Data

In our recent paper, river water depths up to 20 m are inferred from SuperDove imagery and the results are compared with those from Landsat-9 imagery! Vey promising results from the 8-band SuperDove CubeSats! Check out our open access paper here:https://ieeexplore.ieee.org/abstract/document/9810335

Hi everyone,I am currently working with PlanetScope Visual Basemaps, which are licensed under an educational license. According to the product data and specifications, the positioning accuracy is approximately 4.77 meters in high mountainous areas (Kuala Lumpur, Malaysia). The Observation: In my area of interest (hilly terrain), I have observed a distinct color artifact along the boundaries of landslides (the interface between bare soil and vegetation). One edge of the feature consistently shows a Red fringe. The opposite edge shows a Green/Cyan fringe. I am trying to determine if this is an inherent characteristic of the data in steep terrain or something that requires specific post-processing. My Questions:1. Solutions for Color Fringing: What is the recommended method to correct this specific Red/Green sepa

Hello,what package do you purchase to access daily satellite imagery? And is there a package that can be purchased that will give higher resolution than the basic package?

In our recent Agile EO webinar, Transform Tasking Workflows With Tasking Credits and Pelican Imagery, we shared how Tasking Credits work, how Pelican can support and enhance your SkySat workflows, and a peek at the Pelican roadmap. Watch the webinar on-demand now to learn more.  Below are answers to questions from the live event and resources to get you started.             Tanager Questions  Question: For Tanager, what do you mean by sensitivity level?Answer: Tanager has multiple sensitivity modes to allow users to acquire data with varying signal-to-noise ratio (SNR), depending on their needs. Maximum sensitivity mode has an effective integration time that is four times longer than standard sensitivity mode. There is a tradeoff to consider when select

Este estudio caracterizó la dinámica espaciotemporal de la línea de costa en Juanchaco, Buenaventura, para el período 2018-2025, y proyectó su tendencia evolutiva para los años 2030 y 2050. La investigación se basó en el procesamiento de un total de 37 imágenes satelitales de la constelación PlanetScope, con una resolución espacial de 3 metros, las cuales fueron sometidas a correcciones radiométricas y atmosféricas. Para la extracción automatizada de la línea de costa, se aplicó el Índice de Diferencia Normalizada de Agua (NDWI), seguido de un proceso de umbralización y vectorización en ArcGIS Pro. Las líneas resultantes fueron analizadas con el Sistema de Análisis Digital de Línea de Costa (DSAS) v6.0, lo que permitió cuantificar el desplazamiento y identificar patrones espaciales a través de 308 transectos generados cada 20 metros. Se calcularon métricas de tasa de cambio como el Desplazamiento Neto (NSM), la Tasa entre Puntos Extremos (EPR) y la Tasa de Regresión Lineal (L

Just looking for some clarification regarding the harmonization process for the 8-band surface reflectance product. I am particularly interested in using the yellow band surface reflectance. Since harmonization is with Sentinel-2, is there any harmonization/correction that occurs to the yellow and green 1 band, which Sentinel-2 does not have? 

soy nuevo en la plataforma, deseo saber como puedo ver una imagen en alta resolucion cuando importo un KML y quiero ver la resolcuion mejorada dentro del area del poligono de kml 

Hello, I’ve been working with Dove and Super Dove time series to explore in-season variable rate nitrogen adjustments with private sector stakeholders, where NDVI and other indices are key metrics to characterize in-field variability. In some of the scenes (such as the one shared above) I’ve noticed a visual striping pattern, and I am wondering if there is a way to adjust for this, or to know which satellites may be prone to this to avoid them in our analyses. We will eventually be using imagery over large areas and won’t be able to evaluate each scene visually, so an automated way to 1) adjust for the striping, or 2) know which scenes have them to remove from our time series would be quite valuable. Thank you!- Jyoti Jennewein, USDA-ARS

Hi everyone,I'm conducting a crop monitoring project in southeastern Turkey and comparing NDVI values across three platforms (AWS, GEE, and Sentinel Hub) using the exact same Sentinel-2 tiles and date.During this process, I observed consistent NDVI differences across platforms, even when using the same data product level (e.g., L1C).  Scene MetadataDate: 24 August 2024 Tiles: 37SDA, 37SDB, 37SEA, 37SEB AOI: Same polygon used on all platforms Bands: B04 (Red) & B08 (NIR), scaled to [0–1] as needed NDVI Comparison (Tile 37SDA Example) Platform Product

Hello, 

Hi everyone - I am a co-founder and the CEO at Cecil (docs.cecil.earth). We recently launched public sign-up - you can now explore the Cecil platform with no call or setup required.With a few lines of code, you can access data providers like Planet and their Forest Carbon datasets on our Python SDK.Get started in under 5 minutes – here’s the documentation and a quick Loom walkthrough to guide you.Join 80+ data users in our Slack community to share use cases and get support.You’ll start on

