You may have heard about a recent re-entering rocket—or part of one, anyway. The 39,200 lbs Long March 5B core fell, uncontrollably, into the ocean on May 9, 2021, nine days after its launch from China. And it’s not the first spacecraft or component to re-enter the Earth’s atmosphere. So how much space junk is orbiting Earth? There are several thousand pieces that are large enough to be tracked. Of these, 26 have returned from space to a launchpad—or hit the water.

With names like Apollo, Cosmos, Pegasus, and even another Long March, it’s clear these objects are out of this world. And yet…they found their way back to Earth. We highlight the largest of these re-entering spacecraft or components, along with the controlled and uncontrolled entries—plus, the countries that launched them on the map below.

View Spacecraft and Satellite Reentry in a full screen map

We used Wikipedia’s table of the heaviest re-entering debris list and paired the data with each object’s splash coordinates. Click through the interactive map to view the space debris field—or where these 26 objects fell. Then, sort by reentry type, reentry timeline, owner, launch information, and more or read on as we launch into the most massive of these spatial objects.

Most Massive Objects Fallen From Space

First things first, let’s go over the size of these falling objects. The 26 spacecraft or their components range in size from 5,300 lbs (a little larger than a rhino) to 260,000 lbs, which is nearly the size of the Statue of Liberty. As for the largest of these already large returning spatial objects? They’re all over 40,000 lbs, as you’ll note on the table below.

Object	Mass (lb)	Mass (kg)	Reentry type	Owner	Reentry year
Mir	260,000	120,000	Controlled	Russia	2001
Skylab	152,000	69,000	Partially Controlled	USA	1979
Salyut 7	88,000	40,000	Uncontrolled	USSR	1991
S-II Stage / Skylab	79,700	36,200	Uncontrolled	USA	1975
Salyut 6	77,000	35,000	Controlled	USSR	1982
STS external tank (Standard Tank)	77,000	35,000	Partially Controlled	USA	1981
STS external tank (Lightweight Tank)	66,000	30,000	Partially Controlled	USA	1983
Cosmos 557	42,800	19,400	Uncontrolled	USSR	1973
Salyut 5	42,000	19,000	Controlled	USSR	1977
Salyut 4	41,700	18,900	Controlled	USSR	1977

The most massive re-entering spacecraft was Russia’s Mir. More than half again as big as the second-largest, the space station’s deorbit was meticulously planned in three stages before ultimately landing in the ocean near Nadi, Fiji. The space station had spent 15 years in service, though its orbit decay and presence of the International Space Station led to its controlled reentry in 2001.

That second-largest returning object was the U.S.’s Skylab. As it was the first American space station, its Earthly return turned into an international media event in 1979, with T-shirts and hats with bullseyes and “Skylab Repellent” with a money-back guarantee, wagering on the time and place of re-entry, and nightly news reports.

The rest of these massive spacecraft or components all weigh in at 88,000 lbs or less. With an idea of the size of these returning objects, let’s move on to the type of re-entry.

Controlled & Uncontrolled Space Debris Re-Entry

Regardless of mass, another important factor of re-entering spacecraft or components is whether their re-entry is controlled or not. During a controlled re-entry, the object may be navigated or follow a preset course. The opposite is true for an uncontrolled entry. Uncontrolled entries have the (albeit slim) chance of crashing somewhere dangerous. Of the 26 spacecraft or components to have re-entered the Earth’s atmosphere, some were controlled, while others ended up uncontrolled or partially controlled.

• Uncontrolled (14)
• Controlled (9)
• Partially Controlled (3)

We’ll begin with the good news: nearly 35% of all re-entries have been controlled. The USSR’s Salyut 1 was the first to intentionally crash, in October of 1971. And when it comes to the need for a “Partially Controlled” category, we can thank the U.S. All three that re-entered between 1979 to 1983 belonged to the country.

