Ongoing | 宋爽

ABSESpy：面向真实社会-生态系统的多主体建模框架

Sun, 10 Oct 2021 00:00:00 +0000

ABSESpy makes it easier to build artificial Social-ecological systems with real GeoSpatial datasets and fully incorporate human behaviour.

Why `ABSESpy`?

Several characteristics of Agent-Based model (ABM) make it an essential method for social-ecological systems (SES) research:

It focuses on the change of an SES over time from mutual adaptations of agents and their environments.
its ability to generate emergent system-level outcomes from micro-level interactions and macro-level feedback.
its ability to represent the diversity and heterogeneity of human and non-human actors and the spatial characteristics of an SES …

However, there is currently no modelling framework that combines geo-spatial data and actor behaviour (actor is the term for agents in the SES framework) well. ABSESpy is designed for spatial modelling that couples human and nature by:

Modelling environment for agents with geo data: Shapefile, GeoTiff, NetCDF.
Modelling human behaviour of agents with cognition, contagion and responses.
Easily manage all parameters, arguments, and variables with a yaml settings file.

Install

Install with pip or your favourite PyPI package manager.

pip install abses

Basic usage & Documents

You can see how to use ABSESpy in these simple tutorials:

Organize an Agent-based model and easily manage parameters.
Using geo-spatial data as the environment.
Simply applying a human behavior framework.

Access the full Documentation here.

Get in touch

For enthusiastic developers and contributors, all contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome.
For SES researchers, welcome to use this package in social-ecological system (SES) studies. If you have a model published, feel free to contribute it to our model library through mailing list.

If you need any help when using ABSESpy, don’t hesitate to get in touch with us through:

Ask usage questions (“How to do?”) on GitHub Discussions.
Report bugs, suggest features or view the source code on GitHub.
For less well-defined questions or ideas or to announce other projects of interest to xarray users, use the mailing list.

License

Licensed under the Apache License, Version 2.0 (the “License”); you may not use this file except in compliance with the License. You may obtain a copy of the License at

https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an “AS IS” BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

ABSESpy bundles portions of AgentPy, pandas, NumPy and Xarray; the full text of these licenses is included in the licenses directory.

黄河流域社会-生态系统分析

Tue, 10 Oct 2017 00:00:00 +0000

Background

The global environment is under unprecedented pressure due to the strong influence of human activities, and the Earth is entering a new era of the Anthropocene. Understanding the mechanisms of modern environmental change and predicting future trends are at the forefront of Earth system science research. This requires developing a holistic systems approach, coupling natural and human processes and exploring the mechanisms of human-earth system coupling in changing environments. The human-terrestrial system is a complex giant in which the natural geographical environment and human socio-economy interact and feedback. Revealing the evolution of its dynamic, resolving the coupling mechanism of processes, and clarifying the optimal regulation pathways can provide a solid theoretical foundation for regional sustainable development.

The Yellow River Basin (YRB) has been influenced by more than 3,000 years of historical development and modern high-intensity economic activities; the spatial linkages between human activities and the resources and environment, and the region’s upper, middle, and lower reaches, are still changing. The river basin is ideal for studying human-water systems in environmental change. Therefore, it is informative to elucidate the mechanism of socio-hydrological system coupling in the YRB, providing fundamental inspiration for water sustainable management worldwide, and promoting the development of earth system science in China through integrated research in the basin.

Goals & Scientific questions

(1) Identifying the evolution of the human-water relationship and its regimes in the YRB To establish indicators and methods for characterising changes in human-water relations regarding socio-ecological water use, water scarcity, water diversion and sand transport, and to analyse the development and evolution of human-water relations in the Yellow River basin at millennial, centennial and decennial scales.

(2) Feedback and its mechanism of the socio-hydrological system in the YRB Quantify the critical variables of the socio-hydrological system, identify the main human-water feedback and quantify the positive and negative feedback loops. Analyse the impact of social factors (e.g. economic development, management decisions, social perceptions, etc.) on socio-ecological processes in the basin (e.g. ecological health of the bay, flood and drought risk adaptation, water and sand regulation, etc.) through feedback loops to reveal human-water interactions and their synergistic evolutionary mechanisms.

(3) Dynamic of coupled human and hydrology system and its resilience in the YRB A comprehensive analysis of the dynamic evolution of the socio-ecological-hydrological system of the Yellow River basin and the establishment of a system of resilience indicators to characterise the basin’s response to climate change and human activities.

Specifically, I focus on the below scientific questions:

What are the main drivers of the evolution of the human-water relationship in the YRB?
How social elements, especially the variables of collective behaviour, influences the processes of the socio-hydrological system, taking the YRB as an informative example.
In addition to engineering, how to build and improve the resilience of the social-hydrological system in the YRB through “soft” solutions from the social aspect.

TimeLine

2017:

I started learning Ostrom’s social-ecological system framework.
I designed and applied a questionnaire survey in the floodplain within YRB.

2018:

I finished my Bachelor’s degree dissertation, “Testing of Human-Flood Model: Taking floodplain of the Yellow River in Ningxia as an example”, which was rewarded an “Excellent Graduation Thesis.”

2019: