| Records |
| Author |
Pan, H.; Xu, Y.; Liang, G.; Wyckhuys, K.A.G.; Yang, Y.; Lu, Y. |
| Title |
Field evaluation of light-emitting diodes to trap the cotton bollworm, Helicoverpa armigera |
Type |
Journal Article |
Year  |
2020 |
Publication |
Crop Protection |
Abbreviated Journal |
Crop Protection |
| Volume |
in press |
Issue |
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Pages |
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| Keywords |
Animals |
| Abstract |
The cotton bollworm, Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae), is a limiting pest of many agricultural crops worldwide. At present, in-field populations of H. armigera are routinely monitored using conventional light traps. During 2014, 2015, we conducted field assays to assess the relative attractiveness of narrow-band light-emitting diodes (LEDs) at 19 single wavelengths (375–748 nm) in H. armigera light traps. Between 2016 and 2019, LEDs with the most attractive wavelengths were then further evaluated in two different sites, i.e., Xinxiang and Anci (China). During 2014–2015, the highest H. armigera trap capture was obtained with LEDs at 395 nm, while it was not significantly different from LED wavelengths of 375 nm and 418 nm in 2015. During field trials in Xinxiang, H. armigera trap capture did not differ among (four) wavelengths (375 nm, 385 nm, 395 nm, and 405 nm) in either year. In the Anci site, most H. armigera adults were caught in traps equipped with LEDs of 385 nm during two years, but it was not significantly different from those at 405 nm in 2017. In 2019, H. armigera trap capture rate was higher for LEDs at 385 nm than for those at 395 nm, and 2.91-fold higher to that of a commercial UV blacklight (365 ± 50 nm) trap. Our work shows how LED-equipped traps constitute an efficient, energy-conserving way to monitor cotton bollworm populations, providing trap capture rates that surpass those of conventional technologies. We discuss how these innovative measures can complement the integrated pest management (IPM) toolbox for H. armigera in China and abroad. |
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0261-2194 |
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no |
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GFZ @ kyba @ |
Serial |
2984 |
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Li, X.; Zhou, Y.; Zhao, M.; Zhao, X. |
| Title |
A harmonized global nighttime light dataset 1992-2018 |
Type |
Journal Article |
| Year |
2020 |
Publication |
Scientific Data |
Abbreviated Journal |
Sci Data |
| Volume |
7 |
Issue |
1 |
Pages |
168 |
| Keywords |
Remote Sensing |
| Abstract |
Nighttime light (NTL) data from the Defense Meteorological Satellite Program (DMSP)/Operational Linescan System (OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership satellite provide a great opportunity for monitoring human activities from regional to global scales. Despite the valuable records of nightscape from DMSP (1992-2013) and VIIRS (2012-2018), the potential of the historical archive of NTL observations has not been fully explored because of the severe inconsistency between DMSP and VIIRS. In this study, we generated an integrated and consistent NTL dataset at the global scale by harmonizing the inter-calibrated NTL observations from the DMSP data and the simulated DMSP-like NTL observations from the VIIRS data. The generated global DMSP NTL time-series data (1992-2018) show consistent temporal trends. This temporally extended DMSP NTL dataset provides valuable support for various studies related to human activities such as electricity consumption and urban extent dynamics. |
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Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA, 50011, USA |
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English |
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2052-4463 |
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PMID:32499523 |
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no |
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GFZ @ kyba @ |
Serial |
2985 |
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Liu, Y.; Zhang, X.; Pan, X.; Ma, X.; Tang, M. |
| Title |
The spatial integration and coordinated industrial development of urban agglomerations in the Yangtze River Economic Belt, China |
Type |
Journal Article |
| Year |
2020 |
Publication |
Cities |
Abbreviated Journal |
Cities |
| Volume |
104 |
Issue |
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Pages |
102801 |
| Keywords |
Remote Sensing |
| Abstract |
Urban agglomeration is the engine of national development and regional prosperity. Although extensive work has investigated issues related to this new form of spatial governance, few studies have directly illustrated the spatial integration of urban agglomeration and its relationship with industrial development. This paper employs nighttime light data and industrial enterprise datasets to investigate the spatial integration and industrial development in the Yangtze River Economic Belt (YREB) of China for 1995–2015. We here illustrate the significant relationship between the spatial integration of urban agglomerations and the characteristics of industrial development. In the process of spatial integration, urban form, intercity relation and their evolution show clear regional differences. Because of the differences in socio-economic and geographical characteristics, urban systems are more advanced and closely related in developed areas. A significant negative (positive) spatial correlation between industrial specialization (diversification) and urban form is supported by using bivariate Moran's I, and spatial clustering patterns are clearly different across the three urban agglomerations. A panel regression reveals that intercity relations are significantly associated with the characteristics of industrial development. Higher levels of industrial diversification and competition are associated with weaker intercity relations, while industrial structures similarities are reversed. These findings could be used to formulate reasonable policies and plans and to support future regional spatial integration and coordinated development. |
