November 23rd, 2020 by Andi Thomas
There are several companies and organizations that provide spherical projector technology, but the first one I had ever heard of was Science on a Sphere (SOS) created by the National Oceanic and Atmospheric Administration (NOAA). Originally envisioned in 1995 by Dr. Alexander “Sandy” MacDonald and later patented in 2005, these Science on a Spheres (and other variations) are in hundreds of locations across the United States and abroad to help increase understanding of Earth’s complex processes.
In support of these visualization systems, NEO provides an archive of time-lapse global imagery to display in spherical projections located in the NEO SOS Archive. NEO uses the Content Creation Guidelines by NOAA to provide a time series in the preferred projection, image format, and resolution. There is also a labels.txt file available with each dataset to label the images with the correct acquisition, a color bar file to provide context to each time series, and a PIP text file (.SOS) that points to the labels and color bar file along with extra features like fade in time and frame rate. Please see the SOS Remote App manual to learn how to display NEO’s time-series datasets on your display system using the SOS Remote App.
This service started based on requests and only has part of the NEO archive available. If you see a dataset that is not in the archive on our site and you would like it for your spherical visualization, please send us an email using the Contact Us link below.
Here is a preview of some of the datasets we currently have available in the SOS Archive:
Active Fires from Terra/ MODIS
Aerosol Optical Thickness (Depth) from Terra/ MODIS
Chlorophyll Concentration from Aqua/ MODIS
Land Surface Temperature Anomaly (Day) from MODIS
Net Radiation from CERES
Outgoing Longwave Radiation from CERES
Rainfall from TRMM
Reflected Shortwave Radiation from CERES
Sea Ice Concentration from SSM/I / DMSP
Sea Surface Temperature from Aqua/ MODIS
Sea Surface Temperature Anomaly from AQUA/AMSR-E
February 8th, 2021 by Andi Thomas
A Little Background Information on WMS
The Web Mapping Service (WMS) protocol has been around since 1999 and gives users the capability to access georeferenced maps via machine-to-machine contact. This means you can connect to a WMS server from a software of your choice that has WMS capabilities and load all or some of the datasets that are included on the WMS server you connect to.
There are a couple of required request types by a WMS server: GetMap and GetCapabilities. GetCapabilities provides information on what is available with a WMS service and GetMap provides the image map along with the image-specific metadata. NEO’s Capabilities Document is located on the WMS information page.
How to use the NEO WMS service
There are several ways to connect to NEO’s WMS server with different software. In fact, Wikipedia has a list of software with the WMS capability to explore. For this tutorial, we are going to use a free and open-source desktop geographic information system application called, QGIS. Assuming you have already installed QGIS on your machine, follow these simple steps to get started:
- Open a new QGIS project and go to Layer > Add Layer > Add WMS/ WMTS Layer…
- The Data Source Manager window should have popped up. Click New and the Create a New WMS/ WMTS Connection window will pop up.
- Fill in Name and URL:
- For Name, I am going to call it, “NASA Earth Observations“.
- The NEO WMS URL is: https://neo.sci.gsfc.nasa.gov/wms/wms
- Click OK and you will see the NEO datasets populate in the Layers box.
- You can Select the datasets you want to add to the map from here or, I prefer to close this window and add data to the map from the Browser window.
- From the Browser window, double-click a few of the datasets you would like to add to your map. I am going to add the Blue Marble basemap and the 1 month Chlorophyll Concentration Aqua/ MODIS dataset.
This is just a start to using the WMS service. There are plenty of other ways to use WMS capabilities as long as you have the URL (https://neo.sci.gsfc.nasa.gov/wms/wms) and you know what datasets you want to use from the WMS service.
We would love to hear how you are using our WMS service. Please let us know in the comments below.
December 23rd, 2020 by Andi Thomas
When you are considering which format to download for a NEO image, there are two GeoTIFF format options: GeoTIFF (raster) and GeoTIFF (floating point). This can be confusing at first. Let’s take a look at both examples using the Chlorophyll Concentration dataset to distinguish the two formats.
