Remote Sensing

Remote Sensing is the science of learning about Earth's surface and atmosphere without touching it. Instruments on satellites, aircraft and the ground collect light, infrared radiation and microwaves that have interacted with the surface or air, and analysts turn those measurements into maps, images and numbers. The event rewards one skill above all: taking a measurement from a sensor, a satellite or a map, working out what physical process produced it, and stating a defensible answer with units.

The two divisions use the same toolkit on different problems, and in 2027 they carry different themes. Division B is Observable Earth: reading maps and images, measuring distance, area, elevation and slope, classifying land cover, and recognizing geohazards and Earth-surface processes such as glaciers and rivers. Division C is Climate Change: how sensors collect data, what a fixed list of climate satellites shows about clouds, gases, temperature, sea level and energy flux, and how a planet's energy balance sets its temperature and how fast it changes.

Event format

The binder is your most valuable preparation: both divisions allow any content in any form, so it can hold formulas, satellite and sensor tables, map-reading pages and worked examples. If the event runs lab stations, nothing may be removed from the binder during the event, so build it assuming you cannot rearrange it. Bring the protractors and rulers; map-distance, perimeter and slope questions are much faster with real tools. There are no separate note sheets: everything you want to consult has to be on the binder rings.

Strategy

Split the work by skill. The usual split is physics and calculations for one partner and imagery, maps and data for the other. In Division C, instrumentation and physics (about 25%) and energy balance (about 20%) are mostly algebra that a calculation-minded partner can own, while interpretation (about 35%) and climate processes (about 20%) reward the partner who knows the satellites. In Division B, interpretation is 65 to 75% of the points, so both partners must be fluent with maps, band combinations, land cover and the look of geohazards in each kind of image; the concept partner should also know which equations Division B may ask you to compute (only three). Both partners should know the whole instrument list, because data questions name an instrument and expect you to know what it measures.

Build the binder in layers.

1. Constants and equations: the wave relation, Wien, Stefan-Boltzmann, Kepler, radar range, ground sample distance, NDVI and the energy-balance formula, each with units and a note of which division may calculate it.
2. Sensor table: active or passive, wavelength region, what it measures, a typical use.
3. Satellite table: for each platform in your division's list, its instruments, orbit and what it is known for, plus (Division B) the Landsat band chart and band combinations.
4. Division B map page: scale conversions, area from pixel counts, slope from contours, display types (natural color, false color, thermal, radar, elevation, classified) with one labeled example each, and drainage-pattern sketches.
5. Division C climate page: gas sources and lifetimes, ENSO diagrams, the energy budget figure, and the three heating-rate models.
6. Worked examples: your own solved problem per formula.

Manage the clock. Scan the test, bank the quick recall items, then do calculations, then explanations. For "explain why" questions, write one sentence naming the mechanism and one tying it to the data; points go to quality, not length.

Always write units and a direction. Many lost points are a correct number with no unit, a slope computed with the wrong contour interval, or a percentage with the wrong base.

What the rules cover

The scope below follows the 2027 rules manual: Division B is titled Observable Earth (section 3 of the Division B rules) and Division C is titled Climate Change (sections 3.c to 3.f of the Division C rules). Neither division marks any item as State-only or National-only, so everything applies at every level. The percentages are the stated weights.

Division B: Observable Earth

Division C: Climate Change

Light, radiation and the spectrum

Almost every remote sensing measurement is a measurement of electromagnetic radiation, which travels through vacuum at the speed of light. Its wavelength $\lambda$ and frequency $f$ are linked by the wave relation, and its photon energy depends on frequency alone, so longer wavelengths carry less energy per photon.

The electromagnetic spectrum runs from gamma rays through X-rays, ultraviolet, visible light, infrared and microwaves to radio. The visible band is a narrow slice, roughly 400 to 700 nm. The atmosphere is transparent in some regions (atmospheric windows) and opaque in others. Water vapor and carbon dioxide absorb strongly in several infrared bands, so instruments that image the surface choose windows, while instruments that measure those gases choose wavelengths where the absorption is informative.

Blackbodies and thermal emission

Every object above absolute zero emits radiation. An idealized emitter that absorbs all incident radiation and emits the maximum possible for its temperature is a blackbody. Two laws describe blackbodies. Both are on the Division C list as calculations; in Division B, Wien's law may be calculated but Stefan-Boltzmann is qualitative only. Wien's displacement law says the wavelength of peak emission is inversely proportional to temperature: hotter objects peak at shorter wavelengths. The Stefan-Boltzmann law says the total power emitted per unit area grows with the fourth power of absolute temperature. Doubling a surface's absolute temperature multiplies its emitted power by 16.

