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Wang, R., Shi, W., & Dong, P. (2020). Mapping Dragon Fruit Croplands from Space Using Remote Sensing of Artificial Light at Night. Remote Sensing, 12(24), 4139.
Abstract: The nighttime light (NTL) on the surface of Earth is an important indicator for the human transformation of the world. NTL remotely sensed data have been widely used in urban development, population estimation, economic activity, resource development and other fields. With the increasing use of artificial lighting technology in agriculture, it has become possible to use NTL remote sensing data for monitoring agricultural activities. In this study, National Polar Partnership (NPP)-Visible Infrared Imaging Radiometer Suite (VIIRS) NTL remote sensing data were used to observe the seasonal variation of artificial lighting in dragon fruit cropland in Binh Thuan Province, Vietnam. Compared with the statistics of planted area, area having products and production of dragon fruit by district in the Statistical Yearbook of Binh Thuan Province 2018, values of the mean and standard deviation of NTL brightness have significant positive correlations with the statistical data. The results suggest that the NTL remotely sensed data could be used to reveal some agricultural productive activities such as dragon fruits production accurately by monitoring the seasonal artificial lighting. This research demonstrates the application potential of NTL remotely sensed data in agriculture.
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Wang, W., & Cao, C. (2019). NOAA-20 VIIRS DNB Aggregation Mode Change: Prelaunch Efforts and On-Orbit Verification/Validation Results. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(7).
Abstract: The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the National Oceanic and Atmospheric Administration-20 (NOAA-20, previously named Joint Polar Satellite System-1 or J1) satellite was successfully launched in late 2017, following six years of a successful operation by its predecessor on the Suomi National Polar-Orbiting Partnership (S-NPP) satellite. NOAA-20 VIIRS day/night band (DNB) adopts a new on-board aggregation option (Op21), which is different from S-NPP DNB (using Op32), to mitigate high non-linearity at high scan angles, observed in its radiometric response during prelaunch test. As a result, NOAA-20 VIIRS DNB has a larger scan angle at the end of scan (∼60.5°) and exhibits a unique feature, i.e., ∼600 km extended Earth view (EV) samples, compared to S-NPP DNB and other VIIRS bands. VIIRS geolocation (GEO) algorithm and geometric calibration parameters were analyzed in-depth and subsequently modified to accommodate the NOAA-20 VIIRS DNB aggregation mode change. The GEO code change was tested using S-NPP data; S-NPP DNB simulated J1 DNB radiance and limited J1 prelaunch test data. After the launch, it was further verified using NOAA-20 VIIRS on-orbit observations. Our results show that the prelaunch VIIRS GEO code change performs well. GEO validation results using nighttime point sources show that NOAA-20 DNB GEO errors are comparable to those for S-NPP DNB over the nominal EV range, with averaged nadir equivalent GEO errors less than 200 m after on-bit updates. Over the extended EV samples (scan angle > 56.06°), the averaged GEO errors are less than 500 m. Moreover, NOAA-20 VIIRS DNB radiometric calibration performance is comparable to S-NPP.
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Yu, B., Shi, K., Hu, Y., & Huang, C. (2015). Poverty Evaluation Using NPP-VIIRS Nighttime Light Composite Data at the County Level in China. IEEE J. Selected Topics in Appl. Earth Obs. and Rem. Sens., (2399416).
Abstract: Poverty has appeared as one of the long-term predicaments facing development of human society during the 21st century. Estimation of regional poverty level is a key issue for making strategies to eliminate poverty. This paper aims to evaluate the ability of the nighttime light composite data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day–Night Band (DNB) carried by the Suomi National Polar-orbiting Partnership (NPP) Satellite in estimating poverty at the county level in China. Two major experiments are involved in this study, which include 1) 38 counties of Chongqing city and 2) 2856 counties of China. The first experiment takes Chongqing as an example and combines 10 socioeconomic variables into an integrated poverty index (IPI). IPI is then used as a reference to validate the accuracy of poverty evaluation using the average light index (ALI) derived from NPP-VIIRS data. Linear regression and comparison of the class ranks have been employed to verify the correlation between ALI and IPI. The results show a good correlation between IPI and ALI, with a coefficient of determination ($R^2$) of 0.8554, and the class ranks of IPI and API show relative closeness at the county level. The second experiment examines all counties in China and makes a comparison between ALI values and national poor counties (NPC). The comparison result shows a general agreement between the NPC and the counties with low ALI values. This study reveals that the NPP-VIIRS data can be a useful tool for evaluating poverty at the county level in China.
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Zhuo, L., Zheng, J., Zhang, X., Li, J., & Liu, L. (2015). An improved method of night-time light saturation reduction based on EVI. International Journal of Remote Sensing, 36(16), 4114–4130.
Abstract: Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) night-time light (NTL) data have been widely applied to studies on anthropogenic activities and their interactions with the environment. Due to limitations of the OLS sensor, DMSP NTL data suffer from a saturation problem in central urban areas, which further affects studies based on nocturnal lights. Recently, the vegetation-adjusted NTL urban index (VANUI) has been developed based on the inverse correlation of vegetation and urban surfaces. Despite its simple implementation and ability to effectively increase variations in NTL data, VANUI does not perform well in certain rapidly growing cities. In this study, we propose a new index, denoted enhanced vegetation index (EVI)-adjusted NTL index (EANTLI), that was developed by reforming the VANUI algorithm and utilizing the EVI. Comparisons with radiance-calibrated NTL (RCNTL) and the new Visible Infrared Imager Radiometer Suite (VIIRS) data for 15 cities worldwide show that EANTLI reduces saturation in urban cores and mitigates the blooming effect in suburban areas. EANTLI’s similarity to RCNTL and VIIRS is consistently higher than VANUI’s similarity to RCNTL and VIIRS in both spatial distribution and latitudinal transects. EANTLI also yields better results in the estimation of electric power consumption of 166 Chinese prefecture-level cities. In conclusion, EANTLI can effectively reduce NTL saturation in urban centres, thus presenting great potential for wide-range applications.
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