toggle visibility Search & Display Options

Select All    Deselect All
 |   | 
Details
   print
  Records Links
Author Marx, A.; Ziegler Rogers, M. url  doi
openurl 
  Title Analysis of Panamanian DMSP/OLS nightlights corroborates suspicions of inaccurate fiscal data: A natural experiment examining the accuracy of GDP data Type Journal Article
  Year 2017 Publication Remote Sensing Applications: Society and Environment Abbreviated Journal (down) Remote Sensing Applications: Society and Environment  
  Volume 8 Issue Pages 99-104  
  Keywords Remote Sensing  
  Abstract Governments have incentives to misreport their economic productivity to advance their political goals. These incentives have long been understood, but the validity of government data has been difficult to estimate in the absence of viable external estimates. Using historic Defense Meteorological Satellite Program's Operational Linescan System nightlights imagery we corroborate reports that Panama's government data has been increasingly politicised since the handover of the Panama Canal on 31 December 1999. The Canal Handover represents a “natural experiment” in which the production of government data changed in Panama for reasons separate from the desire to manipulate that data. The amount of light a country produces at night, known as nightlight production, has been shown to strongly correlate with GDP. Using subnational Panamanian nightlight production from 1996 to 2012, we detect a significant divergence between the relationship of subnational reported GDP and nightlights before the Canal handover (when the U.S.A. was very involved in their statistical agencies) and the correlation after the handover (with no U.S. involvement). Our results indicate that between 2000 and 2012, Panama reported approximately 19% more GDP than what was expected by their nightlight production from 2000 to 2012, or a total of around 40 billion U.S. dollars. Our results suggest governments may engage in political manipulation of government statistics to improve the appearance of government performance. While indirect data can never definitely confirm economic phenomena, this analysis presents a unique research design and application of historic satellite imagery to corroborate reports of GDP misreporting.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2352-9385 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2479  
Permanent link to this record
 

 
Author Ranzoni, J.; Giuliani, G.; Huber, L.; Ray, N. url  doi
openurl 
  Title Modelling the nocturnal ecological continuum of the State of Geneva, Switzerland, based on high-resolution nighttime imagery Type Journal Article
  Year 2019 Publication Remote Sensing Applications: Society and Environment Abbreviated Journal (down) Remote Sensing Applications: Society and Environment  
  Volume 16 Issue Pages 100268  
  Keywords Remote Sensing; Ecology; Switzerland; Europe; orthophotography; viewshed analysis  
  Abstract The increase of artificial light in recent decades has led to a general awareness of the harmful consequences of light pollution on biodiversity. The artificial light is however rarely taken into account in the principles of developing ecological networks. There is currently no standardized method for integrating this darkness factor into ecological network modeling. We propose a methodology for the identification of the nocturnal continuum through an approach based on the automated extraction of light sources from nocturnal orthophotography and the modeling of their visibility within a territory. The model is applied to the transboundary region of the Geneva basin in Switzerland and allows for the integration of the darkness factor into the existing ecological networks. Although the analysis does not consider metric lighting data, a viewshed analysis allows for a first large-scale mapping of the nighttime continuum and highlights the areas benefiting from very low light pollution.  
  Address University of Applied Sciences and Arts, Route de Presinge 150, 1254, Jussy, Switzerland; jessica.ranzoni(at)hesge.ch  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2352-9385 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2687  
Permanent link to this record
 

 
Author Mann, M.; Melaas, E.; Malik, A. url  doi
openurl 
  Title Using VIIRS Day/Night Band to Measure Electricity Supply Reliability: Preliminary Results from Maharashtra, India Type Journal Article
  Year 2016 Publication Remote Sensing Abbreviated Journal (down) Remote Sensing  
  Volume 8 Issue 9 Pages 711  
  Keywords Remote Sensing; NPP-VIIRS; VIIRS-DNB; India; South Asia  
  Abstract Unreliable electricity supplies are common in developing countries and impose large socio-economic costs, yet precise information on electricity reliability is typically unavailable. This paper presents preliminary results from a machine-learning approach for using satellite imagery of nighttime lights to develop estimates of electricity reliability for western India at a finer spatial scale. We use data from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar Partnership (SNPP) satellite together with newly-available data from networked household voltage meters. Our results point to the possibilities of this approach as well as areas for refinement. With currently available training data, we find a limited ability to detect individual outages identified by household-level measurements of electricity voltage. This is likely due to the relatively small number of individual outages observed in our preliminary data. However, we find that the approach can estimate electricity reliability rates for individual locations fairly well, with the predicted versus actual regression yielding an R2 > 0.5. We also find that, despite the after midnight overpass time of the SNPP satellite, the reliability estimates derived are representative of daytime reliability.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2072-4292 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number LoNNe @ kyba @ Serial 1515  
Permanent link to this record
 

