Dingkang Teng

Buffer Analysis

Tue, 10 Feb 2026 00:00:00 +0000

Description

This is the main script for buffer analysis. It builds multi‑ring buffers around source points and counts target features within each buffer ring, specifically designed for sensitive analysis.

Toolbox script Structure

The tool requires the following :

Input Parameters

Source POI Layer

This field specifies the point layer containing the source POIs (centers of the buffers).

Select zone name field of source POI

This field specifies the field that defines zones (e.g., districts) for the source POIs. If you do not need to calculate by zone, select a field where all values are identical.

Target POI Layer

This field specifies the point layer containing the target POIs to be counted within the buffers.

Select zone name field of target POI

This field specifies the field that defines zones for the target POIs. If you do not need to calculate by zone, select a field where all values are identical.

Note

Ensure that the values in the and correspond to the same zones. It is strongly recommended to use the to generate the zone name field.

Buffer (Meter) Syntax (Python)

This field defines the buffer radii in meters using a Python list comprehension.

Example

Define specific buffer distances (e.g., 10, 20, 50, 100, 500, 1000 meters)
```
[10, 20, 50, 100, 500, 1000]
```
Generate a range of distances from 10 to 2000 meters with an interval of 10 meters
```
[10 * x for x in range(1,201)]
```

Save path

Enter the base name for the output CSV file (do not include the .csv extension).
The results will be saved as CSV files.

Run the script

After setting all parameters, click Run to execute the script.

Result structure

The result contains four columns:

city: The name of the zone, as defined by the .
distance: The radius of the buffer (in meters).
Num: The number of points within the buffer for the corresponding city and distance.
totalNum: The total number of points within the corresponding city.

Getting Started

Tue, 10 Feb 2026 00:00:00 +0000

Quick Start

Download the toolbox

Download the Buffer Analysis Tool from my .

For the source code, please refer to the . Feel free to explore, contribute, or report issues.

Unzip the Buffer Analysis Tool

Unzip the Buffer Analysis Tool to any location of your choice. It is recommended to place it in the root folder of your ArcGIS Pro project for convenience, as shown in the figure below.

Open tookbox in ArcGIS

It may take a few seconds to initialize the toolkit when you first open it.

There are three scripts in the toolbox:

: the main script for performing buffer analysis.
: a specialized script that performs buffer analysis based solely on the buffer area.
: an auxiliary script that divides POIs by polygon for buffer analysis.

Note

ArcGIS Pro may warn you that opening a Python toolbox runs third-party code. Simply click “Yes” to proceed.

The following sections will describe the specific usage of these scripts:

Buffer Analysis Buffer Analysis (Area) District Divide

Buffer Analysis (Area)

Tue, 10 Feb 2026 00:00:00 +0000

Description

This is a specialized script that performs buffer analysis based solely on the buffer area. It builds multi‑ring buffers around source points and calculates the area of each buffer ring intersecting with the specified district boundaries.

Toolbox script Structure

The tool requires the following :

Input Parameters

Source POI Layer

This field specifies the point layer containing the source POIs (centers of the buffers).

Select zone name field of source POI

This field specifies the field that defines zones (e.g., districts) for the source POIs.

Disrict Layer

This field specifies the polygon layer define the boundary of each zone.

Select zone name field of district layer

This field specifies the field that defines zones for the polygon layer.

Note

Ensure that the values in the and correspond to the same zones. It is strongly recommended to use the to generate the zone name field for the from the .

Buffer (Meter) Syntax (Python)

This field defines the buffer radii in meters using a Python list or list comprehension.

Example

Define specific buffer distances (e.g., 10, 20, 50, 100, 500, 1000 meters)
```
[10, 20, 50, 100, 500, 1000]
```
Generate a range of distances from 10 to 2000 meters with an interval of 10 meters
```
[10 * x for x in range(1,201)]
```

Save path

Enter the base name for the output CSV file (do not include the .csv extension).
The results will be saved as CSV files.

Run the script

After setting all parameters, click Run to execute the script.

