diff --git a/README.md b/README.md new file mode 100644 index 0000000000..337acb13b5 --- /dev/null +++ b/README.md @@ -0,0 +1 @@ +Source code for personal website at https://guiming.github.io/. diff --git a/articles/2013 - Acta Ecologica Sinica - Mapping wildlife habitat suitability using kernel density estimation.pdf b/articles/2013 - Acta Ecologica Sinica - Mapping wildlife habitat suitability using kernel density estimation.pdf new file mode 100644 index 0000000000..2410216132 Binary files /dev/null and b/articles/2013 - Acta Ecologica Sinica - Mapping wildlife habitat suitability using kernel density estimation.pdf differ diff --git a/articles/2015 - IJGIS - A citizen data-based predictive mapping approach.pdf b/articles/2015 - IJGIS - A citizen data-based predictive mapping approach.pdf new file mode 100644 index 0000000000..070d017f75 Binary files /dev/null and b/articles/2015 - IJGIS - A citizen data-based predictive mapping approach.pdf differ diff --git a/articles/2015 - JAG - Unification of soil feedback patterns.pdf b/articles/2015 - JAG - Unification of soil feedback patterns.pdf new file mode 100644 index 0000000000..6bee1cab51 Binary files /dev/null and b/articles/2015 - JAG - Unification of soil feedback patterns.pdf differ diff --git a/articles/2015 - RemoteSensing - Data-Gap Filling to Understand the Dynamic Feedback Pattern of Soil.pdf b/articles/2015 - RemoteSensing - Data-Gap Filling to Understand the Dynamic Feedback Pattern of Soil.pdf new file mode 100644 index 0000000000..5c7fc69473 Binary files /dev/null and b/articles/2015 - RemoteSensing - Data-Gap Filling to Understand the Dynamic Feedback Pattern of Soil.pdf differ diff --git a/articles/2016 - Geoderma - CyberSoLIM - A cyber platform for digital soil mapping.pdf b/articles/2016 - Geoderma - CyberSoLIM - A cyber platform for digital soil mapping.pdf new file mode 100644 index 0000000000..7077bd2d48 Binary files /dev/null and b/articles/2016 - Geoderma - CyberSoLIM - A cyber platform for digital soil mapping.pdf differ diff --git a/articles/2016 - IJGIS - Parallel Ripley s K function cloud computing.pdf b/articles/2016 - IJGIS - Parallel Ripley s K function cloud computing.pdf new file mode 100644 index 0000000000..9bcf7fcf22 Binary files /dev/null and b/articles/2016 - IJGIS - Parallel Ripley s K function cloud computing.pdf differ diff --git a/articles/2017 - CEUS - A cloud-enabled automatic disaster analysis system of multi-sourced data streams.pdf b/articles/2017 - CEUS - A cloud-enabled automatic disaster analysis system of multi-sourced data streams.pdf new file mode 100644 index 0000000000..837d122805 Binary files /dev/null and b/articles/2017 - CEUS - A cloud-enabled automatic disaster analysis system of multi-sourced data streams.pdf differ diff --git a/articles/2017 - IJGIS - GPU Kernel Density Estimation.pdf b/articles/2017 - IJGIS - GPU Kernel Density Estimation.pdf new file mode 100644 index 0000000000..c595e19559 Binary files /dev/null and b/articles/2017 - IJGIS - GPU Kernel Density Estimation.pdf differ diff --git a/articles/2018 - AGIS - The representativeness and spatial bias of VGI review.pdf b/articles/2018 - AGIS - The representativeness and spatial bias of VGI review.pdf new file mode 100644 index 0000000000..c59a13e658 Binary files /dev/null and b/articles/2018 - AGIS - The representativeness and spatial bias of VGI review.pdf differ diff --git a/articles/2018 - ECOIND - Modelling species habitat suitability from presence-only data using KDE.pdf b/articles/2018 - ECOIND - Modelling species habitat suitability from presence-only data using KDE.pdf new file mode 100644 index 0000000000..511569f1a4 Binary files /dev/null and b/articles/2018 - ECOIND - Modelling species habitat suitability from presence-only data using KDE.pdf differ diff --git a/articles/2018 - PG - Global Madison mobile app design.pdf b/articles/2018 - PG - Global Madison mobile app design.pdf new file mode 100644 index 0000000000..ff13ca1220 Binary files /dev/null and b/articles/2018 - PG - Global Madison mobile app design.pdf differ diff --git a/articles/2018 - TGIS - A heuristic-based approach for mitigating positional errors in patrol data for SDM.pdf b/articles/2018 - TGIS - A heuristic-based approach for mitigating positional errors in patrol data for SDM.pdf new file mode 100644 index 0000000000..8a2531609c Binary files /dev/null and b/articles/2018 - TGIS - A heuristic-based approach for mitigating positional errors in patrol data for SDM.pdf differ diff --git a/articles/2018 - TGIS - Validity of historical VGI-Supporting Information.pdf b/articles/2018 - TGIS - Validity of historical VGI-Supporting Information.pdf new file mode 100644 index 0000000000..0feea83281 Binary files /dev/null and b/articles/2018 - TGIS - Validity of historical VGI-Supporting Information.pdf differ diff --git a/articles/2018 - TGIS - Validity of historical VGI.pdf b/articles/2018 - TGIS - Validity of historical VGI.pdf new file mode 100644 index 0000000000..81932f8fed Binary files /dev/null and b/articles/2018 - TGIS - Validity of historical VGI.pdf differ diff --git a/articles/2019 - BDE - Enhancing VGI application semantics by accounting for spatial bias.pdf b/articles/2019 - BDE - Enhancing VGI application semantics by accounting for spatial bias.pdf new file mode 100644 index 0000000000..7cc7713b7f Binary files /dev/null and b/articles/2019 - BDE - Enhancing VGI application semantics by accounting for spatial bias.pdf differ diff --git a/articles/2019 - GEODERMA - Mitigating spatial bias in existing soil samples for DSM.pdf b/articles/2019 - GEODERMA - Mitigating spatial bias in existing soil samples for DSM.pdf new file mode 100644 index 0000000000..6b76359077 Binary files /dev/null and b/articles/2019 - GEODERMA - Mitigating spatial bias in existing soil samples for DSM.pdf differ diff --git a/articles/2019 - IJGIS - A representativeness directed approach to mitigate spatial bias in VGI.pdf b/articles/2019 - IJGIS - A representativeness directed approach to mitigate spatial bias in VGI.pdf new file mode 100644 index 0000000000..2615b13efb Binary files /dev/null and b/articles/2019 - IJGIS - A representativeness directed approach to mitigate spatial bias in VGI.pdf differ diff --git a/articles/2019 - WPM - Integrating Citizen Science and GIS for Wildlife Habitat Assessment.pdf b/articles/2019 - WPM - Integrating Citizen Science and GIS for Wildlife Habitat Assessment.pdf new file mode 100644 index 0000000000..76d51bffb5 Binary files /dev/null and b/articles/2019 - WPM - Integrating Citizen Science and GIS for Wildlife Habitat Assessment.pdf differ diff --git a/articles/2020 - ECOIND - Data Integration for Habitat Mapping.pdf b/articles/2020 - ECOIND - Data Integration for Habitat Mapping.pdf new file mode 100644 index 0000000000..979b93309e Binary files /dev/null and b/articles/2020 - ECOIND - Data Integration for Habitat Mapping.pdf differ diff --git a/articles/2020 - IJGI - Spatiotemporal Patterns in Volunteer Data Contribution Activities - eBird.pdf b/articles/2020 - IJGI - Spatiotemporal Patterns in Volunteer Data Contribution Activities - eBird.pdf new file mode 100644 index 0000000000..43ca118587 Binary files /dev/null and b/articles/2020 - IJGI - Spatiotemporal Patterns in Volunteer Data Contribution Activities - eBird.pdf differ diff --git a/articles/2020 - TGIS - Sample size and spatial configuration affect effectiveness of spatial bias mitigation.pdf b/articles/2020 - TGIS - Sample size and spatial configuration affect effectiveness of spatial bias mitigation.pdf new file mode 100644 index 0000000000..2fd716050d Binary files /dev/null and b/articles/2020 - TGIS - Sample size and spatial configuration affect effectiveness of spatial bias mitigation.pdf differ diff --git a/articles/2021 - GISTBoK - Volunteered Geographic Information.pdf b/articles/2021 - GISTBoK - Volunteered Geographic Information.pdf new file mode 100644 index 0000000000..ff77e9bce4 Binary files /dev/null and b/articles/2021 - GISTBoK - Volunteered Geographic Information.pdf differ diff --git a/articles/2021 - TGIS - PyCLiPSM.pdf b/articles/2021 - TGIS - PyCLiPSM.pdf new file mode 100644 index 0000000000..52a840ab66 Binary files /dev/null and b/articles/2021 - TGIS - PyCLiPSM.pdf differ diff --git "a/articles/2022 - TGIS - PyCLKDE A big data\342\200\220enabled high\342\200\220performance computational framework for species.pdf" "b/articles/2022 - TGIS - PyCLKDE A big data\342\200\220enabled high\342\200\220performance computational framework for species.pdf" new file mode 100644 index 0000000000..2bc00c64ef Binary files /dev/null and "b/articles/2022 - TGIS - PyCLKDE A big data\342\200\220enabled high\342\200\220performance computational framework for species.pdf" differ diff --git a/articles/2022-NewThinkingGIScience-MitigatingSpatialBiasinVGI.pdf b/articles/2022-NewThinkingGIScience-MitigatingSpatialBiasinVGI.pdf new file mode 100644 index 0000000000..37a3a20c8e Binary files /dev/null and b/articles/2022-NewThinkingGIScience-MitigatingSpatialBiasinVGI.pdf differ diff --git a/articles/2024 - CaGIS - A web-based geovisualization framework for exploratory analysis of individual VGI contributor s participation characteristics.pdf b/articles/2024 - CaGIS - A web-based geovisualization framework for exploratory analysis of individual VGI contributor s participation characteristics.pdf new file mode 100644 index 0000000000..e25aaeb827 Binary files /dev/null and b/articles/2024 - CaGIS - A web-based geovisualization framework for exploratory analysis of individual VGI contributor s participation characteristics.pdf differ diff --git a/assets/img/profile.jpg b/assets/img/profile.jpg index 78f0f8b307..6fac98d1fe 100644 Binary files a/assets/img/profile.jpg and b/assets/img/profile.jpg differ diff --git a/index.html b/index.html index b055998f71..0b5730b43f 100644 --- a/index.html +++ b/index.html @@ -1,225 +1,1098 @@ - - - - - - - - Resume - Start Bootstrap Theme - - - - - - - - - - - - - -
- -
-
-

