Ranjay Shrestha

2.0k total citations · 1 hit paper
38 papers, 1.4k citations indexed

About

Ranjay Shrestha is a scholar working on Global and Planetary Change, Environmental Engineering and Atmospheric Science. According to data from OpenAlex, Ranjay Shrestha has authored 38 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Global and Planetary Change, 18 papers in Environmental Engineering and 16 papers in Atmospheric Science. Recurrent topics in Ranjay Shrestha's work include Remote Sensing in Agriculture (13 papers), Remote Sensing and LiDAR Applications (8 papers) and Flood Risk Assessment and Management (8 papers). Ranjay Shrestha is often cited by papers focused on Remote Sensing in Agriculture (13 papers), Remote Sensing and LiDAR Applications (8 papers) and Flood Risk Assessment and Management (8 papers). Ranjay Shrestha collaborates with scholars based in United States, China and South Sudan. Ranjay Shrestha's co-authors include Miguel O. Román, Zhuosen Wang, Liping Di, Genong Yu, Steven D. Miller, Andrew Molthan, Lingjun Kang, Andreas Jechow, Xi Li and Christopher C. M. Kyba and has published in prestigious journals such as PLoS ONE, Remote Sensing of Environment and Remote Sensing.

In The Last Decade

Ranjay Shrestha

36 papers receiving 1.4k citations

Hit Papers

Remote sensing of night lights: A review and an outlook f... 2019 2026 2021 2023 2019 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ranjay Shrestha United States 16 1.0k 380 342 249 199 38 1.4k
Qiming Zheng China 23 1.1k 1.1× 289 0.8× 368 1.1× 142 0.6× 262 1.3× 49 1.5k
Julian Zeidler Germany 15 632 0.6× 348 0.9× 440 1.3× 218 0.9× 144 0.7× 39 1.2k
Wieke Heldens Germany 16 720 0.7× 282 0.7× 474 1.4× 350 1.4× 160 0.8× 46 1.5k
Yuehong Chen China 24 456 0.4× 437 1.1× 324 0.9× 313 1.3× 209 1.1× 74 1.5k
Christopher D. Lippitt United States 19 1.1k 1.0× 476 1.3× 376 1.1× 228 0.9× 64 0.3× 56 1.8k
Yanhua Xie United States 20 936 0.9× 419 1.1× 483 1.4× 270 1.1× 178 0.9× 43 1.4k
Md. Shahinoor Rahman United States 22 1.1k 1.1× 394 1.0× 792 2.3× 449 1.8× 51 0.3× 51 1.8k
Qiangzi Li China 24 690 0.7× 905 2.4× 404 1.2× 425 1.7× 115 0.6× 97 1.6k
Cláudia Maria de Almeida Brazil 17 885 0.8× 625 1.6× 454 1.3× 251 1.0× 67 0.3× 87 1.6k
Hasi Bagan Japan 16 633 0.6× 292 0.8× 280 0.8× 274 1.1× 97 0.5× 51 1.0k

Countries citing papers authored by Ranjay Shrestha

Since Specialization
Citations

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

Fields of papers citing papers by Ranjay Shrestha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ranjay Shrestha

This figure shows the co-authorship network connecting the top 25 collaborators of Ranjay Shrestha. A scholar is included among the top collaborators of Ranjay Shrestha 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 Ranjay Shrestha. Ranjay Shrestha 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.
Slayback, D. A., Sadashiva Devadiga, Albert J. Kettner, Ranjay Shrestha, & D. K. Davies. (2023). NASA's Updated Near Real-Time Global Flood Product. 1432–1435. 1 indexed citations
2.
Wang, Zhuosen, Ranjay Shrestha, Miguel O. Román, & Virginia Kalb. (2022). NASA’s Black Marble Multiangle Nighttime Lights Temporal Composites. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 29 indexed citations
3.
Román, Miguel O., Eleanor C. Stokes, Ranjay Shrestha, et al.. (2019). Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PLoS ONE. 14(6). e0218883–e0218883. 159 indexed citations
4.
Wang, Zhuosen, Miguel O. Román, Virginia Kalb, Ranjay Shrestha, & Eleanor C. Stokes. (2019). Evaluation of Lunar BRDF Correction for the Retrieval of Daily Viirs Black Marble Nighttime Lights. 8519–8521.
5.
Shrestha, Ranjay, et al.. (2017). Regression model to estimate flood impact on corn yield using MODIS NDVI and USDA cropland data layer. Journal of Integrative Agriculture. 16(2). 398–407. 96 indexed citations
6.
Shrestha, Ranjay, Liping Di, Genong Yu, et al.. (2017). Crop Fraction Layer (CFL) datasets derived through MODIS and LandSat for the continental US from year 2000–2016. 1–7. 5 indexed citations
7.
Di, Liping, Genong Yu, Lingjun Kang, Ranjay Shrestha, & Yuqi Bai. (2017). RF-CLASS: A remote-sensing-based flood crop loss assessment cyber-service system for supporting crop statistics and insurance decision-making. Journal of Integrative Agriculture. 16(2). 408–423. 41 indexed citations
8.
Kang, Lingjun, Liping Di, Genong Yu, et al.. (2016). Study of the vegetation index-meteorological factor correlation adjusted by accumulated growing degree days. 19. 1–6. 2 indexed citations
9.
Shrestha, Ranjay, Liping Di, Genong Yu, et al.. (2016). Regression based corn yield assessment using MODIS based daily NDVI in Iowa state. 1–5. 20 indexed citations
10.
Lin, Li, Liping Di, Genong Yu, et al.. (2016). A review of remote sensing in flood assessment. 1–4. 57 indexed citations
11.
Yu, Genong, Liping Di, Lingjun Kang, et al.. (2016). Online parameterization for WOFOST for United States using open geospatial standards. 1–6. 1 indexed citations
12.
Yang, Zhengwei, Lei Hu, Genong Yu, et al.. (2016). Web service-based SMAP soil moisture data visualization, dissemination and analytics based on vegscape framwork. 3624–3627. 6 indexed citations
13.
Guo, Zhe, et al.. (2015). Land cover classification and change detection analysis using LandSat series and geospatial datasets in Nepal from 1980 to 2010. IFPRI E-brary (International Food Policy Research Institute). 414–418. 8 indexed citations
14.
Shrestha, Ranjay & Liping Di. (2013). Land/water detection and delineation with Landsat data using Matlab/ENVI. 211–214. 6 indexed citations
15.
Shrestha, Ranjay, et al.. (2013). Detection of flood and its impact on crops using NDVI - Corn case. 200–204. 28 indexed citations
16.
Yu, Genong, Liping Di, Bei Zhang, et al.. (2013). Remote-sensing-based flood damage estimation using crop condition profiles. 205–210. 17 indexed citations
17.
Kang, Lingjun, et al.. (2013). Study of the NDVI-precipitation correlation stratified by crop type and soil permeability. 194–199. 8 indexed citations
18.
Shrestha, Ranjay, Ron Mahabir, & Liping Di. (2013). Healthy food accessibility and obesity: Case study of Pennsylvania, USA. i and ii. 329–333. 4 indexed citations
19.
Bai, Yuqi, Liping Di, Aijun Chen, et al.. (2012). GEOSS Component and Service Registry: Design, Implementation and Lessons Learned. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 5(6). 1678–1686. 16 indexed citations
20.
Di, Luigi, et al.. (2011). The GEOSS Component and Service Registry. AGU Fall Meeting Abstracts. 2011. 1 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026