Result structure

The result contains four columns:

city: The name of the zone, as defined by the .
distance: The radius of the buffer (in meters).
Num: The area of the buffer ring (in square meters) intersecting with the corresponding city boundary for the corresponding city and distance.
totalNum: The total area (in square meters) of the corresponding city.

District Divide

Tue, 10 Feb 2026 00:00:00 +0000

Description

This is an auxiliary script that divides POIs by polygon for buffer analysis.

Toolbox script Structure

The tool requires the following :

Input Parameters

Input Layer

This field specifies the point layer that needed to be divided.

Zone Division Layer

This field specifies the polygon layer define the boundary of each zone.

Select zone name field

This field specifies the field that defines zones for the polygon layer.

Save path

Enter the base name for the output.
The results will be automatically saved as shapefiles (.SHP) or feature classes in a file geodatabase, depending on the output path you specify.

Run the script

After setting all parameters, click Run to execute the script.

Result structure

The output contains a field that stores the zone names, named after the you selected.

Suggested Citation

Tue, 10 Feb 2026 00:00:00 +0000

Teng, D., Tang, J. H. C. G., Ma, R., Yang, X., & Zhuge, C. (2026). A global insight into integration of metro and electric vehicle charging stations. Sustainable Cities and Society, 107217. DOI:

Example Talk

Sat, 01 Jun 2030 13:00:00 +0000

Note

Click on the Slides button above to view the built-in slides feature.

Slides can be added in a few ways:

Create slides using Hugo Blox Builder’s feature and link using the slides parameter in the front matter of the talk file
Upload an existing slide deck to this page bundle and link it using links: [{ type: slides, url: path/to/file } ] in front matter
Embed your slides (e.g. Google Slides) or presentation video on this page using .

Further event details, including such as image galleries, can be added to the body of this page.

Working Papers

Mon, 04 May 2026 02:00:00 +0000

Note

This page lists all my working papers

Teng, D., Tang, J.H.C.G., Ma, R., Yang, X., & Zhuge, C. The potential influences of flooding on accessibility and equity of public electric vehicle charging infrastructure: A global insight. (In Preparation). [Target journal: Nature Cities]

From Points to Patterns: Global Spatial Accessibility and Equity in Public Electric Vehicle Charging (Under Review)

Mon, 04 May 2026 00:01:00 +0000

Note

This paper is Under Review.

Advancing accessibility and equity of public electric vehicle charging stations in China (Under Review)

Mon, 09 Mar 2026 00:01:00 +0000

Note

This paper is Under Review.

Dynamic Social Disparities in the U.S. Electric Vehicle Charging Infrastructure System

Tue, 03 Mar 2026 00:00:00 +0000

Tip

Highlights

Charger deployment favored wealthier and more populated counties with high MUD shares.
Social equity is dynamic rather than static.
Asians saw improved accessibility, while Black Americans faced widening disparities.
White Americans benefit more from DC over the past decade.
Elderly have greater access to both DC and AC chargers than younger adults.

A global insight into integration of metro and electric vehicle charging stations

Fri, 06 Feb 2026 00:00:00 +0000

Tip

Highlights

A global geodataset of EV charging stations (EVCS) and metro stations is provided.
The U.S. leads in EVCS aggregation near metro stations, yet development is uneven.
Europe shows balanced co-development of parking facilities and EVCS.
China shows strong potential to upgrade park-and-ride to park-charge-ride services.

This study provides one of the first comprehensive, data-driven assessments of the emerging Park-Charge-Ride (PCR) concept across 153 urban areas in the United States, Europe, and China. By analyzing the spatial proximity, density, and clustering patterns of electric vehicle charging stations (EVCS) and parking lots relative to metro stations, we reveal significant regional disparities in the readiness and development of integrated electric mobility hubs:

Substantial regional contrasts: The United States shows strong but uneven aggregation of EVCS near metro stations; Europe achieves a more balanced integration of EVCS and parking facilities; while China, despite its extensive metro networks, exhibits limited EVCS integration near transit nodes.
No significant link to station type: The distribution of EVCS does not significantly align with metro station types (normal, interchange, or terminal), indicating a missed opportunity for targeted infrastructure planning.
Divergence between PCR and P&R development: The U.S. shows stronger development of PCR relative to traditional Park-and-Ride (P&R), whereas China has strong P&R presence but significant potential to upgrade to PCR. Europe maintains parity between the two.