The first of many uncontrolled reentries took place in 1964. The U.S.’s Apollo SA-7 CSM BP-15 went into the Indian Ocean. Since then, a total of 14 have followed suit, including the recent uncontrolled re-entry of Long March 5B core (5B-Y2 flight) on May 9, 2021. This wasn’t even the first of its name to re-enter uncontrollably. Almost exactly one year earlier, on May 11, 2020, Long March 5B core (5B-Y1 flight) came back to Earth. Both were launched by China, which leads us to which countries owned these massive controlled—or uncontrolled—objects.

Countries That Launched These Space Objects

While the recent uncontrolled re-entries may make it seem as though China’s space program is always launching something that comes back to the atmosphere, it’s astro-not the country with the most re-entering spacecrafts. Here’s an overview of the countries that launched these heavy objects, only to have them come back to Earth.

• USA (10)
• USSR (9)
• China (3)
• Russia (2)
• NASA (1)
• DLR (1)

As you can see, most of the 26 re-entering spacecrafts or components came from the U.S. Only one of those 10 was controlled: CGRO, which returned to Earth in June 2000 after launching back in April 1991. And as we previously mentioned, the only three partially controlled re-entries came from here as well.: STS external Lightweight Tank, STS external Standard Tank, and Skylab. This makes the other six U.S. re-entries uncontrolled, the names of which you can find on the map.

As for the USSR, seven of the nine total were controlled re-entries, arguably making the socialist state the most responsible when it comes to space object re-entry. The two that were uncontrolled? Salyut 7 and Cosmos 557, both from decades past.

There you have it: the largest space objects to re-enter the Earth, those that were controlled or uncontrolled, and the countries that launched them. Get more insight into your data with custom-made maps. And to continue your exploration of space Earth-side, check out Space Stations with Most Rocket Launches.

What’s better than a resort feel combined with the comfort of a home? While not the biggest house in the world, no lavishness was spared during the construction of 100 of the biggest houses in the U.S. The massiveness of these mansions is based on the square footage of the main house (you read that right, some of these properties have multiple houses).

Still standing or not, these homes are worth remembering. And when it comes to 100 of the largest homes in the country, inquisitive minds want to know about the 10 biggest of 80,000 square feet or above. As for where most of these massive homes are located and who they were built for? Go window shopping for this information and more on the map below.

View Largest houses in the U.S. in a full screen map

According to Wikipedia’s list, these are the 100 largest houses in the United States. We mapped them in seconds via our online mapping tool, enabling us (and you!) to sort by the additional data like square footage, year completed, who the home was built for, architectural style, and the owner and architect. Let’s jump into what we can learn from our mapped data.

Biggest of Already Big Houses

The 100 houses on the map range in size from 39,648 to 178,926 square feet. But the biggest of these already big homes? They’re all 80,000 square feet or above.

1. Biltmore Estate
2. Oheka Castle
3. Whitemarsh Hall
4. Arden House
5. Winterthur
6. Shadow Lawn (tied with Cornelius Vanderbilt II House)
7. Cornelius Vanderbilt II House (tied with Shadow Lawn)
8. Meadow Brook Hall
9. Versailles
10. Florham (tied with Harbor Hill)
11. Harbor Hill (tied with Florham)

Of the largest U.S. houses, Biltmore Estate is #1. This Asheville, North Carolina residence sprawls across 178,926 square feet and was built in 1895 for George Washington Vanderbilt II. The second-largest home in the U.S. also happens to be the last one above 100,000 square feet. It’s the West Hills, New York Oheka Castle, also known as the Otto Kahn Estate (109,000 square feet).

As for Wyndmoor, Pennsylvania’s Whitemarsh Hall, it added up to exactly 100,000 square feet before it was torn down in 1980. Additionally, Arden House takes up 97,188 square feet while Winterthur resides on 96,582. Both West Long Branch, New Jersey’s Shadow Lawn and N.Y.C.’s Cornelius Vanderbilt II House weighed in at 90,000 square feet, though the Vanderbilt home was demolished in 1926. Meadow Brook Hall in Rochester Hills, Michigan sits atop 88,000 square feet.

