Abstract
Abstract. Considering the problem in monitoring agricultural condition in the semi-arid areas of Northwest of China, we propose a new method for estimation of crop planting area, using the single phase optical and microwave remote sensing data collaboratively, which have demonstrated their respective advantages in the extraction of surface features. In the model, the ASAR backscatter coefficient is normalized by the incident angle at first, then the classifier based on Bayesian network is developed, and the VV, VH polarization of ASAR and all the 7 TM bands are taken as the input of the classifier to get the class labels of each pixel of the images. Moreover the crop planting areas can be extracted by the classification results. At last, the model is validated for the necessities of normalization by the incident angle and integration of TM and ASAR respectively. It results that the estimation accuracy of crop planting area of corn and other crops garden are 98.47% and 78.25% respectively using the proposed method, with an improvement of estimation accuracy of about 3.28% and 4.18% relative to single TM classification. These illustrate that synthesis of optical and microwave remote sensing data is efficient and potential in estimation crop planting area.
Highlights
Agriculture is the basis of China's national economy, agricultural information monitoring is important for agricultural production, it is the basis for national socioeconomic information of the people's livelihood [1]
To verify the normalization formula (Eq (8) and Eq (12)) and the necessity of coupling optical radar data for classification, we respectively compared the output of the classification of ASAR and TM, using Bayesian network classifier, with the classification only by TM
The extraction accuracy of corn and other crops planted area by proposed method are 98.47% and 78.25%, with an improvement of estimation accuracy of about 3.28% and 4.18% relative to single TM classification
Summary
Agriculture is the basis of China's national economy, agricultural information monitoring is important for agricultural production, it is the basis for national socioeconomic information of the people's livelihood [1]. Estimation of Agricultural crop area is one of the key technologies to monitor the agricultural situation, the traditional methods is based on a sample survey which is human-based, point-based data. It spends a lot of money and has the low efficiency. If we combine the optical and radar data together to extract surface information, it is great significant for improving the extraction accuracy of crop area Based on this consideration, we propose a singlephase optical radar remote sensing of crop acreage synergistic extraction method.
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