{"id":94,"date":"2023-06-30T15:35:14","date_gmt":"2023-06-30T19:35:14","guid":{"rendered":"https:\/\/sites.usnh.edu\/basal-lab\/?page_id=94"},"modified":"2024-01-12T11:09:04","modified_gmt":"2024-01-12T16:09:04","slug":"dr-jianyu-gu","status":"publish","type":"page","link":"https:\/\/sites.usnh.edu\/basal-lab\/past-members\/dr-jianyu-gu\/","title":{"rendered":"Dr. Jianyu Gu"},"content":{"rendered":"\n\n\tDr. Jianyu Gu
\nPost-Doctoral Researcher (2018-2020)
\n<\/strong>\n\t\t\t\t\"gu-bio\"\n\tCONTACT<\/strong>
\njianyu.gu@unh.edu<\/a>\n\t

Research Biography<\/strong><\/p>\n

Dr. Gu was a post-doctoral researcher in the BASAL Lab from 2018-2020.\u00a0 He obtained his Ph.D. in Geographical information science in\u00a02015 at\u00a0Beijing Normal University and B.S. in Geographical information science in\u00a02009 at the\u00a0University of Lanzhou. Dr. Gu’s\u00a0 work at the University of New Hampshire\u00a0 included\u00a0 collecting, compiling, and processing\u00a0forest data from multiple sources such as UAS (unmanned aerial system) images, historical records, and field data. He has also developed a geospatial workflow to find the best scale for single tree detection and delineation. He worked to\u00a0conduct modeling between ground and UAS measurements based on the Bayesian statistics and develop\u00a0improved region growing and graph network algorithms to segment single tree crown from UAS data, which resulted in 11.1% and 23.5% increases in accuracy, respectively. Dr. Gu has also taught advanced remote sensing class as co-instructor and created ArcGIS-python tutorials.<\/p>\n

Prior to his work at the University of New Hampshire, Dr. Gu has worked at the\u00a0University of Changzhou as an\u00a0Associate Professor, at\u00a0Starmap Technology Co., as a Senior consultant, and at the\u00a0University of Heilongjiang as an Associate Professor.\u00a0 Currently, Dr. Gu is employed as a Geospatial Analyst at the National Renewable Energy Lab.<\/p>\n

AWARDS<\/strong><\/p>\n

2018, Second prize as a tutor in “Challenge Cup Competition” awarded by the University of Changzhou<\/p>\n

2018, “State High-level Talent” awarded by Jiangsu provincial government for my consulting service to the agricultural big data project entitled, “Spatially big training data and crop type classification using UAS.”<\/p>\n

2018, “Summit of the Six Top Talents” awarded by Jiangsu provincial Department of Human Resources and Social Security for my consulting service to the agricultural project entitled, “Spatial sampling and crop area estimation.”<\/p>\n

2018, Second prize of excellent surveying and geographic information engineering awarded by the Land and Resources Bureau of Changzhou Municipal Government for the project entitled, “UAS data processing and interpretation for crop area estimation.”<\/p>\n

2017, Third prize of excellent surveying and geographic information engineering awarded by the Land and Resources Bureau of Changzhou Municipal Government for the project entitled, “Spatial sampling and UAS-data collection for crop area estimation.”<\/p>\n

2016, “High-level Science and Technology Service-oriented Scientist” awarded by the Human Resources and Social Security Bureau of Changzhou Municipal Government for my scientific report and advice to the project entitled, “Spatial sampling and crop area estimation.”<\/p>\n

2010, Third prize in the academic contest awarded by Beijing Normal University for the scientific report entitled, “A new method to remove the atmospheric effect in HJ-1A multi-spectral image.”<\/p>\n

2009, Outstanding undergraduate student awarded by University of Lanzhou<\/p>\n

2008, Third prize in the national spatial modeling contest awarded by Environmental Systems Research Institute, ESRI Inc., U.S. for the project entitled, “Assessing the risk of the landslide at the city of Lanzhou based on remote sensing and GIS.”<\/p>\n

PUBLICATIONS<\/strong><\/p>\n

Peer-Reviewed Articles<\/p>\n

Gu J, Congalton R G, The Positional Effect in Soft Classification Accuracy assessment, American Journal of Remote Sensing, 2019, 7(2):50-61<\/p>\n

Gu J, Congalton R G, Pan Y. The Impact of Positional Errors on Soft Classification Accuracy Assessment: A Simulation Analysis. Remote Sensing, 2015, 7(1):579-599<\/p>\n

Congalton R G, Gu J, Yadav K, et al. Global Land Cover Mapping: A Review and Uncertainty Analysis. Remote Sensing, 2014, 6(12):12070-12093<\/p>\n

M. Li, X. Zhu, J. Gu, G. Shuai et al., “SVDD based one class land cover mapping using optimal training samples,” 2014 IEEE Geoscience and Remote Sensing Symposium, Quebec City, QC, 2014, pp. 3570-3573.doi: 10.1109\/IGARSS.2014.6947254<\/p>\n

