Pub Date : 2023-12-21DOI: 10.1080/15481603.2023.2293522
Alessandra Sciortino, Roberta Marini, Vincenzo Guerriero, Paolo Mazzanti, Marco Spadi, Marco Tallini
L’Aquila downtown (Central Italy) is situated in a highly seismic region, making it susceptible to numerous historical and recent earthquakes. Among these, the earthquake of Mw 6.3 on 6 April 2009,...
{"title":"Satellite A-DInSAR pattern recognition for seismic vulnerability mapping at city scale: insights from the L’Aquila (Italy) case study","authors":"Alessandra Sciortino, Roberta Marini, Vincenzo Guerriero, Paolo Mazzanti, Marco Spadi, Marco Tallini","doi":"10.1080/15481603.2023.2293522","DOIUrl":"https://doi.org/10.1080/15481603.2023.2293522","url":null,"abstract":"L’Aquila downtown (Central Italy) is situated in a highly seismic region, making it susceptible to numerous historical and recent earthquakes. Among these, the earthquake of Mw 6.3 on 6 April 2009,...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"31 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138887009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-21DOI: 10.1080/15481603.2023.2287291
Zhonghui Lv, Karinna Nunez, Ethan Brewer, Dan Runfola
Coastal wetlands, especially tidal marshes, play a crucial role in supporting ecosystems and slowing shoreline erosion. Accurate and cost-effective identification and classification of various mars...
{"title":"Mapping the tidal marshes of coastal Virginia: a hierarchical transfer learning approach","authors":"Zhonghui Lv, Karinna Nunez, Ethan Brewer, Dan Runfola","doi":"10.1080/15481603.2023.2287291","DOIUrl":"https://doi.org/10.1080/15481603.2023.2287291","url":null,"abstract":"Coastal wetlands, especially tidal marshes, play a crucial role in supporting ecosystems and slowing shoreline erosion. Accurate and cost-effective identification and classification of various mars...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"53 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138887038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Urban traffic anomaly diagnosis is crucial for urban road management and smart city construction. Most existing methods perform anomaly detection from a data-driven perspective and ignore the uniqu...
{"title":"Diagnosing urban traffic anomalies by integrating geographic knowledge and tensor theory","authors":"Zilong Zhao, Luliang Tang, Chang Ren, Xue Yang, Zihan Kan, Qingquan Li","doi":"10.1080/15481603.2023.2290347","DOIUrl":"https://doi.org/10.1080/15481603.2023.2290347","url":null,"abstract":"Urban traffic anomaly diagnosis is crucial for urban road management and smart city construction. Most existing methods perform anomaly detection from a data-driven perspective and ignore the uniqu...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"1 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138635133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-15DOI: 10.1080/15481603.2023.2293525
Kaifeng Peng, Weiguo Jiang, Peng Hou, Zhifeng Wu, Tiejun Cui
Mapping detailed wetland types can offer useful information for wetland management and protection, which can strongly support the Global Biodiversity Framework. Many studies have conducted wetland ...
{"title":"Detailed wetland-type classification using Landsat-8 time-series images: a pixel- and object-based algorithm with knowledge (POK)","authors":"Kaifeng Peng, Weiguo Jiang, Peng Hou, Zhifeng Wu, Tiejun Cui","doi":"10.1080/15481603.2023.2293525","DOIUrl":"https://doi.org/10.1080/15481603.2023.2293525","url":null,"abstract":"Mapping detailed wetland types can offer useful information for wetland management and protection, which can strongly support the Global Biodiversity Framework. Many studies have conducted wetland ...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"6 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138740089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-14DOI: 10.1080/15481603.2023.2282238
Xiangyu Hao, Jinxiu Liu, J. Heiskanen, E. Maeda, Si Gao, Xuecao Li
ABSTRACT Nighttime light (NTL) remote sensing data plays a crucial role in comprehending changes in human activities. The availability of the daily lunar BRDF-corrected Black Marble NTL product (VNP46A2) enables the use of NTL data to detect and assess the impact of short-term emergencies. However, daily NTL data often experience missing values due to cloud cover and low-quality signals. To address this issue, many studies utilize monthly or annual time-composite NTL products, which restrict the timeliness and potential application scenarios of NTL data usage. Therefore, it is necessary to generate the gap-filled daily NTL product. This study presented a novel NTL gap-filling method comprising rough reconstruction based on spatiotemporal weighting and refined