Identification and area estimation of soybean planting areas in Heilongjiang province based on multi-temporal MODIS data
Multi-temporal MODIS image data of Heilongjiang province from 2017 to 2021 were selected,and based on Google Earth Engine(GEE)geospatial analysis cloud platform,the spectral reflectance of various types of fea-tures as well as the difference characteristics of indices such as Normalized Difference Vegetation Index(NDVI)and Normalized Difference Water Index(NDWI)were compared and analyzed.A classification decision tree was established to identify soybean planting areas in Heilongjiang province,estimate the area,and compare with other classification methods.The results show that the total accuracy of estimating the area of soybean planting areas in Heilongjiang province in 2018 identified based on the decision tree classification method is 97.09%,and the Kap-pa coefficient is 0.77,which is higher than the random forest and support vector machine methods in terms of clas-sification accuracy.By adjusting and optimizing the decision tree model for soybean planting area identification and area estimation in the year without sample,the soybean distribution change in Heilongjiang province from 2017 to 2021 was obtained with a total accuracy of more than 90%,a Kappa coefficient of more than 0.60,and an accura-cy of more than 95%for the area estimation results.
Vegetation indexWater indexSpectral analysisDecision tree classification
国家科技期刊平台
NSTL
万方数据