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0264-2751 |
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GFZ @ kyba @ |
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2986 |
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Sun, C.; Liu, Y.; Zhao, S.; Jin, S. |
| Title |
Estimating offshore oil production using DMSP-OLS annual composites |
Type |
Journal Article |
| Year |
2020 |
Publication |
ISPRS Journal of Photogrammetry and Remote Sensing |
Abbreviated Journal |
ISPRS Journal of Photogrammetry and Remote Sensing |
| Volume |
165 |
Issue |
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Pages |
152-171 |
| Keywords |
Remote Sensing |
| Abstract |
Offshore oil exploitation is expanding worldwide in response to the increasing demand for global energy. The long-term acquisition of information on offshore oil production is essential to solve geo-political conflicts and to control marine pollution. However, such information is either dispersed among different authorities or may not even exist. Night-Time Lights (NTL) data has advantages in terms of synoptic coverage and repeatability, providing the opportunity to collect information about marine resources and energy. Until recently, estimating offshore oil production using NTL data was still challenging, largely due to the inability of distinguishing the NTL of oil and gas production. Here, we present an approach for retrieving the spatio-temporal distribution of offshore oil production using DMSP-OLS annual composites. Starting with the geo-locations of offshore platforms, we first propose a Method for Platform Type Classification (MPTC) to discriminate oil platforms from gas platforms. A Model for Oil Production Estimation and Assignment (MOPEA) was then designed by correlating the sum of brightness from oil platforms with offshore oil production. Given worldwide data availability, the offshore regions of the United Kingdom (UK) were used as the initial study area. The principal results are as follows: (i) the overall accuracy of the MPTC and the relative error of the MOPEA were 87.8% and 11.5%, respectively, and the production of each oilfield was in order of magnitude agreement with reality; (ii) there were 365 oil platforms and 258 gas platforms in the UK during 1992–2013, with a distinct spatial distribution north and south of the latitude of 55°N; and (iii) the offshore oil production of the UK declined substantially during 1992–2013, from 9.92 × 107 to 5.63 × 107 sm3, despite an increase in the number of oilfields from 39 to 120 plots; this was mainly because the loss of production in previously highly productive oilfields was too great to be offset by the increased number of low production oilfields. The regional transferability of the MPTC and MOPEA was then validated with reference to three other offshore regions (the Gulf of Guinea of Nigeria, the South China Sea, and the northern Gulf of Mexico of the USA) with satisfactory results. In addition, the MPTC and MOPEA are demonstrated to be capable of extension to the NPP-VIIRS products, paving the way for future applications. |
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0924-2716 |
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no |
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GFZ @ kyba @ |
Serial |
2987 |
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| Author |
Coesfeld, J.; Kuester, T.; Kuechly, H.U.; Kyba, C.C.M. |
| Title |
Reducing Variability and Removing Natural Light from Nighttime Satellite Imagery: A Case Study Using the VIIRS DNB |
Type |
Journal Article |
| Year |
2020 |
Publication |
Sensors |
Abbreviated Journal |
Sensors |
| Volume |
20 |
Issue |
11 |
Pages |
3287 |
| Keywords |
Remote Sensing; Instrumentation |
| Abstract |
Temporal variation of natural light sources such as airglow limits the ability of night light sensors to detect changes in small sources of artificial light (such as villages). This study presents a method for correcting for this effect globally, using the satellite radiance detected from regions without artificial light emissions. We developed a routine to define an approximate grid of locations worldwide that do not have regular light emission. We apply this method with a 5 degree equally spaced global grid (total of 2016 individual locations), using data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB). This code could easily be adapted for other future global sensors. The correction reduces the standard deviation of data in the Earth Observation Group monthly DNB composites by almost a factor of two. The code and datasets presented here are available under an open license by GFZ Data Services, and are implemented in the Radiance Light Trends web application. |
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1424-8220 |
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GFZ @ kyba @ |
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2988 |
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