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Hi, I’m a new user in Planet and I’d like to measure the number of people gathering for certain events in Mexico. What would be the best way of doing this?I know the date, time and location of events, which sometimes overlap with the timing when the satellite images are taken. I don’t know too much of remote sensing, but my idea was to measure the spatial distribution of image tone intensities, comparing images of a same location with and without the gathering.I’d appreciate if I could get any feedback on how to implement this! One of my questions is what is the appropriate meters per pixel that image that I should use? What is the minimum size of a gathering that I could detect?Example: I know that in this park (24.022724971695283, -104.67158198775181) there was a political gathering on June 21, 2018 around the time the image was taken. Hopefully, if there were enough people attending, I would be able to observe this, right?Thanks for any directions or suggestions!

Can someone help me to identify the water, which is in some place is covered by trees`?

This question is not about visualization so it may not be related to https://community.planet.com/topic/show?tid=159&fid=3 even there are some similarities. My issue is that I am feeding a Keras model where I need to basically use a 0.0 to 1.0 color space. Now for regular RGB images I would simply do a rescaling with /255. For Sentinel2 I’d do /10000 but what is the correct factor for Planet```PSSceneAsset types    ortho_analytic_4b_sr    ortho_analytic_4b_xml    ortho_udm2```I do not want an individual range per scene but a “standard” rescaling factor. If there are outliers (as with Sentinel2 NIR channel) this would be Ok.thank you very much for your support.

Hello every one!I would like to know if there is any document up to date that contains information about all the satélites, such as its constellation, the day of launch, orbital parameters and so on. I have looked for it and couldn't find anything, if anyone knows where I can find this info other than in Planet Labs public ephemerides I would really apreciated it. Thank you in advance,Oscar Gamallo 

Hi,I am finding difficulties in overlaying osmdata over Planet data. Though we reproject them in the same CRS, they don’t seem to overlay perfectly. Has anyone faced the same issue or would anyone please help us in this regard? Thanks.

One of the members of the NICFI Satellite Data Program asks for support on how to run code, at scale, in Google Earth Engine. If you have experienced and solved a similar problem, let us know if you are able to help! You can also check out this thread.“Currently, I am engaged in a significant endeavor to map forest cover. I am utilizing images from the multispectral Planet mosaics as part of the NICFI initiative, which has proven to be a valuable resource for this activity. However, I am facing significant challenges in processing this data at a national scale, particularly in terms of excessive resource consumption, such as memory, when conducting large-scale analyses (800k sqkm) on the GEE platform. Within the scope of this project, I have been trying to divide the national surface area down to the provincial level to address this issue. Unfortunately, I am still encountering considerable memory overruns. I would like to inquire whether you might have any suggestions for optimizing t

I am new to the platform and can’t find any reference to night-time imagery as I’d like to do a classification of illuminated areas. I can understand not having that imagery stored regularly as it is less applicable to most people. However, could this be tasked, can I find examples of this? Any guidance would be appreciated!

I’d like to know what reasons exist for limiting Planet Data to scientists, researchers, and government and private ventures. I think, like EOBrowser, which Planet Labs just acquired, Planet’s near daily imagery should be offered in a free, quick to access manner to users of the general public like Sentinel data. 

Exciting news to share on this week's community post! NICFI Satellite Data Program has recently joined the GitHub community 🚀📦 Check Out Our Repositories:-Codes-Repository: This repository is filled with open-source code that NICFI users have developed, providing a wealth of knowledge for those looking to learn more or contribute to their projects.-Scientific-Publications: The publications repository features research papers that use NICFI Basemaps. Explore to gain valuable insights into the latest research in the field of forest conservation.🤝 Follow us and contributeWe encourage you to check out NICFI's GitHub account. Follow the account and contribute to our Repositories.

Many development projects require offsets to compensate for habitat and vegetation destroyed in the process of “development”. These offsets require monitoring periodically (annually) to meet their environmental compliance requirements. Periodic use of Planet imagery with suitable analysis (for the asset of interest) would seem an obvious application. I am interested in setting up such a system on a commercial basis but wonredif anyohaths already or if there were any research papers on this topic

INVEMAR has benefited from Planet data in various projects, including mangrove restoration, disaster assessment (post-hurricane Julia) in mangroves and seabeds, and mapping mangrove cover in specific areas of the country. As for the viewer tools they created, daily images and monthly Planet mosaics have been used to analyze the temporal dynamics of coastal marine ecosystems such as mangroves. The products have been collected in ArcGIS Pro and QGIS and processed in GEE to improve the scale of some current developments. Among the projects for which the NICFI Satellite Data Program continues to contribute are mangrove restoration monitoring with the Colombian Ministry of Environment and Sustainable Development (MADS), ecosystem-based adaptation for protection against coastal erosion in a changing climate of MADS and the German Development Bank (KfW), mangrove map of Colombia 2020, and Vida Manglar (Cispatá Blue Carbon Project). Besides, NICFI provides input for reports on the state of mar

