Accurate mapping of burned area is of key importance for fire emissions modeling and post-fire rehabilitation planning. In this research, Sentinel-2 data were used to analyze the difference in spectral signature between burned area and false positives from agricultural harvests. 26 fires that were mapped in the field using Global Navigation Satellite System during 2017 and 2018 were analyzed over California and Utah, USA. Individual Sentinel-2 bands and a wide range of commonly used spectral indices for burned area were tested using a spectral separability index. The separability index assessed discrimination between the classes burned area and 1) unburned area and 2) area in agricultural land that were flagged as false positive from agricultural harvest. Separability values higher than one indicate good separation and the higher the values, the better the separation. For each class, we first determined the multitemporal difference, i.e. the absolute value of the pre-minus-post-change value. Second, we compared with other classes by using the spectral separability index. We found that for the burned-to-unburned comparison the near and shortwave infrared spectral regions and spectral indices that make use of these spectral regions, were the best discriminators (separability (M) values of approximately 2), corroborating findings from earlier works. For the burned-to-agricultural false positive comparison Sentinel-2 bands 4 and 5, corresponding with the Red and Red-edge spectral regions, were the best discriminator (M−values greater than 2). Consequently, spectral indices containing the Red band show a similar strong separability of agricultural false positives. The results from our research reveal an additional layer of information that could be exploited to minimize false positives in agricultural lands in space-borne burned area products.

准确绘制燃烧区域对于火灾排放建模和火灾后恢复计划至关重要。在这项研究中，使用Sentinel-2数据分析了燃烧区域和农业收成的假阳性之间的光谱特征差异。在2017年和2018年期间，使用全球导航卫星系统在野外绘制的26起火灾在美国加利福尼亚州和犹他州进行了分析。使用光谱可分离性指数测试了各个Sentinel-2波段和广泛的燃烧区域常用光谱指数。可分离性指数评估了在农业土地上被标记为假阳性的农业土地中燃烧面积与1）未燃烧面积和2）面积之间的区别。分离度值大于1表示分离效果好，分离度值越高，分离效果越好。对于每个类别，我们首先确定多时间差异，即减去前后的值的绝对值。其次，我们通过使用光谱可分离性指数与其他类别进行了比较。我们发现，对于燃烧到未燃烧的比较而言，近波和短波红外光谱区域以及利用这些光谱区域的光谱指数是最好的鉴别器（可分离性（M）值约为2），这证实了早期工作的发现。对于烧毁的农业假阳性比较，与红色和红色边缘光谱区域相对应的Sentinel-2波段4和5是最佳判别器（M值大于2）。因此，包含红色谱带的光谱指数显示出农业假阳性的相似强分离性。