珞珈一号夜间灯光影像在建设用地提取中的应用:以武汉市为例

城市建设用地能够反映城市建设发展在地域空间上的分布形态,是规划主管部门监测城市建设和扩张的关键指标.2018-06-02发射的珞珈一号卫星可提供130 m分辨率的夜间灯光数据,在城市建设用地的提取方面具有较大潜力.首先整合珞珈一号夜间灯光影像与Landsat 8多光谱影像以及网络地图兴趣点数据;然后分别采用人类居住合成...

Extracting Built-up Areas Using Luojia-1A Nighttime Light Imageries in Wuhan,China

The extent of urban built-up areas is important to understand the current status and development of cities,also is one of the preconditions to implement the control of urban boundaries and manage the layout of urban functional space.In the past,the accuracy of urban built-up areas extraction using nighttime light imageries is often limited by data resolution and spatial scales.The Luojia-1 A satellite,launched on2018-06-02,provides a new source of nighttime light data at 130-meter resolution,which has great potential in extent extraction of urban built-up areas.In this paper,integrating Luojia-1 A nighttime light data with Landsat 8 multispectral imageries and point of interest(POI),the extent of built-up areas in Wuhan,China has been extracted using human settlement index(HSI) and thresholds,respectively.The results of Luojia-1 A data have been compared with results obtained from visible infrared imager radiometer suite(VIIRS) data using corresponding methods.The results show that the extracted urban extent extracted by HSI using Luojia-1 A data possesses the highest accuracy,with a Kappa coefficient of 0.769.Correspondingly,the Kappa coefficient of built-up areas extent obtained by HSI method using VIIRS data is 0.702.The accuracies of urban extent extracted by integrating Luojia-1 A and VIIRS images with POIs are relatively lower,which have respectively present Kappa coefficients of 0.618 and 0.574.The Kappa coefficients of extraction accuracies using simple thresholds segementation(STS) method form raw Luojia-1 A and VIIRS images are 0.503 and 0.482.The results reveal that Luojia-1 A nighttime light data benefit urban extent extraction for its finer resolution and more abundant spatial details,compared with its predecessors such as DMSP/OLS and VIIRS.