老挝北部Sentinel-2 A/B云覆盖适宜阈值界定及其影像获取概率时空差异

光学卫星影像云覆盖时空特征评估是衡量其作为重要遥感监测数据源的前提。Sentinel-2 A/B影像因其免费获取、多光谱（红边）、更高时空分辨率等优势,已在全球不同尺度陆面植被与生态监测中受到重视。相较于Landsat等同类影像产品,有关Sentinel-2 A/B的云覆盖分析还未见报道。本文利用2016—2018年老挝北部所有5288景Sentinel-2 A/B影像（Granule/Tile）的云覆盖元数据,基于不同云覆盖阈值（0~100%）水平下的影像获取概率差异确定了影像获取概率分析的云覆盖适宜阈值,并揭示了云量特征阈值水平下的影像获取概率时空差异。主要结论如下:① Sentinel-2 A/B影像获取概率分析云覆盖适宜特征阈值为20%（即云覆盖≤20%）,该阈值水平下老挝北部Sentinel-2 A/B影像的逐月累积平均获取概率最高（约27.41%）;② 在20%云覆盖阈值水平下,老挝北部Sentinel-2 A/B影像逐月累积平均获取概率差异在时间上与旱季（11月—次年4月）雨季（5月—10月）的时间分布较为吻合。旱季获取概率约为42.91%,3月概率（50.27%）最大,4月与2月次之,时间上与刀耕火种焚烧与橡胶林落叶特征吻合;雨季相应概率约为11.81%,6月最低（约1.26%）;③ 老挝北部Sentinel-2 A/B影像逐月累积平均获取概率在空间上存在东西差异,旱季西部省域单元（如琅南塔）影像获取概率远高于东部,雨季西部地区影像获取概率则略低于东部地区。本研究既可为后续开展大区及全球Sentinel-2 A/B影像云量分析提供借鉴,也对开展联合国减少森林砍伐和退化排放（UN-REDD）计划引发的土地利用变化如刀耕火种农业演变、橡胶林扩张等遥感监测有指导意义。

Characteristic Threshold Determination of Cloud Coverage and Its Acquisition Probability Differences of Sentinel-2 A/B in Northern Laos

Spatial and temporal characteristics assessment of cloud coverage for optical satellite images is a prerequisite for evaluating its potential as an important remote sensing monitoring data source. Sentinel-2 A/B images have been highly valued in the aspects of land surface vegetation and ecological monitoring at different spatial scales due to their advantages of free access, multi-spectral bands (especially the introduction of red edge bands), and finer spatial (10 m/20 m) and temporal (5-day) resolutions. Compared with Landsat and other similar satellite products, cloud coverage analysis of Sentinel-2 A/B has not been reported. In this paper, the cloud of 5288 Sentinel-2 A/B images (Granule/Tile) over northern Laos from 2016 to 2018 were used to determine the appropriate threshold of cloud coverage for image acquisition probability analysis under different cloud coverage thresholds (0~100%) based on GIS, aiming to reveal the spatial-temporal difference in acquisition probability. The main conclusions are as follows: (1) Sentinel-2 A/B imagery was highly appropriate for land surface remote sensing monitoring with a cloud coverage threshold of 20% (i.e., cloud coverage is ≤ 20%). This threshold resulted in the largest monthly cumulative probability (~27.41%) of Sentinel-2 A/B images in northern Laos. (2) Using the threshold of 20% cloud coverage, the differences in monthly cumulative average acquisition probabilities of Sentinel-2 A/B images in northern Laos were consistent with the temporal distributions of dry season (November to April) and wet season (May to October). The acquisition probability was 42.91% in the dry season, with the largest in March (50.27%), followed by April and February. The fact that Sentinel-2 is featured by larger acquisition probability during the peak of dry season greatly facilitates the monitoring of dynamics in swidden agriculture and rubber plantations. The corresponding probability in the wet season was merely 11.81%, with the lowest in June (~1.26%). (3) Huge differences in monthly cumulative average acquisition probabilities of Sentinel-2 A/B images between the east and west of northern Laos were revealed. In the dry season, the image acquisition probabilities of the western provinces (e.g., Luang Namtha) were much larger than those of the eastern ones, while the situation was just the opposite in the wet season. This study can provide important reference for the large-scale (e.g. global) cloud coverage analysis of Sentinel-2 A/B images and the selection of Sentinel-2 images for monitoring land use change due to United Nations Collaborative Programme on Reducing Emissions from Deforestation and Forest Degradation in Developing Countries (UN-REDD) in the tropics, including swidden agriculture transformation and rubber plantation expansion.