Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsiTechGuides is reader-supported. When you buy through links on our site, we may earn an affiliate commission. As an Amazon Associate I earn from qualifying purchases. Learn more
For most regional land-surface temperature (LST) studies, start with the free USGS Landsat Collection 2 Level-2 Surface Temperature scenes in EarthExplorer. Choose MODIS when frequent, broad-area sampling is more important than fine spatial detail, or ECOSTRESS when its 70 m gridded observations and irregular sampling fit your study. In every case, treat clouds, quality flags, scale factors, acquisition time, and the distinction between surface temperature and air temperature as part of the method—not cleanup work after download.
What satellite land-surface temperature measures
Satellite LST is a radiometric estimate of the temperature of the Earth’s exposed surface “skin.” It responds to the material being observed, its moisture, shading, solar loading, and the satellite’s viewing and acquisition time. A weather station or forecast normally reports air temperature, commonly at a near-surface reference height. Those are different physical quantities: a roof, road, bare soil, or crop canopy can be substantially hotter or cooler than the air above it. NASA’s ECOSTRESS data explanation describes this distinction and warns against reading a satellite pixel as the temperature people experience.
An LST raster is therefore useful for questions such as urban heat patterns, crop and water stress, surface-energy studies, fire and drought context, and month-to-month or year-to-year changes in the temperature of particular land covers. It is not automatically a substitute for a weather-station record. If your question is about human heat exposure or atmospheric conditions, plan a separate comparison with appropriately timed air-temperature observations and a validated method.
Quick wins for a faster PC:
Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →Which open product should you choose?
There is no universally best sensor. Select the product whose archive, spatial support, observation timing, cloud-free availability, and quality information match the analysis you defined before downloading data.
#1 Best Overall
- Powerful Turbo Fan:CAGIWIRU Electric Air Duster have reached speed up to 130000RPM,Can efficient remove dust and debris.With LED light and Three Adjustable Speed to meet with different cleaning tasks.
- With Attached USB C Fasting Charging cable.Charing 3 hours,Enjoy up to 240 minutes of use on the lowest setting, For third speed can use for 25mins.with four charging options to meet with your needs.
- Wide Application:Upgraded attached 5 different nozzles,making it suitable for a variety of scenes, such as car,pet, pc, keyboards, and other electronic devices. It also serves for office and home clean duster.
- Handy Design & Portable:Cordless air duster electric nozzle is Light weight and small size, design and comfortable to hold and space saving, convenient to carry around. You can put it in your room or inside the car without taking up space.
- Warranty & Support: Our Electric air duster comes with 5 years warranty and 24/7 customer service. During this period, if you have any questions,pls kindly feel free to contact us.
| Product family | What it provides | Best fit | Important limits to check | Official documentation and access |
|---|---|---|---|---|
| Landsat Collection 2 Level-2 Surface Temperature | Scene-based, processed surface-temperature products for Landsat 4–9, with mission-specific availability periods. | Regional studies needing a long archive and detailed scene-based mapping. | Cloud and possible cloud-shadow retrieval errors; scene gaps; sensor transitions; product-specific scaling and QA; delivered thermal data are resampled, so nominal spacing is not proof of identical effective resolution. | USGS product page and EarthExplorer access instructions. |
| MODIS MOD11 | A daily LST/emissivity product family. NASA describes generalized split-window retrievals on 1 km pixels and day/night retrievals on 6 km grids. | Broad-area monitoring where regular temporal sampling matters more than fine spatial detail. | Coarser spatial support; different day/night products and grids; cloud and QA screening; collection and compositing choices. | NASA MODIS MOD11 page. |
| ECOSTRESS ECO_L2G_LSTE | Instantaneous LST and emissivity on a global 70 m grid in the NASA Open Data record’s Version 3 product. | Studies that can use finer gridded support and tolerate irregular, scene-dependent observations. | Not a daily wall-to-wall record; observation time and coverage vary; check collection/version, geolocation, QA, and actual scene availability. | ECOSTRESS data portal and the NASA Open Data record. |
The stated pixel or grid size is not a universal statement of thermal resolving power. Landsat thermal measurements are resampled in delivered products, and sensors use different detectors, algorithms, viewing geometries, and sampling patterns. For an effective-resolution claim, consult the specification for the exact instrument and product rather than comparing the three numbers above as if they were equivalent.
Define the study before opening a data portal
Write a one-page analysis specification first. It prevents an apparently convenient download from becoming an incomparable time series.
- Footprint: record the boundary, coordinate reference system, and whether you need a single site, a watershed, an entire city, or a continental region.
- Period: list the years, months, seasons, and acceptable date window. Check that the selected mission actually has products throughout that period; USGS lists mission-specific ranges on its Landsat Surface Temperature overview.
- Observation timing: decide whether day, night, or a particular local-time window is scientifically meaningful. Satellite overpasses are not interchangeable simply because they occur on the same calendar date.
- Spatial support: specify the minimum mapping unit or analysis scale. A 70 m grid, a 1 km pixel, and a 6 km day/night retrieval answer different questions, even after reprojection.
- Missing-data tolerance: decide how many cloudy months or scenes you can accept, and whether your result will use individual observations, a monthly statistic, or a seasonal composite.
- Outcome: distinguish absolute LST, anomalies, rank order, or relative change. Relative analyses still require consistent QA, scaling, timing, and processing.
- Validation: identify any station, logger, flux-tower, or other independent data you will use. Do not call agreement with an air-temperature series “validation” without accounting for the different quantities and observation times.
Download Landsat Collection 2 Level-2 surface temperature
USGS delivers a processed Level-2 surface-temperature product; ordinary users do not need to assemble the atmospheric auxiliary datasets used internally. The Collection 2 workflow depends on Level-1 thermal data, optical inputs, ASTER GED/emissivity information, ASTER NDVI data, and atmospheric profiles or other auxiliary data, but those inputs are not a prerequisite for using the finished Level-2 scene.
Free tools Windows power users keep installed
One-click scans. No signup required.
- Open EarthExplorer through the USGS access route. The USGS Landsat Data Access page lists EarthExplorer and other current options. Create or use the account required by the portal.
- Set the area of interest. Draw a polygon, enter coordinates, upload a boundary, or use a place search. Keep the boundary file and its coordinate system with your project so later downloads are reproducible.
- Set the date range. Use the exact study dates, then allow a practical search window if cloud-free observations are rare. Do not assume one Landsat sensor covers every year; inspect the mission and acquisition date for each result.
- Select the Landsat Collection 2 Level-2 surface-temperature dataset. Confirm that the result is the Level-2 product rather than only a Level-1 scene. Read the scene metadata, processing date, tier or quality information, and available bands and masks before downloading.
- Inspect browse imagery and metadata. A clear-looking red-green-blue image is not proof that the thermal retrieval is valid. Review cloud and cloud-shadow indicators, acquisition time, scene footprint, and any quality flags. USGS documents a known relationship between surface-temperature retrieval errors and clouds, with possible effects from cloud shadows.
- Download the complete package. Preserve the original files, metadata, quality-assurance layers, and product guide version. Do not keep only a converted temperature raster; you will need the original integers and masks to audit processing later.
- Apply the exact scale and offset. Landsat surface temperature is stored in Kelvin-related scaled values. Use the scale factors in the guide for the exact Collection 2 product and sensor you downloaded, then convert Kelvin to Celsius or Fahrenheit only after that product-specific conversion. A coefficient remembered from another Landsat workflow may be wrong.
- Mask before statistics. Use the product’s QA information to exclude cloud, cloud-shadow, fill, saturation, and other invalid or suspect pixels defined for that product. Save the mask logic and the resulting valid-pixel count for every scene.
- Align only after quality screening. Reproject, resample, clip, or aggregate the screened temperature layer using a documented method. Keep the native delivered grid until you have a reason to change it.
USGS has kept its Landsat no-cost open-data policy in place since 2008. That policy covers access to the imagery; it does not remove the need to manage storage, processing, or any software and computing environment you choose.
