sergio, et al.. (2024). Assessing the impact of overhead agrivoltaic systems on GNSS signal performance for precision agriculture. SHILAP Revista de lepidopterología. 9. 100664–100664. 5 indexed citations
8.
Valente, João, et al.. (2023). A fast two-stage approach for multi-goal path planning in a fruit tree. Socio-Environmental Systems Modeling. 1586–1593. 3 indexed citations
10.
11.
Vélez, Sergio, Mar Ariza-Sentís, & João Valente. (2023). Dataset on unmanned aerial vehicle multispectral images acquired over a vineyard affected by Botrytis cinerea in northern Spain. Data in Brief. 46. 108876–108876. 14 indexed citations
12.
Ariza-Sentís, Mar, Sergio Vélez, & João Valente. (2022). Dataset on UAV RGB videos acquired over a vineyard including bunch labels for object detection and tracking. Data in Brief. 46. 108848–108848. 17 indexed citations
13.
Vélez, Sergio, Mar Ariza-Sentís, & João Valente. (2022). Mapping the spatial variability of Botrytis bunch rot risk in vineyards using UAV multispectral imagery. European Journal of Agronomy. 142. 126691–126691. 44 indexed citations
14.
Zhang, Chenglong, et al.. (2022). Automatic flower cluster estimation in apple orchards using aerial and ground based point clouds. Biosystems Engineering. 221. 164–180. 18 indexed citations
15.
Aguiar, André, Sandro Augusto Magalhães, Filipe Neves dos Santos, et al.. (2021). Grape Bunch Detection at Different Growth Stages Using Deep Learning Quantized Models. Agronomy. 11(9). 1890–1890. 47 indexed citations
16.
Apolo-Apolo, Orly Enrique, Manuel Pérez Ruiz, Jorge Martínez-Guanter, & João Valente. (2020). A Cloud-Based Environment for Generating Yield Estimation Maps From Apple Orchards Using UAV Imagery and a Deep Learning Technique. Frontiers in Plant Science. 11. 1086–1086. 75 indexed citations
17.
Valente, João, et al.. (2020). An Adaptive Informative Path Planning Algorithm for Real-time Air Quality Monitoring Using UAVs. Socio-Environmental Systems Modeling. 1121–1130. 1 indexed citations
18.
Valente, João, David Sanz, Jaime del Cerro, Antonio Barrientos, & M.Á. Frutos. (2012). Near-optimal coverage trajectories for image mosaicing using a mini quad-rotor over irregular-shaped fields. Precision Agriculture. 14(1). 115–132. 70 indexed citations
19.
Valente, João, et al.. (2011). Techniques for Area Discretization and Coverage in Aerial Photography for Precision Agriculture employing mini quad-rotors. UPM Digital Archive (Technical University of Madrid). 3 indexed citations
20.
Valente, João, et al.. (2011). A waypoint-based mission planner for a farmland coverage with an aerial robot - a precision farming tool. UPM Digital Archive (Technical University of Madrid). 9 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.

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