 
Author Geronimo, R.; Franklin, E.; Brainard, R.; Elvidge, C.; Santos, M.; Venegas, R.; Mora, C. url  doi
openurl 
  Title Mapping Fishing Activities and Suitable Fishing Grounds Using Nighttime Satellite Images and Maximum Entropy Modelling Type Journal Article
  Year 2018 Publication Remote Sensing Abbreviated Journal (down) Remote Sensing  
  Volume 10 Issue 10 Pages 1604  
  Keywords Remote Sensing  
  Abstract Fisheries surveys over broad spatial areas are crucial in defining and delineating appropriate fisheries management areas. Yet accurate mapping and tracking of fishing activities remain largely restricted to developed countries with sufficient resources to use automated identification systems and vessel monitoring systems. For many countries, the spatial extent and boundaries of fishing grounds are not completely known. We used satellite images at night to detect fishing grounds in the Philippines for fishing gears that use powerful lights to attract coastal pelagic fishes. We used nightly boat detection data, extracted by U.S. NOAA from the Visible Infrared Imaging Radiometer Suite (VIIRS), for the Philippines from 2012 to 2016, covering 1713 nights, to examine spatio-temporal patterns of fishing activities in the country. Using density-based clustering, we identified 134 core fishing areas (CFAs) ranging in size from 6 to 23,215 km2 within the Philippines’ contiguous maritime zone. The CFAs had different seasonal patterns and range of intensities in total light output, possibly reflecting differences in multi-gear and multi-species signatures of fishing activities in each fishing ground. Using maximum entropy modeling, we identified bathymetry and chlorophyll as the main environmental predictors of spatial occurrence of these CFAs when analyzed together, highlighting the multi-gear nature of the CFAs. Applications of the model to specific CFAs identified different environmental drivers of fishing distribution, coinciding with known oceanographic associations for a CFA’s dominant target species. This case study highlights nighttime satellite images as a useful source of spatial fishing effort information for fisheries, especially in Southeast Asia.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2072-4292 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2033  
Permanent link to this record
 

 
Author Li, K.; Chen, Y.; Li, Y. url  doi
openurl 
  Title The Random Forest-Based Method of Fine-Resolution Population Spatialization by Using the International Space Station Nighttime Photography and Social Sensing Data Type Journal Article
  Year 2018 Publication Remote Sensing Abbreviated Journal (down) Remote Sensing  
  Volume 10 Issue 10 Pages 1650  
  Keywords Remote Sensing  
  Abstract Despite the importance of high-resolution population distribution in urban planning, disaster prevention and response, region economic development, and improvement of urban habitant environment, traditional urban investigations mainly focused on large-scale population spatialization by using coarse-resolution nighttime light (NTL) while few efforts were made to fine-resolution population mapping. To address problems of generating small-scale population distribution, this paper proposed a method based on the Random Forest Regression model to spatialize a 25 m population from the International Space Station (ISS) photography and urban function zones generated from social sensing data—point-of-interest (POI). There were three main steps, namely HSL (hue saturation lightness) transformation and saturation calibration of ISS, generating functional-zone maps based on point-of-interest, and spatializing population based on the Random Forest model. After accuracy assessments by comparing with WorldPop, the proposed method was validated as a qualified method to generate fine-resolution population spatial maps. In the discussion, this paper suggested that without help of auxiliary data, NTL cannot be directly employed as a population indicator at small scale. The Variable Importance Measure of the RF model confirmed the correlation between features and population and further demonstrated that urban functions performed better than LULC (Land Use and Land Cover) in small-scale population mapping. Urban height was also shown to improve the performance of population disaggregation due to its compensation of building volume. To sum up, this proposed method showed great potential to disaggregate fine-resolution population and other urban socio-economic attributes.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2072-4292 ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number GFZ @ kyba @ Serial 2038  
Permanent link to this record
Select All    Deselect All
 |   | 
Details
   print

Save Citations:
Export Records: