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Polynyas are an important factor in the Antarctic and Arctic climate, and their changes are related to the ecosystems in the polar regions. The phenomenon of polynyas is influenced by the combination of inherent persistence and dynamic factors. The dynamics of polynyas are greatly affected by temporal dynamical factors, and it is difficult to objectively reflect the internal characteristics of their formation. Separating the two factors effectively is necessary in order to explore their essence. The Special Sensor Microwave/Imager (SSM/I) passive microwave sensor has been making observations of Antarctica for more than 20 years, but it is difficult for existing current sea ice concentration (SIC) products to objectively reflect how the inherent persistence factors affect the formation of polynyas. In this paper, we proposed a long-term multiple spatial smoothing method to remove the influence of dynamic factors and obtain stable annual SIC products. A halo located on the border of areas of low and high ice concentration around the Antarctic coast, which has a strong similarity with the local seabed in outline, was found using the spatially smoothed SIC products and seabed. The relationship of the polynya location to the wind and topography is a long-understood relationship; here, we quantify that where there is an abrupt slope and wind transitions, new polynyas are best generated. A combination of image expansion and threshold segmentation was used to extract the extent of sea ice and coastal polynyas. The adjusted record of changes in the extent of coastal polynyas and sea ice in the Southern Ocean indicate that there is a negative correlation between them.
Liyuan Jiang; Yong Ma; Fu Chen; Jianbo Liu; Wutao Yao; Yubao Qiu; Shuyan Zhang. Trends in the Stability of Antarctic Coastal Polynyas and the Role of Topographic Forcing Factors. Remote Sensing 2020, 12, 1043 .
AMA StyleLiyuan Jiang, Yong Ma, Fu Chen, Jianbo Liu, Wutao Yao, Yubao Qiu, Shuyan Zhang. Trends in the Stability of Antarctic Coastal Polynyas and the Role of Topographic Forcing Factors. Remote Sensing. 2020; 12 (6):1043.
Chicago/Turabian StyleLiyuan Jiang; Yong Ma; Fu Chen; Jianbo Liu; Wutao Yao; Yubao Qiu; Shuyan Zhang. 2020. "Trends in the Stability of Antarctic Coastal Polynyas and the Role of Topographic Forcing Factors." Remote Sensing 12, no. 6: 1043.
Ice storms greatly affect the structure, dynamics, and functioning of forest ecosystems. Studies on the impact of such disasters, as well as the post-disaster recovery of forests, are important contents in forest biology, ecology, and geography. Remote-sensing technology provides data and methods that can support the study of disasters at the large-to-medium scale and over long time periods. This study took Chebaling National Nature Reserve in Guangdong Province, China, as the study area. First, field-survey data and remote-sensing data were comprehensively analyzed to demonstrate the feasibility of replacing the forest stock volume with the mean annual value of the Enhanced Vegetation Index (EVI), to study forest growth and change. We then used the EVI from 2007 to 2017, together with a variety of other remote-sensing and forest sub-compartment data, to analyze the impact of the 2008 ice storm and the subsequent post-disaster recovery of the forest. Finally, we drew the following conclusions: (1) Topography had a considerable effect on disaster impact and forest recovery in Chebaling. The forest at high altitudes (700–1000 m) and on steep slopes (25–40°) was seriously affected by this disaster but had a stronger post-disaster recovery ability. Meanwhile, the hardest-hit area for coniferous forest was higher and steeper than that for broad-leaved forest. (2) In the same terrain conditions, coniferous forests were less affected by the disaster than broad-leaved forests and showed less variation during the post-disaster recovery process. Nevertheless, broad-leaved forests had faster recovery rates and higher recovery degrees; (3) Under the influence of human activities, the recovery and fluctuation degree for planted forest in the post-disaster recovery process was significantly higher than that for natural forest. The study suggests that forest has high disaster resistance and self-recovery ability after the ice storm, and this ability has a strong correlation with the type of forest and the topographic factors such as elevation and slope. At the same time, human intervention can speed up the recovery of forests after disasters.
