Filtering the NPP-VIIRS Nighttime Light Data for Improved Detection of Settlements in Africa

Xiaotian Yuan,Li Jia,Qiting Chen,Massimo Menenti,Jie Zhou

doi:10.3390/rs11243002

Abstract

Observing and understanding changes in Africa is a hotspot in global ecological environmental research since the early 1970s. As possible causes of environmental degradation, frequent droughts and human activities attracted wide attention. Remote sensing of nighttime light provides an effective way to map human activities and assess their intensity. To identify settlements more effectively, this study focused on nighttime light in the northern Equatorial Africa and Sahel settlements to propose a new method, namely, the patches filtering method (PFM) to identify nighttime lights related to settlements from the National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) monthly nighttime light data by separating signal components induced by biomass burning, thereby generating a new annual image in 2016. The results show that PFM is useful for improving the quality of NPP-VIIRS monthly nighttime light data. Settlement lights were effectively separated from biomass burning lights, in addition to capturing the seasonality of biomass burning. We show that the new 2016 nighttime light image can very effectively identify even small settlements, notwithstanding their fragmentation and unstable power supply. We compared the image with earlier NPP-VIIRS annual nighttime light data from the National Oceanic and Atmospheric Administration (NOAA) National Center for Environmental Information (NCEI) for 2016 and the Sentinel-2 prototype Land Cover 20 m 2016 map of Africa released by the European Space Agency (ESA-S2-AFRICA-LC20). We found that the new annual nighttime light data performed best among the three datasets in capturing settlements, with a high recognition rate of 61.8%, and absolute superiority for settlements of 2.5 square kilometers or less. This shows that the method separates biomass burning signals very effectively, while retaining the relatively stable, although dim, lights of small settlements. The new 2016 annual image demonstrates good performance in identifying human settlements in sparsely populated areas toward a better understanding of human activities.

Highlights

Nighttime light is a good indicator of human activity [1,2,3]
The performance of the patches filtering method (PFM) method was evaluated by comparing nighttime light patches identified in the NPP-VIIRS nighttime light monthly image in January 2016 with settlements identified in the European Space Agency (ESA)-S2-AFRICA-LC20 map (Figure 5)
We applied PFM, which was proposed in this study, to filter the NPP-VIIRS nighttime light monthly data and generated a new NPP-VIIRS annual nighttime light image of the northern Equatorial Africa and Sahel region

Summary

Introduction

Nighttime light is a good indicator of human activity [1,2,3]. Satellite-borne imaging radiometers capture accurate nighttime light data, providing the opportunity to study the nighttime light quantitatively in large areas [4]. Reasons can be sub-optimal electricity infrastructure, nonscheduled black-outs, and relatively low demand induced by high costs of electricity [25,29] This may limit the application of nighttime light data to detect human settlements in developing regions like northern Equatorial Africa and Sahel. Scattered background noise appears throughout the monthly images and should be removed, but the weaker signal associated with either settlements or biomass burning is assessed as being noise when applying a threshold to observed radiance. By sampling areas without artificial light sources, different thresholds were obtained for each region, distributed in the range 0.2 to 0.4 × 10−9 W·cm−2·sr−1 (average 0.29 × 10−9 W·cm−2·sr−1, standard deviation 0.12) These thresholds were consistent with current estimates of the minimum detectable radiance (see Table 1). We generated corrected monthly image data with no background noise by setting pixel values smaller than the corresponding threshold to zero

Objectives

Methods

Results

Conclusion