地球信息科学学报 ›› 2020, Vol. 22 ›› Issue (11): 2227-2237.doi: 10.12082/dqxxkx.2020.190559

• 遥感科学与应用技术 • 上一篇    下一篇

基于复合指数模型的DMSP/OLS夜间灯光影像饱和校正方法

许文鑫1,2(), 梁娟珠1,2,*()   

  1. 1.福州大学,福建省空间信息工程研究中心,数据挖掘与信息共享教育部重点实验室,福州 350116
    2.数字中国研究院(福建),福州 350116
  • 收稿日期:2019-09-29 修回日期:2019-12-23 出版日期:2020-11-25 发布日期:2021-01-25
  • 通讯作者: 梁娟珠 E-mail:xuwxfors@foxmail.com;liangjuanzhu@163.com
  • 作者简介:许文鑫(1995— ),男,安徽六安人,硕士研究生,研究方向为城市遥感、大数据分析与应用。E-mail: xuwxfors@foxmail.com
  • 基金资助:
    国家自然科学基金项目(41771423);福建省科技重点项目(2018Y0054)

Saturation Correction Method of DMSP/OLS Nighttime Lights Image based on Compound Exponential Model

XU Wenxin1,2(), LIANG Juanzhu1,2,*()   

  1. 1. Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Spatial Information Research Center of Fujian Province, Fuzhou 350116, China
    2. The Academy of Digital China (Fujian Province), Fuzhou 350116, China
  • Received:2019-09-29 Revised:2019-12-23 Online:2020-11-25 Published:2021-01-25
  • Contact: LIANG Juanzhu E-mail:xuwxfors@foxmail.com;liangjuanzhu@163.com
  • Supported by:
    National Natural Science Foundation of China(41771423);Fujian Science and Technology Key Project(2018Y0054)

摘要:

由于OLS传感器航行过程中增益记录和交叉定标的缺失,使得DMSP夜光影像在城市中心出现过度饱和等问题,因此探讨灯光数据去饱和方法在人类活动强度评估和城市时空演化分析等方面具有重要意义。为了解决这一难题,有学者提出使用NDVI修正饱和灯光数据的VANUI指数,为研究灯光数据去饱和提供了简单便捷的思路,然而该指数在部分城市中较难有明显的校正效果。本文在VANUI指数思想的基础上,顾及到人口密度随着郊区到城市中心距离的增加呈现指数型增长,提出了基于复合指数模型校正夜间灯光指数CEANI,为人类活动强度评价等研究提供更准确的结果。研究表明:① 与VANUI相比,CEANI在刻画城市内部饱和区域特征时具有更好的细节,较好地凸显城市内部空间异质性;② 在25组随机样本的相关对比中,CEANI(R2mean=0.79)与辐射定标产品比VANUI(R2mean=0.68)具有更高的相关性;③ 三大城市群中CEANI与常住人口的R2分别为0.767、0.676和0.841,比VANUI(R2分别为0.640、0.553和0.775)分别提高了0.127、0.123、0.066,相较于VANUI,CEANI与常住人口具有更强的相关性,对于人口指标的估算能力更强。

关键词: 夜间灯光影像, DMSP/OLS, 城市灯光, 去饱和, VANUI指数, CEANI指数, 人类活动强度, 复合指数模型

Abstract:

The lack of gain recording and cross-calibration during the OLS sensor navigation makes DMSP nighttime lights image oversaturated in the city center, which affects the accuracy of using night light data to evaluate human activity intensity. In order to suppress the occurrence of saturation, the radiometric calibration night light data developed by Elvedge have been widely used. The radiometric calibration data products have a high accuracy and strong reliability. However, the calibration process is complex, and the required data is usually difficult to obtain. At present, only a few results have applied the calibration data to the continuity analysis. In recent years, many scholars found that NDVI can desaturate DMSP/OLS night light images and enhance the heterogeneity of urban center. Based on this, non-radiation calibration method has been applied to correct the saturation effect and shown a good correction result. On the basis of summarizing the idea by VANUI that the difference between night light intensity and vegetation coverage shows a decreasing trend from the city center to the suburb, this paper considers that the population density increases exponentially with the increase of rural-urban distance. We proposed a correction of nighttime light index based on compound exponential model (CEANI). Results show that (1) compared with VANUI, CEANI showed better details and spatial heterogeneity when characterizing the saturated regions of the city. In addition, CEANI not only identified areas where human activity was concentrated, such as stations, airports, and business areas with high traffic and people flow, but also clearly identified the areas with high vegetation coverage and low DN values such as forests and parks with sparse road network; (2) in the correlation analysis using 25 random samples, CEANI showed a higher correlation (R2mean = 0.79) with radiometric calibration products than VANUI (R2mean = 0.68); (3) CEANI had a stronger correlation with the number of permanent residents and significantly estimated population indicators better than VANUI, which suggests the better calculation index for describing the intensity of human activity. In summary, the CEANI can be used to correct the saturation problem in DMSP/OLS luminous data products. It better shows the internal details of the city and its spatial heterogeneity, and thus can derive more accurate results for the evaluation of human activity intensity.

Key words: Nighttime Light, DMSP/OLS, Urban Light, Desaturase, VANUI, CEANI, Human Activity Intensity, Compound Exponential Model