Energy carbon emission remote sensing estimation method based on night light images

Abstract

The invention provides an energy carbon emission remote sensing estimation method based on night light images. The method includes the following steps that first, urban construction land is extracted on the basis of the night light images; second, energy carbon emission is simulated on the basis of the night light images. The first step includes the steps that eleventh, a transition zone of the construction land and non-construction land is recognized; twelfth, the construction land beyond the transition zone is extracted; thirteenth, the construction land contained in the transition zone is extracted; fourteenth, all the construction land is obtained. The second step includes the steps that twenty-first, the total value of night light data within all the construction land of an area to be measured is extracted; twenty-second, multiple leading industry types are divided; twenty-third, energy carbon emission inversion models of different leading industry types are constructed. By building the energy carbon emission models, energy carbon emission of any region can be predicted according to the night light images and different leading industry types.

Description

technical field [0001] The invention relates to inversion technology, in particular to a method for remote sensing estimation of energy and carbon emissions based on night light images. Background technique [0002] Exploring the carbon emissions caused by human activities such as economic development and energy consumption has become a hot topic in domestic and foreign academic circles. According to statistics, since 2000, China's CO 2 The average annual growth rate of emissions is about 10%. In 2008, carbon emissions reached 8.325 billion tons, surpassing the United States to become the world's largest carbon emitter. Huge emissions and high growth rate have put China under enormous pressure to reduce emissions. Due to the great differences in the economic and social development and energy consumption structure of various regions in China, scientifically and accurately measuring and analyzing the temporal and spatial changes of carbon emissions in different regions and r...

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Problems solved by technology

[0007] A few scholars at home and abroad have applied DMSP / OLS night light data to the estimation of energy and carbon emissions. However, the current inversion model still has major shortcomings.

my country's cities have great differences in development levels and industrial structure types. There are also significant differences in the quantitative relationship between energy carbon emissions and DMSP / OLS night light values ​​in cities of different industrial types. However, the current model algorithm has not yet targeted cities with different leading industrial types. Constructed energy carbon emissions DMSP / OLS inversion model

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