Rank #2
- Screen Cleaner is Your Screen’s New Bestfriend! - EVEO is proud to present a screen cleaner that’s perfectly suited for your TV. Meet your new screen cleaner, computer screen cleaner, laptop cleaner, iPad cleaner, Macbook,tv cleaner or any other electronic device. Our screen cleaner spray and wipe along with the included plush microfiber cloth, easily removes dust, fingerprints & other smudges on the screen’s surface. Clean effectively for a streak-free screen
- Gentle on your Screens - Our screen cleaner spray and wipes is compatible to be used even for the most sensitive LCD, LED, CRT, and OLED screens in proper use. Be at ease knowing that this product is compatible with all the major brands: LG, SONY, Samsung, Sharp, iPad, iPhone, Android screens, Kindle, PC monitors - we’ve got you covered! Can be used as LCD screen cleaner, tv cleaner, smart tv screen cleaner, and more
- Premium Super Soft Plush Microfiber Cloth - Included in this efficient screen cleaning kit. This screen cleaner spray and wipe has our signature plush microfiber cloth specially designed to comply with screens and monitors and leave them streak-free. Has been shown to effectively absorbs stubborn stains, zero streaks, and no fiber shedding. Always use this together with our screen cleaner for the best results
- Easy-to-Use Screen Cleaner Kit + microfiber cleaning cloth - The EVEO Screen Cleaning Kit will easily be your new favorite tool when it comes to taking care of the things you love most, quick and easy solution for a streak-free screen. Simply screw on the sprayer gun on the screen cleaner bottle. Spray the cleaning liquid onto the microfiber cloth, then wipe the screen until desired cleanliness & shine is achieved.
- Quality Screen Care Kit Worth Purchasing - Enjoy a convenient Screen Cleaner anytime, anywhere you need it. Your satisfaction is our top priority. We stand behind the quality of our products and that’s why, you shouldn’t be worrying at all. We manufacture the Best Screen Cleaner. and can be used for laptop cleaning kit, laptop screen cleaner, tv screen cleaner for smart tv. MacBook screen cleaner, monitor cleaner or screen cleaner spray for electronic devices with microfiber cleaning cloth
Use MODIS when temporal sampling is the priority
NASA’s MOD11 family is designed for repeated LST and emissivity retrievals over broad areas. The MODIS documentation distinguishes a generalized split-window product at 1 km from day/night retrievals represented on 6 km grids. Do not describe every MOD11 output as a uniform 1 km daily layer.
- Open the NASA MOD11 product page and follow its current access links to the appropriate archive or processing service.
- Choose the collection and specific MOD11 product that match your period and whether you need day, night, or both. Record the collection identifier and version in your methods.
- Filter by geographic extent and date, then inspect acquisition or composite timing, cloud and quality flags, and the product’s stated grid.
- Download the LST, emissivity, and QA layers together. Apply the scale and unit instructions in the product documentation before calculating means, anomalies, or trends.
- For monthly or seasonal analysis, state whether you used all valid observations, a mean, a median, a maximum, or another statistic. Report the number of valid observations contributing to each period; a monthly value based on one clear retrieval is not equivalent to one based on many.
MODIS can provide a more regular broad-area record than a scene-by-scene high-resolution workflow, but the coarser support can mix roofs, vegetation, soil, and water within one pixel. That mixture is a measurement characteristic, not a processing error.
Use ECOSTRESS for fine gridded observations with irregular timing
The NASA Open Data record describes ECO_L2G_LSTE Version 3 as an instantaneous global gridded LST and emissivity product with 70 m grid spacing. “Instantaneous” and “70 m” are both important: the grid is fine, but a location is not guaranteed a daily observation or a common local acquisition time.
The Tool Desk
Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →- Start at the ECOSTRESS data portal and check the current collection status and documentation. NASA states that Collection 1 was discontinued in calendar year 2025, so do not copy a Collection 1 tutorial without verifying its replacement.
- Use NASA Earthdata Search or AppEEARS as described by the portal. Select the current collection and the L2 gridded LST/emissivity product, then specify the area and dates.
- Review each observation’s local acquisition time, swath or scene coverage, geolocation, and quality information. Two observations in the same month may represent different parts of the day and therefore different surface states.
- Download the temperature and emissivity layers with QA and metadata. Apply the documented scale, units, and masks for that collection and version.
