Validation of atmospheric correction approaches for Sentinel-2 under partly-cloudy conditions in an African agricultural landscape
| Autor: | John Odindi, Nosiseko Mashiyi, Paidamwoyo Mhangara, Clement Adjorlolo, Thomas Alexandridis, Georgios Ovakoglou, Mahlatse Kganyago |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
2. Zero hunger
MAJA 010504 meteorology & atmospheric sciences Pixel Mean squared error iCor Cloud cover 0211 other engineering and technologies Atmospheric correction Magnitude (mathematics) 02 engineering and technology Spectral bands 01 natural sciences Aerosol FORCE Sen2Cor Analysis-Ready-Data Radiance Environmental science Sentinel-2 021101 geological & geomatics engineering 0105 earth and related environmental sciences Remote sensing Surface Reflectance |
| Zdroj: | Remote Sensing of Clouds and the Atmosphere XXV |
| Popis: | Globally, remotely sensed agricultural monitoring is impeded by cloudy atmospheric conditions, rendering the acquired images useless. In semi-arid landscapes, agricultural production is dominated by rainfed croplands; thus, the majority of planting occurs in the rainy season, i.e., characterized by erratic cloud cover. The clear-sky pixels in partly-cloudy images are used to increase the number of useful observations for quantitative analysis. This is achieved by cloud screening and atmospheric correction (AC) processes. However, the effectiveness of various AC approaches under partly-cloudy conditions is still unknown. Many studies validate SR under clear-sky conditions, with only a few focusing on the validation of SR under partly-cloudy conditions. This study sought to validate Sentinel-2 SR products derived from various AC approaches, i.e., MAJA, Sen2Cor, iCor, and FORCE, using in-situ spectral measurements. A partly-cloudy image with ~60% cloud cover, acquired over a semi-arid agricultural landscape and ±3 days of the field measurements, was used as a test case. The results showed consistent performance across different AC approaches, i.e., lower relationships with in-situ SR (R2 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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