Urban impervious layer rate information extraction method based on multi-source remote sensing data

Abstract

The invention discloses an urban impervious layer information extraction method based on multi-source remote sensing data. The method comprises the following steps: calculating normalized light brightness and performing area type segmentation on the urban surface based on a threshold segmentation method according to a night light brightness image; constructing enhanced normalized impervious layer indexes by utilizing the light brightness, the land surface temperature and normalized soil regulation vegetation indexes; and performing extraction operation on the impervious layer by constructing a linear quantitative relation between the enhanced normalized impervious layer indexes MNDISI in each type segmentation area and the impervious layer rate. The advantages of the multi-source remote sensing data are well combined, an adverse effect of spectral confusion on an estimation result of the impervious layer rate is effectively inhibited, and a novel way is provided for urban land utilization and environmental change monitoring.

Description

technical field [0001] The invention belongs to the field of information extraction of remote sensing image data, and relates to a method for extracting urban impermeable layer information based on multi-source remote sensing data. Background technique [0002] With the acceleration of economic development and urbanization, various production and construction activities of human beings are increasingly changing the natural environment and land cover types in and around cities. The impermeable layer is defined as an impermeable non-natural ground surface composed of various artificial buildings, roads, airports, etc. The impermeable layer rate refers to the percentage of the impermeable layer in a unit area. The large-scale impermeable layer in the city will affect the heat absorption and release of the underlying surface under solar radiation, causing the "heat island" phenomenon. Around cities, expansion of impervious layers inhibits vegetation response to atmospheric CO ...

AI Technical Summary

Problems solved by technology

[0007] The first type of pixel-based extraction methods are susceptible to the spectral confusion of ground objects. In recent years, the development of high-resolution remote sensing technology has made it possible to extract impermeable layers with high precision in local areas. However, due to the small number of bands, ground objects The problem of spectral confusion still exists. At the same time, the shadow of tall buildings in the image will also adversely affect the extraction accuracy; the second type of mixed pixel decomposition model is based on the assumption that there is no cross-reflection between the various components of the surface, which is not suitable for the non-existent surface. The actual situation of Lambertianity, and the accuracy of pixel decomposition largely depends on the accuracy of endmember selection, so this method has certain instability; the third type of indirect extraction method is mainly aimed at regions and larger scales Extraction of impermeable layers on top, the results are often not fine enough

In addition, this method is also easily affected by other external factors, such as NDVI is easily affected by seasonal changes and soil moisture content, which will adversely affect the results of impermeable layer extraction

[0008] The city is a special area in the whole nature, not only affected by the land, the atmosphere and vegetation, but also by the increasingly frequent and persistent human activities. Compared with the natural landform, the artificial surface represented by the impermeable layer has spectral changes On the other hand, the co-existence of the impervious layer with other natural surface cover types such as vegetation, water body and soil makes the interlaced distribution of various background elements, which greatly interferes with the extraction of the impervious layer

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