Scattering and absorption in the air

When light meets a particle in the air, it can be absorbed (its energy converted to heat or used to excite a molecule), transmitted, or scattered (redirected). The outcome depends on the size of the particle compared with the wavelength. Particles much smaller than the wavelength, such as air molecules, produce Rayleigh scattering, whose strength goes as the inverse fourth power of wavelength. Particles about as large as the wavelength, such as haze, smoke and cloud droplets, produce Mie scattering, which depends only weakly on wavelength and scatters forward more strongly.

Elastic scattering keeps the photon's wavelength (Rayleigh and Mie); inelastic scattering changes it because the photon exchanges energy with the molecule (Raman and Brillouin). Polarization describes the orientation of the electric field. Sunlight is unpolarized, but scattering can partly polarize light from the sky, which makes polarization a useful aerosol diagnostic.

Refraction and the inverse-square law

Refraction is the bending of light as it crosses into a medium with a different speed of light, described by Snell's law, $n_1 \sin\theta_1 = n_2 \sin\theta_2$, where $n$ is the refractive index and the angles are measured from the surface normal. Light entering a denser medium (higher $n$) bends toward the normal. In remote sensing it matters for lenses, for light entering water (the bottom of a clear lake looks shallower than it is) and for the slight bending of light through the atmosphere near the horizon. Division B treats Snell's law qualitatively: know which way the ray bends and why.

The inverse-square law says irradiance from a point source falls as $1/d^{2}$: double the distance and the power per unit area drops to a quarter, because the same power spreads over four times the area. It explains why the solar irradiance at Mars is less than half of Earth's and why an active sensor's echo is weak. Again, Division B asks about it qualitatively; Division C can use it in energy-balance arithmetic.

Two radiometric words are often confused. Irradiance is power arriving per unit area of a surface, in W/m². Radiance is power per unit area per unit solid angle, in W·m⁻²·sr⁻¹, so it describes what a sensor sees looking in one direction. A satellite measures radiance; a surface energy balance uses irradiance.

Sensors and scanning

A sensor is active if it supplies its own energy and measures what comes back. Radar, lidar, laser altimeters and synthetic aperture radar are active. A sensor is passive if it only measures energy that already exists, either reflected sunlight or thermal emission from the surface and atmosphere. Optical cameras, multispectral imagers, infrared radiometers and most climate-monitoring radiometers are passive. The distinction is not about whether sunlight is involved: a camera photographing sunlit land is passive even though the light comes from the Sun.

Radar imaging, interferometry and elevation models

An imaging radar looks sideways and records backscatter, the fraction of its pulse returned toward the antenna. Smooth surfaces such as calm water and runways act like mirrors and send the pulse away, so they look dark. Rough surfaces (forest canopy, plowed fields, rough seas) scatter some energy back and look medium-bright. Buildings and steep slopes facing the radar form corner reflectors and look very bright. Wet soil returns more than dry soil because water raises the surface's dielectric constant.

A synthetic aperture radar (SAR) uses the platform's motion to combine many echoes from one spot, imitating an antenna hundreds of meters to kilometers long, so it reaches meter-to-tens-of-meters detail from orbit, day or night and through cloud. Interferometric SAR (InSAR) compares the phase of two SAR images. Phase differences come from topography (if the two views are from slightly different positions, as in SRTM) or from ground motion between two dates. An InSAR change map shows colored fringes; each full color cycle is a fixed amount of motion toward or away from the satellite (half the radar wavelength, about 2.8 cm for Sentinel-1). Tightly packed fringes mean a lot of motion, for example a swelling volcano, a fault after an earthquake or a city sinking as groundwater is pumped. Division B tests InSAR at this interpretive level only.

A digital elevation model (DEM) is a grid of ground heights. SRTM flew a radar interferometer on the Space Shuttle in February 2000 and produced a near-global DEM; ASTER stereo images produced another. Subtracting an older DEM from a newer one shows where material was removed (a landslide scar, a quarry, a retreating glacier) and where it piled up. Lidar (Division C) times laser pulses instead of radio pulses, so it maps heights and cloud or aerosol layers with fine vertical detail but cannot see through thick cloud.

Doppler radar (Division C) also measures the frequency shift of the echo, which gives the speed of raindrops toward or away from the radar; side-by-side inbound and outbound velocities reveal rotation in a storm. Space-based gravimetry (Division C, GRACE) does not sense light at all: two satellites measure tiny changes in their separation as they fly over regions of more or less mass.