- Clarence - Taylor -

-
- 3542 Berry Street · Cheyenne Wells, CO 80810 · (317) 585-8468 · - name@email.com -
-

I am experienced in leveraging agile frameworks to provide a robust synopsis for high level overviews. Iterative approaches to corporate strategy foster collaborative thinking to further the overall value proposition.

- -
-
-
- -
-
-

Experience

-
-
-

Senior Web Developer

-
Intelitec Solutions
-

Bring to the table win-win survival strategies to ensure proactive domination. At the end of the day, going forward, a new normal that has evolved from generation X is on the runway heading towards a streamlined cloud solution. User generated content in real-time will have multiple touchpoints for offshoring.

-
-
March 2013 - Present
-
-
-
-

Web Developer

-
Intelitec Solutions
-

Capitalize on low hanging fruit to identify a ballpark value added activity to beta test. Override the digital divide with additional clickthroughs from DevOps. Nanotechnology immersion along the information highway will close the loop on focusing solely on the bottom line.

-
-
December 2011 - March 2013
-
-
-
-

Junior Web Designer

-
Shout! Media Productions
-

Podcasting operational change management inside of workflows to establish a framework. Taking seamless key performance indicators offline to maximise the long tail. Keeping your eye on the ball while performing a deep dive on the start-up mentality to derive convergence on cross-platform integration.

