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EarthExplorer (earthexplorer.usgs.gov) is the U.S. Geological Survey's portal for querying and ordering satellite images, aerial photographs, and cartographic products. You can define an area of interest by address, coordinates, map click, or file upload, set a date range, pick a dataset, and then preview and download or order the results. The workflow below follows the four-step structure the site itself uses: Search Criteria, Data Sets, Additional Criteria, Results.

Step 1: Define your search area

On the Search Criteria tab, choose how you want to specify the area of interest. The available methods are:

• Address or place name — type it into the geocoder field.
• Coordinates — enter them directly.
• Map click — click the map to draw your area.
• File upload — supply a GeoJSON, KML, or Shapefile.
• Feature (GNIS) — search by named geographic feature.
• Path/Row — enter a WRS path and row (see below).

For polygon or point entry, you can set the type. If you use Path/Row, select the WRS type first: WRS2 or WRS1. WRS (Worldwide Reference System) is the grid USGS uses to index Landsat scenes, so Path/Row is the fastest route when you already know which scene you need.

You can also set a date range here to limit results by acquisition date.

Watch the 100-record limit

EarthExplorer caps search results at 100 records. The page states this directly and recommends narrowing your search to avoid exceeding it. To stay under the limit, select a Country, Feature Class, and/or Feature Type. The Feature Type list is long and granular — for example, populated places (city, town, village, settlement), administrative boundaries (borough, county, parish, township), and many natural and cultural features (bay, beach, canal, cape, glacier, and so on). Choosing a specific feature type instead of "All" is the simplest way to cut a large result set down.

Step 2: Select your data sets

Move to the Data Sets tab and choose the collection you want. The portal covers satellite imagery, aerial photographs, and cartographic products, so the right choice depends on your goal:

• Satellite imagery — for example Landsat, which is widely used for land-cover and change studies.
• Aerial photographs — historical and recent airborne coverage.
• Cartographic products — maps and related products.

If you are unsure which collection fits, start broad, run the search, and use the preview in the Results step to judge whether the imagery is suitable before committing to a download or order.

Step 3: Add additional criteria

The Additional Criteria tab lets you filter further. Typical filters include cloud cover and other scene-level attributes. This is where you reduce noise: a low cloud-cover threshold removes scenes that would be unusable for visual interpretation, and geographic filters help you stay within the 100-record cap.

Step 4: Review and retrieve results

The Results tab shows your matches along with a "Total Results Approximated" count and a summary of what you searched:

• the data sets you selected,
• your area of interest,
• the criteria you applied.

Use the preview to confirm image quality and coverage before downloading or submitting an order. If the preview looks wrong — wrong season, too much cloud, off-target footprint — go back and adjust rather than downloading a poor scene.

Common problems and how to fix them

Practical notes

• Login and ordering: EarthExplorer has a Login and a Help/Feedback area, and the workflow includes an order step for products that are not immediately downloadable. Treat login requirements and any access conditions as things to confirm on the site rather than assuming a product is open.
• Start narrow, then expand. Because of the 100-record cap, it is usually faster to begin with a specific feature type and date window and loosen only if you get nothing.
• Preview before you commit. The preview step is the cheapest way to avoid downloading scenes that do not actually cover your target.

For help documentation and advanced map tools, use the Help link on the site; the interface notes that advanced map tools are covered there.

Landsat is a joint NASA and U.S. Geological Survey (USGS) satellite program that has been continuously imaging Earth's land surface for more than five decades. It helps scientists and decision-makers study our planet by providing consistent, repeatable observations of the land—revealing changes like deforestation, urban growth, and shifts in agriculture over time. If you want to understand how land changes are tracked from space, Landsat is the reference dataset to start with.

What Landsat Is

Landsat is a series of Earth-observing satellites operated as a partnership between NASA and the USGS. NASA builds and launches the satellites; the USGS manages the data archive and distributes the imagery. Because the program has run for so long and follows consistent imaging methods, it produces a long-term record of Earth's land surfaces rather than a single snapshot.

That continuity is the key feature: the same kinds of measurements are collected repeatedly, so changes can be compared across years and decades.

