Multi-source Remote Sensing for terrestrial ecosystem health monitoring and assessment II

Type: Paper
Theme:
Sponsor Groups: Remote Sensing Specialty Group, Spatial Analysis and Modeling Specialty Group
Poster #:
Day: 4/3/2019
Start / End Time: 9:55 AM / 11:35 AM (Eastern Standard Time)
Room: Stones Throw 2 - Slate, Marriott, Lobby Level
Organizers: Phuong Dao, Yuhong He, Mitchell Bonney
Chairs: Phuong Dao

Call for Submissions

In this session, we are interested in the following potential topics:

(1) Hyperspectral remote sensing for vegetation and crop health monitoring;
(2) Multi-source data fusion for spatio-temporal vegetation dynamics;
(3) Time series image analysis for monitoring and modeling vegetation dynamics;
(4) Image classification, feature extraction, and change detection;
(5) LIDAR data for ecosystem structure;
(6) Crop response to environmental stress and disease;
(7) Land-cover and land-use dynamics monitoring and modeling;
(8) Ecosystem response to the climate change.

To present a paper in the session, please (1) register and submit your abstract through AAG website by November 8, 2018, and (2) send your personal identification number (PIN), paper title, abstract, and your abstract submission confirmation email organizers: phuong.dao@mail.utoronto.ca, yuhong.he@utoronto.ca, or mitchell.bonney@mail.utoronto.ca by November 8, 2018.


Description

Advances in remote sensing technology, including high-resolution data from different sensors and platforms, offer us the opportunity to assess and monitor the terrestrial ecosystem changes over time. The combination of high spatial, temporal, and spectral multi-source data allows us not only to capture the detailed ecosystem dynamics on different spatial and temporal scales but also to detect changes in plant physiology, ecosystem structure, functions, productivity, and composition, which are caused by environmental stress and disease, from leaf to canopy and landscape. However, high data volume requires advances in data processing, data normalization, data integration and fusion, dimension reduction, and information extraction and sharing to better utilize our existing resources and tools for understanding terrestrial ecosystem changes under a warming climate. By organizing this special session, we hope to create an opportunity for researchers to exchange ideas around emerging data sources, novel techniques, data sharing procedures, and applications for retrieving, handling, and making the best use of multi-source data for terrestrial ecosystem health studies.

In this session, we are interested in the following potential topics:
(1) Hyperspectral remote sensing for vegetation and crop health monitoring;
(2) Multi-source data fusion for spatio-temporal vegetation dynamics;
(3) Time series image analysis for monitoring and modeling vegetation dynamics;
(4) Image classification, feature extraction, and change detection;
(5) LIDAR data for ecosystem structure;
(6) Crop response to environmental stress and disease;
(7) Land-cover and land-use dynamics monitoring and modeling;
(8) Ecosystem response to the climate change.


Agenda

Type Details Minutes Start Time
Presenter Bailu Zhao*, University of Wisconsin - Milwaukee, Comparing Autumn Phenology Derived from Field Observations, Satellite Data, and Carbon Flux Measurements in a Northern Mixed Forest 20 9:55 AM
Presenter Guangxing Wang*, Southern Illinois University at Carbondale, Yunlei Cui, Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, Hunan, China, Hua Sun, Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, Hunan, China, Xiaoyu Xu, Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, Hunan, China, Comparative analysis of spectral unmixing methods for improvement of mapping vegetation cover for arid and semi-arid areas 20 10:15 AM
Presenter CHEN WANXU*, China University of Geosciences (Wuhan), Guangqing Chi, The Pennsylvania State University, Jiangfeng Li, China University of Geosciences (Wuhan), The spatial effects of land use and land cover change on ecosystem services intensity at the county level in China, 1995–2015 20 10:35 AM

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