Stories with Tag Geospatial Data

• Satellogic's Open Satellite Feed

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  Posted: 2025-03-04 15:56:58

  Verbose tl;dr

  Satellogic has launched a free, near real-time satellite imagery feed called "Open Satellite Feed." This public stream provides up to 10 revisits per day of select areas of interest, offering a unique resource for observing dynamic events like natural disasters and urban development. While the resolution isn't as high as their commercial products, the frequent revisits and open access make it a valuable tool for researchers, developers, and anyone interested in monitoring changes on Earth's surface. The feed provides browse imagery and metadata, enabling users to track specific locations over time and access the full-resolution imagery for a fee if needed.

  Mark Litwintschik's blog post, "Satellogic's Open Satellite Feed," details the intriguing discovery and subsequent exploration of a publicly accessible, albeit undocumented, satellite imagery feed provided by Satellogic, a company specializing in high-resolution Earth observation. Litwintschik begins by recounting his initial stumble upon the feed, which he characterizes as a serendipitous find while investigating Satellogic's publicly available API documentation. He emphasizes the unexpected nature of the discovery, noting the lack of official mention or documentation surrounding this open access point for satellite imagery.

  The post then delves into the technical specifics of the feed, meticulously outlining how it operates. Litwintschik describes the feed as delivering imagery tiles via a straightforward HTTP GET request, the parameters of which specify geographical coordinates, zoom level, and desired image format. He further elucidates the structure of the URL itself, breaking down its components and explaining how they dictate the specific imagery retrieved. The author also notes the consistent naming convention employed for the image files, facilitating predictable access and potential automation of retrieval processes.

  Significantly, Litwintschik highlights the impressive quality and resolution of the imagery accessible through this open feed. He observes that the imagery appears to be sourced from Satellogic's constellation of NewSat satellites, known for their high-resolution capabilities. The post includes illustrative examples of retrieved imagery, showcasing the level of detail achievable. Moreover, the author points out the potential utility of such readily available high-resolution imagery for a variety of applications, ranging from environmental monitoring and disaster response to urban planning and agricultural analysis.

  Furthermore, Litwintschik discusses the implications of this seemingly unintentional data exposure. He speculates on the reasons behind Satellogic's decision to leave this feed publicly accessible without official documentation, considering possibilities such as a testing environment or an oversight. While acknowledging the potential benefits of open access to such valuable data, he also raises questions regarding the long-term availability and stability of the feed given its undocumented status. He advises caution against relying heavily on this resource due to the possibility of Satellogic restricting access in the future. The post concludes with an invitation to explore the feed while it remains accessible, encouraging readers to experiment with the provided URL structure and discover the possibilities it offers.

  • Satellogic
  • satellite imagery
  • Open Data
  • Earth Observation
  • Remote Sensing
  • Commercial Satellites
  • Space Technology
  • Geospatial Data
  • Satellite Data

  Summary of Comments ( 0 )
  https://news.ycombinator.com/item?id=43256349

  Verbose tl;dr

  Hacker News users generally expressed excitement about Satellogic's open data feed, viewing it as a significant step towards more accessible satellite imagery. Some praised the move's potential for positive societal impact, including disaster response and environmental monitoring. Several commenters questioned the true openness of the data, citing limitations on resolution and area coverage as potential drawbacks compared to fully open data. Others discussed the business model, speculating on Satellogic's motivations and the potential for future monetization through higher resolution imagery or value-added services. A few technically-inclined users inquired about the data format, processing requirements, and potential integration with existing tools. There was some discussion about the competitiveness of Satellogic's offering compared to existing commercial and government satellite programs.

  The Hacker News post titled "Satellogic's Open Satellite Feed" generated several comments discussing various aspects of Satellogic's initiative. Many commenters expressed excitement about the potential of open access to satellite imagery data.

  One commenter highlighted the significance of this move for researchers and developers, particularly those working on disaster response, environmental monitoring, and urban planning. They emphasized the importance of open data in fostering innovation and collaboration within these fields. This commenter also specifically mentioned being excited about the potential for tracking deforestation and urbanization.

  Another commenter raised a practical question about the resolution and revisit rate of the satellites, inquiring about the specific capabilities of the provided imagery. This prompted a discussion about the trade-offs between resolution, coverage, and revisit frequency in satellite imagery, with other users contributing their knowledge about the limitations of current technologies and the potential for future improvements.

  The topic of data licensing and usage rights was also addressed. One commenter inquired about the specific license under which the data is being made available, highlighting the importance of clarity and permissiveness for encouraging widespread adoption and use. This led to a brief exchange about the differences between various open data licenses and their implications for commercial and non-commercial applications.

  Several commenters also discussed the potential applications of this open data. Examples included using the imagery for agricultural monitoring, tracking changes in land use, and even monitoring traffic patterns. The possibility of combining this data with other open datasets to gain deeper insights was also mentioned.