The research underscores that integrating EV charging with transit systems is highly context-dependent and should align strategically with local urban development goals. It provides evidence-based insights to help policymakers, transport planners, and urban developers optimize charging infrastructure placement, enhance multimodal connectivity, and support the global shift toward sustainable electric mobility.

基于机器学习的房地产市场划分方法——以武汉市为例 (Translation: Real estate market segmentation method based on machine learning - a case study of Wuhan)

Sun, 13 Oct 2024 00:00:00 +0000

Abstract (Translation)

This study uses a sample of 6,154 residential real estate transaction records in Wuhan in March 2024, obtained through web scraping, to investigate how machine learning techniques, combined with big data analysis, can be used to segment the real estate market. The study selects the market average price as the feature variable for segmenting the real estate market, explores the application of neural networks and the K-means model in this segmentation, and further investigates how to improve the K-means model into a spatial segmentation model based on the K-means price and coordinate separation model. It ultimately concludes that the K-means price and coordinate separation model is an effective approach for real estate market segmentation. By utilizing normalized mutual information, the results of the K-means price and coordinate separation model are compared with Wuhan’s current “Real Estate Market Regional Segmentation” and the traditional Kriging interpolation method, validating the model’s effectiveness and practicality. The study demonstrates that the machine learning-based “K-means price and coordinate separation model” holds significant importance for the analysis and management of the real estate market.

一种自然资源资产清查方法及系统 (Translation: A Method and System of Natural Resource Asset Inventory)

Fri, 01 Mar 2024 00:00:00 +0000

Abstract (Translation)

The present application relates to a method and system for natural resource asset inventory, which pertain to the technical field of asset inventory. The method includes: obtaining the total area and location information of the region to be inventoried; acquiring terrestrial spatial planning scope data and marine spatial planning scope data for the region to be inventoried; determining whether there is an overlapping area between the region covered by the terrestrial spatial planning scope data and the region covered by the marine spatial planning scope data within the region to be inventoried; if so, dividing the region to be inventoried into a marine zone, a land-sea zone, and a land zone; obtaining the planned use of the land-sea zone according to the terrestrial spatial planning scope data, recorded as the first use; obtaining the planned use of the land-sea zone according to the marine spatial planning scope data, recorded as the second use; and determining the planned use of the land-sea zone based on the first use and the second use.

🎉 Easily create your own simple yet highly customizable blog

Fri, 27 Oct 2023 00:00:00 +0000

Welcome 👋

Table of Contents

Overview

The Hugo Blox website builder for Hugo, along with its starter templates, is designed for professional creators, educators, and teams/organizations - although it can be used to create any kind of site
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🧠 Sharpen your thinking with a second brain

Thu, 26 Oct 2023 00:00:00 +0000

Create a personal knowledge base and share your knowledge with your peers.

Hugo Blox web framework empowers you with one of the most flexible note-taking capabilities out there.

Create a powerful knowledge base that works on top of a local folder of plain text Markdown files.

Use it as your second brain, either publicly sharing your knowledge with your peers via your website, or via a private GitHub repository and password-protected site just for yourself.

Mindmaps

Hugo Blox supports a Markdown extension for mindmaps.

With this open format, can even edit your mindmaps in other popular tools such as Obsidian.

Simply insert a Markdown code block labelled as markmap and optionally set the height of the mindmap as shown in the example below.

