|   | 
Details
   web
Records
Author Song, J.; Tong, X.; Wang, L.; Zhao, C.; Prishchepov, A.V.
Title Monitoring finer-scale population density in urban functional zones: A remote sensing data fusion approach Type Journal Article
Year 2019 Publication Landscape and Urban Planning Abbreviated Journal Landscape and Urban Planning
Volume 190 Issue Pages (down) 103580
Keywords Remote Sensing; nighttime light; numerical methods
Abstract Spatial distribution information on population density is essential for understanding urban dynamics. In recent decades, remote sensing techniques have often been applied to assess population density, particularly night-time light data (NTL). However, such attempts have resulted in mapped population density at coarse/medium resolution, which often limits the applicability of such data for fine-scale territorial planning. The improved quality and availability of multi-source remote sensing imagery and location-based service data (LBS) (from mobile networks or social media) offers new potential for providing more accurate population information at the micro-scale level. In this paper, we developed a fine-scale population distribution mapping approach by combining the functional zones (FZ) mapped with high-resolution satellite images, NTL data, and LBS data. Considering the possible variations in the relationship between population distribution and nightlight brightness in functional zones, we tested and found spatial heterogeneity of the relationship between NTL and the population density of LBS samples. Geographically weighted regression (GWR) was thus implemented to test potential improvements to the mapping accuracy. The performance of the following four models was evaluated: only ordinary least squares regression (OLS), only GWR, OLS with functional zones (OLS&FZ) and GWR with functional zones (GWR&FZ). The results showed that NTL-based GWR&FZ was the most accurate and robust approach, with an accuracy of 0.71, while the mapped population density was at a unit of 30 m spatial resolution. The detailed population density maps developed in our approach can contribute to fine-scale urban planning, healthcare and emergency responses in many parts of the world.
Address Department of Geosciences and Natural Resource Management, University of Copenhagen, 1350 Copenhagen, Denmark; songjinchao08(at)163.com
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 0169-2046 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2516
Permanent link to this record
 

 
Author Heger, M.P.; Neumayer, E.
Title The impact of the Indian Ocean tsunami on Aceh's long-term economic growth Type Journal Article
Year 2019 Publication Journal of Development Economics Abbreviated Journal Journal of Development Economics
Volume 141 Issue Pages (down) 102365
Keywords Remote Sensing; Natural disasters; Aceh; Indonesia
Abstract Existing studies typically find that natural disasters have negative economic consequences, resulting in, at best, a recovery to trend after initial losses or, at worst, longer term sustained losses. We exploit the unexpected nature of the 2004 Indian Ocean tsunami for carrying out a quasi-experimental difference-in-differences analysis of flooded districts and sub-districts in Aceh. The Indonesian province saw the single largest aid and reconstruction effort of any developing world region ever afflicted by a natural disaster. We show that this effort triggered higher long-term economic output than would have happened in the absence of the tsunami.
Address The World Bank, Washington D.C., USA
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 0304-3878 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2558
Permanent link to this record
 

 
Author Wang, C.; Chen, Z.; Yang, C.; Li, Q.; Wu, Q.; Wu, J.; Zhang, G.; Yu, B.
Title Analyzing parcel-level relationships between Luojia 1-01 nighttime light intensity and artificial surface features across Shanghai, China: A comparison with NPP-VIIRS data Type Journal Article
Year 2020 Publication International Journal of Applied Earth Observation and Geoinformation Abbreviated Journal International Journal of Applied Earth Observation and Geoinformation
Volume 85 Issue Pages (down) 101989
Keywords Remote Sensing
Abstract Nighttime light (NTL) remote sensing data have been widely used to derive socioeconomic indices at national and regional scales. However, few studies analyzed the factors that may explain NTL variations at a fine scale due to the limited resolution of existing NTL data. As a new generation NTL satellite, Luojia 1-01 provides NTL data with a finer spatial resolution of ∼130 m and can be used to assess the relationship between NTL intensity and artificial surface features on an unprecedented scale. This study represents the first efforts to assess the relationship between Luojia 1-01 NTL intensity and artificial surface features at the parcel level in comparison to the Suomi National Polar-orbiting Partnership-Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL data. Points-of-interest (POIs) and land-use/land-cover (LULC) data were used in random forest (RF) regression models for both Luojia 1-01 and NPP-VIIRS to analyze the feature contribution of artificial surface features to NTL intensity. The results show that luminosity variations in Luojia 1-01 data for different land-use types were more significant than those in NPP-VIIRS data because of the finer spatial resolution and wider measurement range. Seventeen variables extracted from POI and LULC data explained the Luojia 1-01 and NPP-VIIRS NTL intensity, with a good out-of-bag score of 0.62 and 0.76, respectively. Moreover, Luojia 1-01 data had fewer “blooming” phenomena than NPP-VIIRS data, especially for cropland, water body, and rural area. Luojia 1-01 is more suitable for estimating socioeconomic activities and can attain more comprehensive information on human activities, since the feature contribution of POI variables is more sensitive to NTL intensity in the Luojia 1-01 RF regression model than that in the NPP-VIIRS RF regression model.
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 0303-2434 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2745
Permanent link to this record
 

