Agriculture and forestry area returned farmland information collection method

Abstract

The invention provides an agriculture and forestry area returned farmland information collection method, which comprises the steps of collecting an NDVI sequence value within one year according to a remote sensing image with low space and high time resolution; calculating a CV value of any year and extracting crop phenological information according to the NDVI sequence value, and further determining planting information of any pixel area; according to the planting information and the crop phenology information, determining a multiple cropping index of any pixel area within a monitoring year; and based on the multiple cropping index and in combination with a remote sensing image sequence with medium-high spatial resolution, accurately determining the farmland returning time, the farmland returning area and the farmland returning position. According to the method, the NDVI value of the time sequence is collected by utilizing the agricultural and forestry area remote sensing image with low space and high time resolution, the returned farmland position, returned farmland time and returned farmland area are calculated, then the returned farmland information is collected by applying theremote sensing image with medium-high resolution and combining different multiple cropping index remote sensing models, and the information extraction precision is improved.

Description

technical field [0001] The invention relates to the technical field of agriculture and forestry protection, in particular to a method for acquiring information on converted farmland in agriculture and forestry areas. Background technique [0002] For the protection of some ecologically fragile or important ecological function areas, some farmland needs to be returned to forests and grasslands to maximize the value of the ecosystem. [0003] However, from a management point of view, it is necessary to make timely statistics on the specific spatial location and area of ​​farmland conversion at different times, and provide certain economic compensation to localities or farmers according to the time and area of ​​farmland conversion. support. [0004] Due to its multi-time, multi-space and multi-spectral characteristics, remote sensing technology can effectively obtain relevant information on land cover and changes, so it has irreplaceable potential for the identification of fa...

AI Technical Summary

Problems solved by technology

The problem with this is that the types of crops are different, and the planting time may vary greatly, and the classification method is mostly obtained by using one phase, so there may be some farmland information that cannot be effectively extracted; Second, the characteristic of returned farmland is that the spatial distribution is relatively scattered, and the plots are relatively small, and there may be mixed situations of farmland, forest land, grassland, bare soil, water, etc., so the extraction results have greater uncertainty; It is a method of land use classification, and the calculation amount is relatively large, and the calculation resource consumption is relatively high. In addition, due to the selection of training samples and other reasons, the results of each land use classification will have certain differences.

[0006] Based on the above problems, there is a certain degree of uncertainty in the accuracy of the traditional remote sensing method for extracting fallow land.

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