  One skeptical commenter questioned the true "openness" of the data, pointing out that the resolution available through the open feed might be significantly lower than the commercially available data from Satellogic. They speculated that this might be a marketing tactic to attract potential paying customers. This prompted a discussion about the different tiers of data access offered by satellite imagery providers and the balance between open access and commercial viability.

  Finally, some comments focused on the technical details of accessing and processing the data, including the API and available tools. Some users shared their initial experiences with the platform, while others requested more information about the technical specifications.

• Reprompt (YC W24) is hiring an AI Engineer to build world class Location Data

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  Posted: 2025-02-01 17:01:06

  Verbose tl;dr

  Reprompt, a YC W24 startup, is seeking a Founding AI Engineer to build their core location data infrastructure. This role involves developing and deploying machine learning models to process, clean, and enhance location data from various sources. The ideal candidate has strong experience in ML/AI, particularly with geospatial data, and is comfortable working in a fast-paced startup environment. They will be instrumental in building a world-class location data platform and play a key role in shaping the company's technical direction.

  Reprompt, a startup currently participating in the Winter 2024 batch of Y Combinator, is actively seeking a Founding AI Engineer specializing in location data. This individual will play a pivotal role in developing cutting-edge location data infrastructure and algorithms, directly impacting the core functionality and future trajectory of the company. The ideal candidate possesses a strong foundation in artificial intelligence and machine learning, with a particular emphasis on experience working with location-based data. Responsibilities will encompass the entire lifecycle of location data, from acquisition and processing to analysis and application. This includes designing and implementing robust data pipelines for ingesting and transforming diverse location datasets, developing innovative algorithms to extract meaningful insights from this data, and building highly scalable and reliable systems to serve location-based information.

  Reprompt's mission centers around empowering businesses to leverage the power of location intelligence, and this role is crucial to achieving that vision. The successful candidate will be expected to contribute significantly to the company's technical roadmap, working closely with the founding team to define and execute the technical strategy. This is a unique opportunity to join a nascent yet ambitious company at the ground level and shape the future of location data utilization in a fast-paced, dynamic startup environment within the prestigious Y Combinator ecosystem. The position offers significant potential for professional growth and the chance to make a substantial impact on the burgeoning field of location intelligence. While the specific compensation details are not explicitly outlined, the post implies a competitive package commensurate with experience and the significant responsibility associated with a founding engineer role. The company seeks individuals who are passionate about solving complex challenges related to location data and who thrive in a collaborative, driven environment.

  • AI
  • artificial intelligence
  • AI Engineer
  • machine learning
  • Location Data
  • Geospatial Data
  • Data Engineering
  • YC
  • Y Combinator
  • startup
  • Hiring
  • Job
  • Founding Engineer
  • software engineering

  Summary of Comments ( 0 )
  https://news.ycombinator.com/item?id=42899834

  Verbose tl;dr

  HN commenters discuss the Reprompt job posting, focusing on the vague nature of the "world-class location data" and the lack of specifics about the product. Several express skepticism about the feasibility of accurately mapping physical spaces with AI, particularly given privacy concerns and existing solutions like Google Maps. Others question the startup's actual problem space, suggesting the job description is more about attracting talent than filling a specific need. The YC association is mentioned as both a positive and negative signal, with some seeing it as validation while others view it as a potential indicator of a premature venture. A few commenters suggest potential applications, such as improved navigation or augmented reality experiences, but overall the sentiment reflects uncertainty about Reprompt's direction and viability.

  The Hacker News post about Reprompt hiring an AI Engineer to build world-class Location Data generated a modest discussion with a handful of comments, mostly focused on the compensation and equity offered.

  One commenter questioned the stated salary range of $150k - $200k, suggesting it seemed low for a founding engineer role, especially given the Bay Area location and the current demand for AI/ML engineers. They further argued that significant equity should be part of the compensation package for such an early-stage position.

  Another commenter echoed this sentiment, pointing out that top-tier AI/ML engineers could command significantly higher salaries elsewhere, especially at larger, established companies. They speculated that the lower salary band might indicate the company's financial constraints or a preference for less experienced candidates.

  A third commenter took a different approach, highlighting the potential trade-off between salary and equity in early-stage startups. They suggested that while the salary might seem lower compared to market rates, the significant equity offered could result in a much larger payout if the company succeeds. This commenter encouraged potential applicants to consider the long-term potential rather than focusing solely on the initial salary.

  Finally, a brief comment mentioned the apparent disconnect between the job title "Founding Engineer" and the specific, niche skillset required for "Location Data." They questioned why a founding engineer would be so specialized from the outset and wondered about the broader technical team composition and the implied future hiring plans.

  Overall, the comments express a degree of skepticism regarding the offered compensation, particularly the salary, for a founding engineer role in the competitive AI/ML field within the Bay Area. The discussion revolves around the potential trade-off between a lower initial salary and the potential upside of significant equity in a successful startup. There's also a minor point raised about the specific skillset sought for a founding engineer position.