How Landsat Captures Earth's Land Surface

Landsat satellites orbit Earth and use sensors to record reflected and emitted energy from the land below. Each pass captures imagery across a wide area, and the satellites revisit the same locations on a regular cycle. This repeat coverage is what makes it possible to build a time series rather than a one-time picture.

In practice, the workflow looks like this:

1. Capture — A satellite sensor records energy from the land surface as it passes overhead.
2. Downlink and process — The data is transmitted to the ground and processed into calibrated imagery.
3. Archive — The USGS adds the scene to a long-term archive.
4. Compare — Scientists stack images of the same area from different dates to detect change.

The expected result is a set of images of the same place at different times, aligned closely enough to compare.

What Kinds of Change Landsat Can Reveal

Because Landsat images the land repeatedly, it can show how the surface changes. Common examples include:

• Deforestation — Forest cover disappearing or fragmenting over time.
• Urban growth — Cities and infrastructure expanding into surrounding land.
• Agriculture — Field patterns, crop cycles, and irrigation changing season to season or year to year.
• Coastal and shoreline change — Land shifting along coasts and rivers.

These are general categories of land-surface change that repeat imagery can make visible. The specific conclusions depend on how the data is analyzed.

Why This Matters for Scientists and Decision-Makers

Landsat data supports practical uses such as:

• Tracking land-cover change over long periods
• Informing land and resource management
• Monitoring agriculture and water use at landscape scales
• Providing evidence for environmental and planning decisions

The value comes from consistency: because the record spans decades and uses comparable methods, it can support comparisons that shorter or one-off datasets cannot.

Where to Explore Landsat Imagery and Data

You can explore Landsat imagery and data through NASA Science, which hosts program information and links to the broader Landsat record. For the official data archive and access tools, the USGS is the distributing partner. Start with NASA Science for the program overview, then follow the data links for actual imagery.

Key Takeaways

• Landsat is a joint NASA/USGS satellite program for observing Earth's land.
• It works by repeatedly imaging the same areas, building a long-term record.
• That record reveals changes like deforestation, urban growth, and agricultural shifts.
• It is used by scientists and decision-makers for land and resource questions.
• NASA Science and the USGS are the places to explore the imagery and data.

The National Mapping Division (NMD) is the USGS organizational unit responsible for national mapping and cartographic products — topographic maps, digital elevation data, and orthoimagery among them. You access those products through EarthExplorer (earthexplorer.usgs.gov), the USGS platform for querying and ordering satellite images, aerial photographs, and cartographic products. Use this guide if you need to find NMD-derived mapping data for a specific place and date range, and you want to know how the search interface narrows results before you download.

What the National Mapping Division covers

NMD is the part of the U.S. Geological Survey that produces and maintains the nation's mapping and cartographic holdings. Its scope, as reflected in EarthExplorer's coverage keywords, extends to the United States, its Territories, and Antarctica.

Products associated with this mapping mission include:

• Topographic and cartographic maps — the classic quadrangle-style map products
• Digital elevation models — gridded terrain data
• Orthoimagery — geometrically corrected aerial and satellite imagery

EarthExplorer is the delivery front end for these holdings. It does not host only NMD material — it also serves satellite and aerial datasets from other USGS programs — so the practical task is filtering down to the dataset you actually want.

How to search NMD mapping products in EarthExplorer

The interface is organized as a four-step flow: Search Criteria → Data Sets → Additional Criteria → Results.

Step 1: Define your area of interest

Under Enter Search Criteria, you can narrow the search area in several ways:

• Type an address or place name (geocoder)
• Enter coordinates
• Click the map to draw a point or polygon
• Upload a GeoJSON, KML, or Shapefile
• Use Path/Row with WRS type (WRS2 or WRS1) — the standard Landsat scene grid
• Use Feature (GNIS) search by feature name

Expected result: the map view and search footprint update to your area, and the criteria panel records what you selected.

Step 2: Select datasets

Move to the Data Sets tab and choose the collection you need. This is where you separate NMD cartographic and elevation products from unrelated imagery holdings.

Step 3: Add additional criteria

Use Additional Criteria to filter by date range and dataset-specific attributes. Date range is set in Step 1 alongside the area, so confirm both before running the search.

Step 4: Review results

The Results tab returns matching scenes and products with a Total Results Approximated count. From here you can preview and place an order.