- Aggregate only after deciding how to handle unequal observation times and missing dates. A monthly median of irregular daytime observations is not directly comparable to a fixed-time daily series unless your design accounts for that difference.
Consult the product-level technical material listed in NASA’s ECOSTRESS algorithm and user-guide index whenever you need algorithm, quality, or geolocation details beyond the catalog description.
Rank #3
- 【Large size】：Measuring 800 x 300 mm/ 31. 5×12 inches, which is wider and taller than others. Large mouse pad can perfectly fit your keyboard and mouse of any size, and there is also ample space for peripherals such as phones, tablets, etc.
- 【LED backlight mouse pad】：Blade Hawks RGB mouse pad provides 7 static modes and 7 dynamic modes will give you the options you are looking for. Power-off memory function remembers the last lighting mode you selected. The super glow fiber Chroma will give you a colorful gaming setup that you want.
- 【Anti-slip rubber base】：Made from Natural rubber, this gaming mousepad will firmly grip your desktop, allowing you to enjoy the ultimate precision in the games you are most passionate about. It also comes with a texture that enhances this ability even further.
- 【Smooth and waterproof surface】: Micro-textured cloth surface, for extremely precise mouse control and a smooth movement. When liquid splashes on the gaming mouse pad, it forms water droplets and slides down. Will not delay your work or gameplay.
- 【Plug and play】: This mouse and keyboard pad is powered by USB, plug and play, no driver required. One button control light modes. Press one time to change the lighting mode, press twice to change the brightness, press and hold about 3 seconds turn ON/OFF.
What to do when every scene is cloudy
A thermal-infrared satellite cannot provide a valid clear-sky surface retrieval through an opaque cloud. Do not replace a cloudy value with the nearest clear pixel, treat a cloud-contaminated integer as ground temperature, or infer a trend from a shrinking set of clear observations without documenting the missingness.
- Search a wider date window. Keep the scientific season or month explicit, but examine neighboring acquisitions when the original window has no usable scene.
- Use a second product family. MODIS may offer more frequent broad-area observations; ECOSTRESS may add a valid observation at a different time; neither automatically has the same spatial support or timing as Landsat.
- Use QA, not appearance alone. Cloud and cloud-shadow masks can identify problems that are not obvious in an RGB browse image. Inspect neighboring pixels and scene metadata when an isolated hot or cold value looks suspicious.
- Quantify the gap. For each month or season, record the number and fraction of valid pixels or scenes. State whether missing periods were excluded, represented as missing, or modeled separately.
- Avoid unjustified interpolation. Filling a cloudy thermal observation with a temporal average or weather-station value changes the quantity being analyzed. If you model missing values, describe the model and its assumptions separately from the satellite measurements.
Scaling, units, and quality assurance
Stored satellite temperatures are commonly scaled integers, not ready-to-plot degrees. USGS specifies Kelvin for Landsat surface temperature and directs users to apply the scale factors in the applicable product guide. Because factors can depend on the exact collection, sensor, and band, this workflow intentionally uses the guide rather than a generic coefficient.
- Keep the untouched source raster and metadata.
- Record the exact collection, sensor, product identifier, processing version, and guide consulted.
- Apply scale and offset before converting Kelvin to Celsius or Fahrenheit.
- Apply fill, cloud, cloud-shadow, saturation, and product-specific quality masks before spatial or temporal statistics.
- Check value ranges after conversion. Implausible values can indicate an unmasked fill code, an incorrect scale, or a unit conversion mistake; they are not evidence of a new physical extreme until investigated.
- Preserve the QA layer and a machine-readable mask or expression so another analyst can reproduce the valid-pixel selection.
For cross-sensor work, perform these steps independently for each product. Do not assume that equal-looking Celsius values have equal uncertainty, acquisition timing, emissivity treatment, or spatial support.
Designing monthly and multi-year comparisons
To study how hot or cold conditions vary by month over several years, build a time series whose observation rules are stable enough to interpret.
Rank #4
- 【Softer and More Comfortable】Vaydeer wrist rest has unique diamond pattern, which is the combination of softness and aesthetics. The materials of wrist rest are improved into higher quality memory foam and covered with silky smooth lycra. The computer wrist rest makes you as comfortable and cushiony as like rest your wrists on clouds.
