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.
Urban heat island impacts on building energy consumption: A review of approaches and findings
2019509 citationsYuyu Zhou, Gensuo Jia et al.profile →
Monitoring meteorological drought in semiarid regions using multi-sensor microwave remote sensing data
2013397 citationsAnzhi Zhang, Gensuo JiaRemote Sensing of Environmentprofile →
Climate change reduces extent of temperate drylands and intensifies drought in deep soils
This map shows the geographic impact of Gensuo Jia'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 Gensuo Jia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gensuo Jia more than expected).
This network shows the impact of papers produced by Gensuo Jia. 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 Gensuo Jia. The network helps show where Gensuo Jia may publish in the future.
Co-authorship network of co-authors of Gensuo Jia
This figure shows the co-authorship network connecting the top 25 collaborators of Gensuo Jia.
A scholar is included among the top collaborators of Gensuo Jia 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 Gensuo Jia. Gensuo Jia is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Wang, Jun, Jinming Feng, Zhongwei Yan, Yonghong Hu, & Gensuo Jia. (2013). Nested High Resolution Modeling of the Impact of Urbanization on Regional Climate in Three Vast Urban Agglomerations in China. EGUGA.2 indexed citations
Zhang, Anzhi & Gensuo Jia. (2013). Monitoring meteorological drought in semiarid regions using multi-sensor microwave remote sensing data. Remote Sensing of Environment. 134. 12–23.397 indexed citations breakdown →
14.
Jia, Gensuo. (2011). Spatial pattern of forest ages in China retrieved from national-level inventory and remote sensing imageries. Geographical Research.17 indexed citations
15.
Jia, Gensuo. (2009). Changes in carbon budget of Northeast China forest ecosystems under future climatic scenario. Shengtaixue zazhi.8 indexed citations
Zhao, Junfang, Xiaodong Yan, & Gensuo Jia. (2009). [Simulation of carbon stocks of forest ecosystems in Northeast China from 1981 to 2002].. PubMed. 20(2). 241–9.8 indexed citations
18.
Epstein, Howard E., D. A. Walker, M. K. Raynolds, et al.. (2009). Vegetation biomass, leaf area index, and NDVI patterns and relationships along two latitudinal transects in arctic tundra. AGU Fall Meeting Abstracts. 2009.3 indexed citations
19.
Tàbara, J. David, Xingang Dai, Zsuzsanna Flachner, et al.. (2008). Appraising long-term regional climate policies in Inner Mongolia, the Tisza floodplain and the Guadiana river basin. Socio-Environmental Systems Modeling.1 indexed citations
20.
Walker, D. A., Gensuo Jia, Howard E. Epstein, et al.. (2002). Vegetation-Soil-Active Layer Relationships Along a Low-Arctic Bioclimate Gradient, Alaska. AGUFM. 2002.3 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.