Sentence examples for classification of crops from inspiring English sources

In recent years much research in the field of classification and classification of crops based on characteristics using image processing have been done in this study to determine the level of product quality barberry impurities and the degree of quality we have to use image processing.

Accurate and timely spatial classification of crop types based on remote sensing data is important for both scientific and practical purposes.

Data processing includes three steps: (1) noise is filtered from the time-series NDVI data using empirical mode decomposition (EMD); (2) endmembers are extracted from the filtered time-series data and trained in a linear mixture model (LMM) for classification of rice cropping systems; and (3) classification results are verified by comparing them with the ground-truth and statistical data.

This new approach to training set design was evaluated against conventional approaches with a set of classifications of agricultural crops from satellite sensor data.

The model used is based on the FAO land classification for crops, and data which describe an agricultural area in terms of soil mechanics and environment.

In this study, the performance of the subspace method in land cover classification of a complex cropping mix area is explored.

The findings suggest the methodology presented in this paper is promising for accurate, cost-effective, and in-season classification of field-level crop types, which may be scaled up to large geographic extents such as the U.S. Corn Belt.

Crop classification of homogeneous landscapes and phenology is a common requirement to estimate land cover mapping, monitoring, and land use categories accurately.

Equipment for crop protection drift classification of sprayers and nozzles.] to classify sprayers according to drift risk requires the sprayer to be operated in the field in well defined conditions of wind [ISO TC 23/SC 06 N 22866. Equipment for crop protection methods for the field measurement of spray drift.].

Generally, the overall accuracy of crop classification in Zhangye was high, at 89.38%.

This study shows progress toward more refined crop-specific classification, but some grouping of crop classes remains necessary.