# Near Real-Time Freeze Detection over Agricultural Plots Using Sentinel-1 Data
## 1 Introduction
In recent years, we have observed strong technical progress and an increase in the number of proposals for sensors in orbit. This is particularly true for synthetic aperture radars (SAR) like the recently launched Sentinel-1 constellation of European Copernicus program, and the arrival of long time series at low resolution from radiometer and scatterometer sensors like SMOS, SMAP, and ASCAT. ASCAT and SMOS have already been proven successful in a large body of studies for the detection of freeze/thaw events [15; 16; 17; 18; 26], and are capable of monitoring such events due their high repeat cycles (1-3 days for both sensors), albeit at low spatial resolutions (25 km, and 35 to 50 km for ASCAT and SMOS, respectively). Moreover, SMAP is the first satellite to provide a global freeze/thaw product at low resolutions (9 km) with high repeat cycles (two to three days). The product is based on a temporal change detection approach that assumes that the high variation in the temporal dynamics of the normalized polarization ratio (NPR) of the brightness temperature is related to a large change in the dielectric constant (passing from frozen to unfrozen condition, and vice-versa). However, due to the low resolution of these products, they are unable to detect freeze/thaw events at plot scales, which is the required scale for agricultural surfaces. Currently, C-band data provided by Sentinel-1's (S1) two-satellite constellation offer a good opportunity for the operational mapping of frozen agricultural areas due to S1's free and open access data at high spatial resolutions (10 m \(\times\) 10 m) and high revisit times (6 days or less over Europe). The algorithms developed for the detection of frozen and unfrozen surface states are based either on passive or active microwave sensors. Passive sensor-based algorithms can be classified into four main classes. These algorithms include: (1) dual-indices [25; 27], which use thresholds over temperature brightness and spectral gradient parameters for the detection of freeze/thaw events. (2) New dual-indices [19] use thresholds on the standard deviation of horizontally polarized brightness temperatures, and vertically polarized brightness temperature. (3) Decision trees [28; 29], using brightness temperatures. Finally, (4) the Discriminant Function Algorithm (DFA) is a recently developed method by [PERSON] et al. [30], which relies on temperatures brightness and quasi-emissivity. DFA has also recently been shown to have a better freeze/thaw detection accuracy than the other three methods according to [PERSON] et al. [31]. Freeze/thaw detection algorithms using active microwave sensors rely on change detection and can also be classified into three main classes: (1) threshold algorithms [16; 20; 32; 33; 34], where the frozen/unfrozen states are flagged using a single backscattered value compared to a predefined threshold; (2) moving average algorithms [35; 36; 37; 38], which flag a frozen/unfrozen surface state based on the difference between the backscattered value of the current day and the mean backscattered values of n previous days; and finally, (3) frozen/unfrozen surface detection using probabilistic models [15; 17], based on a variant of hidden Markov models to compute the probability of snow, and FT events using K\({}_{\text{u}}\) - and C-band scatterometer data. Recently, [PERSON] et al. [20] used a thresholding algorithm on the freely available C-band synthetic aperture radar (SAR) Sentinel-1 data, with a constant threshold of 3 dB, to successfully map frozen/unfrozen surfaces. The algorithm calculated the difference of the backscattered S1 signal (\(\sigma^{\circ}\)) acquired on a specific date and its immediate neighbor not considered as frozen. This approach presented some limitations, where some false negatives (frozen surface detected as unfrozen) were detected when, for instance, the SAR returned signal over wet snow (temperature above 0 \({}^{\circ}\)C) will already be 3 dB lower in comparison to the returned signal over unfrozen surfaces.