Method for Extracting Black-Odorous Water Body Based on Cart Classification Model

A method for extracting a black-odorous water body based on a Classification and Regression Tree (CART) classification model, comprising the following steps:

• step 1):
• selecting a research region, and designing a plurality of sampling points within the research region;
• step 2):
• monitoring relevant chemical indicators of the water body at various sampling points, respectively, extracting remote sensing reflectance data of the water body, sending the relevant chemical indicators and the data to a laboratory, and determining a type of the water body according to a classification standard of relevant chemical indicators for an urban black-odorous water body, wherein the relevant chemical indicators comprise transparency, dissolved oxygen, oxidation-reduction potential, and ammonia nitrogen;
• step 3):
• comparing and analyzing the remote sensing reflectance data extracted at the various sampling points to obtain spectral change features of the black-odorous water body and a general water body, wherein the spectral change features comprise a reflectance difference value between a green band and a red band, a reflectance value of a near infrared band, and a sum of reflectance values of a visible light band;
• step 4):
• constructing each node of a decision tree according to the spectral change features and based on a Gini index, constructing a decision tree classification model to obtain classification results of the black-odorous water body and the general water body, and calculating a classification accuracy;
• and
• step 5):
• analyzing the classification results to obtain spatiotemporal distribution changes of black-odorous water bodies in the research region.