#Geospatial Data

[magnasoft01]

How to Find, Evaluate, and Effectively Use Geospatial Data in GIS: A Step-by-Step Guide

In today's data-driven world, geospatial data has become essential for businesses, researchers, and governments to make informed decisions. Whether you're working in urban planning, environmental science, logistics, or other fields, the ability to locate, evaluate, and use geospatial data effectively in GIS (Geographic Information Systems) can make a significant impact. Here’s a step-by-step guide to help you through the process of working with geospatial data to maximize its potential in your GIS projects.

Step 1: Understanding Geospatial Data and Its Types

Before diving into finding geospatial data, it's essential to understand its forms and applications. Geospatial data represents geographic information, typically in terms of latitude, longitude, and elevation. The data comes in two main types:

Raster Data: Composed of grid cells or pixels, such as satellite imagery or aerial photographs.

Vector Data: Includes points, lines, and polygons, used to represent specific features like roads, city boundaries, and infrastructure.

Understanding which type of data is needed will set the foundation for your project.

Step 2: Identifying Your Data Needs

Define the scope and objectives of your project. Questions to ask include:

What area does the project cover? Identify the geographic scope.

What data variables are required? For example, temperature, elevation, or land cover types.

How recent should the data be? Some projects require real-time data, while others may use historical data.

What resolution or detail is needed? Higher resolution is useful for local analyses, while lower resolution might be sufficient for regional or global projects.

With this information, you can start searching for the appropriate data sources.

Step 3: Finding Reliable Sources of Geospatial Data

Many public and private organizations provide access to geospatial data. Here are some popular sources:

Government Databases:

USGS Earth Explorer: Excellent for US-specific data, particularly for geological and topographic information.

NASA Earth Data: Free datasets for satellite imagery and climate information.

Copernicus Open Access Hub: Provides data from the European Union's Sentinel satellites.

Global Databases:

OpenStreetMap (OSM): A community-driven mapping platform, providing access to vector data like roads and landmarks.

Google Earth Engine: A robust platform offering global-scale geospatial datasets and processing capabilities.

Natural Earth: Free vector and raster map data at different scales for global use.

Commercial Data Providers:

DigitalGlobe and Planet Labs: These companies offer high-resolution satellite imagery and geospatial data, typically on a paid basis.

For more specialized datasets, reach out to academic institutions or industry-specific organizations. Once you’ve identified potential sources, move on to evaluating the data.

Step 4: Evaluating Geospatial Data Quality

Once you’ve sourced your data, it's critical to assess its quality to ensure it meets your project's requirements. Consider the following factors:

Accuracy: Ensure the data aligns with real-world measurements. Vector data should match the geographic reality, and raster data should align with known resolutions.

Timeliness: Is the data up-to-date, or is historical data sufficient? Projects that monitor trends over time might require datasets spanning multiple years.

Completeness: Verify that the dataset covers your entire area of interest without gaps.

Reliability: Look for metadata, which provides details about data collection methods, processing, and sources. Reliable data is usually backed by documentation.

Compatibility: Ensure the data format (e.g., shapefile, GeoTIFF, KML) is compatible with your GIS software. Most GIS platforms support common formats, but it’s best to double-check.

Evaluating data quality can help avoid costly errors and inaccuracies during analysis.

Step 5: Processing and Cleaning Geospatial Data

Geospatial data often requires cleaning and processing to prepare it for analysis:

Projection and Coordinate Systems: Ensure all data layers use the same coordinate system. Misaligned layers can lead to inaccurate spatial analyses.

Data Transformation: Adjust formats as needed to fit your analysis. For instance, raster data might need to be reclassified for thematic mapping, while vector data may require simplification.

Error Correction: Check for and correct errors like missing values or outliers.

Resampling: For raster data, resampling may be necessary to match different resolutions across datasets.

These steps prepare your data to integrate seamlessly in GIS, minimizing errors during analysis.

