Estimating Location-Adjustment Factors for Conceptual Cost Estimating Based on Nighttime Light Satellite Imagery

How to estimate regional economic development level is important for solving regional inequality problems. Most of previous studies on regional economic development are based on the statistics collected typically in administrative units. This paper has analyzed the defects of traditional studies, and attempted to research regional economic development problems with 10-year DMSP/OLS nighttime light satellite imagery as a new data source. For exploring the relationship between DMSP/OLS nighttime light data and GDP, different types of curve fitting regression models have been tried, the Cubic model has shown the best performance with a coefficient of determination (R2) equal to 0.803. Based on this positive correlation, we have estimated provincial economic development level of China using DMSP/OLS nighttime light data. The research results have indicated that the DMSP/OLS nighttime light data can well reveal provincial economic development levels.

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Direct measurement of the contribution of street lighting to satellite observations of nighttime light emissions from urban areas

Lighting Research and Technology ◽

10.1177/1477153520958463 ◽

2020 ◽

pp. 147715352095846

Author(s):

CCM Kyba ◽

A Ruby ◽

HU Kuechly ◽

B Kinzey ◽

N Miller ◽

...

Keyword(s):

Confidence Interval ◽

Satellite Imagery ◽

Smart City ◽

Urban Areas ◽

Energy Use ◽

Satellite Observations ◽

Light Sources ◽

Street Lighting ◽

Nighttime Light ◽

The City

Nighttime light emissions are increasing in most countries worldwide, but which types of lighting are responsible for the increase remains unknown. Also unknown is what fraction of outdoor light emissions and associated energy use are due to public light sources (i.e. streetlights) or various types of private light sources (e.g. advertising). Here we show that it is possible to measure the contribution of street lighting to nighttime satellite imagery using ‘smart city’ lighting infrastructure. The city of Tucson, USA, intentionally altered its streetlight output over 10 days, and we examined the change in emissions observed by satellite. We find that streetlights operated by the city are responsible for only 13% of the total radiance (in the 500–900 nm band) observed from Tucson from space after midnight (95% confidence interval 10–16%). If Tucson did not dim their streetlights after midnight, the contribution would be 18% (95% confidence interval 15–23%). When streetlights operated by other actors are included, the best estimates rise to 16% and 21%, respectively. Existing energy and lighting policy related to the sustainability of outdoor light use has mainly focused on street lighting. These results suggest an urgent need for consideration of other types of light sources in outdoor lighting policy.

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A LOCATION VALUE RESPONSE SURFACE MODEL FOR MASS APPRAISING: AN “ITERATIVE” LOCATION ADJUSTMENT FACTOR IN BARI, ITALY

International Journal of Strategic Property Management ◽

10.3846/ijspm.2010.17 ◽

2010 ◽

Vol 14 (3) ◽

pp. 231-244 ◽

Cited By ~ 30

Author(s):

Maurizio d’Amato

Keyword(s):

Response Surface ◽

Spatial Interpolation ◽

Surface Model ◽

Adjustment Factor ◽

Specific Context ◽

Response Surface Models ◽

Surface Models ◽

Adjustment Factors ◽

Geostatistical Techniques ◽

Location Adjustment

The work is focused on a new model of mass appraising including location variable. A location adjustment factor derived from a mathematical iteration was compared to the location adjustment factor based on geostatistical techniques. The work compares three different linear MRA models. The first one uses the location blind linear MRA. The second integrates the linear MRA with a location adjustment factor calculated using spatial interpolation. The second alternative is an application of Location Value Response Surface Models (O'Connor, 1982). It represents the first application of these models for mass appraising in Italy. The third approach introduces the Iterative Location Adjustment Factor. This is a factor which measure the influence of location derived from a mathematical iteration. Empirical results seem to prove the validity of Iterative Location Adjustment Factors in specific context with few observations. Santruka Darbe nagrinejamas naujas masinio turto vertinimo modelis, apimantis geografines padeties kintamaji. Iteraciniu būdu apskaičiuotas geografines padeties korekcijos veiksnys palygintas su geografines padeties korekcijos veiksniu, gautu taikant geostatistinius metodus. darbe lyginami trys skirtingi tiesiniai mrA modeliai. Pirmajame naudojamas geografines padeties nevertinantis tiesinis MRA. Antrajame tiesinis MRA sujungiamas su geografines padeties korekcijos veiksniu, apskaičiuotu pasitelkus erdvine interpoliacija. Antrojoje alternatyvoje pritaikomi geografines padeties vertes stebimojo paviršiaus (angl. Location Value Response Surface) modeliai (O'Connor 1982). Italijoje šie modeliai masiniam turto vertinimui naudojami pirma karta. Trečiojoje alternatyvoje taikomas iteracinis geografines padeties korekcijos veiksnys. Jis ivertina geografines padeties itaka, nustatyta iteraciniu būdu. Empiriniai rezultatai, regis, irodo iteraciniu geografines padeties korekcijos veiksniu pagristuma konkrečiame kontekste, kai stebejimu yra mažai.

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