The invention discloses a
phytoplankton space distribution prediction method based on environment
DNA and
machine learning, and belongs to the technical field of
ecological environment evaluation and treatment. Comprising the following steps: determining a sampling site, and collecting a
phytoplankton eDNA sample; carrying out
DNA extraction and treatment on the collected eDNA sample, and calculating a species abundance matrix; screening a training
data set for training a prediction model according to the sampling time and the sampling site of the eDNA sample; inputting the training
data set as an independent variable of a
training set, inputting the species abundance matrix as a dependent variable of the
training set, and training a prediction model; and inputting
remote sensing image data into the prediction model to obtain a species
spatial distribution diagram. Compared with the prior art, the method has the advantages that efficient and high-species-resolution
spatial distribution prediction of
algae species such as blue-
green algae can be achieved, the
phytoplankton prediction model is trained through the
machine learning model, automatic operation of
spatial prediction of various phytoplanktons is achieved, the arrangement density of sampling points is reduced, and the monitoring efficiency is improved.