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Contribution of Minimum Noise Fraction Transformation of Multi-temporal RADARSAT-2 Polarimetric SAR Data to Cropland Classification
摘要： Agriculture is an important sector in Canada, and annual crop inventories are required in many agricultural applications. Multi-temporal polarimetric synthetic aperture radar (SAR) data have great potential in crop classification due to its less dependency on weather condition. This study, for the first time, investigated the effects of the Minimum Noise Fraction (MNF) transformation of multi-temporal RADARSAT-2 polarimetric SAR data on the performance of cropland classification through the discussing of the performance of different polarimetric SAR parameter sets, and the impact of the timing of RADARSAT-2 datasets in southwestern Ontario. The random forest classifier was adopted due to its excellent ability in crop classification. The results illustrated that the elements of coherency matrix performed the best in agricultural land cover classification. The multi-temporal polarimetric SAR data acquired from the end of June to November gave the best classification accuracy, and an overall accuracy of 90% can be achieved using two images acquired in the middle of September and October. The MNF transformation can further improve the classification accuracy, and this accuracy was competitive with the accuracy produced using the integration of optical and polarimetric SAR data.
关键词： Minimum Noise Fraction,RADARSAT-2,random forest classifier,polarimetric SAR,cropland classification
更新于2025-09-23 15:21:01
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Classification and Estimation of Irrigation Waters Based on Remote Sensing Images: Case Study in Yucheng City (China)
摘要： The downstream plain of the Yellow River is experiencing some of the most severe groundwater depletion in China. Although the Chinese government has issued policies to ensure that the Yellow River can provide enough irrigation waters for this region, groundwater levels continue to decrease. Yucheng City was selected as a case study. A new method was designed to classify the cropland into various irrigated cropland. Subsequently, we analyzed data regarding these irrigated-cropland categories, irrigation norms, and the minimum amount of irrigation water being applied to cropland. The results showed that 91.5% of farmland can be classified as double irrigated (by both canal/river and well water), while 8.5% of farmland can be classified as well irrigated. During the irrigation season, the sediments brought in by the river have blocked portions of the canals. This has led to 23% of the double-irrigated cropland being irrigated by groundwater, and it is thus a main factor causing reductions in groundwater supply. These blocked canals should be dredged by local governments to mitigate local groundwater depletion. The method for classifying irrigated cropland from high-resolution images is valid and it can be used in other irrigated areas with a declining groundwater table for the sustainable use of groundwater resources.
关键词： well irrigation,minimum irrigation water amount,Yellow River Downstream Plain,canal irrigation,irrigated cropland category
更新于2025-09-23 15:21:01
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Applicability of a gas analyzer with dual quantum cascade lasers for simultaneous measurements of N2O, CH4 and CO2 fluxes from cropland using the eddy covariance technique
摘要： We evaluated the applicability of a closed-path gas analyzer with two mid-infrared quantum cascade lasers (QCLs) for simultaneous measurement of nitrous oxide (N2O), methane (CH4) and carbon dioxide (CO2) fluxes from a cropland using the eddy covariance (EC) technique. The measurements were carried out in a typical vegetable field in the subtropical China during the wintertime, when the gas fluxes are at their lowest level in the year. A new approach was proposed to optimize the determination of lag times between the wind and gas concentration data, which was proven efficient to increase the reliability of the measured fluxes when the gas exchanges are weak. The dual-QCL analyzer showed a median precision (1σ) of 0.14 nmol mol?1 for N2O, 3.3 nmol mol?1 for CH4 and 0.36 μmol mol–1 for CO2 at sampling frequency of 10 Hz under the field conditions. Such precisions are better than, or comparable with, those of other commonly used closed-path or open-path gas analyzers, which are capable of measuring only one or two of the three gases. The detection limit of the EC system for measuring half-hourly fluxes were 0.05 nmol m?2 s?1 for N2O, 1.12 nmol m?2 s?1 for CH4 and 0.14 μmol m–2 s–1 for CO2. The results showed that 100% of the N2O, 87% of the CH4 and 96% of the CO2 fluxes were larger than the above detection limits. This study suggests that the EC technique using a closed-path gas analyzer with two quantum cascade lasers is qualified for reliable and simultaneous measurements of N2O, CH4 and CO2 fluxes from a subtropical cropland throughout the year. Moreover, EC method based on this type of gas analyzer provides an additional option for long-term and simultaneous flux measurements of the three greenhouse gases in a wide range of agricultural and natural ecosystems.
关键词： Nitrous oxide,eddy covariance,cropland,methane,flux,quantum cascade laser,carbon dioxide
更新于2025-09-19 17:13:59
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[IEEE 2018 7th International Conference on Agro-geoinformatics (Agro-geoinformatics) - Hangzhou (2018.8.6-2018.8.9)] 2018 7th International Conference on Agro-geoinformatics (Agro-geoinformatics) - Deep Extraction of Cropland Parcels from Very High-Resolution Remotely Sensed Imagery
摘要： Extracting cropland parcels from high resolution remote sensing images is a basic task for precision agriculture and other fields. Object based image analysis rely heavily on segmentation methods and can't satisfy the parcels' requisition in most situation. Inspired by the recent remarkable improvement on image understanding with deep learning, we propose a deep-edge guided method for cropland parcels extraction. Focus on the boundaries of these parcels, hard edge and soft edge are extracted respectively with U-Net and RCF model. Then all edges with the land type of cropland are constructed into parcels. At last accurate cropland-parcels are achieved.
关键词： cropland parcels,deep learning,high-resolution remote sensing,semantic segmentation
更新于2025-09-11 14:15:04