Hi everyone, I recently worked with Planet data for the first time. I downloaded two PlanetScope images from the Planetary Explorer (RGB-IR reflectance and I also chose the option to harmonize images with Sentinel-2)I then calculated NDVI for both images and then the average. I am very surprised by the averages I find. In the center of the image a fire happened in between the two dates so I would expect NDVI to decrease (makes sense). However, I am suspicions of the increases in NDVI I see in other areas, that seem to be the same order of magnitude. While this could be an artifact of NDVI just being quite low in general, I was still wondering if there is an issue with comparing data across difference images taken by different satellites?Here is the code I used to process the data (in R):

Hello, Would it be possible for you to release photos of Budapest Pride crowd to get a good assumption about total crowd size? It is very popular in the news now, everyone guessing the attendance. It was on June 28 between 14:00 and 20:00, the marching was between 15:00 and 17:00. https://budapestpride.hu/hir/minden-amit-tudni-kell-a-30-budapest-pride-felvonulasrol/#terkep

In November’s Agile EO episode, we introduced Analysis-Ready PlanetScope (ARPS)—a new offering that accelerates your analytical workflows with pre-processed, harmonized satellite imagery. Watch the webinar on-demand.  Below are some questions we received during the event and resources to learn more. Questions Question: Is there a technical product sheet for today's products?

In the May Agile EO episode, we shared upcoming updates to Planetary Variables for Agriculture. Watch the webinar on-demand for more information. Below are answers to common questions and some questions that we weren’t able to get to during the live event. Senior Product Manager, Ariel Zajdband, provided answers, plus resources to learn more. Question: Are Planetary Variables available globally? Answer:

Hello, I wanted to know if Planetscope images have the same footprint. For a defined AOI, is the pixel position maintained for images from different dates?

Hi community,We are facing the same challenges as reported here: We see that the solution 9 months ago was solved with support team. Wondering if specific tickets are still needed as we are facing exactly the same challenge.Best,Vivian Ribeiro (Meridia's team)

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Dear Planet Company,Hello, I am a fan from China. Recently, a cycling blogger I follow went through a very terrible setback. During his cycling journey, his beloved cat was poisoned and discarded. Since the area was extremely desolate and there were no available surveillance footage, I was wondering if Planet Company could check satellite images or real-time footage within a 5km radius of the following coordinates for the time frame below?Coordinates: 39°11'54" N, 88°55'36" ETime: April 15, 2025, from 16:00 to 19:00 (GMT+8)Thank you for your consideration.

I need assistance in locating or ordering historical high-resolution satellite imagery or video with the following specifications: Location: Coordinates 39.19825652313258°N, 88.93190839404754°E (within a 25 km² area) Time: April 15, 2025, 16:00-19:00 Beijing Time (UTC+8), equivalent to 14:00-17:00 UTC+6 Resolution: Preferably high-resolution imagery or video capable of identifying ground details (e.g., vehicles, people) Purpose: To investigate and reconstruct the truth behind an incident involving the death of a famous pet cat in China that occurred during this time frame. We are seeking high-resolution images or videos from this specific time period. If you offer relevant commercial services, please provide details on availability, pricing, and delivery.Thank you for your assistance!

In the April Agile EO episode, we introduced Single Order Tasking with our partners at SkyFi. Single Order Tasking allows you to fulfill ad hoc projects or individual tasks with a 100% online, pay-as-you-go self-service portal. Watch the webinar on-demand now or jump right in and get started with Single Order Tasking.  Below are answers to common questions and some questions that we weren’t able to get to during the live ev

Hello!I have a set of scenes of the same area, but there’s some slight misalignment between them (like 3 or 4 pixels), this usually isnt a problem, but I need the most precission possible for my use case (measuring coastal recession), so even a small misalaignment could change results greatly. This happens between images from different and same sensors, so it isnt a result of using different sensors (at least i dont think so),beacuse i have some that are correctly aligned. Also, i used the same AIO to download the images from PlanetScope, so the images have the same extent and are clipped to the same area.  My question is, is there any way to download scenes that are correctly aligned, or should I fix it manually? (or is there a faster way to automatically align them?)  Thanks everyone!

I downloaded 8-band analytics ready surface reflectance PlanetScope scenes for a study. I want to create a visualization of one of the scenes with QGIS. However, when I load the scene in QGIS as a raster, it doesn’t look like the agricultural field I’m expecting. I made sure to assign the bands as red = 6, blue = 2, and green = 4.This is how the scene looks in Planet Explorerscreenshot of planet explorer showing a selected image in an AOIThis is how the PlanetScope scene looks rendered in QGISQGIS with the PlanetScope scene in the drawing area The scene looks like an odd mosaic of colors. I realize that the resolution of the unde

Hi all,I’m working with PlanetScope SuperDove UDM2.1 data in ArcGIS Pro and I’m trying to better understand how to interpret and visualize clear pixels in the UDM RGB composite.As I understand it, the default RGB band mapping is: Red = Clear Green = Snow Blue = Shadow To work around this, we’re also testing the individual UDM bands using Extract Bands and the Raster Calculator, creating binary layers like:Con("UDM2_B1" == 1, 1, 0) (assuming Band 1 = Clear), so that: 1 = clear pixel 0 = not clear This is giving us a more direct view of which pixels are flagged as usable. Are we on the right track with that approach?I'd love to hear how others: