Saturation Math: Per-Capita Supply Benchmarks for Self-Storage, RV and Boat Storage, RV Parks, and Glamping

Saturation Math: Per-Capita Supply Benchmarks for Self-Storage, RV and Boat Storage, RV Parks, and Glamping

Every defensible self-storage feasibility study, RV and boat storage feasibility study, RV park feasibility study, or glamping feasibility study answers one question before any other: how much supply can this trade area absorb? Self-storage has a widely cited answer, the square-feet-per-capita benchmark, now running 7.6 to 7.8 square feet nationally. RV and boat storage, RV parks, and glamping have no equivalent published threshold, which leaves credit files for those asset classes resting on assertion rather than arithmetic. This article sets out the saturation math our analytical team applies across all four asset classes: the equilibrium bands, the demand-pool construction, the worked sizing examples, and the data sources a credit reviewer can independently verify. Where no published benchmark exists, we derive one explicitly and show the derivation, so that a lender, a CDC analyst, or a sponsor can rebuild the number rather than take it on faith.

Section 1: Why Saturation Math Is the Spine of Storage and Outdoor Hospitality Feasibility

The four asset classes covered here share a structural property that most commercial real estate does not: their demand pool can be counted. An office tower's demand depends on diffuse employment decisions. A self-storage facility's demand depends on the households within a drivable radius, their tenure mix, and their mobility. An RV storage facility's demand depends on the registered recreational vehicles and trailerable boats owned by those same households. An RV park's demand depends on camping households within the drive-to market plus the destination draw. A glamping resort's demand depends on the same pool, filtered by income and accommodation preference.

Because the pool is countable, the feasibility question reduces to a ratio: supply per unit of demand. Self-storage matured around exactly this ratio, net rentable square feet per capita, and the discipline that ratio imposes is the reason institutional capital trusts the asset class. The adjacent categories never developed the same convention. The result is visible in credit files: RV storage pro formas that assume stalls fill because "demand is strong," RV park projections that import national camping enthusiasm into a trade area that cannot support it, glamping decks that cite double-digit market growth rates from research houses whose United States market-size estimates disagree with one another by a factor of nearly two.

The corrective is not better adjectives. It is publishing the arithmetic. The sections below set out, for each asset class, the supply metric, the equilibrium band, the demand-pool construction, and the adjustment factors, in that order.

[EXHIBIT 1: Saturation metrics and equilibrium bands across the four asset classes]

Asset class — Supply metric — Equilibrium band — Primary demand pool — Trade area. Self-storage: net rentable sq ft per capita; 7 to 9 sq ft locally, 7.6 to 7.8 national average; population weighted to renters and movers; 3-mile radius urban, 5-mile suburban. RV and boat storage: stalls per 1,000 households; 40 to 70 demanded stalls per 1,000 households (derived; see Section 4); RV-owning households plus trailerable registered boats; 15-minute drive-time. RV parks: annual site-nights demanded vs. supplied; 45 to 60 percent annual occupancy transient parks, 65 to 75 percent destination parks; camping households in drive-to markets plus destination draw; 2 to 4 hour drive-to origin markets. Glamping: unit-nights demanded vs. supplied; 50 to 65 percent annual occupancy at stabilization in seasonal markets; glamping-inclined camper households, income-qualified; destination draw area, 2 to 5 hours.

Section 2: The Lender Context

How a capital provider reviews these four asset classes is shaped by three regulatory facts.

First, none of the four sits on the SBA special-purpose property list under SOP 50 10 8. Self-storage, RV and boat storage, RV parks, and campgrounds are treated as multipurpose or operating-business assets, which keeps the standard SBA 504 borrower contribution at 10 percent under 13 CFR 120.910 rather than the 15 percent that attaches to enumerated special-purpose categories such as marinas, hotels, and car washes. A new business overlay still lifts the contribution to 15 percent, and a marina component inside an outdoor hospitality project can pull the special-purpose treatment back in. Our separate reference on the SOP 50 10 8 special-purpose property list covers that boundary in detail.

Second, eligibility for SBA financing in these categories runs through the active-business test. Under 13 CFR 120.110, passive businesses that primarily own real estate and lease it long term are ineligible. Self-storage, RV and boat storage, and commercial vehicle storage qualify as active operating businesses because revenue arrives through month-to-month occupancy agreements rather than long-term leases. RV parks and campgrounds carry an additional and frequently decisive test: at least 50 percent of gross revenue must come from short-term stays of 30 days or less. A park whose revenue mix has drifted toward seasonal and annual residents can fail the transient test and lose SBA eligibility, which is why the feasibility study must model the transient and long-stay revenue mix explicitly rather than as an afterthought. Glamping structures add a classification wrinkle: units on permanent foundations with utility connections are treated as real property eligible for the 25-year 504 term, while portable structures are classified as equipment on a 10-year term.

Third, the projection standards are concrete. SBA credit practice expects a startup outdoor hospitality project to reach breakeven by roughly month 24 of operations, and most lenders look for debt-service coverage of at least 1.25x by stabilization, with a Year 1 coverage below 1.0x acceptable only where the ramp assumptions are believable and reserves cover the gap. For rural projects, USDA Business and Industry guarantees under 7 CFR Part 5001 apply a parallel framework: market, economic, technical, financial, and management feasibility, each documented by an independent third party. In every case, the saturation math in the sections below is the evidence that makes the ramp assumptions believable.

Section 3: Self-Storage and the Square-Feet-Per-Capita Benchmark

1. 1 The national picture

The United States holds roughly 2.1 billion square feet of rentable self-storage space, and the national average sits at 7.6 to 7.8 net rentable square feet per capita as of 2025 and early 2026, per Yardi Matrix data published through RentCafe and StorageCafe. Industry reporting treats approximately 7 square feet per capita as the balanced-market line: below it, demand typically outweighs supply and street rates climb; above it, with an active pipeline, rates compress. The dispersion around the average is enormous. Boston operates at 0.7 square feet per capita and posted the steepest street-rate growth in the country in early 2026, while the most heavily built Sun Belt and resort markets exceed 16 square feet per capita and carry persistent rate pressure. Jacksonville closed 2025 at 10.8 square feet per capita and Savannah-Hilton Head at 11.7, both well above the national line even as development continued.

The rate cycle confirms the mechanics. National street rates averaged $131 per month in March 2026, down 2.2 percent year over year, with 76 percent of large cities recording annual declines. The December 2025 reading of plus 0.3 percent year over year, against minus 2.3 percent a year earlier, marked the first stabilization after a prolonged correction. Meanwhile 54.2 million net rentable square feet remained under construction nationally, about 2.7 percent of stock, with roughly 43.6 million square feet expected to deliver in 2026 and 37.3 million in 2027. Occupancy across the sector has settled in the low 90s after the 2021 peak near 95 percent.

1. 2 Localizing the benchmark

The national average is a reference, not a verdict. A defensible study computes the ratio inside the actual trade area: a 3-mile radius in urban submarkets, a 5-mile radius or 10-minute drive-time in suburban ones. The numerator is the net rentable square footage of every operating facility whose trade area overlaps the subject's, plus the pipeline (under construction and entitled), counted at expected delivery. The denominator is current population plus a forward population estimate over the absorption horizon.

The raw ratio is then adjusted, because identical per-capita figures conceal very different demand intensities. Tenure mix: renter households use storage at materially higher rates than owner households with garages and basements. A trade area at 8 square feet per capita with 55 percent renters can be undersupplied while a 6-square-foot exurban market of large-lot owners is saturated. Mobility: storage demand is event-driven — moves, household formation and dissolution, downsizing, dislocation, and death. County-to-county migration data and apartment deliveries are the forward indicators. Housing format: average unit sizes below 900 square feet, common in dense coastal metros, convert storage from an episodic service into a structural one. Pipeline as a percentage of stock: a market at 7 square feet per capita with a 6 percent pipeline behaves like a market at 9; a market at 9 with no pipeline behaves like equilibrium.

The decision rule our analytical team applies: trade areas below 6 adjusted square feet per capita with positive household growth support new supply; 6 to 9 requires a differentiated format or micro-location argument; above 10 with an active pipeline, the study should say so plainly and size the rate-compression scenario rather than argue around it.

Section 4: RV and Boat Storage, the Missing Benchmark

1. 1 Why no published threshold exists

RV and boat storage is the fastest-institutionalizing niche in storage, yet there is no per-capita convention equivalent to self-storage's 7-square-foot line. The inventory is fragmented across pure-play toy storage facilities, self-storage facilities with parking rows, marinas with dry stacks, and informal gravel lots, and no national data vendor reconciles them. The absence of a benchmark does not mean demand cannot be counted. It can, because the demand pool is registered.

1. 2 The demand pool

Two federal-grade counts anchor the math. The RV Industry Association's 2025 Owner Demographic Profile places RV ownership at 8.1 million United States households, with a median owner age of 49 and median usage of 30 days per year. That last figure is the storage industry's foundation: the median recreational vehicle sits unused roughly 335 days a year, and it has to sit somewhere. On the marine side, NMMA registration data counts approximately 11.8 million registered boats nationally, new powerboat retail sales of 231,576 units in 2024, and a fleet in which roughly 95 percent of powerboats are under 26 feet and therefore trailerable. Wholesale RV shipments of 342,220 units in 2025, up 2.5 percent, continue to add to the stored fleet even in a cautious consumer environment.

Against approximately 132 million United States households, the national ownership rates are roughly 6 percent for RVs and roughly 9 registered boats per 100 households. Local rates diverge sharply: lake-adjacent counties and Mountain West exurbs can run double the national RV rate, while dense urban cores run a fraction of it. The local rates are knowable, because state DMV and state boat-registration files report counts by county or ZIP code, and that locality is exactly what a credit reviewer should demand.

1. 3 The derived equilibrium band

No association publishes a stalls-per-household threshold, so we derive one and show the work. The convention our analytical team applies, stated for a typical suburban or exurban trade area:

[EXHIBIT 2: RV and boat storage demand worksheet, illustrative 15-minute drive-time trade area]

Step 1: households within 15-minute drive-time — 30,000. Step 2: RV-owning households (local rate, here 6.1%) — 1,830. Step 3: registered boats (local rate, here 8.9 per 100 households) — 2,670. Step 4: trailerable share of boats (95%) — 2,537. Step 5: storable vehicle pool (rows 2 + 4) — 4,367. Step 6: off-site storage propensity (30 to 45%, HOA density driven) — 1,310 to 1,965 vehicles. Step 7: demanded stalls per 1,000 households (row 6 divided by 30) — 44 to 66. Step 8: existing competitive stalls within the same drive-time — subtract from row 6. Step 9: unmet demand available to subject — residual.

Generalized, the band lands at 40 to 70 demanded stalls per 1,000 households within a 15-minute drive-time before competitive supply is netted out. The single most consequential adjustment factor is row 6: off-site storage propensity. It is driven by HOA coverage (covenant restrictions on street and driveway storage of recreational vehicles are the strongest single demand generator the asset class has), lot sizes, municipal parking ordinances, and climate. A master-planned Sun Belt suburb with near-universal HOA coverage justifies the top of the propensity range; a rural county of five-acre lots justifies the bottom or below it.

Stall mix is the second-order question. Enclosed and canopy stalls command rate premiums over open parking, and the appropriate mix tracks vehicle values and climate severity in the trade area. A study that sizes total stalls correctly but assumes an enclosed mix the local fleet will not pay for has answered the saturation question and failed the revenue question.

1. 4 The forward fleet

Demand is not static. RVIA reports 16.9 million households expressing intent to purchase an RV within five years, and the 2025 shipment total adds roughly 342,000 new units to the national fleet in a single year against a much smaller retirement rate. A defensible study projects the storable fleet forward over the absorption horizon using shipment trends and local household growth, and then stresses the projection against the more cautious 2026 shipment outlook that ITR Economics prepares for RVIA.

Section 5: RV Parks and the Site-Night Framework

1. 1 Supply and demand at national scale

The supply side is countable: roughly 16,400 privately owned campgrounds and RV parks per IBISWorld's 2025 business count, holding more than 1.3 million campsites per RVParkIQ, alongside an estimated 13,000 public campgrounds. Total industry revenue runs near $10.9 billion. The demand side comes from Kampgrounds of America's 2026 Camping and Outdoor Hospitality Report: more than 52 million North American households camped in 2025, level with the prior year and above pre-pandemic participation, generating $66 billion in local spending. Two subtleties in the KOA data matter for credit files. RVing specifically is down 14 percent in participating households versus 2019 even as total camping holds, and campers aged 65 and older doubled their share to 22 percent of all campers in 2025. The headline camping boom is real; the RV-specific slice of it is flatter than sponsors assume.

1. 2 The site-night model

A site-night model converts that national picture into trade-area arithmetic. Supply is sites multiplied by available nights, adjusted for season length. Demand is built from origin markets: camping households within the 2-to-4-hour drive-time that supplies the overwhelming majority of stays at non-destination parks, their trips per year, party composition, and the share of trips realistically capturable given the subject's positioning, plus any genuine destination draw (a national park gateway, a coastline, an event anchor), which must be evidenced by visitation data rather than asserted.

The occupancy bands our analytical team applies at stabilization: transient-oriented parks in four-season climates, 45 to 60 percent annual occupancy with peak-season weekends effectively sold out and deep winter near zero; Sun Belt and destination parks, 65 to 75 percent; seasonal northern parks, revenue concentrated such that roughly 20 weeks carry 70 percent or more of the year. Projections above these bands require a named, evidenced demand anchor.

1. 3 Revenue mix and the transient test

Mix is both an economic and a regulatory variable. Nightly transient rates run multiples of the per-night equivalent of monthly and seasonal rates, but long-stay occupancy stabilizes cash flow through shoulder seasons. The SBA's 50 percent transient revenue test sits directly on top of this trade-off: a park that drifts past half its revenue in 30-day-plus stays gains stability and loses SBA eligibility. The feasibility study should therefore present the mix as a managed variable with a target corridor, and the projection should hold the transient share above the eligibility line with margin, not at it.

Ramp expectations follow the lender math in Section 2: roughly 24 to 36 months from opening to stabilized occupancy, breakeven by month 24, 1.25x coverage at stabilization. A study that projects stabilized occupancy in the first full season is not aggressive; it is non-credible.

Section 6: Glamping, Behavioral Demand Over Market-Size Estimates

1. 1 The estimate problem

Published United States glamping market sizes diverge widely: roughly $510 million to $890 million for 2024 across major research houses, with growth rates of 8 to 13 percent annually. When the size estimates for the same market in the same year differ by nearly a factor of two, none of them belongs in a credit file as a demand input. They establish direction, nothing more.

1. 2 The behavioral data

The defensible demand evidence is behavioral. KOA's 2026 report attributes 29 percent of all 2025 camping experiences to glamping and finds that 31 percent of first-time campers entered through glamping accommodations. Glampers also out-spend: earlier KOA research places glamper local spending roughly 45 percent above standard campers, and average daily per-person expenditures across camping exceeded $200 in 2025. Within the existing park inventory, supply remains thin: of the 16,200-plus private parks RVParkIQ tracks, about 581, or 3.6 percent, offer glamping units, and 10.3 percent offer cabins or tiny homes. Thin supply against a 29 percent behavioral share is the genuine structural argument for the asset class, and it is far stronger than any market-size CAGR.

1. 3 Unit economics and sizing discipline

Glamping pricing segments roughly into a low band of $50 to $120 per night, a medium band of $121 to $320, and a high band above $321, per Global Market Insights segmentation, with most viable rural projects living in the medium band. The sizing discipline: model annual occupancy at 50 to 65 percent at stabilization in seasonal markets, concentrated in a 20-to-26-week core season, and let unit count follow demanded unit-nights rather than the site plan. As an illustration, 12 units at a $225 average daily rate and 55 percent annual occupancy produce roughly $540,000 in lodging revenue; the same 12 units modeled at 75 percent year-round occupancy in a snow-belt market produce a projection a reviewer should reject on sight. Operating costs run heavier than RV sites because glamping is lodging: housekeeping, linen, guest services, and unit replacement reserves belong in the pro forma, and the structure classification issue from Section 2 (real property versus equipment) belongs in the financing plan.

Glamping inside an existing park deserves a separate note, because it is the highest-yield expansion the sector currently offers: a modest unit count layered onto an operating park adds lodging-grade revenue to land already entitled and staffed, which is why roughly one in ten parks has added cabin-format units. The feasibility question for those expansions is cannibalization: whether glamping nights are incremental or harvested from existing RV site demand.

For the cross-asset framework, demand regimes, valuation methods and reviewer tests, see the 2026 Feasibility Methodology Atlas.

Section 7: Comparable Supply and Data Sources

The comp set disciplines differ by asset class, but the principle is constant: every competitor named, geocoded, and characterized, with the pipeline counted, and every demand input traceable to a source a reviewer can pull independently.

Self-storage: facility-level inventory and street rates via Yardi Matrix-derived public reporting (RentCafe, StorageCafe), REIT disclosures for operating benchmarks, municipal permit records for the pipeline, Census population and tenure data for the denominator.

RV and boat storage: state DMV recreational vehicle registrations and state boat registration files at county or ZIP level, RVIA shipment and ownership reports, NMMA registration and retail reports, county GIS and HOA coverage mapping for propensity, field reconnaissance for the informal supply that no database captures.

RV parks: IBISWorld public business counts and RVParkIQ inventory for supply, KOA's annual report for participation and behavior, state tourism and park visitation data for destination draw, drive-time demographics for origin markets.

Glamping: KOA behavioral shares, booking-platform supply scans within the destination draw area, and the same origin-market demographics, income-filtered.

Where licensed datasets inform a study, the credit file should still rest on the public anchors above, precisely so that the reviewer can rebuild the arithmetic.

Section 8: Financial Benchmarks at Stabilization

[EXHIBIT 3: Stabilized operating benchmarks across the four asset classes]

Self-storage: low 90s percent physical occupancy; monthly rents, street-rate cyclical; high operating margin profile (lean staffing, low variable cost); 24 to 42 months ramp to stabilization for new builds. RV and boat storage: 85 to 95 percent of stalls; monthly agreements, enclosed premium; highest margin of the four with minimal opex; 18 to 36 months ramp. RV parks: 45 to 75 percent annual occupancy by format; nightly, weekly, monthly, seasonal mix; moderate margin with labor and utilities scaling with transiency; 24 to 36 months ramp. Glamping: 50 to 65 percent annual occupancy, seasonal; nightly ADR, lodging-grade; lodging-like margin with housekeeping and reserves; 24 to 36 months ramp.

Three cross-cutting financial observations. First, the storage formats carry the leanest cost structures and therefore tolerate rate softness better than the hospitality formats tolerate occupancy softness; the stress tests should differ accordingly, rate-led for storage, occupancy-led for parks and glamping. Second, seasonality is a financing-structure question, not only an operating one: a northern park covering annual debt service from a 20-week core season needs reserve sizing in the loan structure, and the feasibility study should say so. Third, mixed projects (a park adding storage rows, a storage facility adding RV stalls, a park adding glamping) should be modeled as separate demand pools sharing a site, never as one blended assumption, because the saturation math for each component is different and a reviewer will test them separately.

Section 9: Risk Factors and What Makes the Study Defensible

The risk hierarchy by asset class. For self-storage: supply, supply, and supply; the street-rate correction of 2023 through 2025 was a pipeline phenomenon, and the single most predictive variable for a new build's first three years is the pipeline as a percentage of trade-area stock. For RV and boat storage: fleet cyclicality (shipments swing hard with consumer credit), the informal-supply blind spot, and entitlement risk, since outdoor storage is a frequent zoning target. For RV parks: the transient-mix regulatory line, weather and season-length variance, the flatter RV-specific participation trend inside the broader camping boom, and entitlement timelines that routinely exceed sponsor expectations. For glamping: demand novelty (the behavioral data is strong but young), seasonality, and the temptation to capitalize a hospitality operation as if it were passive land.

A defensible study across all four does the same five things. It states the saturation metric and computes it from named sources inside a defined trade area. It derives, rather than asserts, any benchmark that lacks a published convention, and shows the derivation. It nets existing and pipeline supply before claiming unmet demand. It models the ramp against the month-24 breakeven and 1.25x coverage expectations a credit committee will apply. And it stresses the variable that actually breaks the asset class: rates for storage, occupancy and season length for parks and glamping, fleet growth for vehicle storage.

The arithmetic in this article is publishable precisely because it is checkable. That is the standard a feasibility study should meet before it reaches a credit file.

To commission a feasibility study for a self-storage, RV and boat storage, RV park, or glamping project, contact our analytical team.

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