- 【Ergonomic Wrist Saver】The wrist rests for keyboard and mouse comes with a 17.32×3.15×0.83 inch keyboard wrist pad and a 5.94×3.15×0.83 inch mouse wrist support. Based on ergonomic design, the unique concave shape is the perfect fit for your wrist joints. The wrist rest pad fits most computer keyboards and laptops, improve hand and wrist posture, release your wrist and arm stress.
- 【Non-Slip Rubber Bottom】Featuring an anti-skid silicone base on the bottom, this wrist keyboard support stays firmly in place on your desk, preventing the padding from sliding around, ensuring stable and consistent wrist support during extended computer sessions.
- 【Better Experience & Pain Relief】Our keyboard arm rest is beneficial to alleviate the soreness caused by direct contact and friction between your arm and a hard desk surface, reducing the risk of wrist fatigue or carpal tunnel. The soft texture of memory foam can evenly distribute the pressure around your wrists and provide good support with just enough give.
- 【Helpful in Multiple Scenarios】Whether you're working, studying, writing, typing, gaming, this keyboard and mouse rest combo is an essential accessory to add comfort and support to your hands and wrists. It’s also a great gift for men, women, family, friend, coworker, gamer, teacher, etc.
- Create a calendar of expected observations. List every month and year in the study, then attach available scenes or retrievals and their local observation times.
- Apply one QA policy. Use the same valid-pixel criteria within a product and document any version change. If a sensor or collection changes, mark the transition rather than hiding it.
- Choose a period statistic. A monthly median is less sensitive to isolated extremes than a maximum; a mean uses all valid values but can be affected by uneven clear-sky sampling. Select the statistic from the scientific question, not convenience.
- Track support. Save valid-pixel counts, scene counts, cloud fraction, and the geographic footprint contributing to each monthly value.
- Separate timing effects from climate effects. A day observation in one month and a night observation in another can differ because of the diurnal cycle. ECOSTRESS’s irregular acquisition times make this check especially important.
- Report gaps and transitions. Explain missing months, mission changes, and any shift from Landsat to MODIS or ECOSTRESS. A visually continuous chart can still combine non-equivalent measurements.
For a relative-change study, consistency is usually more valuable than selecting the smallest available pixel. For an absolute-temperature study, include the product’s units, scaling, QA, and any validation or uncertainty discussion so readers know exactly what the number represents.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Resampling and combining sensors without creating false precision
Reprojection and aggregation are analytical choices. Resampling a 70 m ECOSTRESS grid to 1 km does not make it equivalent to a native 1 km MODIS retrieval, and sharpening a coarse product does not recover lost thermal information.
- Choose a target grid from the question and the coarsest meaningful support, not from the visually smallest pixel.
- Record the source projection, target projection, resampling method, grid alignment, and whether statistics were area-weighted.
- Aggregate only after masking invalid pixels. Keep the valid count and, where useful, the fraction of the target cell represented by valid source pixels.
- Align acquisition windows before comparing products. A daytime Landsat scene, a MODIS night retrieval, and an afternoon ECOSTRESS overpass are not a controlled cross-sensor comparison.
- Use overlap periods and independent validation data if you intend to harmonize sensors. The available product descriptions do not establish a universal cross-sensor conversion or a single accuracy figure.
