Time Series Remote Sensing in Characterizing Long-term Land Surface Dynamics III

Type: Paper
Theme:
Sponsor Groups: Remote Sensing Specialty Group, Geographic Information Science and Systems Specialty Group
Poster #:
Day: 4/9/2020
Start / End Time: 11:10 AM / 12:25 PM
Room: Director's Row I, Sheraton, Plaza Building, Lobby Level
Organizers: Chunyuan Diao, Jin Chen, Xiaoyang Zhang
Chairs: Xiaolin Zhu

Call for Submissions

Recent advances in remote sensing have facilitated the use of large volume of satellite imagery for understanding the dynamics of natural and human-induced processes. The rich archive and continuing acquisition of remote sensing imagery across a range of spatial, temporal and spectral resolutions provide unprecedented opportunities to monitor the evolving land surface dynamics and their responses to climatic and environmental changes. The long-term time series of earth observation data, along with technical advancements, has largely improved our scientific understanding of types, trends, causes, and consequences of various dynamic processes (e.g., land surface phenology and land use land cover changes). It offers tremendous potentials to conduct not only historic change analysis but also near real-time monitoring of complex earth systems. The wealth of information thus facilitates the timely adaptive decision making in varying surface dynamic processes to increase the land resilience to human and climate impacts.

This session invites papers focusing on both theoretical and methodology research and applications to advance remote sensing time series analysis in characterizing land surface dynamics.

Potential session topics include, but not limited to:
1) Time series algorithm development (e.g., curve fitting, trend analysis, and change detection)
2) Multi-source image fusion, data integration, missing data interpolation, and any technologies for generating high-quality time series data
3) Time series remote sensing based domain applications (e.g., vegetation phenology, land cover and land use change, land surface biophysical characteristics, ecosystem evolution and conservation, environmental monitoring, etc.)
4) Long-term, large-scale land surface dynamic analysis catalyzed by cloud computing (e.g., google earth engine) and high performance computing
5) Validation and assessment of remotely sensed time series analysis
To present a paper in the session, please (1) register and submit your abstract through AAG, and (2) send your personal identification number (PIN), paper title, and abstract to one of the co-organizers by Oct. 30 or the extended deadline.

Organizers:
Chunyuan Diao (University of Illinois at Urbana-Champaign, chunyuan@illinois.edu)
Jin Chen (Beijing Normal University, chenjin@bnu.edu.cn)
Xiaoyang Zhang (South Dakota State University, xiaoyang.zhang@sdstate.edu)
Xiaolin Zhu (The Hong Kong Polytechnic University, xlzhu@polyu.edu.hk)


Description

Recent advances in remote sensing have facilitated the use of large volume of satellite imagery for understanding the dynamics of natural and human-induced processes. The rich archive and continuing acquisition of remote sensing imagery across a range of spatial, temporal and spectral resolutions provide unprecedented opportunities to monitor the evolving land surface dynamics and their responses to climatic and environmental changes. The long-term time series of earth observation data, along with technical advancements, has largely improved our scientific understanding of types, trends, causes, and consequences of various dynamic processes (e.g., land surface phenology and land use land cover changes). It offers tremendous potentials to conduct not only historic change analysis but also near real-time monitoring of complex earth systems. The wealth of information thus facilitates the timely adaptive decision making in varying surface dynamic processes to increase the land resilience to human and climate impacts.

This session invites papers focusing on both theoretical and methodology research and applications to advance remote sensing time series analysis in characterizing land surface dynamics.

Potential session topics include, but not limited to:
1) Time series algorithm development (e.g., curve fitting, trend analysis, and change detection)
2) Multi-source image fusion, data integration, missing data interpolation, and any technologies for generating high-quality time series data
3) Time series remote sensing based domain applications (e.g., vegetation phenology, land cover and land use change, land surface biophysical characteristics, ecosystem evolution and conservation, environmental monitoring, etc.)
4) Long-term, large-scale land surface dynamic analysis catalyzed by cloud computing (e.g., google earth engine) and high performance computing
5) Validation and assessment of remotely sensed time series analysis
To present a paper in the session, please (1) register and submit your abstract through AAG, and (2) send your personal identification number (PIN), paper title, and abstract to one of the co-organizers by Oct. 30 or the extended deadline.

Organizers:
Chunyuan Diao (University of Illinois at Urbana-Champaign, chunyuan@illinois.edu)
Jin Chen (Beijing Normal University, chenjin@bnu.edu.cn)
Xiaoyang Zhang (South Dakota State University, xiaoyang.zhang@sdstate.edu)
Xiaolin Zhu (The Hong Kong Polytechnic University, xlzhu@polyu.edu.hk)


Agenda

Type Details Minutes Start Time
Presenter Xiaolin Zhu*, The Hong Kong Polytechnic University, Jiaqi Tian, The Hong Kong Polytechnic University, Zheyan Shen, The Hong Kong Polytechnic University, Shuai Xu, The Hong Kong Polytechnic University, Study the impact of urban heat island on the Winter Wheat Spring Phenology Using Sentinel-2 Time Series 15 11:10 AM
Presenter Yaqian He*, Dartmouth College, Justin S Mankin, Department of Geography, Dartmouth College, Hanover, NH, USA; Department of Earth Sciences, Dartmouth College, Hanover, NH, USA; Lamont-Doherty Earth Observatory of Columbia University, New York, NY, USA, Jonathan Chipman, Department of Geography, Dartmouth College, Hanover, NH, USA. , Deep learning-based time series of land use and land cover mapping in South and Southeast Asia 15 11:25 AM
Presenter Sean Kearney*, USDA - ARS - Fort Collins, CO, Lauren Porensky, USDA - ARS - Fort Collins, CO, David Augustine, USDA - ARS - Fort Collins, CO, Rowan Gaffney, USDA - ARS - Fort Collins, CO, Justin Derner, USDA - ARS - Fort Collins, CO, Feng Gao, USDA - ARS - Beltsville, MD, David Hoover, USDA - ARS - Fort Collins, CO, Big Data Reveals Drivers of Vegetation Phenology and Cattle Productivity in Semi-arid Rangelands 15 11:40 AM
Presenter Eileen Helmer*, USDA Forest Service - International Institute of Tropical Forestry, Xiaolin Zhu, Hong Kong Polytechnic University, David Gwenzi, Humboldt State University, Tropical dry forest canopy and intraspecific leaf chemistry relationships with Landsat-scale phenology 15 11:55 AM
Presenter Xavier Haro-CarriĆ³n*, Macalester College, Peter Waylen , University of Florida , Jane Southworth , University of Florida, Greening in the Tropical Andes between 1982 and 2010: Insights from Ecuador 15 12:10 PM

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