And while not the actual palace, Versailles comes pretty close at 85,000 square feet in Windermere, Florida. This leaves Florham in Florham Park, New Jersey and Harbor Hill in Roslyn, New York to tie with 80,000 square feet. And even though Harbor Hill was demolished in 1947, these two homes are representative of where most of the hundred are located.

A Large Number of Large Homes Are Here

You’ll find pins representing these 100 large homes all across the country. However, most are located in the Eastern states of New York, New Jersey, or Pennsylvania.

City-wise, six are—or were—in New York City alone. This includes the Cornelius Vanderbilt II House (demolished in 1926), Andrew Carnegie Mansion, Felix M. Warburg House, Otto H. Kahn House, Riverside (demolished in 1948), and Henry Clay Frick House.

On the other side of the country, The Manor, The Pritzker Estate, 457 Bel Air Road, Château des Fleurs, and 10697 Somma Way are all located in Los Angeles. Then there’s the White House, one of five tens-of-thousands square feet homes in Washington D.C.

Additional estates in the capital city include Dumbarton Oaks, the Perry Belmont House, Townsend House, and Anderson House. Three mansions can also be found in Palm Beach, Florida along with Newport, Rhode Island, but let’s see what other insights can be illuminated from the map.

Who Were These Huge Homes Built For?

More than the biggest or the cities home to quite a few, it’s notable that nine of the people these houses were built for are named William (including one of six Vanderbilts). Even more, the following folks had two of these large homes built for them:

• Alfred I. du Pont
• Cornelius Vanderbilt II
• Edward T. Stotesbury
• George Crocker
• Otto Hermann Kahn

Of the five, you may most easily recognize Cornelius Vanderbilt II thanks to his connection to the famous family (and that his namesake home was one of the 10 largest and located, among five others, in the Big Apple). This particular Vanderbilt became the Chairman and President of the New York Central and related railroad lines after his father in 1885. In addition to being the goal of the sixth-largest home in the U.S., the Cornelius Vanderbilt II House, The Breakers, a 62,482 square foot home, was also built for him in Newport, Rhode Island.

As for the other four names, Alfred Irénée du Pont was an industrialist, financier, philanthropist, and member of the influential du Pont family until his death in 1935. His two houses included the 65th largest, dubbed Nemours in Wilmington, Delaware and #88 NYIT de Seversky Mansion in New York. Interestingly, family member Henry Francis du Pont was the architect of the fifth-largest home, Winterthur. And prominent investment banker Edward T. Stotesbury owned the previously mentioned third-largest home in the country: Whitemarsh Hall. That along with El Mirasol (60,000 square feet) were his.

George Crocker, the second vice president of the Southern Pacific Railroad, had both the Crocker-McMillin Mansion (50,000 square feet) and Darlington (45,000 square feet) built for him in Mahwah, New Jersey. As for Otto Hermann Kahn, the man was a German-born American investment banker, collector, philanthropist, and patron of the arts with the second largest home in America: Oheka Castle along with the Otto H. Kahn House (50,316 square feet).

Architectural Style, Owner, Architect & More

You can also sort the map by the 30+ different architectural styles of these homes—and it’s clear Châteauesque is the most popular. Do the same with the owners of these homes or the brilliant architects like Carrère and Hastings (who had a hand in at least eight of these homes) and Horace Trumbauer (the architect of seven). Get to grouping your additional data like this now with BatchGeo. Or, if you’re in the market for the biggest house in the world, learn how to make an open house map. Or if you’re not quite there yet, apartment hunt visually with a custom map.

You do millions of things to get ready for college, your wedding, a newborn baby, even natural disasters. When you’re prepared, the end result is usually better. Why not do the same for your data? While there are many map making tools on the web, BatchGeo users appreciate the customized Google Maps built right from your Excel or Google Sheets data.

BatchGeo takes its best guess with the additional fields in your spreadsheets, but this post will share some key preparations to get the most out of your map. You’ll learn how to customize your spreadsheet’s groups, remove any extraneous text from the numerical data in your spreadsheet, and separate your date field into individual columns, among other things. So let’s jump into how best to prepare your spreadsheet for a map, starting with your non-location fields.