The image above is what downloads when you select GeoTIFF (floating point). This is a floating-point image file where each cell has a number with a decimal (ex. 1.1111). We call this format “data-like” for our purposes because it has been scaled and resampled as part of the processing of the original source data for NEO and the files are simplifications of the original data. Keep this in mind when you are using NEO imagery for analysis—our datasets should not be used for scientific research because they were not calibrated to the precision needed for scientific analysis. If you want to do your own processing for scientific research, choose the “Download Raw Data” option located in the Downloads box.
To simplify even further, the GeoTIFF (raster) above is an 8-bit color image. The values are stored as 8 bit grayscale and the color table is applied on-the-fly based on those values.
If you have any additional questions or need further clarification, please email us through the “Contact Us” button below.
Create and Apply the Right Color Palette in Adobe Photoshop for your Map Visualization (Part 3 of 3)
October 28th, 2020 by Andi Thomas
We have added the NEO color table to a grayscale image, learned how to accommodate the color blind easily with our maps, and now we are ready to build custom color palettes.
Adobe has an online color wheel that is helpful to use when surfing through different colors. If you are unsure what colors to start with, use the color wheel to give you a few ideas and follow these three steps as a guide for applying colors to your map with the wheel:
Step 1. Play around with the different color functions of the wheel to find a palette you would like to work with. You can work with a different hue and saturation of one color or look at three different complimentary colors. The radio buttons on the side of the wheel will help guide your decision-making. The RGB value for each color is at the bottom. Feel free to also mess with the lightness, hue and saturation sliders to get exactly what you want after the color wheel gives you an output. I decided to use the shades function and make a minty green palette. I plan to use these colors for land and then choose a contrasting color for the water.
Step 2. Open the color table back up for the grayscale image and use the same method as before: Select a couple of rows and change the colors to what you selected on the wheel, gradually moving from light to dark down the color table. Or, see what happens when you move from dark to light down the color table. Does it change the message of the map?
Step 3. Save your color palette for future use.
Alright, I know, that was short and easy. But not so fast, we have a couple more things to learn.
Follow these steps to make your own color palette in Photoshop:
Step 1. Open a new project for a clean slate to make palettes on. Do not worry about the canvas size as long as you have enough space to work with.
Step 2. Using the brush tool at a size that is easy to see, pick and paint a color on the canvas that you want on your map. I chose green because that is what I think of when I think of vegetation.
Step 3. Now open the Color Picker back up and select a color that is lighter (less saturated) and move the hue up the color scale a little bit. Repeat this process but in the other direction for your third color. There is a tutorial by Greg Gunn that has a very similar process but is way more detailed. Please check out the video if you need a little more context on choosing the right colors.
Step 4. I have chosen a few colors to work with and am ready to add them to the color table. Clip the canvas to the colors you would like on your map. Go to Image, Mode, and select Indexed Color. Now open up the Color Table under Image, Mode. The colors you have chosen may be scattered around the table.
Step 5. Select one of your lightest colors on the table and add it to the 5th and 6th rows using the RGB values located on Color Picker. I may choose to add the same colors to three rows instead of two but this is a good starting place.
Step 6. Create a lighter color from the one you just filled in the 5th and 6th rows by toggling hue and saturation in Color Picker and add it to the 3rd and 4th rows. Repeat this process for rows 1 and 2.
Step 7. Now pick a second color that is darker than rows 5 and 6 and add it to rows 7 and 8. Repeat this process all the way down.
Step 8. Choose and apply a contrasting color for the last cell to represent water.
Step 9. Save the color table somewhere that is easy to find and open up a new project with the grayscale NDVI map.
Step 10. Change the mode to Indexed Color and open up the Color Table.
Step 11. Load the color table you just created and see what you think. Feel free to change the colors up or maybe even repeat the steps with an entirely new set of colors. This tutorial is not available to get it right on the first try. We simply want to give you the tools you need to make the right map for your needs.
Create and Apply the Right Color Palette in Adobe Photoshop for your Map Visualization (Part 2 of 3)
October 21st, 2020 by Andi Thomas
Now that we have finished part one and understand how the color table provided with each dataset on NEO is applied to each grayscale map, let’s focus on creating custom color palettes that are easy for everyone to see.