Scanning systems

A satellite builds an image by moving and sampling. A whiskbroom scanner uses a rotating or oscillating mirror to sweep detectors across the track, one ground spot at a time, while the platform moves forward. A pushbroom scanner uses a line of detectors, one per cross-track pixel, that images an entire strip at once; the platform's motion builds the second dimension. Pushbroom designs have no moving mirror, so each pixel is viewed longer, but they need many detectors calibrated against each other.

Imagers, radiometers and spectrometers

An imager forms an image in several bands. A multispectral imager records a handful of broad bands. A radiometer measures radiance or irradiance in a few broad channels without necessarily forming a detailed image, as climate instruments do. A spectrometer records many narrow bands and identifies composition from the shape of the spectrum. Spectra come in three basic types: a continuous spectrum from a hot dense source, an emission spectrum where a hot gas emits only at particular wavelengths, and an absorption spectrum where a cooler gas removes particular wavelengths from a continuous background. Gas identification relies on absorption features.

A band ratio divides one band by another (NDVI is a normalized version). Ratios cancel brightness differences caused by slope and shadow, and they isolate features: a ratio of a band inside a gas's absorption line to a nearby band outside it measures how much of that gas lies along the path. OCO-2 uses this idea in the 1.6 and 2.06 µm CO₂ bands, with an oxygen band as reference for the air column. The Division C list now also names atmospheric interactions with the terrestrial biosphere: plants draw down CO₂ each Northern Hemisphere summer and release it in winter (seen in OCO-2 maps), wetlands emit methane (seen by TROPOMI), fires release CO and aerosol, and healthy leaves emit a faint solar-induced fluorescence in the far red, which OCO-2's spectrometer retrieves near 760 nm as a measure of photosynthesis.

Orbits and satellites

Satellites stay in orbit because gravity supplies the centripetal force that bends their path around Earth. The orbit's altitude sets its period, how much of the planet it sees at once and how fine its detail can be. Both divisions list orbit types by name, but the lists differ: Division B names low, medium and high Earth orbit, polar and non-polar, geostationary and geosynchronous; Division C adds sun-synchronous and uses the abbreviation HEO.

A sun-synchronous orbit is slightly retrograde, which makes Earth's equatorial bulge swing the orbit plane eastward by about 1° per day, matching the Sun's apparent motion. Consistent local time matters because comparing two dates only means something if shadows and sun angle are similar.

Kepler's laws describe every such orbit. (1) Orbits are ellipses with the central body at one focus. (2) A line from the central body to the satellite sweeps equal areas in equal times, so the satellite moves fastest at perigee and slowest at apogee. (3) The square of the period is proportional to the cube of the semi-major axis.

Division C may calculate with Kepler's third law; Division B treats it qualitatively (higher orbit, longer period). The law also gives a ratio method that skips the constants. If one orbit's radius is 4 times another's, its period is $4^{3/2} = 8$ times longer. A planet at 4 AU has an 8-year period if one at 1 AU has 1 year.

Coverage, swath and revisit

Low orbits give finer spatial detail for the same instrument, because each detector's ground footprint shrinks with altitude. The price is coverage: a low satellite sees a narrow strip, the swath. A geostationary satellite sees a hemisphere and images a storm every few minutes, but with coarser pixels.

Do not confuse three periods. The orbital period is the time for one orbit. The revisit period (repeat cycle) is the time between images of one location, set by the orbit, the swath and any off-nadir pointing. For a camera that takes frames, the frame rate must be high enough that successive frames just touch along the track: $f = v_{g}/L$, where $v_{g}$ is the speed of the ground track and $L$ the along-track footprint length.

Image quality: resolution and signal

Image quality has four independent parts, and both divisions test each one. Spatial resolution is the smallest ground feature a sensor can distinguish. Spectral resolution is the number and width of the bands it measures. Radiometric resolution is how many brightness levels it can distinguish, limited in practice by noise. Temporal resolution is how often it revisits a location. A sensor can be excellent in one and poor in another, so always name the type of resolution a question is asking about.

Spatial resolution has two closely related quantities that students confuse. The instantaneous field of view (IFOV) is the angle one detector element sees. The ground sample distance (GSD) is the ground size of one pixel. The field of view (FOV) is the whole angular width the sensor can see. Only the GSD is measured on the ground, and it is the pixel size, not the resolution limit. The calculations below belong to the Division C imaging-quality item; Division B needs the ideas (lower altitude or a narrower IFOV gives smaller pixels) but not the arithmetic.

