Satellite Electric Vehicle Dataset (TESLA,LUCID, RIVIAN

SpaceKnow uses satellite (SAR) data to capture activity in electric vehicles and automotive factories. Data is updated daily, has an average lag of 4-6 days, and history back to 2017. The insights provide you with level and change data that monitors the area which is covered with assembled light vehicles in square meters. We offer 3 delivery options: CSV, API, and Insights Dashboard Available companies Rivian (NASDAQ: RIVN) for employee parking, logistics, logistic centers, product distribution & product in the US. (See use-case write up on page 4) TESLA (NASDAQ: TSLA) indices for product, logistics & employee parking for Fremont, Nevada, Shanghai, Texas, Berlin, and Global level Lucid Motors (NASDAQ: LCID) for employee parking, logistics & product in US Why get SpaceKnow's EV datasets? Monitor the company’s business activity: Near-real-time insights into the business activities of Rivian allow users to better understand and anticipate the company’s performance. Assess Risk: Use satellite activity data to assess the risks associated with investing in the company. Types of Indices Available Continuous Feed Index (CFI) is a daily aggregation of the area of metallic objects in square meters. There are two types of CFI indices. The first one is CFI-R which gives you level data, so it shows how many square meters are covered by metallic objects (for example assembled cars). The second one is CFI-S which gives you change data, so it shows you how many square meters have changed within the locations between two consecutive satellite images. How to interpret the data SpaceKnow indices can be compared with the related economic indicators or KPIs. If the economic indicator is in monthly terms, perform a 30-day rolling sum and pick the last day of the month to compare with the economic indicator. Each data point will reflect approximately the sum of the month. If the economic indicator is in quarterly terms, perform a 90-day rolling sum and pick the last day of the 90-day to compare with the economic indicator. Each data point will reflect approximately the sum of the quarter. Product index This index monitors the area covered by manufactured cars. The larger the area covered by the assembled cars, the larger and faster the production of a particular facility. The index rises as production increases. Product distribution index This index monitors the area covered by assembled cars that are ready for distribution. The index covers locations in the Rivian factory. The distribution is done via trucks and trains. Employee parking index Like the previous index, this one indicates the area covered by cars, but those that belong to factory employees. This index is a good indicator of factory construction, closures, and capacity utilization. The index rises as more employees work in the factory. Logistics index The index monitors the movement of materials supply trucks in particular car factories. Logistics Centers index The index monitors the movement of supply trucks in warehouses. Where the data comes from: SpaceKnow brings you information advantages by applying machine learning and AI algorithms to synthetic aperture radar and optical satellite imagery. The company’s infrastructure searches and downloads new imagery every day, and the computations of the data take place within less than 24 hours. In contrast to traditional economic data, which are released in monthly and quarterly terms, SpaceKnow data is high-frequency and available daily. It is possible to observe the latest movements in the EV industry with just a 4-6 day lag, on average. The EV data help you to estimate the performance of the EV sector and the business activity of the selected companies. The backbone of SpaceKnow’s high-quality data is the locations from which data is extracted. All locations are thoroughly researched and validated by an in-house team of annotators and data analysts. Each individual location is precisely defined so that the resulting data does not contain noise such as surrounding traffic or changing vegetation with the season. We use radar imagery and our own algorithms, so the final indices are not devalued by weather conditions such as rain or heavy clouds. → Reach out to get a free trial Use Case - Rivian: SpaceKnow uses the quarterly production and delivery data of Rivian as a benchmark. Rivian targeted to produce 25,000 cars in 2022. To achieve this target, the company had to increase production by 45% by producing 10,683 cars in Q4. However the production was 10,020 and the target was slightly missed by reaching total production of 24,337 cars for FY22. SpaceKnow indices help us to observe the company’s operations, and we are able to monitor if the company is set to meet its forecasts or not. We deliver five different indices for Rivian, and these indices observe logistic centers, employee parking lot, logistics, product, and product distribution of Rivian, separately. We plotted the production and delivery data of Rivian against the SpaceKnow logistic centers index. SpaceKnow index foresees the production activities of the company and provides the trend of production. Figure 1 - SK Logistic Centers Index (90-day rolling) vs Rivian production and delivery data [Available upon request] All SpaceKnow Rivian indices, employee parking index, product index, and product distribution index, increased in Q4. Activity in these locations gained momentum which supports the increase in production and deliveries. [Available upon request] Figure 2 - SK Employee Parking index (90-day rolling) vs Rivian production and delivery data [Available upon request] Figure 3 - SK Product index (90-day rolling) vs Rivian production and delivery data Delivery Options Data can be visualized and downloaded directly on the dashboard, and charts can be customized using our data explorer. Another access method is via API or email, we deliver our data only in CSV format. All data is available for a free one-month trial. SpaceKnow at its core is a satellite imagery analytics firm. The Nowcasting Packages are just one of many services provided to the financial services industry. Urban growth monitoring, water reservoir monitoring, and open-pit mine volumetrics are just a few examples of SpaceKnow’s extended service offering. 50+ readily available proprietary algorithms and automated pipelines enable us to solve problems of all kinds, quickly and at scale. If you would like to learn more, please contact us: Website: www.spaceknow.com Email: [email protected] LinkedIn: https://www.linkedin.com/company/spaceknow/ Blog: https://blog.spaceknow.com/