Wutao Yao; Yong Ma; Fu Chen; Zhishu Xiao; Zufei Shu; Lijun Chen; Wenhong Xiao; Jianbo Liu; Liyuan Jiang; Shuyan Zhang. Analysis of Ice Storm Impact on and Post-Disaster Recovery of Typical Subtropical Forests in Southeast China. Remote Sensing 2020, 12, 164 .
AMA StyleWutao Yao, Yong Ma, Fu Chen, Zhishu Xiao, Zufei Shu, Lijun Chen, Wenhong Xiao, Jianbo Liu, Liyuan Jiang, Shuyan Zhang. Analysis of Ice Storm Impact on and Post-Disaster Recovery of Typical Subtropical Forests in Southeast China. Remote Sensing. 2020; 12 (1):164.
Chicago/Turabian StyleWutao Yao; Yong Ma; Fu Chen; Zhishu Xiao; Zufei Shu; Lijun Chen; Wenhong Xiao; Jianbo Liu; Liyuan Jiang; Shuyan Zhang. 2020. "Analysis of Ice Storm Impact on and Post-Disaster Recovery of Typical Subtropical Forests in Southeast China." Remote Sensing 12, no. 1: 164.
Quarry sites result from human activity, which includes the removal of original vegetation and the overlying soil to dig out stones for building use. Therefore, the dynamics of the quarry area provide a unique view of human mining activities. Actually, the topographic changes caused by mining activities are also a result of the development of the local economy. Thus, monitoring the quarry area can provide information about the policies of the economy and environmental protection. In this paper, we developed a combined method of machine learning classification and quarry region analysis to estimate the quarry area in a quarry region near Beijing. A temporal smoothing based on the classification results of all years was applied in post-processing to remove outliers and obtain gently changing sequences along the monitoring term. The method was applied to Landsat images to derive a quarry distribution map and quarry area time series from 1984 to 2017, revealing significant inter-annual variability. The time series revealed a five-stage development of the quarry area with different growth patterns. As the study region lies on two jurisdictions—Tianjin and Hebei—a comparison of the quarry area changes in the two jurisdictions was applied, which revealed that the different policies in the two regions could impose different impacts on the development of a quarry area. An analysis concerning the relationship between quarry area and gross regional product (GRP) was performed to explore the potential application on socioeconomic studies, and we found a strong positive correlation between quarry area and GRP in Langfang City, Hebei Province. These results demonstrate the potential benefit of annual monitoring over the long-term for socioeconomic studies, which can be used for mining decision making.
Haoteng Zhao; Yong Ma; Fu Chen; Jianbo Liu; Liyuan Jiang; Wutao Yao; Jin Yang. Monitoring Quarry Area with Landsat Long Time-Series for Socioeconomic Study. Remote Sensing 2018, 10, 517 .
AMA StyleHaoteng Zhao, Yong Ma, Fu Chen, Jianbo Liu, Liyuan Jiang, Wutao Yao, Jin Yang. Monitoring Quarry Area with Landsat Long Time-Series for Socioeconomic Study. Remote Sensing. 2018; 10 (4):517.
Chicago/Turabian StyleHaoteng Zhao; Yong Ma; Fu Chen; Jianbo Liu; Liyuan Jiang; Wutao Yao; Jin Yang. 2018. "Monitoring Quarry Area with Landsat Long Time-Series for Socioeconomic Study." Remote Sensing 10, no. 4: 517.
With the rapid development of satellite remote sensing technology, the size of image datasets in many application areas is growing exponentially and the demand for Land-Cover and Land-Use change remote sensing data is growing rapidly. It is thus becoming hard to efficiently and intelligently retrieve the change information that users need from massive image databases. In this paper, content-based image retrieval is successfully applied to change detection, and a content-based remote sensing image change information retrieval model is introduced. First, the construction of a new model framework for change information retrieval from a remote sensing database is described. Then, as the target content cannot be expressed by one kind of feature alone, a multiple-feature, integrated retrieval model is proposed. Thirdly, an experimental prototype system that was set up to demonstrate the validity and practicability of the model is described. The proposed model is a new method of acquiring change detection information from remote sensing imagery and so can reduce the need for image pre-processing and also deal with problems related to seasonal changes, as well as other problems encountered in the field of change detection. Meanwhile, the new model has important implications for improving remote sensing image management and autonomous information retrieval. The experiment results obtained using a Landsat data set show that the use of the new model can produce promising results. A coverage rate and mean average precision of 71% and 89%, respectively, were achieved for the top 20 returned pairs of images.