Step 6: Conducting Geospatial Analysis in GIS

Once the data is clean and ready, GIS provides powerful tools to analyze and interpret it. Here are a few common types of geospatial analysis:

Spatial Analysis: Use tools like overlay, buffering, and spatial joins to find relationships between different datasets. For example, analyze how close schools are to certain environmental hazards.

Temporal Analysis: For time-based data, use temporal analysis to observe changes over time. This is useful for tracking urban growth, deforestation, or climate patterns.

Statistical Analysis: GIS platforms offer statistical tools that allow you to quantify spatial patterns, helping in hotspot analysis or population density mapping.

Predictive Modeling: Create models that use spatial data to predict future trends, such as urban sprawl or wildlife habitat migration.

Each type of analysis provides unique insights to support data-driven decisions.

Step 7: Visualizing and Presenting Geospatial Data

Good visualization makes data insights accessible. Use GIS tools to create clear, informative maps, and customize visualization elements:

Layering and Symbology: Adjust colors, symbols, and labels to represent different data types clearly. For example, use blue for water bodies and green for vegetation.

Classification: Group data into meaningful categories, like low, medium, and high elevation, for better interpretation.

Legends and Scale Bars: Include legends, scale bars, and north arrows to make maps easy to read and understand.

Presenting data in visually appealing formats enhances comprehension and effectively communicates your findings to stakeholders.

Step 8: Sharing and Storing Your Geospatial Data

Once your analysis and visualization are complete, you may want to share it with others or store it for future use:

Export Options: Most GIS platforms allow you to export maps in various formats, such as PDFs, JPGs, or online interactive maps.

Data Sharing Platforms: Platforms like ArcGIS Online and QGIS Cloud make it easy to share data and maps with collaborators.

Data Storage: Geospatial data files can be large, so store them in a secure location. Cloud storage solutions like Google Drive, Dropbox, or Amazon S3 provide scalable options.

Following these steps ensures that your data is preserved and accessible for future projects.

Final Thoughts

Working with geospatial data requires a blend of technical skills and attention to detail, but the potential insights are invaluable. Choose experienced partner like Magnasoft who hold decades of experience, industry connections, and advanced tools. From sourcing quality data to advanced analysis and visualization, Magnasoft supports every stage of your GIS project, empowering you to make data-driven decisions confidently and effectively.

Start your next GIS project with Magnasoft and unlock the power of precise, reliable geospatial data! For more insights and tips, follow Magnasoft’s updates as we continue to lead in GIS solutions.

[lepton-software]

Optimizing Networks for Efficiency: Strategies and Best Practices

In the ever-evolving landscape of telecoms, network optimization is now a focus for service providing companies searching to enhance performance and offer extraordinary service quality. 

The Role of Fiber Management

Fiber Management is a cornerstone of current network optimization. As  fiber optic networks become the backbone for worldwide connectivity, managing these assets efficiently is important. Fiber management is the systematic management and control of fiber optic cable, connectors and the associated infrastructure to ensure uninterrupted data transmission.

Click to read more.

Originally published: https://leptonsoftware.com/optimizing-networks-for-efficiency-strategies-and-best-practices/

[mapgubbins]

FOI release: discussion paper on Measuring Impact of the Geospatial Commission

Post: 8 August 2024

New blog post on my website:

FOI release: discussion paper on Measuring Impact of the Geospatial Commission

[aranict]

When the only thing you need after a 10h work schedule is to know the distance between two imaginary towns so you can accurately calculate the time to travel between them given the average horse speed so that you can accurately reference this in one line of a fic

[jennaflare]

i really thought the society & sustainability class would be my fave this quarter but NAY. map city baby.

