Quantum Solutions And Delmar Aerospace: Real-time Water Mapping With Water

New alliance will roll out Water real-time normalized difference moisture index surface-moisture mapping—up to 1,000× finer than conventional satellite products—supporting agriculture, infrastructure, and environmental monitoring across the U.S. Pacific Coast and Canada.

Real-Time Moisture Index Coverage

The company has entered a strategic agreement with Delmar Aerospace and its Canadian arm, Perspectum Drone Inspection Services, to deliver drone-based moisture intelligence throughout the Western United States and Canada.

Under the collaboration, Delmar and Perspectum will operate the Water payload to provide high-resolution water intelligence for agriculture, infrastructure oversight, and environmental management using the normalized difference moisture index. The index is a spectral ratio designed to estimate vegetation and surface moisture from reflected light, calculated as (near-infrared − shortwave infrared) ÷ (near-infrared + shortwave infrared). In practice, the inputs come from a sensor’s near-infrared band and a shortwave-infrared band (or the closest available equivalent on the payload) captured over the same ground area.

As a moisture-focused metric, the normalized difference moisture index differs from the normalized difference vegetation index, which emphasizes “greenness” and vigor using red and near-infrared reflectance, and from the normalized difference water index, which is commonly used to highlight open water or water-related features using green and near-infrared (or, in some workflows, near-infrared and shortwave infrared). Use the moisture index when the goal is canopy or surface moisture and water stress; use the vegetation index for general crop vigor, stand establishment, and biomass trend checks; and use the water index for identifying open water, inundation, or water boundary changes.

Interpreting moisture-index values is typically done on a relative scale from about −1 . Higher values generally indicate wetter canopies or surfaces (more moisture), mid-range values often reflect moderate moisture or mixed cover, and lower values can indicate dry vegetation, bare soil, or stressed areas—best confirmed by comparing to baseline conditions for the same field, season, and crop stage.

Higher Resolution Than Satellite: End-to-End Services

The initiative pairs the UK-developed and manufactured Water system with Delmar and Perspectum’s on-the-ground operations and North American footprint. As a specialist UAS inspection provider, Perspectum brings proven field experience across energy, infrastructure, and environmental inspection.

Delmar and Perspectum will deploy the drone-mounted system across the region, capturing live surface moisture in real time to generate actionable insights for cropland, critical assets, and sensitive habitats. Typical operations include flight planning over the area of interest, pre-flight checks and sensor calibration, and collection of aligned spectral imagery during the drone mission. The captured bands are processed into georeferenced outputs, the moisture index is computed per pixel, and the results are delivered as map layers and decision-ready visuals that teams can review immediately in the field or route into existing GIS and reporting workflows.

Real-time delivery helps shorten the gap between measurement and action, supporting timely irrigation decisions, earlier detection of developing water stress, and faster triage of emerging issues that can change within hours. Measurement accuracy can be influenced by sensor calibration and stability, atmospheric conditions (haze, variable humidity), illumination and time of day, shadows and view angle, surface cover and mixed pixels (soil, residue, canopy density), wind-driven canopy motion, and the consistency of processing settings used to generate comparable maps across flights.

For drought and water stress detection, teams typically look for consistent downward shifts in moisture-index values compared with a known baseline for the same crop stage or with nearby “healthy” reference zones. For example, a block that trends lower than surrounding areas after a heat event can indicate emerging stress and guide targeted scouting, irrigation adjustments, or leak checks before visible symptoms spread.

Common beneficiaries include water-sensitive and high-value crops where within-field variability matters—such as grapes, berries, leafy vegetables, potatoes, orchard crops (including almonds and apples), corn, and wheat—especially when paired with variable-rate irrigation and rapid follow-up scouting.

Together, the teams will deliver a full workflow—from airborne data capture to analysis and decision-ready reporting—covering a range of operational and environmental use cases.

For organizations that need automated access, no public API for moisture-index outputs is described in the announcement; access is typically handled through delivered map products and reporting, with data integration options available by request through the service team.