Adam Oliphant

2.0k total citations · 2 hit papers
26 papers, 1.6k citations indexed

About

Adam Oliphant is a scholar working on Ecology, Global and Planetary Change and Plant Science. According to data from OpenAlex, Adam Oliphant has authored 26 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Ecology, 9 papers in Global and Planetary Change and 6 papers in Plant Science. Recurrent topics in Adam Oliphant's work include Remote Sensing in Agriculture (14 papers), Land Use and Ecosystem Services (5 papers) and Remote Sensing and Land Use (5 papers). Adam Oliphant is often cited by papers focused on Remote Sensing in Agriculture (14 papers), Land Use and Ecosystem Services (5 papers) and Remote Sensing and Land Use (5 papers). Adam Oliphant collaborates with scholars based in United States, India and China. Adam Oliphant's co-authors include Prasad S. Thenkabail, Pardhasaradhi Teluguntla, Jun Xiong, Murali Krishna Gumma, Kamini Yadav, Russell G. Congalton, Alfredo Huete, James C. Tilton, Noel Gorelick and Itiya Aneece and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing and ISPRS Journal of Photogrammetry and Remote Sensing.

In The Last Decade

Adam Oliphant

25 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

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.

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

2018 424 citations Pardhasaradhi Teluguntla, Prasad S. Thenkabail et al. ISPRS Journal of Photogrammetry and Remote Sensing profile →
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

2017 312 citations Jun Xiong, Prasad S. Thenkabail et al. Remote Sensing profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Adam Oliphant United States	14	957	749	344	286	256	26	1.6k
Pengyu Hao China	26	975 1.0×	584 0.8×	386 1.1×	384 1.3×	372 1.5×	55	1.8k
Ahmad Khan United States	10	710 0.7×	711 0.9×	302 0.9×	221 0.8×	255 1.0×	15	1.4k
Muhammad Mubeen Pakistan	23	418 0.4×	713 1.0×	393 1.1×	275 1.0×	361 1.4×	48	1.4k
Zhixiang Wu China	20	807 0.8×	692 0.9×	317 0.9×	159 0.6×	263 1.0×	88	1.5k
Yuanyuan Zhao China	26	1.1k 1.1×	1.2k 1.7×	528 1.5×	603 2.1×	221 0.9×	85	2.7k
Fangjie Mao China	26	760 0.8×	965 1.3×	508 1.5×	250 0.9×	380 1.5×	78	1.7k
Huaqiang Du China	33	1.2k 1.3×	1.6k 2.1×	864 2.5×	478 1.7×	701 2.7×	137	2.9k
Sajjad Hussain Pakistan	17	347 0.4×	540 0.7×	295 0.9×	236 0.8×	109 0.4×	42	985

Countries citing papers authored by Adam Oliphant

Since Specialization

Citations

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

Fields of papers citing papers by Adam Oliphant

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adam Oliphant

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Teluguntla, Pardhasaradhi, Adam Oliphant, Itiya Aneece, et al.. (2025). Landsat-Derived Rainfed and Irrigated-Area Product for Conterminous United States for the Year 2020 (LRIP30 CONUS 2020) Using Supervised and Unsupervised Machine Learning on the Cloud. Photogrammetric Engineering & Remote Sensing. 91(11). 703–714.

McCormick, Richard L., Prasad S. Thenkabail, Itiya Aneece, et al.. (2025). Artificial Neural Network Multi-layer Perceptron Models to Classify California's Crops using Harmonized Landsat Sentinel (HLS) Data. Photogrammetric Engineering & Remote Sensing. 91(2). 91–100. 2 indexed citations

Thenkabail, Prasad S., Pardhasaradhi Teluguntla, Adam Oliphant, Itiya Aneece, & Daniel J. Foley. (2024). Mapping the agricultural croplands of the world using Petabyte-scale big-data analytics from Landsat 30m satellite sensor data, multiple machine learning algorithms, and Google Earth Engine (GEE) cloud computing. 11–11. 1 indexed citations

Aneece, Itiya, Prasad S. Thenkabail, Richard L. McCormick, et al.. (2024). Machine Learning and New-Generation Spaceborne Hyperspectral Data Advance Crop Type Mapping. Photogrammetric Engineering & Remote Sensing. 90(11). 687–698. 6 indexed citations