Common mistakes and their fixes
| Symptom | Likely cause | Fix |
|---|---|---|
| Temperatures are enormous or all values are identical. | Stored integers were plotted without the product’s scale and offset, or a fill code was retained. | Re-read the exact collection guide, apply scaling, and mask fill before conversion. |
| A hot patch follows a cloud edge. | Cloud or cloud-shadow contamination in the thermal retrieval. | Use QA masks, inspect neighboring pixels and metadata, and exclude or flag the observation. |
| A “daily” series has large gaps. | Cloud screening, orbit or swath coverage, or an instantaneous product’s irregular sampling. | List valid observations by date, quantify missingness, and do not imply guaranteed daily coverage. |
| Satellite LST disagrees with a weather report. | Surface skin temperature and air temperature are different quantities, often observed at different times. | Compare like quantities, align times, and use a validated relationship if an air-temperature estimate is required. |
| Two sensors show different monthly trends. | Different spatial support, local observation times, retrieval algorithms, QA, or collection versions. | Harmonize the analysis design, document transitions, and avoid claiming disagreement is a physical trend until these factors are evaluated. |
| An old tutorial cannot find its product. | Collection or catalog status changed; ECOSTRESS Collection 1, for example, was discontinued in 2025. | Use the current portal and product guide, and record the collection/version at download time. |
How to document a defensible LST analysis
A reader should be able to reconstruct the dataset and every transformation from your methods section. Report:
- sensor, product family, collection and version;
- download or access date and official portal;
- study footprint, date range, expected observation schedule, and local-time treatment;
- cloud, cloud-shadow, fill, saturation, and other QA rules;
- scale and offset source, units, and Kelvin-to-Celsius or Fahrenheit conversion;
- projection, clipping, resampling, grid alignment, and aggregation method;
- valid-pixel or valid-scene counts and treatment of missing months;
- any sensor transition, cross-product comparison, validation data, and uncertainty discussion.
For Landsat, cite the Collection 2 Surface Temperature documentation and the relevant access page. For ECOSTRESS, cite the current data portal, the Version 3 dataset record, and any product-level guide used. For MODIS, identify the specific MOD11 retrieval and collection rather than citing “MODIS” generically.
Best Value
- 【No Drill Mounted】Cable management tray can be assembled in as little as 3 minutes or less-simply. Side clips easily clampe the edge of desk, pass through the holes on the sides, and secure excess cables with baskets. Desk cable management supports inward or outward installation to meet your needs in different scenarios, and provides you with great convenience when collecting and organizing wires.
- 【Rubber Pad Protects Desk】Wire organizer under desk built-in soft rubber pads on the clamp protect your desk from scratches, so you will not damage your furniture or office.
- 【Sturdy and Beautiful】Cord management under desk is made of high-quality carbon steel and holds about 15 lbs. The wire basket has 2 holes on each side of the tray to enable your cables to pass freely. Cable baskets are suitable for desk thickness use from 0.4" to 2.4".
- 【Space Saving & Keep Organized】Desk cable management tray holds all your power cords, outlet strips, USB hubs and computer transformers hidden from your feet, and the data cables will not enter the vacuum cleaner to keep your desk clean and tidy. Desk wire organizer is also suitable for use in the kitchen and outdoors.
- 【Reduce Safety Risks】Cable tray under desk keeps all plugs away from your kids, no more worry about tripping. Using 2 holes wire tray saves extra space, helps you easily cabling and wire protection. The mesh design is not easy to accumulate dust, but avoids safety accidents caused by messy wires.
Practical choices for common study designs
Detailed mapping of one city across many years
Begin with Landsat Collection 2 Level-2 scenes. Its scene archive and spatial detail can resolve contrasts among built surfaces, vegetation, and open ground better than a kilometre-scale product. Define a consistent seasonal window, screen every scene with QA, and report the mission or sensor for each year.
Regular regional or continental monitoring
Evaluate MOD11 first when broad spatial support and frequent observations outweigh the need to distinguish individual parcels. Select day or night deliberately, retain the product’s stated grid, and report how many valid retrievals support each monthly statistic.
Fine-scale observations where overpass timing can vary
Evaluate ECOSTRESS when its 70 m Version 3 grid and available observations match the footprint. Build the analysis around actual scene dates and local times rather than assuming a regular daily series.
Long-term monthly trend analysis with frequent clouds
Use the product with the best combination of archive coverage and usable observations for your location, and consider a complementary sensor only if you can preserve a clear break in the record. Do not splice products into one seamless trend without addressing spatial support, timing, scaling, QA, and collection differences.
Bottom line
Download the finished Landsat Level-2 surface-temperature product from EarthExplorer when you need a long, scene-based archive; use MODIS for frequent broad-area sampling; and use current ECOSTRESS L2 documentation when finer gridded observations fit an irregular sampling design. Whichever you choose, a defensible result comes from the full chain—study definition, product/version selection, cloud and QA masking, exact scaling, timing-aware aggregation, and an explicit statement that LST is surface skin temperature rather than air temperature.
Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