Mindmaps can be created by simply writing the items as a Markdown list within the markmap code block, indenting each item to create as many sub-levels as you need:


```markmap {height="200px"}
- Hugo Modules
- Hugo Blox
- blox-plugins-netlify
- blox-plugins-netlify-cms
- blox-plugins-reveal
```

renders as

- Hugo Modules
- Hugo Blox
- blox-plugins-netlify
- blox-plugins-netlify-cms
- blox-plugins-reveal

Anh here’s a more advanced mindmap with formatting, code blocks, and math:


```markmap
- Mindmaps
- Links
- [Hugo Blox Docs](https://docs.hugoblox.com/)
- [Discord Community](https://discord.gg/z8wNYzb)
- [GitHub](https://github.com/HugoBlox/hugo-blox-builder)
- Features
- Markdown formatting
- **inline** ~~text~~ *styles*
- multiline
text
- `inline code`
- Math: $x = {-b \pm \sqrt{b^2-4ac} \over 2a}$
```

renders as

- Mindmaps
- Links
- [Hugo Blox Docs](https://docs.hugoblox.com/)
- [Discord Community](https://discord.gg/z8wNYzb)
- [GitHub](https://github.com/HugoBlox/hugo-blox-builder)
- Features
- Markdown formatting
- **inline** ~~text~~ *styles*
- multiline
text
- `inline code`
- Math: $x = {-b \pm \sqrt{b^2-4ac} \over 2a}$

Highlighting

Highlight important text with mark:

<mark>Highlighted text</mark>

Callouts

Use (aka asides, hints, or alerts) to draw attention to notes, tips, and warnings.

Use the > [!NOTE] syntax to create a callout.

> [!NOTE]
> A Markdown aside is useful for displaying notices, hints, or definitions to your readers.

renders as

Note

A Markdown aside is useful for displaying notices, hints, or definitions to your readers.

Or use the warning callout type so your readers don’t miss critical details:

Warning

A Markdown aside is useful for displaying notices, hints, or definitions to your readers.

📈 Communicate your results effectively with the best data visualizations

Wed, 25 Oct 2023 00:00:00 +0000

Hugo Blox is designed to give technical content creators a seamless experience. You can focus on the content and Hugo Blox handles the rest.

Use popular tools such as Plotly, Mermaid, and data frames.

Embed Rich Content

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HuggingFace Dataset

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kit

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🧱 Describe your site, AI builds it, you own it as Markdown. Snap together Tailwind blocks like Lego — landing pages, blogs, portfolios, docs & more. No AI slop. Free to deploy anywhere 👇

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academic blog documentation-tool +17

Custom embed with manual data

My Custom Resource

example.com

A great resource for learning

Custom Images

Embed beautiful images from any source with Hugo image processing (Unsplash, custom URLs, etc.):

Data Visualization Guide

example.com

Beautiful data visualization workspace

You can also add images to any platform embed:

plotly.py

by plotly • Python

The interactive graphing library for Python ✨

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d3 dashboard declarative +11

Charts

Hugo Blox supports the popular format for interactive data visualizations. With Plotly, you can design almost any kind of visualization you can imagine!

Save your Plotly JSON in your page folder, for example line-chart.json, and then add the {{< chart data="line-chart" >}} shortcode where you would like the chart to appear.

Demo:

You might also find the useful.

Diagrams

Hugo Blox supports the Mermaid Markdown extension for diagrams.

An example flowchart:

```mermaid
graph TD
A[Hard] -->|Text| B(Round)
B --> C{Decision}
C -->|One| D[Result 1]
C -->|Two| E[Result 2]
```

renders as

graph TD A[Hard] -->|Text| B(Round) B --> C{Decision} C -->|One| D[Result 1] C -->|Two| E[Result 2]

An example sequence diagram:

```mermaid
sequenceDiagram
Alice->>John: Hello John, how are you?
loop Healthcheck
John->>John: Fight against hypochondria
end
Note right of John: Rational thoughts!
John-->>Alice: Great!
John->>Bob: How about you?
Bob-->>John: Jolly good!
```

renders as

sequenceDiagram Alice->>John: Hello John, how are you? loop Healthcheck John->>John: Fight against hypochondria end Note right of John: Rational thoughts! John-->>Alice: Great! John->>Bob: How about you? Bob-->>John: Jolly good!