-
-
July 2010 - December 2011
-
-
-
-

Web Design Intern

-
Shout! Media Productions
-

Collaboratively administrate empowered markets via plug-and-play networks. Dynamically procrastinate B2C users after installed base benefits. Dramatically visualize customer directed convergence without revolutionary ROI.

-
-
September 2008 - June 2010
-
-
-
-
- -
-
-

Education

-
-
-

University of Colorado Boulder

-
Bachelor of Science
-
Computer Science - Web Development Track
-

GPA: 3.23

-
-
August 2006 - May 2010
-
-
-
-

James Buchanan High School

-
Technology Magnet Program
-

GPA: 3.56

-
-
August 2002 - May 2006
-
-
-
-
- -
-
-

Skills

-
Programming Languages & Tools
-
    -
    • -
    • -
    • -
    • -
    • -
    • -
    • -
    • -
    • -
    • -
    • -
    • -
-
Workflow
-
    -
  • - - Mobile-First, Responsive Design -
    • -
  • - - Cross Browser Testing & Debugging -
    • -
  • - - Cross Functional Teams -
    • -
  • - - Agile Development & Scrum -
    • -
-
-
-
- -
-
-

Interests

-

Apart from being a web developer, I enjoy most of my time being outdoors. In the winter, I am an avid skier and novice ice climber. During the warmer months here in Colorado, I enjoy mountain biking, free climbing, and kayaking.

-

When forced indoors, I follow a number of sci-fi and fantasy genre movies and television shows, I am an aspiring chef, and I spend a large amount of my free time exploring the latest technology advancements in the front-end web development world.

-
-
-
- -
-
-

Awards & Certifications

-
    -
  • - - Google Analytics Certified Developer -
    • -
  • - - Mobile Web Specialist - Google Certification -
    • -
  • - - 1 - st - Place - University of Colorado Boulder - Emerging Tech Competition 2009 -
    • -
  • - - 1 - st - Place - University of Colorado Boulder - Adobe Creative Jam 2008 (UI Design Category) -
    • -
  • - - 2 - nd - Place - University of Colorado Boulder - Emerging Tech Competition 2008 -
    • -
  • - - 1 - st - Place - James Buchanan High School - Hackathon 2006 -
    • -
  • - - 3 - rd - Place - James Buchanan High School - Hackathon 2005 -
    • -
-
-
-
- - - - - - + + + + + + + + Guiming Zhang, Ph.D. + + + + + + + + + + + + + +
+ +
+
+

+ Guiming + Zhang +

+
+ 5050 E. Iliff Avenue, Boettcher West #240 · Denver, CO 80208 · (303) 871-7908 · + guiming.zhang@du.edu +
+

I am an Associate Professor of GIScience in the Department of Geography & the Environment at the University of Denver, USA. My research interests are GIScience, volunteered geographic information (VGI), geospatial big data analytics, geovisualization/geovisual analytics and high-performance geocomputation, and their applications in environmental modeling and mapping (species distribution modeling, habitat suitability mapping, digital soil mapping, etc.).

+ + + +
+
+
+ + +
+
+

Appointments

+ +
+
+

University of Denver

+
Department of Geography & the Environment
+
+
Associate Professor | Assistant Professor
+
+
+
+

University of Wisconsin-Madison

+
Department of Geography
+
+
Lecturer | Graduate Teaching Assistant
+
+
+
+
+ + +
+
+

Education

+
+
+

University of Wisconsin-Madison

+
Ph.D. Geography
+
+
+
+
+

University of Wisconsin-Madison

+
M.S. Computer Sciences
+
+
+
+
+

Beijing Normal University

+
M.S. Geographic Information Science
+
+
+
+
+

Beijing Normal University

+
B.S. Geographic Information Systems
+
+
+
+
+
+ +
+
+

RESEARCH AREAS

+
+ +

I am particularly interested in volunteered geographic information (VGI) and other types of geospatial big data, and their applications in environmental modeling and mapping. I am also interested in geocomputation as an enabler of such endeavors. My research at these fronts has led to quality publications in top GIScience journals including the International Journal of Geographical Information Science and Transactions in GIS. I was also invited to author the topic entry "Volunteered Geographic Information" in The Geographic Information Science & Technology Body of Knowledge compiled by The University Consortium for Geographic Information Science.

+ +

Volunteered Geographic Information

+

Data quality of VGI (and other geospatia big data) is under constant scrutiny as it is a fundamental issue to address when using such kinds of data in geographic research. My research specifically contributes to developing novel methodologies for tackling spatial sampling/observation bias in geospatial big data (one of the prominent data quality issues) to improve the quality of inferences made from them, with practical applications in environmental modeling and mapping (e.g., species distribution modeling and digital soil mapping).

