Abstract
Many soil remote sensing applications rely on narrow-band observations to exploit molecular absorption features. However, broadband sensors are invaluable for soil surveying, agriculture, land management and mineral exploration, amongst others. These sensors provide denser time series compared to high-resolution airborne imaging spectrometers and hold the potential of increasing the observable bare-soil area at the cost of spectral detail. The wealth of data coming along with these applications can be handled using cloud-based processing platforms such as Earth Engine. We present a method for identifying the least-vegetated observation, or so called barest pixel, in a dense time series between January 1985 and March 2017, based on Landsat 5, 7 and 8 observations. We derived a Barest Pixel Composite and Bare Soil Composite for the agricultural area of the Swiss Plateau. We analysed the available data over time and concluded that about five years of Landsat data were needed for a full-coverage composite (90% of the maximum bare soil area). Using the Swiss harmonised soil data, we derived soil properties (sand, silt, clay, and soil organic matter percentages) and discuss the contribution of these soil property maps to existing conventional and digital soil maps. Both products demonstrate the substantial potential of Landsat time series for digital soil mapping, as well as for land management applications and policy making.
Highlights
Soils are often at the heart of the services that ecosystems deliver, in terms of food production, and in filtering, the cycling of nutrients, the storage and regulation of water and providing habitats for soil biota [1]
We show the result of (A) the preprocessing steps of the satellite data including the selection of the aggregation window (Section 4.1); (B) the generation of the Barest Pixel Composite (Section 4.2); and (C) the generation of the Bare Soil Composite, including the selection of the threshold (Section 4.3)
The results showed that, for the agricultural area of Switzerland, Landsat data could offer detailed (30 m spatial resolution) soil information between 1985 and 1990 and from 2000 until now
Summary
Soils are often at the heart of the services that ecosystems deliver, in terms of food production, and in filtering, the cycling of nutrients, the storage and regulation of water and providing habitats for soil biota [1]. In these studies, the application is limited to the amount of bare soil visible in a single acquisition This reduces the usability of remote sensing techniques in soil science, especially for generating large and continuous soil maps showing the spatial variation of different soil properties. To reduce this problem, several studies used multi-temporal images [14,15,16]. They combined three airborne images from the same area at different dates and more than doubled the amount of bare soil pixels compared to one acquisition These studies show that the use of multi-temporal remote sensing can be used to increase the amount of spectral bare soil information. We show a comparison between the remote sensing soil property maps and available conventional and digital soil maps
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