The 100-record limit and how to stay under it

EarthExplorer caps search results at 100 records. If your area or date range is too broad, you will hit that ceiling and lose the ability to see everything that matched.

The interface tells you this directly: "The search result limit is 100 records; select a Country, Feature Class, and/or Feature Type to reduce your chances of exceeding this limit."

Practical ways to reduce result count:

The Feature Type list is long and granular — for example, populated places are grouped as PPL*CITY*POPULATED PLACE*PPL*SETTLEMENT*TOWN*VILLAGE, and hydrographic features as ARM*BAY*BIGHT*COVE*ESTUARY*GOLF*INLET*SOUND. Choosing a specific class instead of "All" is the fastest way to drop below the limit.

Common sticking points

• Hitting 100 results with no warning sign until the count appears. Set Country and Feature Class before you search, not after.
• Confusing the area-of-interest tools. Path/Row is for scene-grid datasets; address, coordinates, and file upload are for arbitrary footprints. Pick the one that matches your dataset.
• Assuming everything in EarthExplorer is NMD output. The platform aggregates multiple USGS sources, so verify the dataset name against what you need.
• Forgetting the date range. It is set in Step 1, not in Additional Criteria, and it silently limits results.

What to do next

If you know your area and dataset, go straight to EarthExplorer, set the area in Step 1, pick the dataset in Step 2, and check the result count before ordering. If you exceed 100 records, add a Country, Feature Class, or Feature Type filter and re-run. For help with the advanced map tools, EarthExplorer links to its own help documentation from the search page.

Interactive map quizzes help you learn geography by turning recall into a repeated, low-stakes action: you see a map, choose or type an answer, and get immediate feedback. Lizard Point Quizzes is one example built around this loop, offering hundreds of map-based quizzes on countries, states, cities, physical features, and flags, plus trivia and other subjects. They suit self-learners of any age, home and school students, and teachers who want students to practice before a graded test.

What makes a map quiz different from reading a map or textbook

Reading a map or textbook gives you information; a quiz makes you retrieve it. That retrieval step is where the learning happens.

• Active recall instead of passive review. You have to locate the country, name the river, or match the flag rather than just recognize it on a page.
• Immediate feedback. You find out right away whether you were correct, so errors get corrected before they harden into habits.
• Repeatable practice. You can retake the same quiz as many times as you want, which is hard to do with a textbook chapter.

Lizard Point describes its quizzes as "fun, free, interactive map quizzes" and notes the site is used by home, elementary, middle and high schools, colleges and universities, as well as adults who want to follow world news with better context.

How different quiz formats build geographic knowledge

Different quiz types train different kinds of knowledge, so mixing them covers more ground than drilling one format.

Lizard Point also includes a large trivia section covering geography definitions, capitals, landmarks, and geo-history, plus sections on World Leaders and Flags, Art and Artists, and Math worksheets and games for kids. That range means you can stay within geography or branch out when you want variety.

Why immediate feedback and repetition reduce test anxiety

Several teachers quoted on the site point to the same mechanism. Carol Miron of Don Mills Collegiate Institute said the ability to get immediate feedback was valuable, and that practicing before the "test" motivated students to try multiple times and reduced anxiety about being tested. Her students reportedly said things like "That wasn't a test. It was more like a game!" and "Can I try again?"

The pattern is straightforward: when practice is unlimited and low-stakes, a wrong answer costs nothing, so you keep going. By the time a graded quiz arrives, you already know what to expect. Randa Hendricks of Eastern Mennonite School described using the quizzes in class so students could practice all week and arrive at quiz day knowing the format.

How to customize quizzes to what you actually need to study

Rather than working through everything, narrow the quiz to your target region or feature set. Lizard Point states that quizzes can be customized "to make exactly the quiz you need to study." In practice, that means choosing the region, the feature type, or the difficulty level that matches your goal instead of taking a full world quiz when you only need one continent.

A workable routine:

1. Pick one region or feature category (for example, countries of a single continent).
2. Take the quiz once without studying to see your baseline.
3. Review only the items you missed.
4. Retake the same quiz until you can complete it without errors.
5. Move to a new region, then return to earlier ones periodically to keep them fresh.