Signal-to-noise ratio and sensitivity

Division B limits radiometric resolution to signal-to-noise ratio and sensitivity. The signal-to-noise ratio (SNR) is how strong the measured signal is compared with the random noise of the detector and electronics. A high SNR means two surfaces with slightly different brightness can be told apart; a low SNR buries small differences in speckle and grain. Sensitivity is the smallest change in radiance (or, for a thermal sensor, temperature) the instrument can reliably detect. Dark targets such as water and dim bands such as narrow thermal or SWIR channels have the lowest signal, so they suffer most from noise. Larger pixels, longer viewing time per pixel (one reason pushbroom sensors outperform whiskbroom ones) and cooled detectors all raise SNR.

Radiometric resolution is also described by bit depth: an 8-bit sensor records $2^{8} = 256$ levels per band and a 12-bit sensor records $2^{12} = 4{,}096$. Finer quantization does not help if the noise is larger than the level spacing, so a high bit depth with a low SNR gives little extra information.

Reading maps and images (Division B)

Interpretation is 65 to 75% of Division B points, so this section deserves the most practice. Read the map before you read the feature. A map's marginal information (title, location, date, scale, orientation or north arrow, legend and labels) controls every measurement you make on it. Check the scale, the units, the date and which way is up before you measure; a "change" question is meaningless until you know the two dates.

Display types

The 2027 list names the displays you must read. Each answers a different question.

Scale, distance, perimeter and area

A representative fraction scale such as 1:24,000 means one unit on the map equals 24,000 of the same unit on the ground. A bar scale gives the same information graphically and stays correct if the map is enlarged. Ground distance is map distance times the scale denominator, and a perimeter is the sum of such distances around a feature. Area is the number of pixels or grid squares times the area each one covers; for a satellite image, one pixel covers the square of its ground size.

Elevation, altitude and slope

Elevation is the height of the ground above sea level; altitude usually refers to the height of something above the ground or sea level, such as an aircraft or satellite. Contour lines connect points of equal elevation, and the contour interval is the elevation step between adjacent lines. Closely spaced contours mean a steep slope; widely spaced ones mean gentle ground. Elevation between two contours is estimated by interpolation.

Classifying land cover

A land-cover map labels each pixel with a class such as water, forest, cropland, or built-up area. Two approaches dominate. In supervised classification, the analyst supplies training areas of known cover type, and the algorithm assigns every other pixel to the class it most resembles. In unsupervised classification, the algorithm first groups pixels with similar spectral signatures into clusters without any training data; the analyst then decides which land cover each cluster corresponds to. The difference is who supplies the labels: supervised methods need labeled examples before classification, and unsupervised methods need labels afterward.

Land-cover change is measured by comparing classified maps from two dates, or by comparing a spectral index across dates. The National Land Cover Database (NLCD) change index, a Landsat-based product for the conterminous United States, is of this kind. Describe the change the data show (forest to cropland, urban expansion) and remember the image shows a change in cover, not its cause. The 2027 rules group the human and environmental implications as their own item: habitat loss (forest or wetland pixels converted and fragmented into smaller patches), land-cover change in general, urbanization (impervious surface growing outward, hotter in thermal images, brighter in radar), deforestation (NDVI loss, often in fishbone patterns along new roads) and damage assessment and monitoring (before-and-after pairs after a flood, fire or earthquake, often from radar because it sees through cloud and smoke). A strong answer names the evidence in the image, the change it shows, and one consequence for people or ecosystems.

Vegetation and spectral indices

The normalized difference vegetation index (NDVI) compares near-infrared and red reflectance. Healthy vegetation absorbs red light for photosynthesis and reflects near-infrared strongly, so it has high NIR and low red reflectance. NDVI is a ratio, so it ranges from $-1$ to $+1$ and partly cancels out differences in overall brightness.

The 2027 rules do not name NDVI, but they list vegetation change in forests and farmland, and NDVI is the standard way to measure it; it also appears in archive questions (for example, which MODIS channel responses signal healthy vegetation). Bare soil gives values near zero to slightly positive, and open water gives values near or below zero.

Division B platforms, bands and band combinations

The Division B list is short, so learn each platform's sensor type, bands, pixel size and coverage. ECOSTRESS and GOES are new to the Division B list in 2027: ECOSTRESS gives fine-scale surface temperature (urban heat islands, crop water stress, lava flows), and GOES gives a near-continuous view of fires, smoke, volcanic ash and storms over the Americas. Figures below are standard published mission values; a test will give any value you need, but you should recognize them.