+ +
[GVA/VGI 31]   Zhang G. (2024). A web-based geovisualization framework for exploratory analysis of individual VGI contributor’s participation characteristics. Cartography and Geographic Information Science, accepted. + [Web] + [PDF] + [Demo] + [Code] +
+ +
[VGI 30]   Huang X, Wang S, Yang D, Hu T, Chen M, Zhang M, Zhang G, Biljecki F, Lu T, Zou L, Wu C Y, Park Y M, Li X, Liu Y, Fan H, Mitchell J, Li Z and Hohl A. (2024). Crowdsourcing geospatial data for Earth and human observations: a review. Journal of Remote Sensing, Accepted. + [Web] + [PDF] +
+ +
[VGI/GVA 29]   Zhang G, Gong X and Zhu D. (2024). Geographic proximity and homophily effects drive social interactions within VGI communities: an example of iNaturalist. International Journal of Digital Earth, 17(1): 2297948. + [Web] + [PDF] +
+ +
[VGI/GVA 28]   Kottwitz M#, Zhang G* and Xu J. (2023). The time- and distance-decay effects of hurricane relevancy on social media: an empirical study of three hurricanes in the United States. Annals of GIS, 29(4): 469-484. + [Web] + [PDF] +
+ +
[VGI/GC/GVA 26]   Zhang G and Xu J. (2023). Multi-GPU-parallel and tile-based kernel density estimation for large-scale spatial point pattern analysis. ISPRS International Journal of Geo-Information, 12(2): 31. + [Web] + [PDF] + [Code] +
+ +
[VGI/EM 25]   Zhang G. (2022). Mitigating spatial bias in volunteered geographic information for spatial modeling and prediction." in: Li, B., Shi, X., Zhu, A.X., Wang, C., and Lin, H. (Eds.): New Thinking in GIScience. Springer Nature, Singapore.  + [Web] + [PDF] +
+ +
[VGI/GVA/GC 23]   Zhang G. (2022). Detecting and visualizing observation hot-spots in massive volunteer-contributed geographic data across spatial scales using GPU-accelerated kernel density estimation. ISPRS International Journal of Geo-Information, 11(1): 55. + [Web] + [PDF] + [Code] +
+ +
[VGI 21]   Zhang G. (2021). Volunteered Geographic Information. The Geographic Information Science & Technology Body of Knowledge (1st Quarter 2021 Edition), John P. Wilson (Ed.). doi: 10.22224/gistbok/2021.1.1. + [Web] +
+ +
[VGI/GVA 20]   Zhang G. (2020). Spatial and temporal patterns in volunteer data contribution activities: A case study of eBird. ISPRS International Journal of Geo-Information, 9(10): 597. + [Web] + [PDF] +
+ +
[VGI 19]   Zhang G, Zhu A. (2020). Sample size and spatial configuration of volunteered geographic information affect effectiveness of spatial bias mitigation. Transactions in GIS, 24(5): 1315–1340. + [Web] + [PDF] +
+ +
[VGI/EM 15]   Zhang G, Zhu A. (2019). A representativeness directed approach to spatial bias mitigation in VGI for predictive mapping. International Journal of Geographical Information Science, 33(9): 1873–1893. + [Web] + [PDF] +
+ +
[VGI 17]   Zhang G. (2019). Enhancing VGI application semantics by accounting for spatial bias. Big Earth Data, 3(3): 255-268. + [Web] + [PDF] +
+ +
[VGI/EM 14]   Zhang G. (2019). Integrating citizen science and GIS for wildlife population monitoring and habitat assessment." in: Ferretti, M. (Eds.): Wildlife Population Monitoring. IntechOpen Limited, London, UK.  + [Web] + [PDF] +
+ +
[VGI 13]   Zhang G, Zhu A. (2018). The representativeness and spatial bias of volunteered geographic information: a review. Annals of GIS, 24(3): 151–162. + [Web] + [PDF] +
+ +
[VGI 10]   Zhang G, Zhu A, Huang Z, Ren G, Qin C, Xiao W. (2018). Validity of historical volunteered geographic information: Evaluating citizen data for mapping historical geographic phenomena. Transactions in GIS, 22(1): 149–164. + [Web] + [PDF] +
+ +
[VGI/GC 8]   Huang Q, Cervone G, Zhang G. (2017). A cloud-enabled automatic disaster analysis system of multi-sourced data streams: An example synthesizing social media, remote sensing and Wikipedia data. Computers, Environment and Urban Systems, 66: 23-37. + [Web] + [PDF] +
+ +
[VGI/EM 2]   Zhu A, Zhang G*, Wang W, Xiao W, Huang Z, Dunzhu G, Ren G, Qin C, Yang L, Pei T, Yang S. (2015). A citizen data-based approach to predictive mapping of spatial variation of natural phenomena. International Journal of Geographical Information Science, 29(10): 1864–1886. + [Web] + [PDF] +
+ +

Geovisualization and Geovisual Analytics

+

Bias mitigation for VGI (and other geospatia big data) should be grounded in a sound understanding of the processes through which the data is generated. For instance, biases in VGI largely root from VGI contributors’ observation efforts. My research also employs geovisualization and geovisual analytics to examine the patterns (and drivers) of VGI contributors’ data contribution activities (including inter-contributor social interactions). Such endeavors help gain a deeper understanding of VGI data and its quality, which informs bias mitigation and proper use of VGI data.

+ +
[GVA/VGI 31]   Zhang G. (2024). A web-based geovisualization framework for exploratory analysis of individual VGI contributor’s participation characteristics. Cartography and Geographic Information Science, accepted. + [Web] + [PDF] + [Demo] + [Code] +
+ +
[VGI/GVA 29]   Zhang G, Gong X and Zhu D. (2024). Geographic proximity and homophily effects drive social interactions within VGI communities: an example of iNaturalist. International Journal of Digital Earth, 17(1): 2297948. + [Web] + [PDF] +
+ + +
[VGI/GVA 28]   Kottwitz M#, Zhang G* and Xu J. (2023). The time- and distance-decay effects of hurricane relevancy on social media: an empirical study of three hurricanes in the United States. Annals of GIS, 29(4): 469-484. + [Web] + [PDF] +
+ + +
[VGI/GC/GVA 26]   Zhang G and Xu J. (2023). Multi-GPU-parallel and tile-based kernel density estimation for large-scale spatial point pattern analysis. ISPRS International Journal of Geo-Information, 12(2): 31. + [Web] + [PDF] + [Code] +
+ +
[VGI/GVA/GC 23]   Zhang G. (2022). Detecting and visualizing observation hot-spots in massive volunteer-contributed geographic data across spatial scales using GPU-accelerated kernel density estimation. ISPRS International Journal of Geo-Information, 11(1): 55. + [Web] + [PDF] + [Code] +
+ + +
[VGI/GVA 20]   Zhang G. (2020). Spatial and temporal patterns in volunteer data contribution activities: A case study of eBird. ISPRS International Journal of Geo-Information, 9(10): 597. + [Web] + [PDF] +
+ +

Environmental Modeling

+

My research develops new methods and computational tools for enviornmental modeling (e.g., species distribution modeling and digital soil mapping). The developed methods and tools are capable of accounting for spatial sampling/observation bias and integrating multi-source data and can exploit heterogeneous computing resources for parallel computing to accelerate modeling involving geospatial big data.

