|   | 
Details
   web
Records
Author Alabia, I.; Dehara, M.; Saitoh, S.-I.; Hirawake, T.
Title Seasonal Habitat Patterns of Japanese Common Squid (Todarodes Pacificus) Inferred from Satellite-Based Species Distribution Models Type Journal Article
Year 2016 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 8 Issue 11 Pages 921
Keywords Remote Sensing; Animals
Abstract The understanding of the spatio-temporal distributions of the species habitat in the marine environment is central to effectual resource management and conservation. Here, we examined the potential habitat distributions of Japanese common squid (Todarodes pacificus) in the Sea of Japan during a four-year period. The seasonal patterns of preferential habitat were inferred from species distribution models, built using squid occurrences detected from night-time visible images and remotely-sensed environmental factors. The predicted squid habitat (i.e., areas with high habitat suitability) revealed strong seasonal variability, characterized by a reduction of potential habitat, confined off of the southern part of the basin during the winter–spring period (December–May). Apparent expansion of preferential habitat occurred during summer–autumn months (June–November), concurrent with the formation of highly suitable habitat patches in certain regions of the Sea of Japan. These habitat distribution patterns were in response to changes in oceanographic conditions and synchronous with seasonal migration of squid. Moreover, the most important variables regulating the spatio-temporal patterns of suitable habitat were sea surface temperature, depth, sea surface height anomaly, and eddy kinetic energy. These variables could affect the habitat distributions through their impacts on growth and survival of squid, local nutrient transport, and the availability of favorable spawning and feeding grounds.
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 (down) 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number LoNNe @ kyba @ Serial 1551
Permanent link to this record
 

 
Author Zhu, X.; Ma, M.; Yang, H.; Ge, W.
Title Modeling the Spatiotemporal Dynamics of Gross Domestic Product in China Using Extended Temporal Coverage Nighttime Light Data Type Journal Article
Year 2017 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 9 Issue 6 Pages 626
Keywords Remote Sensing
Abstract Nighttime light data derived from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) in conjunction with the Soumi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) possess great potential for measuring the dynamics of Gross Domestic Product (GDP) at large scales. The temporal coverage of the DMSP-OLS data spans between 1992 and 2013, while the NPP-VIIRS data are available from 2012. Integrating the two datasets to produce a time series of continuous and consistently monitored data since the 1990s is of great significance for the understanding of the dynamics of long-term economic development. In addition, since economic developmental patterns vary with physical environment and geographical location, the quantitative relationship between nighttime lights and GDP should be designed for individual regions. Through a case study in China, this study made an attempt to integrate the DMSP-OLS and NPP-VIIRS datasets, as well as to identify an optimal model for long-term spatiotemporal GDP dynamics in different regions of China. Based on constructed regression relationships between total nighttime lights (TNL) data from the DMSP-OLS and NPP-VIIRS data in provincial units (R2 = 0.9648, P < 0.001), the temporal coverage of nighttime light data was extended from 1992 to the present day. Furthermore, three models (the linear model, quadratic polynomial model and power function model) were applied to model the spatiotemporal dynamics of GDP in China from 1992 to 2015 at both the country level and provincial level using the extended temporal coverage data. Our results show that the linear model is optimal at the country level with a mean absolute relative error (MARE) of 11.96%. The power function model is optimal in 22 of the 31 provinces and the quadratic polynomial model is optimal in 7 provinces, whereas the linear model is optimal only in two provinces. Thus, our approach demonstrates the potential to accurately and timely model long-term spatiotemporal GDP dynamics using an integration of DMSP-OLS and NPP-VIIRS data.
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 (down) 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number LoNNe @ kyba @ Serial 1673
Permanent link to this record
 

 
Author Jiang, W.; He, G.; Long, T.; Liu, H.
Title Ongoing Conflict Makes Yemen Dark: From the Perspective of Nighttime Light Type Journal Article
Year 2017 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 9 Issue 8 Pages 798
Keywords Remote Sensing
Abstract The Yemen conflict has caused a severe humanitarian crisis. This study aims to evaluate the Yemen crisis by making use of time series nighttime light images from the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite sensor (NPP-VIIRS). We develop a process flow to correct NPP-VIIRS nighttime light from April 2012 to March 2017 by employing the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) stable nighttime light image. The time series analyses at national scales show that there is a sharp decline in the study period from February 2015 to June 2015 and that the total nighttime light (TNL) of Yemen decreased by 71.60% in response to the decline period. The nighttime light in all provinces also showed the same decline period, which indicates that the Saudi-led airstrikes caused widespread and severe humanitarian crisis in Yemen. Spatial pattern analysis shows that the areas of declining nighttime light are mainly concentrated in Sana’a, Dhamar, Ibb, Ta’izz, ’Adan, Shabwah and Hadramawt. According to the validation with high-resolution images, the decline in nighttime light in Western cities is caused by the damage of urban infrastructure, including airports and construction; moreover, the reason for the decline in nighttime light in eastern cities is the decrease in oil exploration. Using nighttime light remote sensing imagery, our findings suggest that war made Yemen dark and provide support for international humanitarian assistance organizations.
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 (down) 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number LoNNe @ kyba @ Serial 1700
Permanent link to this record
 

