Globally, the unprecedented increase in population in many cities has led to rapid changes in urban landscape, which requires timely assessments and monitoring. Accurate determination of built-up information is vital for urban planning and environmental management. Often, the determination of the built-up area information has been dependent on field surveys, which is laborious and time-consuming. Remote sensing data are the only option for deriving spatially explicit and timely built-up area information. There are few spectral indices for built-up areas and often not accurate as they are specific to impervious material, age, colour, and thickness, especially using higher resolution images. The objective of this study is to test the utility of a new built-up extraction index (NBEI) using WorldView-2 (WV-2) to improve built-up material mapping irrespective of material type, age, and color. The new index was derived from spectral bands such as green, red edge, NIR1, and NIR2 bands that profoundly explain the variation in built-up areas on WV-2 image. The result showed that NBEI improves the extraction of built-up areas with high accuracy [area under the receiver operating characteristic curve, ( AUROC ) = ∼ 0.82] compared to the existing indices such as built-up area index (AUROC = ∼ 0.73), built-up spectral index (AUROC = ∼ 0.78), red edge/green index (AUROC = ∼ 0.71) and WorldView-Built-up Index (WV-BI) (AUROC = ∼ 0.67). The study demonstrated that the new built-up index could extract built-up areas using high-resolution images. The performance of NBEI could be attributed to the fact that it is not material-specific, and would be necessary for urban area mapping.

中文翻译：

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光谱指数可改善从WorldView-2影像中提取建筑物区域的能力

在全球范围内，许多城市的人口空前增长导致城市景观快速变化，这需要及时进行评估和监测。准确确定积累的信息对于城市规划和环境管理至关重要。通常，对建筑面积信息的确定取决于现场调查，这既费力又费时。遥感数据是得出空间明确和及时的建筑面积信息的唯一选择。建筑物区域的光谱指数很少，并且通常不准确，因为它们特定于不渗透的材料，年龄，颜色和厚度，尤其是使用高分辨率图像时。这项研究的目的是使用WorldView-2（WV-2）测试新的堆积提取指数（NBEI）的实用性，以改善堆积的材质贴图，而不论材质类型，年龄和颜色如何。新的索引来自诸如绿色，红色边缘，NIR1和NIR2波段之类的光谱带，这些光谱带深刻地解释了WV-2图像上堆积区域的变化。结果表明，与现有指标（例如建筑面积指数（AUROC =〜0.73））相比，NBEI能够以更高的精度（在接收机工作特性曲线下的面积（AUROC）=〜0.82）提高对建筑面积的提取。 ，累积光谱指数（AUROC =约0.78），红边/绿色指数（AUROC =约0.71）和WorldView内置指数（WV-BI）（AUROC =约0.67）。研究表明，新的建筑物索引可以使用高分辨率图像提取建筑物区域。