gap-filling using a Bidirectional Long Short-Term Memory (Bi-LSTM) model. We evaluate the accuracy of the proposed method using the “remove-reconstruct-compare” approach, which randomly removes some original data from the complete image, fills the gaps with the proposed gap-filling method, and compares the reconstructed NTL data with the original observations in Beijing, Shanghai, Xi’an and New York. The results reveal that when the rate of missing values in Beijing is 40% and 50%, the proposed gap-filling method achieves accuracy with mean coefficient of determination (R2) values of 0.834 and 0.841, accompanied by corresponding root mean square (RMSE) values of 7.793 and 7.171, respectively. Furthermore, the gap-filling accuracy was evaluated quantitatively, and our proposed gap-filling method performed better than the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). Our proposed gap-filling method had R2 values of 0.685, 0.781, 0.720 and 0.642, which were higher than those for STARFM (0.430, 0.662, 0.221 and 0.345). The RMSE values of our gap-filling method were 9.628, 12.083, 10.963 and 19.882 for the four sites, while those of STARFM were 12.953, 14.872, 18.280 and 26.990, respectively. The temporal and spatial analysis results demonstrate that this model is robust, capturing city boundaries and NTL high-brightness hotspots with high accuracy and stability. The gap-filling model proposed in this study provides a new technique for expanding the potential applications and reliability of NASA’s daily Black Marble product (VNP46A2) in remote sensing.
{"title":"A robust gap-filling method for predicting missing observations in daily Black Marble nighttime light data","authors":"Xiangyu Hao, Jinxiu Liu, J. Heiskanen, E. Maeda, Si Gao, Xuecao Li","doi":"10.1080/15481603.2023.2282238","DOIUrl":"https://doi.org/10.1080/15481603.2023.2282238","url":null,"abstract":"ABSTRACT Nighttime light (NTL) remote sensing data plays a crucial role in comprehending changes in human activities. The availability of the daily lunar BRDF-corrected Black Marble NTL product (VNP46A2) enables the use of NTL data to detect and assess the impact of short-term emergencies. However, daily NTL data often experience missing values due to cloud cover and low-quality signals. To address this issue, many studies utilize monthly or annual time-composite NTL products, which restrict the timeliness and potential application scenarios of NTL data usage. Therefore, it is necessary to generate the gap-filled daily NTL product. This study presented a novel NTL gap-filling method comprising rough reconstruction based on spatiotemporal weighting and refined gap-filling using a Bidirectional Long Short-Term Memory (Bi-LSTM) model. We evaluate the accuracy of the proposed method using the “remove-reconstruct-compare” approach, which randomly removes some original data from the complete image, fills the gaps with the proposed gap-filling method, and compares the reconstructed NTL data with the original observations in Beijing, Shanghai, Xi’an and New York. The results reveal that when the rate of missing values in Beijing is 40% and 50%, the proposed gap-filling method achieves accuracy with mean coefficient of determination (R2) values of 0.834 and 0.841, accompanied by corresponding root mean square (RMSE) values of 7.793 and 7.171, respectively. Furthermore, the gap-filling accuracy was evaluated quantitatively, and our proposed gap-filling method performed better than the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). Our proposed gap-filling method had R2 values of 0.685, 0.781, 0.720 and 0.642, which were higher than those for STARFM (0.430, 0.662, 0.221 and 0.345). The RMSE values of our gap-filling method were 9.628, 12.083, 10.963 and 19.882 for the four sites, while those of STARFM were 12.953, 14.872, 18.280 and 26.990, respectively. The temporal and spatial analysis results demonstrate that this model is robust, capturing city boundaries and NTL high-brightness hotspots with high accuracy and stability. The gap-filling model proposed in this study provides a new technique for expanding the potential applications and reliability of NASA’s daily Black Marble product (VNP46A2) in remote sensing.","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"20 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138973092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-13DOI: 10.1080/15481603.2023.2285178
Sonu Kumar, Edward Park, Dung Duc Tran, Jingyu Wang, Huu Loc Ho, Lian Feng, Sameh A. Kantoush, Doan Van Binh, Dongfeng Li, Adam D. Switzer
Rapid urbanization has dramatically increased the demand for river sand, leading to soaring sand extraction rates that often exceed natural replenishment in many rivers globally. However, our under...