Spectral signatures are the key to using bands. Healthy vegetation absorbs blue and red for photosynthesis, reflects a little green, then jumps to high reflectance in the NIR (the "red edge"), with SWIR reflectance lowered by leaf water. Water is dark everywhere, almost black in NIR and SWIR. Bare soil reflectance rises smoothly with wavelength and drops when wet. Snow is bright in visible light but dark in SWIR, while cloud stays bright in SWIR, which is how the two are told apart.

A band combination assigns three bands to the red, green and blue display channels. Band numbers shift between sensors: Landsat 8 and 9 add a coastal band at number 1, so TM and ETM+ band 3 (red) is OLI band 4.

Spectral indices combine bands into one number per pixel.

Geohazards and what the image shows

The 2027 rules name four geohazards for Division B, and each leaves a different signature.

• Volcanoes: hot lava and vents are thermal-infrared (and SWIR) hot spots; ash and sulfur dioxide plumes are visible in UV and thermal bands; ground swelling or sinking before an eruption shows in radar interferometry.
• Landslides: a bare scar replaces vegetation (NDVI drops), and comparing elevation models before and after shows lost and gained height.
• Flooding: smooth standing water reflects radar away from the sensor, so it is dark (low backscatter) in Sentinel-1 images, even under cloud. In optical images water is dark in NIR and SWIR. Compare with a dry-season image.
• Wildfires: active fire is hot in SWIR and thermal bands. A burn scar has low NIR and high SWIR, so NBR falls. A single image is weak evidence; before-and-after pairs are strong.

Aerosols affect all of these. Smoke, dust and haze scatter sunlight into the sensor's view, adding a bright veil that changes measured reflectance, especially in blue. Atmospheric correction removes the scattering and absorption of gases and aerosols before a surface property is estimated.

Surface properties: albedo, temperature and materials

Every material has a characteristic albedo, temperature behavior and spectral signature, and the 2027 rules ask you to use these to classify land, including engineered materials. Asphalt and dark roofs have low albedo and run hot in thermal images on a summer afternoon; concrete and white roofs are brighter and cooler; vegetation stays cool through transpiration; water heats slowly, so it is cool by day and relatively warm at night. These differences produce the urban heat island seen in Landsat thermal bands, ASTER and ECOSTRESS. Fresh snow is the brightest natural surface, fresh lava and active fires are the hottest, and wet soil is darker and cooler than dry soil of the same type.

Elevation and subsidence change

Ground that rises or sinks shows up in three ways: a difference between two DEMs (meters of change, as after a landslide or volcanic eruption), radar altimetry heights from two dates, or InSAR fringes (centimeters of change, as over pumped aquifers, mines and swelling volcanoes). Subsidence over a city is usually slow and spread over many square kilometers, with a bowl of concentric fringes; an earthquake gives an abrupt pattern bounded by a fault.

Earth processes: glaciers, rivers and stream patterns

Glacial movement is tracked by matching features (crevasses, debris bands) between two images and measuring how far they moved, by InSAR, and by DEM differencing that shows thinning. Retreat shows as a terminus farther up-valley and bare rock or new lakes where ice used to be. Glacial landscapes have U-shaped valleys, cirques and moraines visible in hillshaded DEMs.

Fluvial processes are what rivers do: erode the outside of bends, deposit on the inside (point bars), cut off meanders into oxbow lakes, build deltas and alluvial fans, and carry sediment that shows up as brown or tan plumes in natural color. Comparing two dates shows channel migration.

Stream (drainage) patterns reveal the rock and structure beneath.

Climate processes and satellite data (Division C)

Division C uses satellites to study how the atmosphere, oceans and land store and move energy, carbon and water. Most archive questions in this area are about what an instrument measures and what a measured pattern means. The 2027 rules list specific platforms for each data topic, so learn what each one contributes and which topic it is listed under.

Greenhouse gases, aerosols and clouds

Greenhouse gases absorb outgoing infrared radiation and re-emit it in all directions, so part of it returns downward and the lower atmosphere stays warmer than it would otherwise be. The Division C list names the gases below.

(Nitrous oxide, N₂O, is a different gas: a long-lived greenhouse gas from fertilized soils, covered under the nitrogen cycle below.) The global warming potential (GWP) compares the heat a gas traps over a stated period (commonly 100 years) with the same mass of CO₂, so it combines per-molecule absorption with lifetime. Four natural or orbital factors also move concentrations and climate: solar activity (an 11-year cycle changing total irradiance by about 0.1%), volcanic eruptions (sulfate aerosol cooled the planet by roughly 0.5 °C for a year or two after Mount Pinatubo in 1991), Earth's orbit and seasons (the Northern Hemisphere's growing season draws CO₂ down each summer, giving the sawtooth in the Mauna Loa record) and atmospheric and ocean circulation.