+ +
[EM 27]   Luo W. and Zhang G. (2023). Advances and applications of geospatial modeling and analysis in digital twins. Frontiers in Earth Science, 11: 1226466. + [Web] + [PDF] +
+ +
[VGI/EM 25]   Zhang G. (2022). Mitigating spatial bias in volunteered geographic information for spatial modeling and prediction." in: Li, B., Shi, X., Zhu, A.X., Wang, C., and Lin, H. (Eds.): New Thinking in GIScience. Springer Nature, Singapore.  + [Web] + [PDF] +
+ +
[GC/EM 24]   Zhang G. (2022). PyCLKDE: A big data-enabled high-performance computational framework for species habitat suitability modeling and mapping. Transactions in GIS,  26(4): 1754-1774. + [Web] + [PDF] + [Code] +
+ +
[GC/EM 22]   Zhang G, Zhu, A, Liu J, Guo S, Zhu Y. (2021). PyCLiPSM: Harnessing heterogeneous computing resources on CPUs and GPUs for accelerated digital soil mapping. Transactions in GIS, 25(3): 1396-1418. + [Web] + [PDF] + [Code] +
+ +
[EM 18]   Zhang G, Zhu A, He Y, Huang Z, Ren G, Xiao W. (2020). Integrating multi-source data for wildlife habitat mapping: A case study of the black-and-white snub-nosed monkey (Rhinopithecus bieti) in Yunnan, China. Ecological Indicators, 118: 106735. + [Web] + [PDF] +
+ +
[EM 16]   Zhang G, Zhu A. (2019). A representativeness heuristic for mitigating spatial bias in existing soil samples for digital soil mapping. Geoderma, 351: 130–143. + [Web] + [PDF] +
+ +
[VGI/EM 15]   Zhang G, Zhu A. (2019). A representativeness directed approach to spatial bias mitigation in VGI for predictive mapping. International Journal of Geographical Information Science, 33(9): 1873–1893. + [Web] + [PDF] +
+ +
[VGI/EM 14]   Zhang G. (2019). Integrating citizen science and GIS for wildlife population monitoring and habitat assessment." in: Ferretti, M. (Eds.): Wildlife Population Monitoring. IntechOpen Limited, London, UK.  + [Web] + [PDF] +
+ +
[EM 12]   Zhang G, Zhu A, Windels S, Qin C. (2018). Modelling species habitat suitability from presence-only data using kernel density estimation. Ecological Indicators, 93: 387-396. + [Web] + [PDF] +
+ +
[EM 11]   Zhang G, Zhu A, Huang Z, Xiao W. (2018). A heuristic-basedapproach to mitigating positional errors in patrol data for species distribution modeling. Transactions in GIS, 22(1): 202-216. + [Web] + [PDF] +
+ +
[GC/EM 5]   Jiang J, Zhu A, Qin C, Zhu T, Liu J, Du F, Liu J, Zhang G, An Y. (2016). CyberSoLIM: A cyber platform for digital soil mapping. Geoderma, 263: 234-243. + [Web] + [PDF] +
+ +
[EM 4]   Guo S, Meng L, Zhu A, Burt J, Du F, Liu J, Zhang G. (2015).Unification of soil feedback patterns under different evaporation conditions to improve soil differentiation over flat area. International Journal of Applied Earth Observation and Geoinformation, 49: 126-137. + [Web] + [PDF] +
+ +
[EM 3]   Guo S, Meng L, Zhu A, Burt J, Du F, Liu J, Zhang G. (2015). Data-gap filling to understand the dynamic feedback pattern of soil.. Remote Sensing, 7: 11801–11820. + [Web] + [PDF] +
+ +
[EM 1]   张桂铭, 朱阿兴, 杨胜天, 秦承志, 肖文, Steve K. Windels. (2013). 基于核密度估计的动物生境适宜度制图方法. 生态学报, 33(23): 7590-7600. Zhang G, Zhu A, Yang S, Qin C, Xiao W, Windels S. (2013). Mapping wildlife habitat suitability using kernel density estimation. Acta Ecologica Sinica, + 33(23): 7590-7600.  + [Web] + [PDF]  +
+ +

Geo-computation

+

There is an increasing need to address computational challenges associated with geospatial big data analytics in order to keep pace with the ever-faster-growing big data volume and analytical complexity. Traditional spatial analysis tools often are unable to handle big geospatial data efficiently, and therefore computational challenges occur when applying these methods on geospatial big data. My research with this regard develops algorithmic optimizations for spatial analysis methods and utilizes cutting-edge computing technologies such as cloud computing and GPU (graphics processing units) computing to accelerate the algorithms to support geospatial big data analytics (i.e., spatial point pattern analysis of massive VGI data).

