Suburban greenhouses with intensive agricultural productivity have increasingly influenced the daily diet and vegetable supply in Chinese cities.With their enormous input of fertilizers and pesticides,greenhouses have...Suburban greenhouses with intensive agricultural productivity have increasingly influenced the daily diet and vegetable supply in Chinese cities.With their enormous input of fertilizers and pesticides,greenhouses have considerably changed the local soil quality and environmental risk factors.The ability to obtain timely and accurate information regarding the spatial distribution of greenhouses could make an important contribution to local agricultural management and soil protection.This paper attempts to present a practical framework for extracting suburban greenhouses,integrating remote sensing data from Landsat-8 and object-oriented classification.Inheritance classification was implemented,and various properties,including texture and neighborhood features in addition to spectral information,were investigated through the popular random forest technique for feature selection prior to SVM classification to improve the mapping accuracy.The results demonstrated that object-based classification incorporating non-spectral features yielded a significant improvement compared with the classification results obtained using only the spectral information in traditional per-pixel classification.Both the producer’s and user’s accuracy were higher than 85%for greenhouse identification.Although it remained a challenge to completely distinguish greenhouses from sparse plants,the final greenhouse map indicated that the proposed object-based classification scheme,providing multiple feature selections and multi-scale analysis,yielded worthwhile information when applied to a continuous series of the freely available Landsat-8 imagery data.展开更多
The Lunar-based Ultraviolet Telescope (LUT) is a funded lunar-based ultraviolet telescope dedicated to continuously monitoring variable stars for as long as dozens of days and performing low Galactic latitude sky surv...The Lunar-based Ultraviolet Telescope (LUT) is a funded lunar-based ultraviolet telescope dedicated to continuously monitoring variable stars for as long as dozens of days and performing low Galactic latitude sky surveys. The slow and smooth spin of the Moon makes its step by step pointing strategy possible. A flat mirror mounted on a gimbal mount is configured to enlarge the sky coverage of the LUT. A Ritchey-Chrétien telescope with a Nasmyth focus configuration is adopted to reduce the total length of the system. A UV enhanced back illuminated AIMO CCD 47-20 chip together with the low noise electric design will minimize the instrumental influence on the system. The preliminary proposal for astrometric calibration and photometric calibration are also presented.展开更多
基金The authors are grateful for the support of the National Ecological Survey and Evaluation(2000-2010)under the auspices of the Remote Sensing Program of the Chinese Ministry of Environmental Protection(No.STSN-05-11).
文摘Suburban greenhouses with intensive agricultural productivity have increasingly influenced the daily diet and vegetable supply in Chinese cities.With their enormous input of fertilizers and pesticides,greenhouses have considerably changed the local soil quality and environmental risk factors.The ability to obtain timely and accurate information regarding the spatial distribution of greenhouses could make an important contribution to local agricultural management and soil protection.This paper attempts to present a practical framework for extracting suburban greenhouses,integrating remote sensing data from Landsat-8 and object-oriented classification.Inheritance classification was implemented,and various properties,including texture and neighborhood features in addition to spectral information,were investigated through the popular random forest technique for feature selection prior to SVM classification to improve the mapping accuracy.The results demonstrated that object-based classification incorporating non-spectral features yielded a significant improvement compared with the classification results obtained using only the spectral information in traditional per-pixel classification.Both the producer’s and user’s accuracy were higher than 85%for greenhouse identification.Although it remained a challenge to completely distinguish greenhouses from sparse plants,the final greenhouse map indicated that the proposed object-based classification scheme,providing multiple feature selections and multi-scale analysis,yielded worthwhile information when applied to a continuous series of the freely available Landsat-8 imagery data.
基金supported by the Ministry of Science and Technology of China and the National Natural Science Foundation of China (Grant Nos. 10803008, 10978020 and 10878019)
文摘The Lunar-based Ultraviolet Telescope (LUT) is a funded lunar-based ultraviolet telescope dedicated to continuously monitoring variable stars for as long as dozens of days and performing low Galactic latitude sky surveys. The slow and smooth spin of the Moon makes its step by step pointing strategy possible. A flat mirror mounted on a gimbal mount is configured to enlarge the sky coverage of the LUT. A Ritchey-Chrétien telescope with a Nasmyth focus configuration is adopted to reduce the total length of the system. A UV enhanced back illuminated AIMO CCD 47-20 chip together with the low noise electric design will minimize the instrumental influence on the system. The preliminary proposal for astrometric calibration and photometric calibration are also presented.