{"title":"A deep learning framework to map riverbed sand mining budgets in large tropical deltas","authors":"Sonu Kumar, Edward Park, Dung Duc Tran, Jingyu Wang, Huu Loc Ho, Lian Feng, Sameh A. Kantoush, Doan Van Binh, Dongfeng Li, Adam D. Switzer","doi":"10.1080/15481603.2023.2285178","DOIUrl":"https://doi.org/10.1080/15481603.2023.2285178","url":null,"abstract":"Rapid urbanization has dramatically increased the demand for river sand, leading to soaring sand extraction rates that often exceed natural replenishment in many rivers globally. However, our under...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"98 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138634378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-12DOI: 10.1080/15481603.2023.2292374
Duo Jia, Cangjiao Wang, Christopher R. Hakkenberg, Izaya Numata, Andrew J. Elmore, Mark A. Cochrane
The Global Ecosystem Dynamics Investigation (GEDI) is expected to revolutionize the quantification of aboveground carbon at continental scales, through its unprecedented dense vertical observations...
{"title":"Accuracy evaluation and effect factor analysis of GEDI aboveground biomass product for temperate forests in the conterminous United States","authors":"Duo Jia, Cangjiao Wang, Christopher R. Hakkenberg, Izaya Numata, Andrew J. Elmore, Mark A. Cochrane","doi":"10.1080/15481603.2023.2292374","DOIUrl":"https://doi.org/10.1080/15481603.2023.2292374","url":null,"abstract":"The Global Ecosystem Dynamics Investigation (GEDI) is expected to revolutionize the quantification of aboveground carbon at continental scales, through its unprecedented dense vertical observations...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"70 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138634381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-11DOI: 10.1080/15481603.2023.2290352
Xiaoyong Tan, Min Deng, Kaiqi Chen, Yan Shi, Bingbing Zhao, Qinghao Liu
Understanding the spatio-temporal evolution of urban expansion is essential for urban planning and sustainable development. Recently, cellular automata (CA)-based models have emerged as highly effe...
{"title":"A spatial hierarchical learning module based cellular automata model for simulating urban expansion: case studies of three Chinese urban areas","authors":"Xiaoyong Tan, Min Deng, Kaiqi Chen, Yan Shi, Bingbing Zhao, Qinghao Liu","doi":"10.1080/15481603.2023.2290352","DOIUrl":"https://doi.org/10.1080/15481603.2023.2290352","url":null,"abstract":"Understanding the spatio-temporal evolution of urban expansion is essential for urban planning and sustainable development. Recently, cellular automata (CA)-based models have emerged as highly effe...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"10 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138565193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-06DOI: 10.1080/15481603.2023.2285166
Lu Zhang, Zhuohang Xin, Qi Guan, Lian Feng, Chuanmin Hu, Chi Zhang, Huicheng Zhou
Lakes in the Northeast Plains-Mountain Lake Region (NPLR) of China face severe risks of eutrophication due to climate change and intensive anthropogenic pressures. As a vital indicator for eutrophi...
{"title":"Monitoring and understanding chlorophyll-a concentration changes in lakes in northeastern China using MERIS and OLCI satellite data","authors":"Lu Zhang, Zhuohang Xin, Qi Guan, Lian Feng, Chuanmin Hu, Chi Zhang, Huicheng Zhou","doi":"10.1080/15481603.2023.2285166","DOIUrl":"https://doi.org/10.1080/15481603.2023.2285166","url":null,"abstract":"Lakes in the Northeast Plains-Mountain Lake Region (NPLR) of China face severe risks of eutrophication due to climate change and intensive anthropogenic pressures. As a vital indicator for eutrophi...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"4 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138544685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Satellite datasets have revealed significant greening and soil drying in arid Central Asia. However, the influence mechanism of vegetation and climate on soil moisture dynamics is still unclear. In...
{"title":"Climate overtakes vegetation greening in regulating spatiotemporal patterns of soil moisture in arid Central Asia in recent 35 years","authors":"Nigenare Amantai, Yuanyuan Meng, Jingzhe Wang, Xiangyu Ge, Zhiyao Tang","doi":"10.1080/15481603.2023.2286744","DOIUrl":"https://doi.org/10.1080/15481603.2023.2286744","url":null,"abstract":"Satellite datasets have revealed significant greening and soil drying in arid Central Asia. However, the influence mechanism of vegetation and climate on soil moisture dynamics is still unclear. In...","PeriodicalId":55091,"journal":{"name":"GIScience & Remote Sensing","volume":"40 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138544659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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