Caihong Ma; Wei Xia; Fu Chen; Jianbo Liu; Qin Dai; Liyuan Jiang; Jianbo Duan; Wei Liu. A Content-Based Remote Sensing Image Change Information Retrieval Model. ISPRS International Journal of Geo-Information 2017, 6, 310 .
AMA StyleCaihong Ma, Wei Xia, Fu Chen, Jianbo Liu, Qin Dai, Liyuan Jiang, Jianbo Duan, Wei Liu. A Content-Based Remote Sensing Image Change Information Retrieval Model. ISPRS International Journal of Geo-Information. 2017; 6 (10):310.
Chicago/Turabian StyleCaihong Ma; Wei Xia; Fu Chen; Jianbo Liu; Qin Dai; Liyuan Jiang; Jianbo Duan; Wei Liu. 2017. "A Content-Based Remote Sensing Image Change Information Retrieval Model." ISPRS International Journal of Geo-Information 6, no. 10: 310.
With the rapid development of satellite remote sensing technology, the volume of image datasets in many application areas is growing exponentially and the demand for Land-Cover and Land-Use change remote sensing data is growing rapidly. It is thus becoming hard to efficiently and intelligently retrieve the change information that users need from massive image databases. In this paper, content-based image retrieval is successfully applied to change detection and a content-based remote sensing image change information retrieval model is introduced. First, the construction of a new model framework for change information retrieval in a remote sensing database is described. Then, as the target content cannot be expressed by one kind of feature alone, a multiple-feature integrated retrieval model is proposed. Thirdly, an experimental prototype system that was set up to demonstrate the validity and practicability of the model is described. The proposed model is a new method of acquiring change detection information from remote sensing imagery and so can reduce the need for image pre-processing, deal with problems related toseasonal changes as well as other problems encountered in the field of change detection. Meanwhile, the new model has important implications for improving remote sensing image management and autonomous information retrieval.
Caihong Ma; Wei Xia; Fu Chen; Jianbo Liu; Qin Dai; Liyuan Jiang; Jianbo Duan; Wei Liu. A Content-Based Remote Sensing Image Change Information Retrieval Model. 2017, 1 .
AMA StyleCaihong Ma, Wei Xia, Fu Chen, Jianbo Liu, Qin Dai, Liyuan Jiang, Jianbo Duan, Wei Liu. A Content-Based Remote Sensing Image Change Information Retrieval Model. . 2017; ():1.
Chicago/Turabian StyleCaihong Ma; Wei Xia; Fu Chen; Jianbo Liu; Qin Dai; Liyuan Jiang; Jianbo Duan; Wei Liu. 2017. "A Content-Based Remote Sensing Image Change Information Retrieval Model." , no. : 1.
Li-Yuan Jiang; Ming-Xu Wang; Guang-Feng Xiang; Li-Hong Yan; You-Jun He; Wei Liu. Tulipa gesneriana introduced from Netherland to Changsha]]>. JOURNAL OF HUNAN AGRICULTURAL UNIVERSITY 2011, 37, 177 -180.
AMA StyleLi-Yuan Jiang, Ming-Xu Wang, Guang-Feng Xiang, Li-Hong Yan, You-Jun He, Wei Liu. Tulipa gesneriana introduced from Netherland to Changsha]]>. JOURNAL OF HUNAN AGRICULTURAL UNIVERSITY. 2011; 37 (2):177-180.
Chicago/Turabian StyleLi-Yuan Jiang; Ming-Xu Wang; Guang-Feng Xiang; Li-Hong Yan; You-Jun He; Wei Liu. 2011. "Tulipa gesneriana introduced from Netherland to Changsha]]>." JOURNAL OF HUNAN AGRICULTURAL UNIVERSITY 37, no. 2: 177-180.