Leaf area index (LAI) product inversion method and system for global earth surface

Abstract

The invention discloses a leaf area index (LAI) product inversion method and an LAI product inversion system for a global earth surface, and relates to the field of remote sensing data processing. The method comprises the following steps of: inputting original data into a system; preprocessing earth surface reflection index data of a moderate resolution imaging spectroradiometer (MODIS) and earth surface reflection index data of an advanced very high resolution radiometer (AVHRR); performing smoothing processing on MODIS LAI data and CYCLOPES LAI data; converting the CYCLOPES LAI data subjected to the smoothing processing into CYCLOPES LAI real data; obtaining fused LAI data; and obtaining a neural network by utilizing the fused LAI data, the preprocessed earth surface reflection index data of the MODIS and the earth surface reflection index data of the AVHRR and training earth surface grouped data of the MODIS, and thus obtaining LAI products of the global earth surface. By the method, the precision of the LAI products is improved and the requirements on earth system science and application research can be met.

Description

technical field [0001] The invention relates to the technical field of remote sensing data processing, in particular to a global land surface LAI product inversion method and system. Background technique [0002] In recent years, scholars at home and abroad have produced multiple global or regional LAI (Leaf Area Index) products using satellite remote sensing observation data, among which the most representative LAI products include CYCLOPES, GLOBCARBON and CCRS LAI produced using SPOT / VEGETATION data Products; MODIS LAI products produced using TERRA-AQUA / MODIS data. Others include LAI products produced using sensor data such as ADEOS / POLDER, ENVISAT / MERIS, MSG / SEVIRI, and TERRA / MISR. [0003] The existing LAI product production systems all use personal computers to produce a small amount of products, and there is a lack of long-term global land surface area index data sets. So far, for the study of global land surface changes and the development of land surface models, th...

AI Technical Summary

Problems solved by technology

The production of remote sensing products in China uses personal computers to produce small batches of products, which cannot meet the needs of long-term sequence, high temporal and spatial resolution, and high-quality remote sensing production

[0004] At present, several typical LAI global products mainly have the following two problems: first, these products are relatively short in time span, and are mainly generated from a single satellite sensor and a single time-phase remote sensing data, due to the amount of information in the inversion process Insufficient, these products have problems such as low precision, incompleteness in time and space; second, due to different sensors and inversion algorithms, there are obvious differences between different products

These problems of LAI products affect the application level of data, and it is difficult to meet the needs of earth system science and applied research

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