Color-blindness is a common condition that prohibits some individuals (mostly men) from distinguishing between colors. Especially, red and green.
Luckily, there are plenty of resources that can help with creating color-blind friendly maps. Color Brewer is one great place to start for pairing colors together and we will use the site throughout this part of the series to guide our color decision-making.
Follow these steps to surf through Color Brewer and customize a color palette that suits your needs and the color-blind:
Step 1. Navigate to the Color Brewer site and make sure the colorblind safe box is selected.
Step 2. Select 9 classes so you will have plenty of colors to work with for an 8-bit dataset. An 8-bit dataset has 256 values (0-255) which means the color table we are working with is a 16 x 16 grid. This will make more sense when we are looking at the color table in Photoshop. You could select 8 classes so every two rows have a different color, but I like to graduate the color to one row at the end. I encourage you to play around with a few combinations and decide what is best for your map.
Step 3. Instead of the default HEX codes, Select RGB from the drop down.
Step 4. Pick a color scheme. I am going to choose the yellow to green combo under sequential multi-hue. It is similar to what we are displaying now but lighter and I really want the water to be more of a dark blue rather than black.
Step 5. Go back to Photoshop and open the Color Table window again (Image, Mode, Color Table…). To make it easier, my Color Brewer window and Photoshop application are sitting side-by-side on my screen.
Step 6. Select two rows at a time on the color table and change the color using the RBG values that are on Color Brewer for the scheme you selected. Repeat this step as you move down the color bar until you get to the last two rows. Then you can graduate to one row and use the darker colors at the bottom of the scheme for the last two rows. The very last color (0) on the table is the map’s water (technically, it is areas of no data that are also where the oceans are). I chose to make the water a dark blue color rather than black.
Step 7. Save the color table you have created to load to another map if you like what you see.
Spend a little more time trying out different colors and using the options Color Brewer provides. Keep in mind, the map represents a dataset and in this case we are trying to show areas of less and more vegetation. Choose wisely on the colors you want to represent places with dense and sparse vegetation. Next time we will look at creating a custom color palette from scratch and applying it to your map.
Create and Apply the Right Color Palette in Adobe Photoshop for your Map Visualization (Part 1 of 3)
October 16th, 2020 by Andi Thomas
Applying the right color palette to an image is crucial to conveying the right message to your audience. There are obvious no-nos in map-making like, do not color land and water blue because it may look like your entire map is water. Or, do not color a disaster map green because it may convey a message of positivity. This tutorial series will show you how to apply and save different color palettes, but it is important to look into why different colors are chosen, basic color theory, and best practices for choosing the right palette. There is a 6-part series on Earth Observatory published several years ago called the “Subtleties of Color” that is still a great base to start from before making and applying your own palettes. If you already feel comfortable with your knowledge and use of colors, let’s make color palettes!
Each NEO image is natively grayscale and the color table is applied in post-processing to display the colored image on each dataset’s page. Underneath the image is a downloadable Adobe Color Table (ACT) that can be saved and used to create and save color palettes for other grayscale images.
Let’s look at the Vegetation Index (NDVI) MODIS imagery as an example for applying a ready-made color table for the dataset following these steps:
Step 1. Download and save the color palette displayed for the NDVI imagery (filename: modis_ndvi.act) and a grayscale PNG at the temporal and spatial resolution of your choice. I saved the files to my desktop so they would be easy to find.
Step 2. Open Photoshop and load the grayscale NDVI image into a new project.
Step 3. Make sure the swatches window is open. There should be a check mark next to “Swatches” and the window should appear on the top right.
Step 4. In the swatches window, expand the hamburger button on the right and click Import Swatches
Step 5. Navigate to where you saved the ACT file and open the file. You should now see the color palette in the Swatches window under its filename and you will be able to access it later and even reuse some of the colors for your own palette creations.
Step 6. Now go to Image, Mode, and select Indexed Color. Keep the default settings and click Ok. Your image name should have changed to “index”.