Tracking progress and saving scores

Lizard Point offers a free account that lets you save your score and track your progress, and teachers can access their students' scores. If you are studying over weeks rather than in one sitting, an account turns isolated quiz attempts into a visible record, so you can see which regions are solid and which still need work. If you only want a quick practice session, you can take quizzes without one.

Fitting map quizzes into a study routine

For self-learners, a short daily session works better than a long weekly one, because the repetition is what drives retention. For teachers, the site's own framing is useful: assign practice during the week so students arrive at a graded quiz already familiar with the format. Cora Roselli, a professor at Conestoga College, reported that her students were engaged and learning "in a fun interactive way," and Jonathan Porter of Michaela Community School in London simply recommended getting kids onto the site because they love it.

The main thing to decide is your goal: broad world knowledge, a specific region, or a specific feature type like rivers or flags. Pick the matching quiz, repeat it until it is automatic, and use saved scores to decide what to review next.

GMAO data is the collection of atmospheric, land surface, ocean, and ozone datasets produced by NASA's Global Modeling and Assimilation Office (GMAO) at Goddard Space Flight Center. You can use it for research and applications spanning weather, subseasonal-to-decadal prediction, and reanalysis — provided you understand that these products come from models combined with observations, not from direct measurement alone. This guide explains what the data covers, how assimilation produces it, and how to pick and access the right product.

What GMAO Data Covers

GMAO's stated research scope spans several Earth system components and timescales. Based on the office's own description, its work and data products address:

• Atmosphere — atmospheric state and dynamics
• Land surface — land-atmosphere interactions and surface fields
• Ocean — ocean state as part of the coupled Earth system
• Ozone — atmospheric ozone and related chemistry
• Subseasonal to decadal — prediction and analysis across timescales longer than typical weather forecasts but shorter than climate projections

This range matters when choosing a product: a dataset built for subseasonal prediction has different strengths and caveats than one built for short-range weather analysis.

How Data Assimilation Produces These Datasets

Data assimilation is the core mechanism behind GMAO products. It combines observations (satellite, in situ, and other measurements) with a numerical model of the Earth system to estimate the state of the atmosphere, ocean, land, and chemistry at a given time.

The practical consequence for users:

• Assimilated products (reanalysis) blend observations and model physics to create a consistent, gridded record. They fill gaps where observations are sparse, but the model's influence means the result is an estimate, not a pure measurement.
• Forecast products start from an assimilated initial state and evolve it forward in time. Skill generally decreases with lead time.

Understanding this distinction is the single most useful thing for interpreting any GMAO dataset correctly.

Finding GMAO Data and Documentation

GMAO data products and their documentation are hosted on the GMAO site at gmao.gsfc.nasa.gov. To locate what you need:

1. Go to the GMAO research site.
2. Navigate to the data products or datasets section (products are organized by system and timescale).
3. Open the documentation for a candidate product before downloading — it describes variables, resolution, time coverage, and known issues.
4. Confirm the product matches your required variables, spatial resolution, and time period.

Because GMAO maintains multiple modeling and assimilation systems, the same variable may exist in more than one product with different characteristics. Always check the specific product page rather than assuming consistency across datasets.

Choosing the Right Product

Use the same dimensions to compare candidates:

If your goal is a consistent historical record for research, a reanalysis product is the usual choice. If your goal is prediction, a forecast product initialized from assimilation is appropriate — and you should expect accuracy to vary with lead time.

Common Limitations and Caveats

• Model influence: Assimilated data reflects both observations and model physics, so it is not a direct measurement.
• Sparse-observation regions: Where observations are limited, the model contributes more, and uncertainty is typically higher.
• Forecast skill decay: Forecast products lose skill as lead time increases; subseasonal-to-decadal products are inherently probabilistic in nature.
• Version differences: Different GMAO systems and versions can produce different values for the same variable. Cite the specific product and version you used.

Quick Decision Guide

• Need a gridded historical record across atmosphere, land, ocean, or ozone? → Look for a GMAO reanalysis product.
• Need predictions beyond typical weather range? → Look for subseasonal-to-decadal forecast products.
• Unsure which product fits? → Start from the GMAO site's product documentation and match variables, resolution, and time coverage to your task before downloading.

For current product names, versions, and access details, consult the GMAO site directly, since these are maintained and updated by the office.