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Author Sutton, P.; Roberts, D.; Elvidge, C.; Meij, H.
Title (up) A comparison of nighttime satellite imagery and population density for the continental United States. Type Journal Article
Year 1997 Publication Photogrammetric Engineering and Remote Sensing Abbreviated Journal
Volume 63 Issue 11 Pages 1303–1313
Keywords Remote Sensing
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Call Number LoNNe @ kagoburian @ Serial 974
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Author Richter, A.; Ng, K.T.W.; Karimi, N.
Title (up) A data driven technique applying GIS, and remote sensing to rank locations for waste disposal site expansion Type Journal Article
Year 2019 Publication Resources, Conservation and Recycling Abbreviated Journal Resources, Conservation and Recycling
Volume 149 Issue Pages 352-362
Keywords Remote Sensing
Abstract Landfilling is the most common method for final treatment of municipal solid waste worldwide. Canadians generated 973 kg/cap of waste in 2016, and 73% of that was sent to landfills or incinerators. This study proposes a novel method which combines remote sensing and vector data to rank the suitability of current landfill sites and their area of influence for expansion in Saskatchewan, Canada; where there are currently more than 500 active landfills. This study found that using average normalized data, 55.3% of the land in the study area was suitable or moderately suitable for landfill expansion while 45% of the area was unsuitable for landfill expansion. Polygon 32, an area dominated by agriculture and pasture land, is the most suitable for landfill expansion based on the mean normalized rank and was ranked 9th (out of 39) in terms of standard deviation. Polygon 27 is the least suitable for landfill expansion, having the largest mean normalized rank, and was ranked 38th (out of 39) in terms of standard deviation. This method is advantageous compared to other decision-making tools which rely on expert opinion. This method relies solely on remote sensing and vector data; but is flexible enough that weighting of data sets can be applied by policy makers if so desired. Results show that using remote sensing data and vector data together are capable of capturing distinctly different aspects of the study area, and that vector data can be used as a proxy for imagery where cloud cover is present.
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ISSN 0921-3449 ISBN Medium
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Notes Approved no
Call Number GFZ @ kyba @ Serial 2582
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Author Song, G.; Yu, M.; Liu, S.; Zhang, S.
Title (up) A dynamic model for population mapping: a methodology integrating a Monte Carlo simulation with vegetation-adjusted night-time light images Type Journal Article
Year 2015 Publication International Journal of Remote Sensing Abbreviated Journal International Journal of Remote Sensing
Volume 36 Issue 15 Pages 4054-4068
Keywords Remote Sensing
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ISSN 0143-1161 ISBN Medium
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Notes Approved no
Call Number LoNNe @ kyba @ Serial 1226
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Author Seaman, C.J.; Miller, S.D.
Title (up) A dynamic scaling algorithm for the optimized digital display of VIIRS Day/Night Band imagery Type Journal Article
Year 2015 Publication International Journal of Remote Sensing Abbreviated Journal International Journal of Remote Sensing
Volume 36 Issue 7 Pages 1839-1854
Keywords Remote Sensing
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ISSN 0143-1161 ISBN Medium
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Call Number LoNNe @ christopher.kyba @ Serial 1147
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Author Li, K.; Chen, Y.
Title (up) A Genetic Algorithm-Based Urban Cluster Automatic Threshold Method by Combining VIIRS DNB, NDVI, and NDBI to Monitor Urbanization Type Journal Article
Year 2018 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 10 Issue 2 Pages 277
Keywords Remote Sensing
Abstract Accurate and timely information related to quantitative descriptions and spatial distributions of urban areas is crucial to understand urbanization dynamics and is also helpful to address environmental issues associated with rapid urban land-cover changes. Thresholding is acknowledged as the most popular and practical way to extract urban information from nighttime lights. However, the difficulty of determining optimal threshold remains challenging to applications of this method. In order to address the problem of selecting thresholds, a Genetic Algorithm-based urban cluster automatic threshold (GA-UCAT) method by combining Visible-Infrared Imager-Radiometer Suite Day/Night band (VIIRS DNB), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Built-up Index (NDBI) is proposed to distinguish urban areas from dark rural background in NTL images. The key point of this proposed method is to design an appropriate fitness function of GA by means of integrating between-class variance and inter-class variance with all these three data sources to determine optimal thresholds. In accuracy assessments by comparing with ground truth—Landsat 8 OLI images, this new method has been validated and results with OA (Overall Accuracy) ranging from 0.854 to 0.913 and Kappa ranging from 0.699 to 0.722 show that the GA-UCAT approach is capable of describing spatial distributions and giving detailed information of urban extents. Additionally, there is discussion on different classifications of rural residential spots in Landsat remote sensing images and nighttime light (NTL) and evaluations of spatial-temporal development patterns of five selected Chinese urban clusters from 2012 to 2017 on utilizing this proposed method. The new method shows great potential to map global urban information in a simple and accurate way and to help address urban environmental issues.
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ISSN 2072-4292 ISBN Medium
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Call Number GFZ @ kyba @ Serial 2340
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