[airwavesdotblog]

High Water Ahead: The New Normal of American Flood Risks

According to a map created by the National Oceanic and Atmospheric Administration (NOAA) that highlights ‘hazard zones’ in the U.S. for various flooding risks, including rising sea levels and tsunamis. Here’s a summary and analysis: Summary: The NOAA map identifies areas at risk of flooding from storm surges, tsunamis, high tide flooding, and sea level rise. Red areas on the map indicate more…

[12thwonderindia]

Dictionary of GIS Terms

Aerial Photography Mapping: The creation of maps based on the interpretation and analysis of aerial photographs, utilizing differences in vantage points and angles to construct detailed representations of the Earth’s surface for planning and analysis.

Cartography and Map Design: The art, science, and technology of creating maps, involving the representation of spatial information visually in order to communicate geographic data effectively and accurately.

Climate Change Mapping: The process of using geographic data and mapping technologies to illustrate and analyze the effects of climate change, including rising temperatures, changing precipitation patterns, and extreme weather events.

Consulting Service: Geospatial consulting services offer expert guidance on the strategic implementation and use of geospatial technologies. This includes Presales support, QA&QC, Staffing, Onshore and offshore support, Proof of support and Business process evaluation.

Data Services: In the context of geospatial solutions, data services refer to the processes and technologies used for managing, storing, retrieving, and distributing geospatial data, facilitating decision-making processes across. It comprises data conflation, data standardization, data management across different sectors.

Environmental Geospatial Studies: The application of geospatial technologies and analytical methods to environmental science, studying spatial patterns and processes affecting ecosystems, biodiversity, climate change, and natural resource management.

Enterprise GIS Framework: An enterprise GIS framework is an integrated approach to managing and utilizing geographic information throughout an organization. It enables the sharing of GIS resources, data, and applications across different departments, improving collaboration and efficiency.

Geographic Coordinate Systems: Frameworks that utilize latitude and longitude to pinpoint precise locations on the Earth’s surface, enabling accurate mapping and navigation worldwide.

Geographic Data Visualization: The technique of representing spatial data through graphical forms, including maps and 3D models, to help users understand geographic patterns, relationships, and trends more effectively, enhancing the interpretability of complex spatial information. Digital Terrain Model (DTM), Digital Elevation Model (DEM) are important 3D models to determine the type of terrain and assets.

Geographic Information Science Education: The academic field focused on teaching the principles, technologies, and applications of geographic information systems, including data collection, analysis, and visualization techniques.

Geofencing Technologies: Digital tools that create defined virtual perimeters around real-world geographic areas, enabling automated alerts or actions when objects enter or leave those boundaries.

Geospatial Big Data Analytics: The analysis of large volumes of geographic data from various sources to discover patterns, trends, and insights, supporting complex decision-making processes.

Geospatial Cloud Computing: This concept involves leveraging cloud technology to store, process, and manage geospatial data, enabling scalable and efficient access to GIS resources and data analysis capabilities from anywhere.

Geospatial Data Integration: The merging of geographical data from diverse sources into a coherent dataset, often involving the alignment of different coordinate systems, formats, and data models, to create a comprehensive spatial representation for analysis and decision-making.(Read More…)

[jcmarchi]

Meta-learning to find every needle in every haystack - Technology Org

New Post has been published on https://thedigitalinsider.com/meta-learning-to-find-every-needle-in-every-haystack-technology-org/

Meta-learning to find every needle in every haystack - Technology Org

The quest to efficiently identify regions of interest in geospatial exploration has recently taken a leap forward with visual active search (VAS). This modeling framework uses visual cues to guide exploration with potential applications ranging from wildlife poaching detection to search-and-rescue missions to identifying illegal trafficking activities.

A new framework for visual active search developed by McKelvey engineers leverages reinforcement learning to improve search performance. An adaptive search approach initially makes a mistake but quickly adapts by learning from it. Image credit: Anindya Sarkar

A new approach to VAS developed at the McKelvey School of Engineering at Washington University in St. Louis combines deep reinforcement learning, where a computer can learn to make better decisions through trial and error, with traditional active search, where human searchers go out and verify what’s in a selected region. The team that developed the novel VAS framework includes Yevgeniy Vorobeychik and Nathan Jacobs, computer science and engineering professors, and Anindya Sarkar, a doctoral student in Vorobeychik’s lab. The team presented its work at the New Orleans Neural Information Processing Systems conference.

“VAS improves on traditional active search more or less depending on search task,” Jacobs said. “If a task is relatively easy, then improvements are modest. But if an object is very rare — for example, an endangered species that we want to locate for wildlife conservation — then VAS offers substantial improvements. Notably, this isn’t about finding things faster. It’s about finding as many things as possible given limited resources, especially limited human resources.”

The team’s VAS framework improves on previous methods by breaking down the search into two distinct modules. The framework first uses a prediction module to produce regions of interest based on geospatial image data and search history. Then a search module takes the resulting prediction map as an input and outputs a search plan. Each module can be updated as human explorers return results from physical searches in real time.

“Instead of an end-to-end search policy, decomposing into two modules allows us to be much more adaptable,” Sarkar said. “We can update our prediction module with the search results during the actual search. Then the search module can learn the dynamics of the prediction module — how it’s changing across search steps — and adapt. In this meta-learning strategy, the search module is basically learning how to search. It’s also human interpretable, so if the model isn’t working properly, the user can check it and debug as needed.”

The major strength of the framework comes from its ongoing incorporation of two deployment levels: the computational model predicts where to search, then humans go out into the world to search. The human component is vastly more expensive in terms of time and other resources required to explore large geospatial areas, so it makes sense to adapt and optimize the computer-generated search plan for a maximally efficient search.

Adaptability in the computer model is especially important when the object sought varies drastically from the objects the model is trained on. Experimental results showed marked improvement by Sarkar, Vorobeychik and Jacobs’ proposed VAS framework over existing methods in various visual active search tasks.

Source: Washington University in St. Louis

You can offer your link to a page which is relevant to the topic of this post.

[geek-cc]

GIS Data Viewer In Leaflet JS — For Standalone & Offline Use

GIS Data Viewer In Leaflet JS��— For Standalone & Offline Use https://medium.com/towardsdev/gis-data-viewer-in-leaflet-js-for-standalone-offline-use-758ed2abe1a7

Runs entirely in client-side JavaScript. Supports GeoJSON, KML and SHP spatial data formats.

[haivoai]

Geospatial Annotation | Ground Truth Data Collection 

Haivo AI provides accurate geospatial annotation and data collection services for machine learning models. Get high-quality ground truth data for your AI projects. 

[lepton-software]

Revolutionize your Fuel Management with Lepton Maps Fuel API

Get Real-Time Fuel Price, Seamless Integration, Enhanced Operational Efficiency and Accurate Data. Click to learn more: https://leptonmaps.com/docs/nearby/fueling_stations

[shakespeariancryptid]

I am once again pinging between hyperfixations like a pinball in a machine.

[autocadservices-erasmus]

Cad Conversion Services

Geospatial services and solutions refer to the use of technology and data to provide insights and solutions for spatial analysis, mapping, and visualization. These services leverage geographic information systems (GIS) and other tools to analyze and interpret data in the context of its geographic location. Geospatial solutions can be used across various industries, including urban planning, transportation, environmental management, agriculture, and disaster response.

Some common geospatial services and solutions include:

1. Geospatial data collection: This involves gathering various types of data, such as satellite imagery, aerial photography, LiDAR data, and GPS data. These data sources are used as a foundation for spatial analysis.

2. GIS mapping and visualization: GIS platforms are used to create maps and visualize data in a geographic context. This allows users to understand patterns, trends, and relationships between different variables.

3. Spatial analysis: Geospatial services enable the analysis of spatial data to derive insights and make informed decisions. This can include tasks like proximity analysis, spatial interpolation, hotspot analysis, and network analysis.

4. Remote sensing: Remote sensing techniques, such as satellite imagery and aerial photography, are used to gather information about the Earth's surface from a distance. This data can be used for monitoring and analyzing environmental changes, land use, and natural resource management.

5. Location-based services: Geospatial solutions can be used to develop location-based services, such as mobile mapping applications, real-time navigation systems, and geofencing.

6. Emergency response and disaster management: Geospatial services play a crucial role in emergency response and disaster management by assisting in the identification of vulnerable areas, planning evacuation routes, and assessing the impact of natural disasters.

7. Urban planning and smart cities: Geospatial solutions are used in urban planning to analyze land use, infrastructure planning, and transportation networks. They also support the development of smart cities by integrating IoT sensors and data analytics for efficient resource management.

Overall, geospatial services and solutions provide valuable insights and tools for decision-makers to effectively manage spatial data and solve complex problems.

At Erasmus, we provide end-end geospatial solutions for critical projects and keep a record of all project works in highly reliable, accurate and cost-effective fashion. We offer various kinds of geospatial and visual services and data analysis in a more tactical manner which is as follows:

[mariacallous]

Mormons!!?!?

https://www.rawstory.com/news/kamala-harris-mormons/

A group of Kamala Harris supporters convened in a virtual call Tuesday evening. It was an eclectic mix with attorneys, lawmakers, podcasters, singers and a mayor. There were, certainly, Democrats on the speaker lists, but also Republicans who have decided to step away from their party’s ticket this year.

What connected all of them? Their Latter-day Saint faith.

Members of The Church of Jesus Christ of Latter-day Saints may be a substantial force in presidential outcomes in deeply red Utah and battleground Arizona, according to speakers, including Mayor of Mesa, Arizona, John Giles, who is Republican, but is a vocal Harris supporter; former Democratic U.S. representative from Utah Ben McAdams; and Salt Lake City Democratic legislators Sen. Luz Escamilla and Rep. Brian King, the latter also being the Democratic gubernatorial nominee in Utah.

Data shows that Latter-day Saints are poised to support Harris “more than any other presidential Democratic ticket in 60 years,” said Jacob Rugh, an associate professor in the Department of Sociology at church-run Brigham Young University, during the call. He cited his research and past races that have moved the needle left in Utah and Maricopa County in Arizona.

“My geospatial analysis shows that areas heavy with LDS chapels in the east valley were most likely to flip blue (in 2020),” Rugh said on Tuesday. Nationwide, in 2020, 1 in 3 Latter-day Saint voters picked the Biden-Harris ticket, and the majority of the faith’s millennial and Gen Z voters chose the Democratic ticket, according to Rugh.

The 2020 Biden-Harris ticket performance in Utah “was the best of any Democratic ticket since 1964. Salt Lake County flipped blue in 2016 and, in 2020, voters did what others said was impossible by flipping four precincts blue in Provo,” Rugh said. He predicts they “will flip even more in 2024.”

There are 2.1 million members of The Church of Jesus Christ of Latter-day Saints in Utah, according to data from the church. It’s the most prominent faith in Utah, which has historically voted red. There are also more than 442,800 members in Arizona.

About 1,400 people tuned into Tuesday’s call, a first from a group called Latter-day Saints for Harris-Walz, which on its social media boasted of as many as 2,600 registrants. The event came the same day Harris announced she had picked Minnesota Gov. Tim Walz as her running mate.

The remarks from presenters, mostly from Utah and Arizona, were preceded by a prayer. Speakers also cited scripture as they spoke about the character of the Republican presidential nominee, former President Donald Trump, and to explain why, in their view, the most Latter-day Saint-aligned candidate is Harris.

Mostly, it was a discussion on how to organize to elect Harris. After all, Rob Taber, an organizer said, Latter-day Saints “from missions and ministering, (are) pretty good at reaching out to people and building bridges.”

However, Taber also advised those on the call not to use ward or stake membership lists when reaching out to people because that violates the church’s neutrality policy.