Oliphant, Adam, Prasad S. Thenkabail, Pardhasaradhi Teluguntla, et al.. (2024). Automated Cropland Fallow Algorithm (ACFA) for the Northern Great Plains of USA. International Journal of Digital Earth. 17(1). 3 indexed citations

Foley, Daniel J., Prasad S. Thenkabail, Adam Oliphant, Itiya Aneece, & Pardhasaradhi Teluguntla. (2023). Crop Water Productivity from Cloud-Based Landsat Helps Assess California’s Water Savings. Remote Sensing. 15(19). 4894–4894. 5 indexed citations

Aneece, Itiya, Daniel J. Foley, Prasad S. Thenkabail, Adam Oliphant, & Pardhasaradhi Teluguntla. (2022). New Generation Hyperspectral Data From DESIS Compared to High Spatial Resolution PlanetScope Data for Crop Type Classification. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 15. 7846–7858. 15 indexed citations

Thenkabail, Prasad S., Pardhasaradhi Teluguntla, Jun Xiong, et al.. (2021). 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. USGS professional paper. 50 indexed citations

Thenkabail, Prasad S., Itiya Aneece, Pardhasaradhi Teluguntla, & Adam Oliphant. (2021). Hyperspectral Narrowband Data Propel Gigantic Leap in the Earth Remote Sensing. Photogrammetric Engineering & Remote Sensing. 87(7). 461–467. 6 indexed citations

10.

Foley, Daniel J., Prasad S. Thenkabail, Itiya Aneece, Pardhasaradhi Teluguntla, & Adam Oliphant. (2019). A meta-analysis of global crop water productivity of three leading world crops (wheat, corn, and rice) in the irrigated areas over three decades. International Journal of Digital Earth. 13(8). 939–975. 64 indexed citations

11.

Gumma, Murali Krishna, Prasad S. Thenkabail, Pardhasaradhi Teluguntla, et al.. (2019). Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud. GIScience & Remote Sensing. 57(3). 302–322. 119 indexed citations

12.

Teluguntla, Pardhasaradhi, Prasad S. Thenkabail, Adam Oliphant, et al.. (2018). 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. ISPRS Journal of Photogrammetry and Remote Sensing. 144. 325–340. 424 indexed citations breakdown →

13.

Xiong, Jun, Prasad S. Thenkabail, James C. Tilton, et al.. (2017). 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. Remote Sensing. 9(10). 1065–1065. 312 indexed citations breakdown →

14.

Teluguntla, Pardhasaradhi, Prasad S. Thenkabail, Jun Xiong, et al.. (2017). Spectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series (2000–2015) data. International Journal of Digital Earth. 10(9). 944–977. 53 indexed citations

15.

Oliphant, Adam, Randolph H. Wynne, Carl E. Zipper, et al.. (2016). Autumn olive (Elaeagnus umbellata) presence and proliferation on former surface coal mines in Eastern USA. Biological Invasions. 19(1). 179–195. 25 indexed citations

16.

Li, Jing, et al.. (2015). Character analysis of mining disturbance and reclamation trajectory in surface coal-mine area by time-series NDVI.. Nongye gongcheng xuebao. 31(16). 251–257. 11 indexed citations

17.

Li, Jing, Carl E. Zipper, P Donovan, Randolph H. Wynne, & Adam Oliphant. (2015). Reconstructing disturbance history for an intensively mined region by time-series analysis of Landsat imagery. Environmental Monitoring and Assessment. 187(9). 557–557. 51 indexed citations

18.

Wang, Zhaofeng, Hao Chen, Adam Oliphant, et al.. (2014). Synthesis and colour prediction of stable pigments from rice husk biomass. Green Materials. 3(1). 10–14. 18 indexed citations

19.

Oliphant, Adam, Jun Li, Randolph H. Wynne, P Donovan, & Carl E. Zipper. (2014). Identifying woody vegetation on coal surface mines using phenological indicators with multitemporal Landsat imagery. SHILAP Revista de lepidopterología. XL-1. 339–345. 4 indexed citations

20.

Chen, Hao, Weixing Wang, Jarett C. Martin, et al.. (2012). Extraction of Lignocellulose and Synthesis of Porous Silica Nanoparticles from Rice Husks: A Comprehensive Utilization of Rice Husk Biomass. ACS Sustainable Chemistry & Engineering. 1(2). 254–259. 155 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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