Aerosols can cool or warm. Bright ones scatter sunlight back to space, which cools; dark soot absorbs sunlight and warms the air. Clouds are two-sided too: bright, thick, low clouds mainly reflect sunlight and cool the surface, while high thin clouds mainly trap outgoing infrared and warm it. That is why the 2027 rules ask about their radiative effects, not simply "warming" or "cooling".

Radar and lidar see vertical structure. CloudSat's radar measures the reflectivity of droplets and ice at each height; CALIPSO's lidar is especially sensitive to thin clouds and aerosol layers; GPM's precipitation radar maps rain and snow in three dimensions; Doppler radar adds the radial velocity of particles, which reveals storm rotation.

Climate change acts on existing weather processes. Warmer air holds about 7% more water vapor per degree Celsius, which favors heavier downpours and flooding; heat waves become more frequent; wildfire smoke adds aerosol to the atmosphere. Ecological effects include shifting biome boundaries poleward and upslope and earlier spring green-up, which shows up as changes in vegetation indices over time.

El Niño–Southern Oscillation

The El Niño–Southern Oscillation (ENSO) is a coupled ocean-atmosphere cycle in the tropical Pacific. Normally, trade winds blow west along the equator, piling warm surface water in the west, deepening the warm layer there and letting cold, nutrient-rich water well up along South America. During El Niño, the trade winds weaken, warm water spreads east, upwelling along South America is suppressed, and the sea surface in the east becomes higher as well as warmer. During La Niña, the trade winds strengthen, the east cools further and upwelling increases. NOAA defines an event by the sea-surface temperature anomaly in the central Pacific (Niño 3.4 region) of at least +0.5 °C for El Niño or −0.5 °C for La Niña, sustained over several months.

Regional effects are the tested part: El Niño tends to bring heavy rain to coastal Peru and Ecuador and drought to Indonesia and Australia, and La Niña often does the reverse. In satellite questions, look for sea-surface temperature anomalies in the equatorial eastern Pacific (MODIS on Aqua, GOES) or sea-surface-height anomalies (JASON) to identify the phase.

Carbon and nitrogen cycles

The carbon cycle moves carbon among the atmosphere, oceans, plants and soils. Photosynthesis takes CO₂ out of the air; respiration, decomposition and fire return it. Fossil-fuel burning and land-use change add carbon faster than natural sinks absorb it, and the ocean takes up part of the excess, which makes seawater more acidic. Remote sensing measures pieces of this: column CO₂ from OCO-2, vegetation greenness from optical sensors, and ocean chlorophyll (a proxy for marine primary production) from ocean-color sensors such as PACE and MODIS.

The nitrogen cycle is linked through plant growth. Nitrogen-fixing bacteria (and lightning, and the industrial Haber-Bosch process for fertilizer) convert atmospheric N₂ into forms plants can use; microbes later return it as N₂ and as N₂O by denitrification. Excess fertilizer therefore raises N₂O emissions, and runoff feeds algal blooms that change ocean color. Combustion nitrogen oxides feed ozone and aerosol formation.

Ocean color makes the link visible. Chlorophyll a absorbs blue and red light and reflects green, so greener water means more phytoplankton. As warming moves the zones of ideal phytoplankton growth, regional ocean color shifts, which matters to fisheries and the coastal economies that depend on them.

Sea-level rise and surface waves

Sea level rises for two reasons. Warm water expands (thermal expansion, a volume change), and melting land ice adds mass. GRACE tracks the distance between two satellites as Earth's gravity field changes, so it sees ocean mass, ice-sheet loss, groundwater storage and hydrologic redistribution, but not thermal expansion. Altimeters such as JASON measure the sea-surface height, which combines both effects, and thermal expansion is measured with temperature profiles from ocean instruments such as Argo floats. The rise is a few millimeters per year, small enough that altimeters must average many measurements.

An altimeter finds the surface height as the satellite's altitude minus the range $R = c\Delta t/2$. The same echo carries more: the shape of the returned pulse gives the significant wave height (rougher seas smear the echo) and the strength of the return gives wind speed. Read each question's wording for whether it asks about mass, height or temperature.

Energy balance and feedbacks (Division C)

Planetary energy balance is the most mathematical area of the Division C scope, and it rewards clean, labeled diagrams. The idea is simple: Earth absorbs energy from the Sun, emits infrared radiation to space, and stays at a temperature where the two are equal, averaged over time. Everything else (albedo, clouds, greenhouse gases, aerosols) changes the terms in that balance.

The factor of 4 comes from geometry. Earth intercepts sunlight over a disk of area $\pi R^{2}$, but emits over a sphere of area $4\pi R^{2}$, so the average incoming power per unit area is one quarter of the solar irradiance times the fraction not reflected.

Published energy budgets differ by a few W/m²; use the values a question gives, not the diagram's.

Albedo

Albedo is the fraction of incoming sunlight a surface reflects. It is one of the largest controls on energy absorption. Fresh snow reflects most of the sunlight that reaches it, open ocean reflects very little, and forests and dark soils fall in between. Clouds raise planetary albedo a great deal, which is why their net effect on climate is so sensitive to their type and height.

Approximate values (they vary with sun angle, wetness and season; confirm against a reference such as NASA Earth Observatory):

Radiative forcing

Radiative forcing is the change in net energy flux at the top of the atmosphere caused by a change in a driver, such as the concentration of a greenhouse gas, with the rest of the system held fixed. It is measured in W/m². Forcing is not temperature. A positive forcing means the planet gains energy and will warm until the balance is restored, which takes time because the oceans store heat. For carbon dioxide, a widely used approximation from a published radiative-transfer study is $\Delta F \approx 5.35 \ln(C/C_0)$ W/m² (Myhre et al., 1998).

The eventual temperature change is $\Delta T = \lambda\,\Delta F$, where $\lambda$ is the climate sensitivity parameter in K per W/m² and includes the feedbacks. The IPCC's best estimate for the warming after a CO₂ doubling is about 3 °C, with a likely range of 2.5 to 4 °C, so $\lambda \approx 0.8$ K/(W/m²).

Feedbacks

A feedback is an effect that changes the system's response to a forcing. A positive feedback amplifies the change; a negative feedback reduces it. The cleanest example is ice-albedo feedback. Warming melts ice, exposing darker ocean or land, which absorbs more sunlight, which warms the planet further. Water vapor feedback works similarly: a warmer atmosphere holds more water vapor, which is itself a greenhouse gas, amplifying warming. The main negative feedback is the increase in outgoing thermal emission as the planet warms, which scales with the fourth power of temperature, and so tends to restore balance.

Heating and cooling rates

Heating and cooling rates over time were already on the Division C list, but the 2027 wording stresses interpreting them. Expect a graph or table of temperature, heat content or energy imbalance over time, and questions asking you to read the rate, identify the type of change and explain what physical change caused it. No calculus is needed: a rate is the slope between two points.

• Linear: a constant heating rate. Power $P$ into a mass $m$ with specific heat $c$ gives $\Delta T = Pt/(mc)$, so the rate is $P/(mc)$ in K/s.
• Piecewise linear: a different constant rate in each interval. Compute each segment starting from the temperature at the end of the one before. Example: starting at 280 K, a surface warms at 2.0 K/h for 6 h, then cools at 0.5 K/h for 10 h. After 6 h it is 292 K; after 16 h it is $292 - 5 = 287$ K.
• Exponential: a body relaxing toward equilibrium, with the rate proportional to the remaining gap.

Reading the shape. A straight line means a steady imbalance (constant forcing, no feedback yet). A piecewise-linear record has breakpoints where something changed: a volcanic eruption that cools for a year or two, a step in emissions, or the shift between seasons. An exponential approach that flattens out means a negative feedback (more outgoing radiation as the planet warms) is closing the gap. Exponential growth that steepens means the driver itself is compounding: CO₂ rising 0.5% per year doubles in $\ln 2 / 0.005 \approx 139$ years. Because forcing depends on the logarithm of concentration, steady exponential growth in CO₂ gives a forcing that rises roughly linearly in time.

Common pitfalls

How tournaments test this

Scio.ly's question archive holds 7,480 archived questions and 6,095 question-bank items in the remote sensing scope. Of the archive, 5,480 are tagged Division C, 1,812 Division B and 188 shared. The 2026 season supplies 4,571 archive questions (about 61%), with a tail from earlier seasons, including 1,084 from 2018 and 946 from 2023. Older questions were written for earlier topics, so do not assume each matches the 2027 rules. In particular, the 2026 Division B list included azimuths, bearings and latitude-longitude conversion, which the 2027 Observable Earth list no longer includes, and the 2026 Division C list included the Rayleigh-Jeans law and ATMS, which are also gone; skip archive questions on those.

Question types. Free response makes up 3,908 archive items (52%) and multiple choice 3,160 (42%); the rest are multiple-select (184), numeric (123), true or false (98) and matching (7). The bank is 55% multiple choice (3,364 of 6,095) and 39% free response (2,378).