+ +
[VGI/GC/GVA 26]   Zhang G and Xu J. (2023). Multi-GPU-parallel and tile-based kernel density estimation for large-scale spatial point pattern analysis. ISPRS International Journal of Geo-Information, 12(2): 31. + [Web] + [PDF] + [Code] +
+ +
[GC/EM 24]   Zhang G. (2022). PyCLKDE: A big data-enabled high-performance computational framework for species habitat suitability modeling and mapping. Transactions in GIS,  26(4): 1754-1774. + [Web] + [PDF] + [Code] +
+ +
[VGI/GVA/GC 23]   Zhang G. (2022). Detecting and visualizing observation hot-spots in massive volunteer-contributed geographic data across spatial scales using GPU-accelerated kernel density estimation. ISPRS International Journal of Geo-Information, 11(1): 55. + [Web] + [PDF] + [Code] +
+ +
[GC/EM 22]   Zhang G, Zhu, A, Liu J, Guo S, Zhu Y. (2021). PyCLiPSM: Harnessing heterogeneous computing resources on CPUs and GPUs for accelerated digital soil mapping. Transactions in GIS, 25(3): 1396-1418. + [Web] + [PDF] + [Code] +
+ +
[VGI/GC 8]   Huang Q, Cervone G, Zhang G. (2017). A cloud-enabled automatic disaster analysis system of multi-sourced data streams: An example synthesizing social media, remote sensing and Wikipedia data. Computers, Environment and Urban Systems, 66: 23-37. + [Web] + [PDF] +
+ +
[GC 7]   Zhang G, Zhu A, Huang Q. (2017). A GPU-accelerated adaptive kernel density estimation approach for efficient point pattern analysis on spatial big data. International Journal of Geographical Information Science, 31(10): 2068-2097. + [Web] + [PDF] + [Code] +
+ +
[GC 6]   Zhang G, Huang Q, Zhu A, Keel J. (2016). Enabling point pattern analysis on spatial big data using cloud computing: Optimizing and accelerating Ripley’s K function. International Journal of Geographical Information Science, 30(11): 2230–2252. + [Web] + [PDF] + [Code] +
+ +
[GC/EM 5]   Jiang J, Zhu A, Qin C, Zhu T, Liu J, Du F, Liu J, Zhang G, An Y. (2016). CyberSoLIM: A cyber platform for digital soil mapping. Geoderma, 263: 234-243. + [Web] + [PDF] +
+ +
+ +
+ +
+ +
+
+

Publications

+ +
+ [VGI] - Volunteered Geographic Information
+ [GVA] - Geovisualization and Geovisual Analytics
+ [EM] - Environmental Modeling
+ [GC] - GeoCompuation
+ [OT] - Other +
+ +
+
+

Refereed Journal Articles

+
* Corresponding Author  # Student Author
+
+ +
[GVA/VGI 31]   Zhang G. (2024). A web-based geovisualization framework for exploratory analysis of individual VGI contributor’s participation characteristics. Cartography and Geographic Information Science, accepted. + [Web] + [PDF] + [Demo] + [Code] +
+ +
[VGI 30]   Huang X, Wang S, Yang D, Hu T, Chen M, Zhang M, Zhang G, Biljecki F, Lu T, Zou L, Wu C Y, Park Y M, Li X, Liu Y, Fan H, Mitchell J, Li Z and Hohl A. (2024). Crowdsourcing geospatial data for Earth and human observations: a review. Journal of Remote Sensing, Accepted. + [Web] + [PDF] +
+ +
[VGI/GVA 29]   Zhang G, Gong X and Zhu D. (2024). Geographic proximity and homophily effects drive social interactions within VGI communities: an example of iNaturalist. International Journal of Digital Earth, 17(1): 2297948. + [Web] + [PDF] +
+ +
[VGI/GVA 28]   Kottwitz M#, Zhang G* and Xu J. (2023). The time- and distance-decay effects of hurricane relevancy on social media: an empirical study of three hurricanes in the United States. Annals of GIS, 29(4): 469-484. + [Web] + [PDF] +
+ +
[EM 27]   Luo W. and Zhang G. (2023). Advances and applications of geospatial modeling and analysis in digital twins. Frontiers in Eartch Science, 11: 1226466. + [Web] + [PDF] +
+ +
[VGI/GC/GVA 26]   Zhang G and Xu J. (2023). Multi-GPU-parallel and tile-based kernel density estimation for large-scale spatial point pattern analysis. ISPRS International Journal of Geo-Information, 12(2): 31. + [Web] + [PDF] + [Code] +
+ +
[GC/EM 24]   Zhang G. (2022). PyCLKDE: A big data-enabled high-performance computational framework for species habitat suitability modeling and mapping. Transactions in GIS,  26(4): 1754-1774. + [Web] + [PDF] + [Code] +
+ +
[VGI/GVA/GC 23]   Zhang G. (2022). Detecting and visualizing observation hot-spots in massive volunteer-contributed geographic data across spatial scales using GPU-accelerated kernel density estimation. ISPRS International Journal of Geo-Information, 11(1): 55. + [Web] + [PDF] + [Code] +
+ +
[GC/EM 22]   Zhang G, Zhu, A, Liu J, Guo S, Zhu Y. (2021). PyCLiPSM: Harnessing heterogeneous computing resources on CPUs and GPUs for accelerated digital soil mapping. Transactions in GIS, 25(3): 1396-1418. + [Web] + [PDF] + [Code] +
+ +
[VGI 21]   Zhang G. (2021). Volunteered Geographic Information. The Geographic Information Science & Technology Body of Knowledge (1st Quarter 2021 Edition): John P. Wilson (Ed.). doi: 10.22224/gistbok/2021.1.1. + [Web] +
+ +
[VGI/GVA 20]   Zhang G. (2020). Spatial and temporal patterns in volunteer data contribution activities: A case study of eBird. ISPRS International Journal of Geo-Information, 9(10): 597. + [Web] + [PDF] +
+ +
[VGI 19]   Zhang G, Zhu A. (2020). Sample size and spatial configuration of volunteered geographic information affect effectiveness of spatial bias mitigation. Transactions in GIS, 24(5): 1315–1340. + [Web] + [PDF] +
+ +
[EM 18]   Zhang G, Zhu A, He Y, Huang Z, Ren G, Xiao W. (2020). Integrating multi-source data for wildlife habitat mapping: A case study of the black-and-white snub-nosed monkey (Rhinopithecus bieti) in Yunnan, China. Ecological Indicators, 118: 106735. + [Web] + [PDF] +
+ +
[VGI 17]   Zhang G. (2019). Enhancing VGI application semantics by accounting for spatial bias. Big Earth Data, 3(3): 255-268. + [Web] + [PDF] +
+ +
[EM 16]   Zhang G, Zhu A. (2019). A representativeness heuristic for mitigating spatial bias in existing soil samples for digital soil mapping. Geoderma, 351: 130–143. + [Web] + [PDF] +
+ +
[VGI/EM 15]   Zhang G, Zhu A. (2019). A representativeness directed approach to spatial bias mitigation in VGI for predictive mapping. International Journal of Geographical Information Science, 33(9): 1873–1893. + [Web] + [PDF] +
+ +
[VGI 13]   Zhang G, Zhu A. (2018). The representativeness and spatial bias of volunteered geographic information: a review. Annals of GIS, 24(3): 151–162. + [Web] + [PDF] +
+ +
[EM 12]   Zhang G, Zhu A, Windels S, Qin C. (2018). Modelling species habitat suitability from presence-only data using kernel density estimation. Ecological Indicators, 93: 387-396. + [Web] + [PDF] +
+ +
[EM 11]   Zhang G, Zhu A, Huang Z, Xiao W. (2018). A heuristic-basedapproach to mitigating positional errors in patrol data for species distribution modeling. Transactions in GIS, 22(1): 202-216. + [Web] + [PDF] +
+ +
[VGI 10]   Zhang G, Zhu A, Huang Z, Ren G, Qin C, Xiao W. (2018). Validity of historical volunteered geographic information: Evaluating citizen data for mapping historical geographic phenomena. Transactions in GIS, 22(1): 149–164. + [Web] + [PDF] +
+ +
[OT 9]   Roth R, Young S, Nestel C, Sack C, Davidson B, Janicki J, Knoppe-Wetzel V, Ma F, Mead R, Rose C, Zhang G. (2018). Global landscapes: Teaching globalization through responsive mobile map design. The Professional Geographer, 70(3): 395-411. + [Web] + [PDF] +
+ +
[VGI/GC 8]   Huang Q, Cervone G, Zhang G. (2017). A cloud-enabled automatic disaster analysis system of multi-sourced data streams: An example synthesizing social media, remote sensing and Wikipedia data. Computers, Environment and Urban Systems, 66: 23-37. + [Web] + [PDF] +
+ +
[GC 7]   Zhang G, Zhu A, Huang Q. (2017). A GPU-accelerated adaptive kernel density estimation approach for efficient point pattern analysis on spatial big data. International Journal of Geographical Information Science, 31(10): 2068-2097. + [Web] + [PDF] + [Code] +
+ +
[GC 6]   Zhang G, Huang Q, Zhu A, Keel J. (2016). Enabling point pattern analysis on spatial big data using cloud computing: Optimizing and accelerating Ripley’s K function. International Journal of Geographical Information Science, 30(11): 2230–2252. + [Web] + [PDF] + [Code] +
+ +
[GC/EM 5]   Jiang J, Zhu A, Qin C, Zhu T, Liu J, Du F, Liu J, Zhang G, An Y. (2016). CyberSoLIM: A cyber platform for digital soil mapping. Geoderma, 263: 234-243. + [Web] + [PDF] +
+ +
[EM 4]   Guo S, Meng L, Zhu A, Burt J, Du F, Liu J, Zhang G. (2015). Unification of soil feedback patterns under different evaporation conditions to improve soil differentiation over flat area. International Journal of Applied Earth Observation and Geoinformation, 49: 126-137. + [Web] + [PDF] +
+ +
[EM 3]   Guo S, Meng L, Zhu A, Burt J, Du F, Liu J, Zhang G. (2015). Data-gap filling to understand the dynamic feedback pattern of soil.. Remote Sensing, 7: 11801–11820. + [Web] + [PDF] +
+ +
[VGI/EM 2]   Zhu A, Zhang G*, Wang W, Xiao W, Huang Z, Dunzhu G, Ren G, Qin C, Yang L, Pei T, Yang S. (2015). A citizen data-based approach to predictive mapping of spatial variation of natural phenomena. International Journal of Geographical Information Science, 29(10): 1864–1886. + [Web] + [PDF] +
+ +
[EM 1]   张桂铭, 朱阿兴, 杨胜天, 秦承志, 肖文, Steve K. Windels. (2013). 基于核密度估计的动物生境适宜度制图方法. 生态学报, 33(23): 7590-7600. Zhang G, Zhu A, Yang S, Qin C, Xiao W, Windels S. (2013). Mapping wildlife habitat suitability using kernel density estimation. Acta Ecologica Sinica, + 33(23): 7590-7600.  + [Web] + [PDF]  +
+ +
+
+
+ + + +
+
+