Know How Many Groups Will Appear on Your Map

There are plenty of instances where you’ll find a data source with more information than just location. In these cases, BatchGeo will take the additional data columns in your spreadsheet and group the data together.

If you want more control over how they are displayed, it can be helpful to know ahead of time how many of the groups in your spreadsheet will appear on your map. BatchGeo will prominently display nine groups, while the rest are classified as Others until you click the “Others” group to view the data within. If you want all of the groups to appear, you’ll need to combined categories until just nine are in your spreadsheet.

To see how many groups you have, make a pivot table to count your data. Then, sort the table by descending count to isolate the lowest quantity categories. From here you can decide to combine categories together until you end up with nine or so.

View Famous Protests in American History in a full screen map

Current BatchGeo users might think of these as grouping best practices, though it all boils down to preparing your data beforehand. When your groups include more markers, your map users will better understand the data within. Of course, some grouping data is numeric, which means BatchGeo will create ranges—but only if the data can be interpreted as a number. The next section shows how to remove unnecessary text from your data.

Remove Extraneous Text From Numerical Data

The way BatchGeo groups your additional data like category or type also applies to your numerical data. Take, for example, data about the tallest lighthouses in the U.S. In addition to the lighthouse name and state, the Wikipedia table also contains information about the height, both in feet and in meters.

While these details are great, after you add the data into a spreadsheet, you’ll need to do a bit of formatting to get the most out of any metric data. Specifically, you’ll want to separate the two different measurements into their own columns by splitting “Text to Columns”.

Select the column you’d like to separate. In Excel’s “Data” menu, opt for “Text to Columns…” and select what you’d like to split the column based on: Delimited (characters such as commas or tabs separate each field) or Fixed width (fields are aligned in columns with spaces between each field) in the Text Wizard. Finish the Wizard.

But more importantly, you should remove the feet and m, also via “Text to Columns”. For more information about simplifying complicated data in Excel visit our post on the subject.

Instead, you can indicate the measurement in the heading like so:

This will enable the numerical data to automatically be detected. When you copy and paste it in BatchGeo to be mapped, the numbers will show as ranges. The map below demonstrates the benefit of removing extraneous text from numerical data to enable ranges:

View Tallest lighthouse in the United States in a full screen map

While this is what your map will look like if you keep the text in:

This applies to more than just the feet and meters in the lighthouse example. Among others, you should do this with numerical such as:

• Length
• Weight
• Volume
• Distance traveled
• Number of occurrences
• Light-years, parsecs, and other measurements

But removing any text from your numerical data isn’t the only thing you can do to prepare your data for a map.

Separate Your Date Data

Like types or categories and numerical data, dates also provide important context. For example, dates are included in the table of 550+ Major Plane Crashes. However, more often than not, their format isn’t ideal for a spreadsheet (or a map!). Indeed, you’ll find Pivot Tables and other Excel data analysis tricks used to combine dates for maximum insights. We can do something similar for our maps, but that requires a little data preparation.

Instead of complete dates, you’ll want the components of a date. For example, 1977-03-27 separates into individual columns for Year, Month, and Day. This way, you’re able to more easily sort your data by month or year (or both!) in your Excel spreadsheet. Furthermore, when you make your map, the months will be grouped together as displayed below when you opt for Month.

View 550+ Major Plane Crashes in a full screen map

The years, on the other hand, will automatically range (i.e. 1938 – 1923) as you can see above when you select Year.

Add Decades For a More Interesting Story

One final way to add even more insight to your data when prepping it is by assigning decades to the information. This can be an interesting way to push together data that may otherwise be looked at separately.

The methods we’ve covered in this post are some of the ways we’ve altered spreadsheets before we make our maps. You can get creative and find more. The overarching theme of all these tips is to look for ways to manipulate the data to maximize how it will look on the map.

Look for the interesting pieces of your data before you map it. Alternatively, paste your spreadsheet in and see what BatchGeo does on the first try. You can always edit and adjust later. This way, you can be sure the most important parts of your spreadsheet are properly highlighted on your map.

Get started preparing and mapping your data at batchgeo.com today.