The invention relates to the technical field of agricultural
data analysis, in particular to a
land reclamation suitability evaluation and
cultivated land quality improvement method based on
big data, which comprises the following steps of: acquiring and superposing
land utilization, soil and
elevation data to construct a multi-source land attribute
evaluation data set, calculating the distance from a pattern spot to a
water source, reconstructing a weight through
Gaussian attenuation, and calculating the
land utilization, soil and
elevation data; the method comprises the following steps: forming a spatial distance weighted
feature matrix, extracting a gradient and an
irrigation guarantee rate, performing weight reduction on an overrun part of a conflict threshold value, performing linear weighting calculation on a comprehensive
score after normalization, dividing a regulation priority area, matching quality improvement measures, and forming a
cultivated land quality improvement project
layout map. A pattern spot level evaluation basis is formed through multi-source attribute space superposition,
water source distance attenuation calculation is introduced to enable weight to change along with
reachability,
irrigation difference response is enhanced, conflict constraint correction is carried out on gradient and
irrigation guarantee, adverse combination influence is inhibited, stable sorting is formed through uniform scale weighting, and the method is applied to the field of irrigation. And improvement priority area identification and quality improvement measure directional configuration are supported.