Refereed Book Chapters

+ +
[VGI/EM 25]   Zhang G. (2022). Mitigating spatial bias in volunteered geographic information for spatial modeling and prediction." in: Li, B., Shi, X., Zhu, A.X., Wang, C., and Lin, H. (Eds.): New Thinking in GIScience. Springer Nature, Singapore.  + [Web] + [PDF] +
+ +
[VGI/EM 14]   Zhang G. (2019). Integrating citizen science and GIS for wildlife population monitoring and habitat assessment." in: Ferretti, M. (Eds.): Wildlife Population Monitoring. IntechOpen Limited, London, UK.  + [Web] + [PDF] +
+
+
+ +
+
+

Dissertation

+
Zhang G. (2018). A Representativeness Directed Approach to Spatial Bias Mitigation in VGI for Predictive Mapping. The University of Wisconsin-Madison. [Web]
+
+
+
+
+ +
+ + +
+
+

Teaching

+ +
University of Denver
+
    +
  • + + GEOG 2000  Geographic Statistics +
    • + +
  • + + GEOG 2100  Introduction to Geographic Information Systems +
    • + +
  • + + GEOG 3120  Environmental GIS Modeling +
    • +
  • + + GEOG 3140  GIS Database Design +
    • +
+ +
University of Wisconsin-Madison
+
    +
  • + + Geography 377  An Introduction to Geographic Information System  
    • +
  • + + Geography 576 Geospatial Web and Mobile Programming [Online]
    • +
  • + + Geography 579  GIS and Spatial Analysis [Online]  
    • +
+ +
+
+ +
+ + +
+
+

