Earth surface albedo inversion method based on BRDF prototype

Abstract

The invention relates to an earth surface albedo inversion method based on a BRDF prototype. The earth surface albedo inversion method includes the steps of carrying out the loop iteration fitting on multi-angle observation data by applying the BRDF prototype, determining the minimum RMSE, and proposing a new earth surface albedo inversion method based on the BRDF prototype. Taking test data of a WiDAS in the Back River area as an example, the BRDF prototype is used as bidirectional reflectance priori knowledge to restrain acute changes of a bidirectional reflectance shape at a large observation zenith angle and overcome the albedo uncertainty caused by the changes of the extreme reflectance. Being different from a business-operation earth surface albedo inversion algorithm based on a nuclear driving model at present, the earth surface albedo inversion method based on the BRDF prototype provides an earth surface albedo inversion solution for a sensor which is insufficient in space sampling capacity. The earth surface albedo inversion method based on the BRDF prototype has the important application value on the technical field of spatial information and particularly on the quantitative remote sensing aspect.

Description

1. Technical field [0001] The invention relates to a method for inverting surface albedo based on a bidirectional reflection distribution function (BRDF) prototype, which belongs to the technical field of spatial information. 2. Background technology [0002] The anisotropic reflection of the earth's surface is a basic macroscopic phenomenon of the reflection of electromagnetic waves by objects in nature. The study of the distribution function of the ditropic reflection of the earth's surface is an important part of the field of optical quantitative remote sensing research. Since the 1970s, satellite remote sensing mainly adopts the vertical observation method to obtain the biophysical parameters of the surface vegetation canopy. With the development of remote sensing technology, the in-depth study of the interaction mechanism between vegetation and light radiation, and various new needs, people have increasingly realized that in inferring key parameters of the surface (such...

AI Technical Summary

Problems solved by technology

In the past 20 years, with the successful launch of multi-angle spaceborne sensors, earth research has accumulated a large amount of multi-angle observation data. However, due to the limitation of space sampling capabilities, most airborne or spaceborne sensors usually cannot Obtaining enough spatial sampling data is the same as measuring. Some sparse multi-angle observation data often lead to inversion failure due to insufficient spatial information. Therefore, how to effectively use these sparse multi-angle observation data with insufficient information to invert surface albedo The rate is one of the key issues that need to be solved urgently in the field of spatial information technology, and it is also one of the scientific issues that scientists from all over the world are actively researching and exploring in the field of quantitative remote sensing.

[0003] At present, the application of sparse multi-angle observation data to invert the surface albedo usually relies on a bidirectional reflectance database. The early bidirectional reflectance database tried to establish the law between the surface ecological type and the change of the surface bidirectional reflectance. However, Studies have shown that the intra-class variance of bidirectional reflectance changes of surface ecological types is usually greater than the inter-class variance, which brings great theoretical obstacles to the practical application of this method; currently, MODIS uses the global BRDF database of pixel-to-pixel The database is based on the accumulation of high-quality historical data. The problems of this database itself are: (1) It is necessary to assume that the BRDF changes in the same period in different years are stable and consistent. Through years of data accumulation and filling, high-quality BRDF data in the same period can be obtained, and this assumption does not cannot be fully established; (2) Even if the assumption is established, it is very difficult to obtain global complete multi-angle data. Obtain high-quality BRDF data; (3) The amount of data is large, that is, the BRDF database generated by this method usually has hundreds of GB and cannot obtain the basic law of BRDF changes, although the MODIS sensor relies on such a tailor-made database to obtain The quantity retrieval quality of the global albedo, but when this database is used for other multi-angle sensors, there are great difficulties due to the difference in spatial scale and time scale. The inversion of airborne WiDAS sparse multi-angle data, this database application is very difficult

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