“But you can share on social media how you’re feeling. This actually does make a big difference,” Taber said.

‘Examine the character’

Ask Mesa Mayor John Giles why he decided to support a Democratic candidate and he may cite the arguments he made in an op-ed he wrote in Arizona Central criticizing Trump’s refusal to accept the outcome of the 2020 election and his disinvestment in cities like Mesa, and where he called on other Arizona Republicans to choose “country over party this election.”

But, he may also mention an admonition he heard at a Latter-day Saint church meeting that encouraged members to be good citizens, to participate in elections and to “examine the character of the candidates.”

“Man, I sincerely hope that we get that admonition this election season, because I think that would help our brothers and sisters to look with fresh eyes at this election,” Giles said on Tuesday.

Giles also cited the church’s stance on defending the U.S. Constitution and how different that perspective is from Trump’s view, he said.

Trump is “more than willing to compromise the rule of law and the United States Constitution to further his own gains,” Giles said. “I think that we have a particular mission as Latter-day Saints to step up and point those things out to our friends inside the church and outside as well.”

Some of the attendees, such as McAdams, said they vote Democrat “not in spite of our religion, but because of our religion,” arguing that “negativity, divisiveness, rage, political violence, discrimination and racism are not of God.”

Utah Senate Minority Leader Luz Escamilla said that, as she was preparing to teach Sunday School, it was clear to her that Trump may not be aligned with Latter-day Saint doctrine. She quoted Elder Dallin H. Oaks, first counselor in the church’s First Presidency.

“He said ‘knowing that we are all children of God, give us a divine vision of the worth of all others and the will and ability to rise above prejudice and racism.’ The current candidate for the Republican Party is literally working tirelessly to create prejudice and racism against Americans,” Escamilla said. “And that alone is a reason why all members of The Church of Jesus Christ of Latter-day Saints should be supporting Vice President Harris for President of the United States in the 2024 election cycle.”

Utah gubernatorial candidate Rep. Brian King also praised Harris’ running mate, arguing that Walz fits into the model he likes to see in the country’s candidates and elected officials.

“He’s the kind of candidate that leaders of our faith have called for us to support, a person of integrity, compassion, with a commitment to service,” King said. “I’m so glad that Vice President Harris has revealed her own personality so clearly in her choice of running mate.”

[zvaigzdelasas]

There’s little doubt that the American government has decided to slow China’s economic rise, most notably in the fields of technological development. To be sure, the Biden administration denies that these are its goals. Janet Yellen said on April 20, “China’s economic growth need not be incompatible with U.S. economic leadership. The United States remains the most dynamic and prosperous economy in the world. We have no reason to fear healthy economic competition with any country.” And Jake Sullivan said on April 27, “Our export controls will remain narrowly focused on technology that could tilt the military balance. We are simply ensuring that U.S. and allied technology is not used against us.”

Yet, in its deeds, the Biden administration has shown that its vision extends beyond those modest goals. It has not reversed the trade tariffs Donald Trump imposed in 2018 on China, even though presidential candidate Joe Biden criticized them in July 2019, saying: “President Trump may think he’s being tough on China. All that he’s delivered as a consequence of that is American farmers, manufacturers and consumers losing and paying more.” Instead, the Biden administration has tried to increase the pressure on China by banning the export of chips, semiconductor equipment, and selected software.

It has also persuaded its allies, like the Netherlands and Japan, to follow suit. More recently, on Aug. 9, the Biden administration issued an executive order prohibiting American investments in China involving “sensitive technologies and products in the semiconductors and microelectronics, quantum information technologies, and artificial intelligence sectors” which “pose a particularly acute national security threat because of their potential to significantly advance the military, intelligence, surveillance, or cyber-enabled capabilities” of China.

All these actions confirm that the American government is trying to stop China’s growth. Yet, the big question is whether America can succeed in this campaign—and the answer is probably not. Fortunately, it is not too late for the United States to reorient its China policy toward an approach that would better serve Americans—and the rest of the world.[...]

Since the creation of the People’s Republic of China in 1949, several efforts have been made to limit China’s access to or stop its development in various critical technologies, including nuclear weapons, space, satellite communication, GPS, semiconductors, supercomputers, and artificial intelligence. The United States has also tried to curb China’s market dominance in 5G, commercial drones, and electric vehicles (EVs). Throughout history, unilateral or extraterritorial enforcement efforts to curtail China’s technological rise have failed and, in the current context, are creating irreparable damage to long-standing U.S. geopolitical partnerships. In 1993 the Clinton administration tried to restrict China’s access to satellite technology. Today, China has some 540 satellites in space and is launching a competitor to Starlink.

When America restricted China’s access to its geospatial data system in 1999, China simply built its own parallel BeiDou Global Navigation Satellite System (GNSS) system in one of the first waves of major technological decoupling. In some measures, BeiDou is today better than GPS. It is the largest GNSS in the world, with 45 satellites to GPS’s 31, and is thus able to provide more signals in most global capitals. It is supported by 120 ground stations, resulting in greater accuracy, and has more advanced signal features, such as two-way messaging[...]

American measures to deprive China access to the most advanced chips could even damage America’s large chip-making companies more than it hurts China. China is the largest consumer of semiconductors in the world. Over the past ten years, China has been importing massive amounts of chips from American companies. According to the US Chamber of Commerce, China-based firms imported $70.5 billion worth of semiconductors from American firms in 2019, representing approximately 37 percent of these companies’ global sales. Some American companies, like Qorvo, Texas Instruments, and Broadcom, derive about half of their revenues from China. 60 percent of Qualcomm’s revenues, a quarter of Intel’s revenues, and a fifth of Nvidia’s sales are from the Chinese market. It’s no wonder that the CEOs of these three companies recently went to Washington to warn that U.S. industry leadership could be harmed by the export controls. American firms will also be hurt by retaliatory actions from China, such as China’s May ban on chips from US-based Micron Technology. China accounts for over 25 percent of Micron’s sales.[...]

The U.S. Semiconductor Industry Association released a statement on July 17, saying that Washington’s repeated steps “to impose overly broad, ambiguous, and at times unilateral restrictions risk diminishing the U.S. semiconductor industry’s competitiveness, disrupting supply chains, causing significant market uncertainty, and prompting continued escalatory retaliation by China,” and called on the Biden administration not to implement further restrictions without more extensive engagement with semiconductor industry representatives and experts.

The Chips Act cannot subsidize the American semiconductor industry indefinitely, and there is no other global demand base to replace China. Other chip producing nations will inevitably break ranks and sell to China (as they have historically) and the American actions will be for naught. And, in banning the export of chips and other core inputs to China, America handed China its war plan years ahead of the battle. China is being goaded into building self-sufficiency far earlier than they would have otherwise. Prior to the ZTE and Huawei components bans, China was content to continue purchasing American chips and focusing on the front-end hardware. Peter Wennink, the CEO of ASML, stated that China is already leading in key applications and demand for semiconductors. Wennink wrote, “The roll-out of the telecommunication infrastructure, battery technology, that’s the sweet spot of mid-critical and mature semiconductors, and that’s where China without any exception is leading.”[...]

Former State Department official Susan Thornton, who oversaw the study as director of the Forum on Asia-Pacific Security at NCAFP, said: “This audit of U.S.-China diplomacy shows that we can make progress through negotiations and that China follows through on its commitments. The notion that engagement with China did not benefit the U.S. is just not accurate.”[...]

One fundamental problem is that domestic politics in America are forcing American policymakers to take strident stands against China instead of pragmatic positions. For instance, sanctions preventing the Chinese Defense Minister, Li Shangfu, from traveling to the United States are standing in the way of U.S.-China defense dialogues to prevent military accidents.

19 Sep 23