Indigenous peoples and local communities are essential to preserving and protecting the world's lands and ecosystems. Because of their reliance on and intimate contact with the environment and its resources, they are among the first to experience the direct effects of climate change (UN, 2007). The importance and potential of including their knowledge and expertise are vital to developing and implementing national policies and agendas to support the proposed Sustainable Development Goals (IPCC AR6). This week, we’re focusing on the organizations that work with indigenous people using the NICFI Data Program, demonstrating their active roles in helping to safeguard the ecosystems that inhabit their lands and territories.As a Level 2 user, the Nature Conservancy utilizes NICFI basemaps and daily imagery to correlate Sentinel-1 SAR data and detect/verify logging roads in Central Africa: this data and the corresponding tool support indigenous communities that are logging and sustainably uti

In recent years, the effects of droughts, aggravated by climate change, have increased in frequency and magnitude, affecting people's livelihoods and food security. Therefore, the "Crowdmapping for Food Security in the Horn of Africa" program aims to address this issue by using cutting-edge technology and community mapping to create an early warning system in Ethiopia’s Lowe Omo Valley. Marcos Moreu, a researcher at UCL, explained the science behind FEWS NET (Famine Early Warning Systems Network) in a blogpost. The tool's main goal is to assist land users in producing terrestrial data so that maps combining satellite and user-generated data from the ground can be more locally relevant. This concept incorporates NICFI Basemaps, allowing participants to localize, on and off-site, the state of resources and map the natural resources to which they have access in an effort to better manage their resources and offer information to assess the severity of the disaster. The researcher highlight

African Parks is an NGO that helps in the rehabilitation and long-term management of national parks in partnership with governments and local communities. They manage national parks and protected areas in 12 countries, including Angola, Benin, the Central African Republic, Chad, the Democratic Republic of Congo, Malawi, Mozambique, the Republic of Congo, Rwanda, South Sudan, Zambia and Zimbabwe. You can check out the organization’s website. In the NICFI Survey carried out in November 2022, they noted they use NICFI Basemaps in GEE to monitor the protected area landscapes they manage in the Central African Republic and Mozambique. More specifically, NICFI basemaps are central to developing a detailed map of the Chinko landscape in the Central African Republic in GEE by combining them with Sentinel-2 data. This data fusion enhanced the resulting vegetation map allowing them to better distinguish between wet and dry forests, woodlands and wet and dry grasslands.

Hi everyone!We are starrting to research on detecting greenhouse gasses emitted by rice crops. This post is to ask you for any information or essays you may have on the topic.The aim is to detect methane emissions with NIR and SWIR bands.Thank you for your help!Kuna’s Team.

CONAFOR, a NICFI level 2 user, uses NICFI Basemaps through QGIS and GEE. They adjusted their workflow so that calibration processes of change detection are performed in PS images. Additionally, they evaluate deforestation alerts for monitoring specific change processes such as settlements and illegal airstrips. Another use of individual Planet imagery is to conduct tests to understand possible underestimates of forest cover loss due to the spatial resolution of Sentinel 2 imagery. For this purpose, they have run change detection algorithms in different images to check the best performance. Finally, they mentioned they have also consumed planet images through the Google Earth Engine tool to generate exploratory change analysis.Here you can see one of their Early Warning Reports on Deforestation. In this one, they focus on Montes Azules and Calakmul.If you like to know more about their work, please follow this link.Taken from CONAFOR - General Partner Reporting to NICFI, November 2022

This week, we’re going to Brazil! Since 2019, deforestation in Brazil has reached record levels. Even only in 2021, more than 13,000 sq km of the Brazilian Amazon were cleared. This was the highest total in 15 years. According to projections, total deforestation will reach almost 15,000 sq km by 2022.InfoAmazonia and PlenaMata examined Planet-NICFI basemaps from 2018 to 2022 and focused on critical areas that helped illustrate how the previous government had a destructive effect on the Amazon.You can check out this link for more information and see how NICFI data is used to detect deforestation in the Brazilian Amazon. 

Apparently, the delete functionality does not currently exist on the Community Platform. But hope it will be implemented in the future.

Next, for Earth Day this month , we will go to Ethiopia, where a NICFI user is using data to pursue NICFI Strategic Objectives 3 "Effective international incentive structures to reduce deforestation in tropical forest countries" and 4. "Increased transparency in land management, land use, value chains and finance". The Consultative Group on International Agricultural Research (CGIAR) reported on their work in the November 2022 survey. With NICFI program data products, including Planet Scope mosaics and Planet Daily images, they conduct visual validation of deforestation alerts, land use/land cover analysis and report on potential drivers of deforestation (e.g., agricultural, illegal logging, mining or natural causes) in Ethiopia.They stream and use the data in Google Earth Engine, QGIS plugin, Collect Earth Online, and Global Forest Change to carry out this.In their response, they mentioned, "Our institute appreciates the continued availability of these images and plans to support nati

For this month's earth day we will report on user stories from around the world and how they use NICFI maps in their workflow.In this first story, we’re going to Indonesia, where Astraea in collaboration with The Nature Conservancy are developing pond and mangrove analyses. They are studying mangrove distribution and canopy cover under the Mangrove Ecosystem Restoration Alliance (MERA) program and other programs that require analysis of this critical ecosystem.Being part of user level 2, the experts explain that they use single images (for small areas) and create mosaics themselves if they need a large area containing a lot of scene data. However, for the use of base maps, these are downloaded for quick validation and evaluation of the study area.If you like to know more about their work, please follow this link Taken from Indonesia Oceans Program team - Astraea - General Partner Reporting November 2022 to NICFI.