MalaGIS

Sharing GIS Technologies, Resources and News.

Recently in the Mala GIS group, someone raised an interesting question: Can GIS be used to analyze which province in China has produced the most leaders? Previously, you might have had to search via a search engine, but the data might not be up-to-date, and quantitative analysis would be cumbersome, requiring tedious data cleaning. However, in the AI era, we can easily accomplish this task using AI + GIS.

P.S.: This article is purely technical, and the data may not be entirely accurate. Corrections are welcome if any issues are found.

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Extracting river/canal centerlines is a common task in GIS data processing. Users of ArcMap or ArcGIS Pro likely find it straightforward. Recently, many colleagues have started exploring QGIS, someone in My GIS Group asked about this, making it a good time to document the process.

PS: The author will focus on introducing methods to achieve ArcGIS-equivalent functions in QGIS. If you have specific needs in this area, feel free to leave a comment.

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In a previous article "Practical Application of Geo Hound: Extracting Wuhan's Unified Planning Map Services for GIS Analysis", I demonstrated using Geo Hound to access Wuhan's planning map data in QGIS. A key objective was comparing land-use planning attributes against reality to identify discrepancies. While I mentioned using layer swipe for this comparison, many readers inquired about implementing swipe functionality in QGIS.

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Share an official ESRI ArcGIS Pro tutorial book. The book uses ArcGIS Pro version 3.1. If you need this version, you can download it from our site. Refer to "Share ArcGIS Pro 3.1 'Learning Edition' Complete Installation Package (Includes Chinese Language Pack, Updated to 3.1.7)".

This PDF comes from the MalaGIS WeChat group. It is not a scanned copy but a high-quality original, making it an excellent resource for learning both GIS technology and English.

Book Introduction

GIS Tutorial for ArcGIS Pro 3.1 is a widely acclaimed introductory textbook on Geographic Information Systems (GIS). Co-authored by Wilpen L. Gorr and Kristen S. Kurland, renowned educators from Carnegie Mellon University, and published by Esri Press, this fifth edition was released in June 2023. Designed specifically for ArcGIS Pro 3.1, it provides a systematic and practical learning path for beginners with no prior GIS experience.

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Following my previous article "This Certification is Highly Valuable for GIS Job Seekers, Yet Overlooked by Many", which helped numerous GIS professionals advance their careers, a middle school geography teacher recently requested vector data for China's geographic regional partitions for classroom presentations. After research, I'm sharing this valuable dataset.

Data Specifications

• Geographic Coordinate System: GCS_Krasovsky_1940
• Projected Coordinate System: Krasovsky_1940_Albers

• Regions Included:

  • Tarim and Turpan Basins
  • Qaidam Basin
  • Central Shanxi-Northern Shaanxi-Eastern Gansu Plateau
  • Eastern Qinghai-Qilian Mountains
  • Liaodong-Jiaodong Hills
  • Central Shandong Hills
  • Southern Shanxi-Guanzhong Basin
  • Ngari Mountains
  • Qiangtang Plateau Lake Basin
  • Western Sichuan-Eastern Tibet High Mountains
  • Sichuan Basin
  • Jiangnan and Nanling Mountains
  • Guizhou Plateau
  • Jiangnan Hills
  • Yunnan Plateau
  • Qiong-Lei Hills
  • Sanjiang Plain
  • Northeastern Mountain Region
  • Northeastern Piedmont Plain
  • Central Songliao Plain
  • Southern Greater Khingan Range
  • Sanhe Piedmont Hills
  • Southwestern Songliao Plain
  • Eastern Inner Mongolia High Plain
  • Western Inner Mongolia High Plain
  • Northern Kunlun Mountains
  • Junggar Basin
  • Altai Mountains and Tacheng Basin
  • Ili Basin
  • North China Plain
  • Southern Himalayas
  • Fujian-Guangxi-Guangdong Hills and Plains
  • Kunlun Alpine Plateau
  • Central-Northern Taiwan Mountains and Plains
  • Golog-Nagqu Hilly Plateau
  • Alxa and Hexi Corridor
  • Qiong-Lei Lowlands
  • South Tibet Mountains
  • Qiong-Lei Lowlands and Dongsha Islands
  • Southern Yunnan Valleys and Hills
  • Southern Qinghai Plateau Wide Valleys
  • Hanzhong Basin
  • Huainan and Middle-Lower Yangtze Plains
  • North China Hills
  • Southern Taiwan Lowlands
  • Greater Khingan Range

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QGIS 3.44 has now been officially released. I downloaded and tried it out immediately. For Windows users, QGIS 3.44 offers both a test version with Qt6 support ("Latest Version for Windows (3.44) with Qt6 (experimental)") and the standard 3.44 version ("Latest Version for Windows (3.44)").

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Following my previous article on extracting Wuhan's planning map services using Geo Hound, the original Wuhan data source implemented access restrictions. For a recent leadership demonstration, I identified an alternative: Shanghai's Detailed Planning Map service.

Note: While workarounds exist for Wuhan's restricted data, this article focuses on ethically accessible sources.

Shanghai Detailed Planning Map

Shared by members of the MalaGIS community (special thanks!), this official platform provides comprehensive urban planning data:
https://shanghai.tianditu.gov.cn/xg/map.html

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In my previous article "Please Use Legitimate Compression Software", I addressed common decompression issues. Recently, I've received numerous complaints claiming the passwords for my shared archives are incorrect and files can't be extracted - some even accusing me of sharing fake resources.

Initially, I dismissed these claims since I personally compress each archive and verify extraction before uploading. With thousands of successful downloads, isolated complaints seemed implausible. But persistent reports made me investigate a specific case:

User's failed extraction attempt

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Author: An anonymous GIS professional specializing in astronomy, geography, remote sensing, and geomancy.

Tianditu (National Platform for Common Geospatial Information Services), hosted by the Ministry of Natural Resources, provides public online geospatial services and promotes geospatial data sharing. For GIS professionals, a common requirement is loading various online basemaps. Tianditu offers convenient services for desktop software like ArcMap and QGIS. While QGIS has mature plugins, this guide focuses on ArcMap users.

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This article reviews prominent water detection indices - NDWI, MNDWI, NDMI, AWEI, and WRI - highlighting their distinct formulas, applications, and limitations in remote sensing analysis.

NDWI

Normalized Difference Water Index
Developed by McFeeters (1996) to identify open water bodies using spectral reflectance differences:

Formula:
NDWI = (NIR - Green) / (NIR + Green)

Principle:

• High reflectance in Green band
• Strong absorption in Near-Infrared (NIR) band
• Maximizes contrast between water and vegetation/soil

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