An example class diagram:

```mermaid
classDiagram
Class01 <|-- AveryLongClass : Cool
Class03 *-- Class04
Class05 o-- Class06
Class07 .. Class08
Class09 --> C2 : Where am i?
Class09 --* C3
Class09 --|> Class07
Class07 : equals()
Class07 : Object[] elementData
Class01 : size()
Class01 : int chimp
Class01 : int gorilla
Class08 <--> C2: Cool label
```

renders as

classDiagram Class01 <|-- AveryLongClass : Cool Class03 *-- Class04 Class05 o-- Class06 Class07 .. Class08 Class09 --> C2 : Where am i? Class09 --* C3 Class09 --|> Class07 Class07 : equals() Class07 : Object[] elementData Class01 : size() Class01 : int chimp Class01 : int gorilla Class08 <--> C2: Cool label

An example state diagram:

```mermaid
stateDiagram
[*] --> Still
Still --> [*]
Still --> Moving
Moving --> Still
Moving --> Crash
Crash --> [*]
```

renders as

stateDiagram [*] --> Still Still --> [*] Still --> Moving Moving --> Still Moving --> Crash Crash --> [*]

Data Frames

Save your spreadsheet as a CSV file in your page’s folder and then render it by adding the Table shortcode to your page:

{{< table path="results.csv" header="true" caption="Table 1: My results" >}}

renders as

Table 1: My results
customer_id	score
1	0
2	0.5
3	1

Interactive Buttons

Add engaging call-to-action buttons to your data visualization posts:

Basic Buttons

Learn Plotly

{{< button url="/" >}}Contact Us{{< /button >}}

{{< button url="https://plotly.com/python/" new_tab="true" style="secondary" >}}Learn Plotly{{< /button >}}

Styled Buttons for Data Actions

View Dashboard

Download Data

View Source Code

{{< button url="#" style="primary" size="lg" align="center" icon="chart-bar" >}}View Dashboard{{< /button >}}

{{< button url="/data/results.csv" style="outline" icon="document-arrow-down" >}}Download Data{{< /button >}}

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Multiple Aligned Buttons

Try Jupyter

Open in Colab

{{< button url="https://jupyter.org/" new_tab="true" style="secondary" rounded="full" align="center" >}}Try Jupyter{{< /button >}}

{{< button url="https://colab.research.google.com/" new_tab="true" style="primary" rounded="full" align="center" icon="rocket-launch" >}}Open in Colab{{< /button >}}

👩🏼‍🏫 Teach academic courses

Tue, 24 Oct 2023 00:00:00 +0000

is designed to give technical content creators a seamless experience. You can focus on the content and the Hugo Blox Builder which this template is built upon handles the rest.

Embed videos, podcasts, code, LaTeX math, and even test students!

On this page, you’ll find some examples of the types of technical content that can be rendered with Hugo Blox.

Citation

Here’s an example of citing a publication using the cite shortcode:

You can also use the default view by omitting the view parameter:

Video

Teach your course by sharing videos with your students. Choose from one of the following approaches:

Youtube:

{{< youtube D2vj0WcvH5c >}}

Bilibili:

{{< bilibili BV1WV4y1r7DF >}}

Video file

Videos may be added to a page by either placing them in your assets/media/ media library or in your , and then embedding them with the video shortcode:

{{< video src="my_video.mp4" controls="yes" >}}

Podcast

You can add a podcast or music to a page by placing the MP3 file in the page’s folder or the media library folder and then embedding the audio on your page with the audio shortcode:

{{< audio src="ambient-piano.mp3" >}}

Try it out:

Test students

Provide a simple yet fun self-assessment by revealing the solutions to challenges with the spoiler shortcode:

{{< spoiler text="👉 Click to view the solution" >}}
You found me!
{{< /spoiler >}}

renders as

👉 Click to view the solution

You found me 🎉

Math

Hugo Blox Builder supports a Markdown extension for $\LaTeX$ math. Enable math by setting the math: true option in your page’s front matter, or enable math for your entire site by toggling math in your config/_default/params.yaml file:

features:
 math:
 enable: true

To render inline or block math, wrap your LaTeX math with $...$ or $$...$$, respectively.

Example math block:

$$
\gamma_{n} = \frac{ \left | \left (\mathbf x_{n} - \mathbf x_{n-1} \right )^T \left [\nabla F (\mathbf x_{n}) - \nabla F (\mathbf x_{n-1}) \right ] \right |}{\left \|\nabla F(\mathbf{x}_{n}) - \nabla F(\mathbf{x}_{n-1}) \right \|^2}
$$

renders as

$$\gamma_{n} = \frac{ \left | \left (\mathbf x_{n} - \mathbf x_{n-1} \right )^T \left [\nabla F (\mathbf x_{n}) - \nabla F (\mathbf x_{n-1}) \right ] \right |}{\left \|\nabla F(\mathbf{x}_{n}) - \nabla F(\mathbf{x}_{n-1}) \right \|^2}$$

Example inline math $\nabla F(\mathbf{x}_{n})$ renders as $\nabla F(\mathbf{x}_{n})$.

Example multi-line math using the math linebreak (\\):

$$f(k;p_{0}^{*}) = \begin{cases}p_{0}^{*} & \text{if }k=1, \\
1-p_{0}^{*} & \text{if }k=0.\end{cases}$$

renders as

$$ f(k;p_{0}^{*}) = \begin{cases}p_{0}^{*} & \text{if }k=1, \\ 1-p_{0}^{*} & \text{if }k=0.\end{cases} $$

Code

Hugo Blox Builder utilises Hugo’s Markdown extension for highlighting code syntax. The code theme can be selected in the config/_default/params.yaml file.

```python
import pandas as pd
data = pd.read_csv("data.csv")
data.head()
```

renders as

import pandas as pd
data = pd.read_csv("data.csv")
data.head()

Inline Images

{{< icon name="python" >}} Python

renders as

Python

Experience

Tue, 24 Oct 2023 00:00:00 +0000

✅ Manage your projects

Mon, 23 Oct 2023 00:00:00 +0000

Easily manage your projects - create ideation mind maps, Gantt charts, todo lists, and more!

Ideation

Hugo Blox supports a Markdown extension for mindmaps.

Simply insert a Markdown code block labelled as markmap and optionally set the height of the mindmap as shown in the example below.

Mindmaps can be created by simply writing the items as a Markdown list within the markmap code block, indenting each item to create as many sub-levels as you need:


```markmap {height="200px"}
- Hugo Modules
- Hugo Blox
- blox-plugins-netlify
- blox-plugins-netlify-cms
- blox-plugins-reveal
```

renders as

- Hugo Modules
- Hugo Blox
- blox-plugins-netlify
- blox-plugins-netlify-cms
- blox-plugins-reveal

Diagrams

Hugo Blox supports the Mermaid Markdown extension for diagrams.

An example Gantt diagram:

```mermaid
gantt
section Section
Completed :done, des1, 2014-01-06,2014-01-08
Active :active, des2, 2014-01-07, 3d
Parallel 1 : des3, after des1, 1d
Parallel 2 : des4, after des1, 1d
Parallel 3 : des5, after des3, 1d
Parallel 4 : des6, after des4, 1d
```

renders as

gantt section Section Completed :done, des1, 2014-01-06,2014-01-08 Active :active, des2, 2014-01-07, 3d Parallel 1 : des3, after des1, 1d Parallel 2 : des4, after des1, 1d Parallel 3 : des5, after des3, 1d Parallel 4 : des6, after des4, 1d

Todo lists

You can even write your todo lists in Markdown too:

- [x] Write math example
 - [x] Write diagram example
- [ ] Do something else

renders as

Write math example
- Write diagram example
Do something else

Land Classification and Standard Price in Collective Agricultural Land

Thu, 01 Jun 2023 00:00:00 +0000

06/2023—06/2024

Working as a project leader. Led spatial analysis, rank classification, price estimation and Geographic Information System (GIS) related processes.

国有农用地使用权评估方法研究 (Translation: Study on the evaluation method of the use rights of state-owned agricultural land)

Mon, 01 Feb 2021 00:00:00 +0000

Abstract (Translation)

This paper focuses on the valuation methods for the use rights of state-owned agricultural land. By analyzing the ownership system and implications of state-owned agricultural land, it can be concluded that the use rights of state-owned agricultural land are not strictly statutory property rights. However, it is clear that the holder of the use rights of state-owned agricultural land is the registrant after legal registration of the land. Finally, the paper conducts an empirical evaluation using the example of a state-owned farm in Wuhan, demonstrating that the cost approach and the income capitalization method can most accurately reflect the price of the use rights of state-owned agricultural land. Additionally, whether comprehensive and accurate foundational data is available is a crucial guarantee for the precision of the valuation conclusion.

China’s Urban Land Price Dynamic Monitoring of Huangshi

Tue, 01 Dec 2020 00:00:00 +0000

12/2020—12/2023

Worked as project leader.
Responsible for data analysis and authoring comprehensive reports.
Received the 2021 Excellence Award from the provincial department.

Natural Resource Asset Inventory of Tieshan and Daye

Tue, 01 Dec 2020 00:00:00 +0000

12/2020—06/2024

Worked as project leader.
Managed price calculation, database creation, result summarization, and mapping tasks.
Provided guidance to teams working in other cities, including Huanggang and Haikou.

Innovation Leadership and Entrepreneurship Internship

Thu, 01 Jun 2017 00:00:00 +0000

Huazhong Agricultural University

Study on influencing factors of paid withdrawal of homestead

06/2017—06/2019

Designed questionnaires, utilized AHP for in-depth data analysis and drew accurate and weighted conclusions.
Synthesized the collected data and findings. Drafted a detailed, evidence-based report.

Abstract

Rural residential land is a crucial component of the three key reforms in land policy. While ensuring the mandatory protection of the red line of 1.8 billion mu (Chinese acre) of cultivated land and addressing the demands of urbanization, industrialization, and balanced urban-rural development, the withdrawal of idle and surplus rural residential land holds significant importance for protecting cultivated land resources and effectively supplying land for urban construction. This paper conducts an investigative study using Yicheng, Hubei, China as a case study, involving visits and surveys across 4 towns and 10 villages to explore farmers’ willingness to withdraw from residential land and the factors influencing it. The findings offer feasible suggestions for local governments in formulating policies related to rural residential land reform.

Dingkang Teng

Buffer Analysis

Description

Toolbox script Structure

Input Parameters

Source POI Layer

Select zone name field of source POI

Target POI Layer

Select zone name field of target POI

Buffer (Meter) Syntax (Python)

Save path

Run the script

Result structure

Getting Started

Quick Start

Download the toolbox

Unzip the Buffer Analysis Tool

Open tookbox in ArcGIS

Next

Buffer Analysis (Area)

Description

Toolbox script Structure

Input Parameters

Source POI Layer

Select zone name field of source POI

Disrict Layer

Select zone name field of district layer

Buffer (Meter) Syntax (Python)

Save path

Run the script

Result structure

District Divide

Description

Toolbox script Structure

Input Parameters

Input Layer

Zone Division Layer

Select zone name field

Save path

Run the script

Result structure

Suggested Citation

Example Talk

Working Papers

From Points to Patterns: Global Spatial Accessibility and Equity in Public Electric Vehicle Charging (Under Review)

Advancing accessibility and equity of public electric vehicle charging stations in China (Under Review)

Dynamic Social Disparities in the U.S. Electric Vehicle Charging Infrastructure System

A global insight into integration of metro and electric vehicle charging stations

基于机器学习的房地产市场划分方法——以武汉市为例 (Translation: Real estate market segmentation method based on machine learning - a case study of Wuhan)

Abstract (Translation)

一种自然资源资产清查方法及系统 (Translation: A Method and System of Natural Resource Asset Inventory)

Abstract (Translation)

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