Application of a Handheld Near Infrared Spectrophotometer to Farm‐Scale Soil Carbon Monitoring

European Journal of Soil Science, Год журнала: 2025, Номер 76(1)

Опубликована: Янв. 1, 2025

ABSTRACT Recent advances in hardware technology have enabled the development of handheld sensors with comparable performance to laboratory‐grade near‐infrared (NIR) spectroradiometers. In this study, we explored effect uncertainty from NeoSpectra Scanner Handheld NIR Analyzer (Si‐Ware) on estimating farm‐level soil organic carbon (SOC) stocks at three small farms Massachusetts, USA. A field campaign conducted Falmouth, MA, collected 192 samples depths 0–10, 10–20 and 20–30 cm. All were scanned both moisture under laboratory conditions after being dried sieved. Samples analysed for SOC via elemental analysis, while bulk density was determined weighing dry fine earth sampled cylindrical cores field. Several strategies spectral prediction tested content (BD) using moist scans, including testing application prebuilt models Open Soil Spectral Library. Cubist used train all models, conformal estimate intervals one standard deviation. The Cholesky decomposition algorithm allowed us consider correlation between variables over depth layers during propagation Monte Carlo come up robust estimates field‐scale uncertainty. This analysis revealed that spectroscopy predictions, although less precise, can detect same statistical patterns stock across a large cost savings compared traditional analytical methods.

Язык: Английский

Developing a near-infrared spectroscopy calibration algorithm for soil organic carbon content in South Africa

Soil Advances, Год журнала: 2025, Номер 3, С. 100039 - 100039

Опубликована: Фев. 21, 2025

Язык: Английский

Advancing Ecosystem Monitoring with Global High-Resolution Maps of Vegetation Biophysical Properties

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

Environmental restoration projects are crucial for ecosystem recovery and biodiversity conservation but monitoring progress at a global scale poses substantial challenges. Publicly funded satellite missions such as Sentinel-2 have great potential to transform due their high spatial temporal resolution if they can be reliably linked characteristics. Here, we present the first global, analysis-ready, decametric maps three key vegetation biophysical properties on an annual basis, including effective leaf area index (LAIe), fraction of absorbed photosynthetically active radiation (FAPAR), fractional cover (FCOVER). We utilize hybrid retrieval approach physically based radiative transfer model PROSAIL directly estimate variables from multispectral images, making use multiple observations during peak growing season. All retrievals aggregated into mean values, standard deviations, number taken this period. The available 20 m, 100 1000 m years 2019 2024, totaling approximately TB analysis-ready data, validated using in-situ data Ground-Based Observations Validation (GBOV). these provides new opportunities monitoring, enabling more assessments efforts contributing development standardized frameworks.

Язык: Английский