 
Author Chen, X.; Jia, X.; Pickering, M.
Title A Nighttime Lights Adjusted Impervious Surface Index (NAISI) with Integration of Landsat Imagery and Nighttime Lights Data from International Space Station Type Journal Article
Year 2019 Publication International Journal of Applied Earth Observation and Geoinformation Abbreviated Journal International Journal of Applied Earth Observation and Geoinformation
Volume 83 Issue Pages (down) 101889
Keywords Remote Sensing
Abstract Accurate mapping of impervious surface is essential for both urbanization monitoring and micro-ecosystem research. However, the confusion between impervious surface and bare soil is the major concern due to their high spectral similarity in optical imagery. Integration of multi-sensor images is considered to offer a better capacity for distinguishing impervious surface from background. In this paper, a new impervious surface index namely nighttime light adjusted impervious surface index (NAISI), which integrates information from Landsat and nighttime lights (NTL) data from International Space Station (NTL-ISS), is proposed. Parallel to baseline subtraction approaches, NAISI integrate the information from the first component of principal component (PC) transformation of NTL-ISS, the Soil Adjusted Vegetation Index (SAVI) and the third component of tasseled cap transform (TC3) of the Landsat data. Visual interpretation and quantitative indices (SDI, Kappa and overall accuracy) were adopted to elevate the accuracy and separability of NAISI. Comparative analysis with NTL derived light intensity, optical indices, as well as existing optical-NTL indices were conducted to examine the performance of NAISI. Results indicate that NAISI achieves a more promising capability in impervious surface mapping. This demonstrates the superiority of integration of optical and nighttime lights information for imperviousness detection.
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 0303-2434 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2658
Permanent link to this record
 

 
Author Kosicki, J.Z.
Title Anthropogenic activity expressed as ‘artificial light at night’ improves predictive density distribution in bird populations Type Journal Article
Year 2020 Publication Ecological Complexity Abbreviated Journal Ecological Complexity
Volume 41 Issue Pages (down) 100809
Keywords Remote Sensing; Animals; Ecology
Abstract Artificial Light At Night (ALAN) is one of the most important anthropogenic environmental components that affects biodiversity worldwide. Despite extensive knowledge on ALAN, being a measure of human activity that directly impacts numerous aspects of animal behaviour, such as orientation and distribution, little is known about its effects on density distribution on a large spatial scale. That is why we decided to explore by means of the Species Distribution Modelling approach (SDM) how ALAN as one of 33 predictors determines farmland and forest bird species densities. In order to safeguard study results from any inconsistency caused by the chosen method, we used two approaches, i.e. the Generalised Additive Model (GAM) and the Random Forest (RF). Within each approach, we developed two models for two bird species, the Black woodpecker and the European stonechat: the first with ALAN, and the second without ALAN as an additional predictor. Having used out-of-bag procedures in the RF approach, information-theoretic criteria for the GAM, and evaluation models based on an independent dataset, we demonstrated that models with ALAN had higher predictive density power than models without it. The Black woodpecker definitely and linearly avoids anthropogenic activity, defined by the level of artificial light, while the European stonechat tolerates human activity to some degree, especially in farmland habitats. What is more, a heuristic analysis of predictive maps based on models without ALAN shows that both species reach high densities in regions where they are deemed rare. Hence, the study proves that urbanisation processes, which can be reflected by ALAN, are among key predictors necessary for developing Species Density Distribution Models for both farmland and forest bird species.
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 1476945X ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2776
Permanent link to this record