Rice-Crop Intensity Identification via Radar Troughs and Temperature
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Solution Overview
Problem
Current methods for large-scale rice-crop intensity identification using radar time series data face challenges such as diversity in backscatter data due to complex agricultural practices, ambiguity in backscatter characteristics between rice and non-rice objects, and overestimation of rice-crop intensity, particularly due to meteorological interference and lack of phenological information.
Innovation Solution
A rice-crop intensity identification method based on radar time series observation and temperature analysis, involving time series reconstruction, trough identification, potential rice phenological phase estimation, temperature suitability assessment, and correction for overestimation, to accurately determine rice-crop intensity by capturing periodic features and excluding invalid troughs based on temperature limitations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If optical satellite data is used for rice-crop intensity identification, then large-scale monitoring can be achieved, but accuracy deteriorates due to cloudiness and rainfall interference
Solution Approach 1:
The patent introduces radar satellites as an intermediary data source to replace optical satellites when cloud cover interferes with optical imaging. Radar data serves as a mediator that can penetrate clouds and provide continuous monitoring capability, resolving the contradiction between maintaining large-scale coverage and ensuring identification accuracy under adverse weather conditions
Solution Approach 2:
The patent changes the observation parameter from optical reflectance to radar backscatter characteristics. By utilizing the different physical principles of radar imaging (which is immune to cloud cover), the system maintains both large-scale monitoring capability and high identification accuracy regardless of weather conditions
2Reliability
If radar time series backscatter data is used for rice-crop intensity identification, then immunity to meteorological interference is achieved, but identification accuracy deteriorates due to diversity of backscatter data from complex agricultural practices
Solution Approach 1:
The patent segments the continuous time series backscatter data into distinct growth stages by identifying phenological troughs. This segmentation transforms the complex, diverse backscatter signals into discrete, interpretable stages (seedling, vegetative, reproductive, maturation), enabling accurate rice-crop intensity identification despite variations in agricultural practices
Solution Approach 2:
The patent performs preliminary phenological phase estimation before final rice-crop intensity identification. By first estimating the phenological stages and then using temperature suitability assessment to validate them, the system prepares the data in advance to filter out false signals from non-rice objects and complex farming practices, improving subsequent identification accuracy
3Loss of information
If phenological troughs are identified in radar time series data, then rice growth stages can be detected, but overestimation of rice-crop intensity occurs due to ambiguity between rice and non-rice objects
Solution Approach 1:
The patent implements a feedback mechanism through temperature suitability assessment. After identifying potential phenological troughs, the system checks whether the temperature conditions during those periods are suitable for rice growth. This feedback loop filters out false positive troughs from non-rice objects, correcting overestimation while preserving genuine rice phenological information
Solution Approach 2:
The patent introduces temperature data as an intermediary validation criterion between trough identification and final rice-crop intensity determination. This intermediary step uses temperature suitability as a filter to distinguish rice-related troughs from those caused by non-rice objects, resolving the ambiguity without losing phenological information
Data Source
AI summary
A rice-crop intensity identification method based on radar time series observation and temperature analysis is provided. Capturing of diversified periodic characteristics of time series backscatter and detection of backscatter troughs are achieved through time series reconstruction and trough identification; potential phenological phases corresponding to the backscatter troughs are determined through potential rice phenological phase estimation; and through temperature limitation of rice phenological phase, temperature suitability of potential rice phenological phases is evaluated, a backscatter trough that does not satisfy a temperature condition is removed by combining a rice growth mechanism and a regulation of rice-crop intensity, thereby realizing the identification of the rice troughs and the correction of the overestimation of the rice-crop intensity, and finally realizing the identification of rice-crop intensity.