| id |
cdrf2023_305 |
| authors |
Wang Yueyang, Philip F. Yuan |
| year |
2023 |
| title |
A Parametric Approach Towards Carbon Net Zero in Agricultural Planning |
| doi |
https://doi.org/https://doi.org/10.1007/978-981-99-8405-3_26
|
| source |
Proceedings of the 2023 DigitalFUTURES The 5st International Conference on Computational Design and Robotic Fabrication (CDRF 2023) |
| summary |
This paper presents a new tool called the Space Data Generator, which is a parametric tool for organizing open spaces in rural areas. It can optimize the layout of buildings, solar panels, and agricultural planting spaces. While architects have been exploring ways to achieve net-zero carbon emissions in building design, it is equally important to attain a feasible carbon-neutral goal in rural areas. This is particularly crucial as 40% of the world’s population resides in rural areas, and transitioning towards a more sustainable and efficient economy can bring about not only moral but also economic benefits through proper management [1]. The Space Date Generator offers a powerful spatial planning approach for optimizing and planning agricultural resources on any given land. This innovative tool utilizes a combination of remote sensing to generate precise maps of the land, providing a comprehensive understanding of its terrain and potential agricultural resources. With this information, farmers and land managers can make informed decisions about crop selection, irrigation, and fertilizer application, among other factors. By using the Space Date Generator, they can optimize the use of available resources and maximize crop yields, ultimately increasing profitability and sustainability in agriculture [2]. Overall, the Space Date Generator is a valuable tool for any farmer or land manager looking to make the most of their land and resources. Its ability to provide detailed and accurate data on the land’s potential agricultural resources can help to streamline decision-making processes and ultimately lead to more efficient and sustainable land use practices. 1. The Space data generator uses the collected site coordinate information, geographical status (including stones, lakes, and water patterns), and the planted plants’ price as input. 2. Divide the site into small squares, then configure enough solar panels in the optimal sunlight area of the site to meet the user’s needs, and then plant crops on the remaining land. 3. The Space data generator will analyze the number of calories a household needs each year as a percentage. If there is a surplus, the excess food can be allocated to generate economic outcomes on the market. The land area at hand will be subdivided based on its sun ratio, which is a relatively straightforward process. However, we are also interested in determining the value of excess vegetation that may grow in the allocated space. In this regard, the Space Data Generator can prove to be a valuable tool, not only for this particular scenario but also in other types of agricultural settings such as those involving a mix of livestock and crops. Additionally, it may be possible to use this tool to
calculate the optimal harvesting of various plant species at different points in the
seasonal cycle.
The Space Date Generator has the potential to offer valuable references for
optimizing agricultural schemes. However, it must provide users with completely
accurate results. Unfortunately, it currently cannot measure crucial factors such as
soil type and moisture level, which are essential for agricultural planning. Despite
this limitation, the Space Data Generator is a flexible tool that can be modified as
research advances, allowing for more inputs to be added to improve its accuracy.
Moreover, the Space Data Generator can provide guidance in various other areas
based on the specific needs of the user. For instance, it can offer guidelines for
traffic and urban design, among other demands. By leveraging this technology,
users can access more precise and relevant information, enhancing their decisionmaking capabilities. As such, the Space Data Generator represents a valuable tool
for various industries and sectors. |
| series |
cdrf |
| email |
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| full text |
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| references |
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| last changed |
2024/05/29 14:04 |
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