Yizhan L, Zhu X, Pan Y, Gu J, et al. A Comparison of Model-Assisted Estimators to Infer Land Cover\/Use Class Area Using Satellite Imagery. Remote Sensing, 2014, 6(1):8904-8922<\/p>\n

Li Y, Pan Y, X Zhu, Li Y, Gu J. Comparison analysis on land cover area estimators: confusion matrix calibration and regression. Transactions of the Chinese Society of Agricultural Engineering, 2013, 29(11): 115-123<\/p>\n

Zhang Y, Pu X, Chen H, Gu J, et al. Ecological Security assessment of Shiyang River Basin based on Remote sensing and GIS, Journal of Desert Research, 2011, 6:1493-1500<\/p>\n

Hou D, Song G, Dong Y, Gu J. Precision Analysis of Different Radiation Parameters of Landsat Thematic Mapper Sensor, Remote Sensing for Land & Resource, 2010(4): 14-18<\/p>\n

Articles in Preparation<\/em><\/p>\n

Compare the canopy height model (CHM) and RGB image for tree detection and crown delineation (in the draft, scheduled in 2.2020)<\/p>\n

Combine region growing and spatially adjusted Euclidean to delineate individual tree crown (in the draft, scheduled in 4.2020)<\/p>\n

Region growing by over-segmented polygons for individual tree crown delineation considering crown shape prior (in preparation, scheduled in 6.2020)<\/p>\n

Region merging using local mean color and boundary threshold for individual tree crown delineation (in preparation, scheduled in 9.2020)<\/p>\n

Tree height measurement and mapping: A review and uncertainty analysis (developing)<\/p>\n

Symposium Proceedings and Other Articles<\/strong><\/p>\n

J. Gu, G. Sun, Y. Pan and D. Fan, “Accuracy assessment based on the distribution of the classified errors on classified map: Simulation analysis,” Agro-Geoinformatics (Agro-Geoinformatics), 2012 First International Conference on, Shanghai, 2012, pp. 1-4<\/p>\n

J. Gu, D. Fan, N. Jiang, and J. Liu, “A noise detection method for NDVI time series data based on dixon test,” Agro-Geoinformatics (Agro-Geoinformatics), 2012 First International Conference on, Shanghai, 2012, pp. 1-5<\/p>\n

G. Sun, Y. Li and J. Gu, “Assessing the sustainability of agriculture in Beijing based on the biological capacity theory,” Agro-Geoinformatics (Agro-Geoinformatics), 2012 First International Conference on, Shanghai, 2012, pp. 1-4<\/p>\n

Y. Li, G. Sun, J. Gu and J. Zhang, “Comparison of area estimators for land cover using simulated data,” Agro-Geoinformatics (Agro-Geoinformatics), 2012 First International Conference on, Shanghai, 2012, pp. 1-5<\/p>\nPUBLIC SERVICE
\n<\/strong>Reviewer for the following journals:
\nRemote Sensing, Photogrammetric Engineering & Remote Sensing, and u IEEE Geoscience and Remote Sensing\n\n","protected":false},"excerpt":{"rendered":"

Dr. Jianyu Gu Post-Doctoral Researcher (2018-2020) CONTACT jianyu.gu@unh.edu Research Biography Dr. Gu was a post-doctoral researcher in the BASAL Lab from 2018-2020.\u00a0 He obtained his Ph.D. in Geographical information science in\u00a02015 at\u00a0Beijing Normal University and B.S. in Geographical information science in\u00a02009 at the\u00a0University of Lanzhou. Dr. Gu’s\u00a0 work at the University of New Hampshire\u00a0 included\u00a0 […]<\/p>\n","protected":false},"author":29,"featured_media":0,"parent":144,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"disabled","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"class_list":["post-94","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sites.usnh.edu\/basal-lab\/wp-json\/wp\/v2\/pages\/94","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.usnh.edu\/basal-lab\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.usnh.edu\/basal-lab\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.usnh.edu\/basal-lab\/wp-json\/wp\/v2\/users\/29"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.usnh.edu\/basal-lab\/wp-json\/wp\/v2\/comments?post=94"}],"version-history":[{"count":3,"href":"https:\/\/sites.usnh.edu\/basal-lab\/wp-json\/wp\/v2\/pages\/94\/revisions"}],"predecessor-version":[{"id":210,"href":"https:\/\/sites.usnh.edu\/basal-lab\/wp-json\/wp\/v2\/pages\/94\/revisions\/210"}],"up":[{"embeddable":true,"href":"https:\/\/sites.usnh.edu\/basal-lab\/wp-json\/wp\/v2\/pages\/144"}],"wp:attachment":[{"href":"https:\/\/sites.usnh.edu\/basal-lab\/wp-json\/wp\/v2\/media?parent=94"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}