Rice planting area information extraction based on multi-temporal remote sensing data

doi:10.14088/j.cnki.issn0439-8114.2020.02.035

Abstract

Abstract: In remote sensing images, the moisture content and soil moisture of plants were sensitive to the short-wave infrared band, while the red band and near-infrared band reflected the coverage rate and growth rate of plants strongly. According to the characteristics of rice growing in moist soil, based on a decision tree rice extraction model with time difference, this paper carried out relevant research on rice growing area extraction in sheyang county, yancheng city, jiangsu province by calculating NDVI and LSWI of normalized vegetation index and soil moisture index at different growth periods. The comparison of the extracted rice area and local statistical data showed that the model can effectively distinguish the water area, corn and vegetable fields that were easily confused with rice, and the precision of area extraction reached 76.26%.

Key words: multi-temporal image, decision tree, rice, information extraction

CLC Number:

P237

PENG Le-wen, ZHANG Ya. Rice planting area information extraction based on multi-temporal remote sensing data[J]. HUBEI AGRICULTURAL SCIENCES, 2020, 59(2): 157-160.

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