Students

+
+
+ +

Doctoral

+
    +
  • + Jin Xu (advisor)    2021 – present +
    • +
+

Masters

+
    + +
  • + Oblanuju Emmanuel (advisor)    2023 – 2024 +
    • + +
  • + Mackenzie Kottwitz (advisor)    2020 – 2022 +
    • + +
  • + Alex Van De Water (thesis committee member)    2024 – present +
    • + +
  • + Elena Arroway (thesis committee member)    2023 – 2024 +
    • + +
  • + Erin Lammott (thesis committee member)    2023 – 2024 +
    • + +
  • + Joe Hiebert (independent study advisor, thesis committee member)    2021 – 2022 +
    • + +
  • + Jennifer Murdock (thesis committee member)    2020 – 2021 +
    • + +
  • + Matt Hugel (thesis committee member)    2019 – 2020 +
    • + +
  • + Sophie-Min Thomson (thesis committee member)    2019 – 2020 +
    • + +
  • + Hayley Miller (thesis committee member)    2019 – 2020 +
    • +
+ +

Undergraduate

+
    +
  • + Juanlin Liu (independent study advisor)    2022 +
    • +
  • + Chloe Pepke (honors thesis co-advisor)    2020 +
    • +
  • + Mark Ludke (independent study advisor)    2020 +
    • +
+ +
+
+
+ +
+ + +
+
+

Service

+
+
+

Professional Community

+
    + +
  • + + Committee Member. Research Committee: Initiative on CyberGIS and Decision Support Systems [Web]. University Consortium for Geographic Information Science (UCGIS) +    2021 - present
    • + + +
  • + + Chair. American Association of Geographers (AAG) Cyberinfrastructure Specialty Group (CISG) [Web] +    2022 – 2023
    • + +
  • + + Vice Chair. AAG CISG +    2021 – 2022
    • + +
  • + + Board of Director. AAG CISG +    2019 – 2021
    • + + +
  • + + Judge. The Jacques May Thesis Prize. AAG Health and Medical Geography Specialty Group +    2019
    • + +
    + + +
  • + + Co-Guest Editor. Special Issue: Advances and Applications of Geospatial Modeling and Analysis in Digital Twins [Web]. Frontiers in Earth Science +    2022 -
    • + +
  • + + Co-Guest Editor. Special Issue: Remote Sensing and GIS Technologies for Sustainable Ecosystem Management [Web]. Remote Sensing +    2022 -
    • + +
  • + + Guest Editor. Special Issue: Mapping, Modeling and Prediction with VGI [Web]. ISPRS International Journal of Geo-Information +    2020 - 2021
    • + +
  • + + Guest Editor. Special Issue: Geospatial Semantic, Ontology and Knowledge Graph [Web]. Big Earth Data +    2019
    • +
  • + + Reviewer Board. Remote Sensing Journal [Web] +    2019 – present
    • +
+ +

Conference Organization

+
    +
  • + + Paper Session Organizer/Chair: 2022 CISG Robert Raskin Student Competition. 2022 AAG Annual Meeting, New York City, NY +    Feb 25 - Mar 1, 2022
    • + +
  • + + Paper Session Organizer: Symposium on Data-Intensive Geospatial Understanding in the Era of AI and CyberGIS: UCGIS GeoAI & CyberGIS Research Initiative - GeoAI and CyberGIS for Advancing Spatial Decision Making. 2022 AAG Annual Meeting, New York City, NY +    Feb 25 - Mar 1, 2022
    • + +
  • + + Organizing Committee Member: The 8th Symposium on Human Dynamics Research. 2022 AAG Annual Meeting, New York City, NY +    Feb 25 - Mar 1, 2022
    • +
  • + + Paper Session (Virtual) Organizer/Chair: Symposium on Human Dynamics Research: Mining Human Dynamics with Big Data. 2022 AAG Annual Meeting, New York City, NY +    Feb 25 - Mar 1, 2022
    • +
  • + + Organizing Committee Member: The 7th Symposium on Human Dynamics Research. 2021 AAG Annual Meeting, Seattle, WA +    Apr 7 - 11, 2021
    • +
  • + + Paper Session (Virtual) Organizer/Chair: Symposium on Human Dynamics Research: Mapping, Modeling and Prediction with VGI. 2021 AAG Annual Meeting, Seattle, WA +    Apr 7 - 11, 2021
    • + +
  • + + Paper Session Organizer/Chair: Mapping, Modeling and Prediction with VGI. 2020 AAG Annual Meeting, Denver, CO +    Apr 6-10, 2020 [Cancelled due to COVID-19]
    • + +
+ +

Journal Reviewer

+ +
    +
  • + 10+    + 5+    + 2+    +
    • +
+ +
    + +
  • Annals of GIS
    • + +
  • + + Applied Sciences
    • + +
  • + + Arabian Journal of Geosciences
    • + +
  • Big Earth Data
    • + +
  • Big Data and Cognitive Computing
    • + +
  • Computers & Geosciences
    • + +
  • Data
    • + +
  • + + Diversity and Distributions
    • +
  • + + Earth Science Informatics
    • + +
  • + Geocarto International
    • + +
  • + + Geo-Spatial Information Science
    • + +
  • Natural Hazards
    • + +
  • + + IEEE Access
    • + +
  • + Information
    • + +
  • + + ISPRS International Journal of Geo-Information
    • + +
  • + + International Journal of Environmental Research and Public Health
    • + +
  • + + International Journal of Geographical Information Science
    • + +
  • + International Journal of Image and Data Fusion
    • + +
  • + + ISPRS International Journal of Geo-Information
    • + +
  • + Journal of Maps
    • + +
  • + Journal of the Royal Statistical Society: Series C (Applied Statistics)
    • + +
  • + Pedosphere
    • + +
  • + + Plos One
    • + +
  • + + Remote Sensing
    • + +
  • + + Scientific Reports
    • + +
  • + Sensors
    • + +
  • + Social Sciences
    • + +
  • + + Sustainability
    • + +
  • + + Scientific Reports
    • + +
  • + + The Professional Geographer
    • + +
  • + The 2nd International Conference on Physics, Mathematics and Statistics
    • + +
  • + + Transactions in GIS
    • +
+
+
+
+
+ +
+ + +
+
+

Awards & Honors

+ +
+
+ + + + + + +