 
Author Wang, R.; Wan, B.; Guo, Q.; Hu, M.; Zhou, S.
Title Mapping Regional Urban Extent Using NPP-VIIRS DNB and MODIS NDVI Data Type Journal Article
Year 2017 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 9 Issue 8 Pages 862
Keywords Remote Sensing
Abstract The accurate and timely monitoring of regional urban extent is helpful for analyzing urban sprawl and studying environmental issues related to urbanization. This paper proposes a classification scheme for large-scale urban extent mapping by combining the Day/Night Band of the Visible Infrared Imaging Radiometer Suite on the Suomi National Polar-orbiting Partnership Satellite (NPP-VIIRS DNB) and the Normalized Difference Vegetation Index from the Moderate Resolution Imaging Spectroradiometer products (MODIS NDVI). A Back Propagation (BP) neural network based one-class classification method, the Present-Unlabeled Learning (PUL) algorithm, is employed to classify images into urban and non-urban areas. Experiments are conducted in mainland China (excluding surrounding islands) to detect urban areas in 2012. Results show that the proposed model can successfully map urban area with a kappa of 0.842 on the pixel level. Most of the urban areas are identified with a producer’s accuracy of 79.63%, and only 10.42% the generated urban areas are misclassified with a user’s accuracy of 89.58%. At the city level, among 647 cities, only four county-level cities are omitted. To evaluate the effectiveness of the proposed scheme, three contrastive analyses are conducted: (1) comparing the urban map obtained in this paper with that generated by the Defense Meteorological Satellite Program/Operational Linescan System Nighttime Light Data (DMSP/OLS NLD) and MODIS NDVI and with that extracted from MCD12Q1 in MODIS products; (2) comparing the performance of the integration of NPP-VIIRS DNB and MODIS NDVI with single input data; and (3) comparing the classification method used in this paper (PUL) with a linear method (Large-scale Impervious Surface Index (LISI)). According to our analyses, the proposed classification scheme shows great potential to map regional urban extents in an effective and efficient manner.
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 (down) 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number LoNNe @ kyba @ Serial 1703
Permanent link to this record
 

 
Author Zhang, X.; Wu, J.; Peng, J.; Cao, Q.
Title The Uncertainty of Nighttime Light Data in Estimating Carbon Dioxide Emissions in China: A Comparison between DMSP-OLS and NPP-VIIRS Type Journal Article
Year 2017 Publication Remote Sensing Abbreviated Journal Remote Sensing
Volume 9 Issue 8 Pages 797
Keywords Remote Sensing
Abstract Nighttime light data can characterize urbanization, economic development, population density, energy consumption and other human activities. Additionally, carbon dioxide (CO2) emissions are closely related to the scope and intensity of human activities. In this study, we assess the utility of nighttime light data as a powerful tool to reflect CO2 emissions from energy consumption, analyze the uncertainty associated with different nighttime light data for modeling CO2 emissions, and provide guidance and a reference for modeling CO2 emissions based on nighttime light data. In this paper, Mainland China was taken as a case study, and nighttime light datasets (the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) nighttime light data and the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light data) as well as a global gridded CO2 emissions dataset (PKU-CO2) were used to perform simple regressions at provincial, prefectural and 0.1° × 0.1° grid levels, respectively. The analyses are aimed at exploring the accuracy and uncertainty of DMSP-OLS and NPP-VIIRS nighttime light data in modeling CO2 emissions at different spatial scales. The improvement of nighttime light index and the potential factors influencing the effects of modeling CO2 emissions based on nighttime light datasets were also explored. The results show that DMSP-OLS is superior to NPP-VIIRS in modeling CO2 emissions at all spatial scales, and the bigger the scale, the more evident the advantages of DMSP-OLS. When modeling CO2 emissions with nighttime light datasets, not only the total amount of lights within a given statistical unit but also the agglomeration degree of lights should be taken into account. Furthermore, the geographical location and socio-economic conditions at the study site, such as gross regional product per capita (GRP per capita), population, and urbanization were shown to have an impact on the regression effect of the nighttime lights-CO2 emissions model. The regression effect was found to be better at higher latitude and longitude areas with higher GRP per capita and higher urbanization, while population showed little effect on the regression effect of the nighttime lights – CO2 emissions model. The limitation of this study is that the thresholds of potential factors are unclear and the quantitative guidance is insufficient.
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 (down) 2072-4292 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number LoNNe @ kyba @ Serial 1710
Permanent link to this record