Creating a repeatable view for resource surveys

On 23 July 1972, NASA launched Earth Resources Technology Satellite 1 (ERTS-1) from Vandenberg Air Force Base in California. The problem it addressed was not how to photograph Earth once, but how to observe the same land repeatedly at similar scales, spectral bands and lighting conditions, allowing comparison of farmland, forests, water bodies and urban change. The programme adopted the Landsat name in 1975, and ERTS-1 accordingly became Landsat 1.

The US Geological Survey (USGS) and other Department of the Interior agencies connected satellite observation with land, water-resource and geological surveys, while NASA developed and operated the spacecraft and data systems. Researchers also had to organize ground surveys to establish which materials corresponded to different image brightness levels. Launch marked the experimental system's entry into orbit; resource classification, change measurement and routine applications emerged through validation over subsequent years.

References: [1]

Two approaches: cameras and a scanner

The satellite carried Return Beam Vidicon (RBV) cameras and a Multispectral Scanner (MSS). The former captured complete scenes in a manner resembling a television camera; the latter swept a scanning mirror across the surface and built images line by line as the satellite advanced. Virginia Norwood and her team at Hughes played a key role in developing the MSS. Initially regarded as an experimental payload, the scanner in practice produced highly useful data.

The MSS separately recorded reflected signals in green, red and two near-infrared bands. Plants respond differently in red and near-infrared light, while water is generally dark in the near infrared. Combining different channels for the same feature therefore offered more clues than a single black-and-white photograph. Ground resolution of roughly eighty metres suited regional surveys, but could not identify every crop plant or field ridge directly. Early in the mission, the RBV malfunctioned, leaving the MSS to perform the principal imaging work.

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Repeat orbits and the ground data chain

Landsat 1 operated in a near-polar, sun-synchronous orbit at an altitude of about 900 kilometres, with a nominal eighteen-day repeat cycle for the same region and a swath width of approximately 185 kilometres. Similar local solar times aided comparisons across dates, although seasonal changes in solar elevation still affected shadows and brightness. Eighteen days was only the orbital revisit interval: cloud cover or the absence of a scheduled acquisition could prevent usable imagery.

After ground stations received the observation signals, they entered NASA's data-processing system. The USGS Earth Resources Observation Systems Data Center in Sioux Falls, South Dakota, participated in archiving and distribution. Users could obtain film for individual bands, composite images or computer-readable tapes. Orbital positioning, radiometric correction, geometric processing and catalogue indexing determined whether the material could be matched to maps, field plots and imagery from another date.

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From pixel brightness to farmland and floods

Agricultural applications first required linking spectral responses to crop types, growth stages and soil backgrounds. Researchers selected known fields as references, then compared multispectral features in other areas. Repeat observations could help distinguish crops that looked similar at one moment but changed differently through the seasons. The resulting planting maps and area estimates were products of interpretation and ground validation, not crop names or yields directly measured by the satellite.

Water-resource surveys could exploit spectral differences between land and water to compare the extent of rivers, lakes and snow cover. Albert Rango and Vincent Salomonson's 1974 paper on flood mapping discussed identifying regional inundation with ERTS-1 data, using low near-infrared reflectance as an important clue. Wet soil and affected vegetation might preserve signs of change after a flood. Image timing therefore had to be compared with the flood peak and ground records; not every dark area could be treated as standing water at that time.

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Experimental images become a historical baseline

In 1976, the USGS published ERTS-1, a New Window on Our Planet, bringing together applications from different institutions and showing how satellite data entered hydrological, land-use and geological research. Contemporary and later user handbooks explained instruments, data formats and access to products. Turning experimental images into reusable information required not only sensors but standardized processing and analysts familiar with local conditions.

Landsat 1 operated until early 1978, exceeding its original one-year design goal. Its value was not limited to maps produced at the time: early images became baselines for later comparisons of deforestation, urban expansion and changes in water bodies. Sensors, pixel sizes and processing levels differ across periods, however, and long-term comparisons must address those differences. The first satellite pioneered a method of continuously recording the Earth's surface. Its interpretable and traceable data chain was as important as the launch itself.

References: [1]