Task profile. The most common task is explaining why something happens (12.6% of archive items), then "which of the following" (8.5%), interpreting a graph, table or curve (5.9%) and calculating a value (4.4%). Comparison (1.8%) and definitions (1.2%) are smaller. The bank shows a similar pattern.

Subtopics. Archive tags overlap: climate processes 2,829 (about 38%), data analysis 1,927 (26%), sensors 1,703 (23%), imaging 1,503 (20%), satellites 1,259 (17%) and mapping only 446. The tags skew toward Division C because that division supplies most of the archive; plan study time from the 2027 percentages, not tag counts.

Recurring terms. Among two-word terms, "remote sensing" itself leads (649 questions), then surface temperature (253), climate change (188), electromagnetic spectrum (175), greenhouse gas (165), spatial resolution (163), radiative forcing (105), equilibrium temperature (104), Rayleigh scattering (90), radiometric resolution (71) and Stefan-Boltzmann law (69).

Most common correct answers. Rayleigh scattering (54 questions), MODIS (45), infrared (44), Mie scattering (41), passive (35), water vapor (34), OCO-2 (32), active (30), visible (27), geostationary orbit (25), lidar (25) and carbon dioxide (24). Classification words (active, passive, infrared, visible) and instrument names dominate: when a question describes a measurement, it often expects you to name the platform or instrument.

Test yourself

The questions below are real archive questions whose official keys were re-solved while writing this guide, chosen because their content is inside the 2027 rules. Each links to its public practice test. Try them before reading the explanations.

Test yourselfTest yourself: sensors, light and orbits

0 / 0 correct

1. 1

   Which of the following instruments are classified as Active Sensors?

   Question 1 options

   ARadar (radio detection and ranging)BLiDAR (light detection and ranging)CImaging RadiometerDLaser altimeter
   Check answer

   From: Raisbeck Aviation Invitational - WA, 2025-26, Division C

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Test yourselfTest yourself: image quality and interpretation

0 / 0 correct

1. 1

   Spectral resolution refers to:

   Question 1 options

   ANumber and width of wavelength bandsBNumber of pixels in an imageCHow often images are takenDHow bright the line appears

   From: Blue Dragon Invitational - NY, 2025-26, Division B

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Test yourselfTest yourself: climate processes and energy balance

0 / 0 correct

1. 1

   Identify which of the following feedback loops is positive:

   Question 1 options

   AIncreased cloud cover → increased albedo → cooling → reduced evaporationBWarming → ice melt → decreased albedo → more absorption → warmingCCO₂ increase → plant growth → CO₂ absorption → reduced CO₂DWarming → increased evaporation → more clouds → cooling

   From: Cypress Falls - TX, 2025-26, Division C

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References and further reading

• Science Olympiad, soinc.org: the 2027 rules manual (Remote Sensing B, Observable Earth; Remote Sensing C, Climate Change).
• NASA, TROPOMI and Sentinel-5P overview and ECOSTRESS: the instruments new to the 2027 lists.
• USGS, Earth Resources Observation and Science Center: the NLCD and SRTM elevation products.
• NASA Earthdata, earthdata.nasa.gov: satellite missions, instrument descriptions and data products, including MODIS, CERES, GRACE and OCO-2.
• NASA Earth Observatory, earthobservatory.nasa.gov: accessible explanations of Earth's energy budget, albedo, ENSO and the carbon cycle.
• USGS, Landsat Missions: the Landsat sensors (TM, ETM+ and OLI) named in the Division B scope.
• Copernicus, copernicus.eu: the Sentinel missions, including Sentinel-1 radar and Sentinel-2 multispectral imaging.
• NOAA NESDIS, nesdis.noaa.gov: geostationary and polar-orbiting weather satellites, including GOES and Suomi NPP.
• Kopp, G. and Lean, J. L. (2011), "A new, lower value of total solar irradiance," Geophysical Research Letters 38, L01706: doi:10.1029/2010GL045777. Source for the solar irradiance of about 1,361 W/m².
• Myhre, G., Highwood, E. J., Shine, K. P. and Stordal, F. (1998), "New estimates of radiative forcing due to well mixed greenhouse gases," Geophysical Research Letters 25, 2715: doi:10.1029/98GL01908. Source for the CO₂ forcing approximation.
• Wikipedia, Remote sensing: a general overview of platforms, sensors and applications. Use it to orient yourself, then check the primary sources above.
• SciOly Wiki, Remote Sensing: the community event page. Read it for context; this guide does not reproduce its content.