Step 7. Go back to Image, Mode and select Color Table…
Step 8. Select Custom from the drop-down menu at the top of the window and click Load…
Step 9. Navigate to the modis_ndvi.act file, select the file, and click Ok.
Step 10. The color applied to the map should now look the same as what is on our site for the MODIS Vegetation Index dataset.
Now we are ready to move on to part 2 where we will learn how to apply a custom color palette that is color-blind friendly. See you then!
September 15th, 2020 by Andi Thomas
Did you know you can use Excel to visualize raster datasets? If not, follow this short tutorial and find out how.
Let’s use the cloud fraction imagery NEO provides for this example.
Step 1. Go to the cloud fraction imagery page and choose the CSV for Excel download option from the drop-down at 1.0-degree resolution for a month and year of your choice. I am going to download the latest monthly image for August 2020.
Step 2. Open the CSV in Excel and select all data except for the latitude and longitude row and column (which are the first row and first column).
Step 3. Find and replace all 9999 values with an empty cell. I pressed the space bar a couple of times in the Replace with: cell. Once you click the Replace All button, an alert message will come up, and you will notice the cells that previously had 9999 are now empty.
Step 4. From the Excel home tab: Select conditional formatting, color scales, and choose one of the 2-color scheme options available or select More Rules… and choose a different minimum and maximum value color. I am going to choose blue for the minimum color and white for the maximum color to create a look similar to what is available on the cloud fraction page.
Step 5. Zoom out using the slider on the bottom right side of the excel window and you will notice the global imagery taking shape.
I remember learning the difference between raster and vector data in my entry-level GIS courses. Vector data is all of the point, line, and polygon data while raster data is made of cells or pixels. I wish my professor would have shown me how to visualize raster data in Excel at the time to really grasp cell values that make up the imagery we see as a whole. It certainly would have been easier to process!
Please share what you process in the comments below. We would love to hear any feedback or suggestions you may have.
September 3rd, 2020 by Andi Thomas
After many years of serving the public with global visualizations of Earth’s system processes, we gathered the most frequent questions visitors of our site ask and answered them for you. The FAQs page can be found on the home page and lives here: https://neo.sci.gsfc.nasa.gov/faq/. Please look these questions over and see if they answer questions you may have had already or discoveries that will help understand our site better.
If you read through the page and still have your own unanswered questions we did not cover, please send us an email using the contact form below and we will make sure you are heard.
August 12th, 2020 by Andi Thomas
On March 11, 2020, COVID-19 was classified as a global pandemic by the World Health Organization. That same month, all New York City non-essential businesses were ordered to close by the governor’s office and several residents fled the city to get away from the rapidly spreading virus. There is typically a significant amount of nitrogen dioxide (NO2) in the air from the burning of fossil fuels during mass transportation, especially in larger cities like New York City. But, because all of the non-essential businesses were closed, along with many transportation lines, there was a significant decrease in NO2 in March 2020 compared to previous years.
By adding the Nitrogen Dioxide dataset to the analysis tool for March 2018, 2019 & 2020, we can compare NO2 levels over one geographic coordinate using the data probe function or over a distance using the plot transect function. For more information on how this is done, check out our post on NEO Analysis in 10 Easy Steps. According to these New York City snapshots, NO2 levels decreased by roughly half in comparison to the previous 2018 and 2019 average NO2 levels when city operations were normal.
The Governor of Sao Paulo, Brazil, Joao Dorio, also ordered a shutdown of the state for two weeks at the end of March 2020 to help slow the spread of the virus. The NO2 levels in April 2020 in comparison to the previous two years also decreased by nearly half.
Global human behavior changed rapidly as COVID-19 spread across the globe and the change can be detected from satellites in space. NASA scientists are monitoring several atmospheric indicators globally, including NO2, to read a global pulse on how our atmosphere is responding. Although NEO datasets are heavily processed for visualization and should not be used for scientific analysis, we can still qualitatively see changes on a global scale.
June 13th, 2019 by Kevin Ward
Effective June 13, 2019, the NEO File Transfer Protocol (FTP) service is no longer available. It has been replaced with access via HTTPS.
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