Effectiveness of Sentinel-2 in Multi-Temporal Post-Fire Monitoring When Compared with UAV Imagery

Abstract

Unmanned aerial vehicles (UAVs) have become popular in recent years and are now used in a wide variety of applications. This is the logical result of certain technological developments that occurred over the last two decades, allowing UAVs to be equipped with different types of sensors that can provide high-resolution data at relatively low prices. However, despite the success and extraordinary results achieved by the use of UAVs, traditional remote sensing platforms such as satellites continue to develop as well. Nowadays, satellites use sophisticated sensors providing data with increasingly improving spatial, temporal and radiometric resolutions. This is the case for the Sentinel-2 observation mission from the Copernicus Programme, which systematically acquires optical imagery at high spatial resolutions, with a revisiting period of five days. It therefore makes sense to think that, in some applications, satellite data may be used instead of UAV data, with all the associated benefits (extended coverage without the need to visit the area). In this study, Sentinel-2 time series data performances were evaluated in comparison with high-resolution UAV-based data, in an area affected by a fire, in 2017. Given the 10-m resolution of Sentinel-2 images, different spatial resolutions of the UAV-based data (0.25, 5 and 10 m) were used and compared to determine their similarities. The achieved results demonstrate the effectiveness of satellite data for post-fire monitoring, even at a local scale, as more cost-effective than UAV data. The Sentinel-2 results present a similar behavior to the UAV-based data for assessing burned areas.

Is Precision Viticulture Beneficial for the High-Yielding Lambrusco (Vitis Vinifera L.) Grapevine District?

“…While the target is not to exceed 1 kg/ PW/m of cordon length, a step forward would be to estimate pending pruning weight through a proximal sensing approach (Millan et al 2019) that could quickly estimate PW amounts at the ground level. On a more general basis, confirming previous work done on Barbera vineyards of limited size (Gatti et al 2017), the 5m ground resolution granted by RapidEye image acquisition seems anyway accurate enough to detect intra-vineyard variability, confirming what has been previously shown in studies comparing acquisition platforms at varying ground resolution (Breunig et al 2020, Matese et al 2015, Pádua et al 2020, Sozzi et al 2020. In this study, the reliability of the RapidEye images might have benefitted from the fact that at the timing that images were captured mid rows in all cases were grassed, thereby minimizing the interference of mixels where soil contribution is significant.…”

Mapping the Essential Urban Land Use in Changchun by Applying Random Forest and Multi-Source Geospatial Data

“…Therefore, the Sen2cor module of the sentinel application platform (SNAP) software was used for atmospheric correction to obtain corrected bottom-of-atmosphere (BOA) reflectance values. Sentinel-2A satellite provides 13 spectral bands at various spatial resolutions [39][40][41]. In this study, the used image was taken on 28 October, 2016, and the near-infrared, red, and mid-infrared bands with a spatial resolution of 10, 10, and 20 m, respectively, were used to calculate the texture features, the normalized difference vegetation index (NDVI), and the normalized difference built-up index (NDBI) [42].…”

Burned Area Mapping over the Southern Cape Forestry Region, South Africa Using Sentinel Data within GEE Cloud Platform

“…Because accurate information on burned areas is a prerequisite for effective fire management [44], fine-scale satellite imagery is required to provide a reliable depiction of burned areas [45]. The Sentinel satellite constellations are uniquely suited to monitor forest fires as they provide unrestricted high-resolution images with near-daily acquisitions [46,47], the only one of its kind to deliver rich and affordable global observations so far. This facility also includes the monitoring of fire-emitted gases such as carbon monoxide (CO) with the latest Sentinel-5 sensor [48].…”

“…Sentinel-2 has become an attractive source for burned area monitoring because of its superior spectral properties, including the red-edge bands suited for chlorophyll content characterization [58], which provides the means to create novel indices for burn severity mapping [59]. Several previous studies have evaluated forest fires using the normalized burn ratio (NBR) with a high degree of success [47,60]. The NBR exploits the near-infrared (NIR) and short-wave infrared (SWIR) regions of the electromagnetic spectrum [61].…”