Pub Date : 2024-02-06DOI: 10.3389/ffgc.2024.1236203
Margot Vanhellemont, A. Leyman, Leen Govaere, Luc De Keersmaeker, K. Vandekerkhove
In situ carbon sequestration in forests is important in the context of climate change mitigation, and setting aside managed forests has been proposed as an option for increased carbon sequestration. Comparing set-aside and managed forests may provide insights and rules of thumb on the potential for additional in situ carbon sequestration in set-aside forest.In an observational study, we compared re-inventory data from the network of set-aside forest reserves in Flanders, which have been unmanaged for 17–66 years (2 surveys with a 10 years interval), with re-inventory data from the regional forest inventory, representing the overall forest area in Flanders (2 surveys with a 15 years interval).The aboveground carbon pools and sequestration rates were higher in the set-aside forests compared to the average forest in Flanders. In the average Flemish forest, the aboveground carbon pool increased from 64.7 to 85.1 tC ha−1, over a period of 15 years. In the set-aside forests, the mean pool was higher at the first measurement and further increased from 84.8 to 102.4 tC ha−1, over a period of 10 years. The mean aboveground annual carbon sequestration rate was 1.3 tC ha−1 year−1 in the average forest in Flanders and 1.8 tC ha−1 year−1 in the set-aside forests. The stocks and fluxes depended on the soil conditions and were higher in set-aside forests on silt and sandy silt sites compared to wet and sand sites. The set-aside forests on dry sites showed additionality in in situ aboveground carbon sequestration. We saw no indication of approaching a culmination point in the first decades following set-aside: plots with high carbon pools did not show lower carbon sequestration. In conclusion, set-aside forests can combine high carbon pools with high sequestration rates on suitable sites. Under the current management policy, we expect Flemish forests—regular and set-aside—to further increase their carbon pools in the coming decades.
{"title":"Site-specific additionality in aboveground carbon sequestration in set-aside forests in Flanders (northern Belgium)","authors":"Margot Vanhellemont, A. Leyman, Leen Govaere, Luc De Keersmaeker, K. Vandekerkhove","doi":"10.3389/ffgc.2024.1236203","DOIUrl":"https://doi.org/10.3389/ffgc.2024.1236203","url":null,"abstract":"In situ carbon sequestration in forests is important in the context of climate change mitigation, and setting aside managed forests has been proposed as an option for increased carbon sequestration. Comparing set-aside and managed forests may provide insights and rules of thumb on the potential for additional in situ carbon sequestration in set-aside forest.In an observational study, we compared re-inventory data from the network of set-aside forest reserves in Flanders, which have been unmanaged for 17–66 years (2 surveys with a 10 years interval), with re-inventory data from the regional forest inventory, representing the overall forest area in Flanders (2 surveys with a 15 years interval).The aboveground carbon pools and sequestration rates were higher in the set-aside forests compared to the average forest in Flanders. In the average Flemish forest, the aboveground carbon pool increased from 64.7 to 85.1 tC ha−1, over a period of 15 years. In the set-aside forests, the mean pool was higher at the first measurement and further increased from 84.8 to 102.4 tC ha−1, over a period of 10 years. The mean aboveground annual carbon sequestration rate was 1.3 tC ha−1 year−1 in the average forest in Flanders and 1.8 tC ha−1 year−1 in the set-aside forests. The stocks and fluxes depended on the soil conditions and were higher in set-aside forests on silt and sandy silt sites compared to wet and sand sites. The set-aside forests on dry sites showed additionality in in situ aboveground carbon sequestration. We saw no indication of approaching a culmination point in the first decades following set-aside: plots with high carbon pools did not show lower carbon sequestration. In conclusion, set-aside forests can combine high carbon pools with high sequestration rates on suitable sites. Under the current management policy, we expect Flemish forests—regular and set-aside—to further increase their carbon pools in the coming decades.","PeriodicalId":507254,"journal":{"name":"Frontiers in Forests and Global Change","volume":"303 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139799423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-06DOI: 10.3389/ffgc.2024.1236203
Margot Vanhellemont, A. Leyman, Leen Govaere, Luc De Keersmaeker, K. Vandekerkhove
In situ carbon sequestration in forests is important in the context of climate change mitigation, and setting aside managed forests has been proposed as an option for increased carbon sequestration. Comparing set-aside and managed forests may provide insights and rules of thumb on the potential for additional in situ carbon sequestration in set-aside forest.In an observational study, we compared re-inventory data from the network of set-aside forest reserves in Flanders, which have been unmanaged for 17–66 years (2 surveys with a 10 years interval), with re-inventory data from the regional forest inventory, representing the overall forest area in Flanders (2 surveys with a 15 years interval).The aboveground carbon pools and sequestration rates were higher in the set-aside forests compared to the average forest in Flanders. In the average Flemish forest, the aboveground carbon pool increased from 64.7 to 85.1 tC ha−1, over a period of 15 years. In the set-aside forests, the mean pool was higher at the first measurement and further increased from 84.8 to 102.4 tC ha−1, over a period of 10 years. The mean aboveground annual carbon sequestration rate was 1.3 tC ha−1 year−1 in the average forest in Flanders and 1.8 tC ha−1 year−1 in the set-aside forests. The stocks and fluxes depended on the soil conditions and were higher in set-aside forests on silt and sandy silt sites compared to wet and sand sites. The set-aside forests on dry sites showed additionality in in situ aboveground carbon sequestration. We saw no indication of approaching a culmination point in the first decades following set-aside: plots with high carbon pools did not show lower carbon sequestration. In conclusion, set-aside forests can combine high carbon pools with high sequestration rates on suitable sites. Under the current management policy, we expect Flemish forests—regular and set-aside—to further increase their carbon pools in the coming decades.
{"title":"Site-specific additionality in aboveground carbon sequestration in set-aside forests in Flanders (northern Belgium)","authors":"Margot Vanhellemont, A. Leyman, Leen Govaere, Luc De Keersmaeker, K. Vandekerkhove","doi":"10.3389/ffgc.2024.1236203","DOIUrl":"https://doi.org/10.3389/ffgc.2024.1236203","url":null,"abstract":"In situ carbon sequestration in forests is important in the context of climate change mitigation, and setting aside managed forests has been proposed as an option for increased carbon sequestration. Comparing set-aside and managed forests may provide insights and rules of thumb on the potential for additional in situ carbon sequestration in set-aside forest.In an observational study, we compared re-inventory data from the network of set-aside forest reserves in Flanders, which have been unmanaged for 17–66 years (2 surveys with a 10 years interval), with re-inventory data from the regional forest inventory, representing the overall forest area in Flanders (2 surveys with a 15 years interval).The aboveground carbon pools and sequestration rates were higher in the set-aside forests compared to the average forest in Flanders. In the average Flemish forest, the aboveground carbon pool increased from 64.7 to 85.1 tC ha−1, over a period of 15 years. In the set-aside forests, the mean pool was higher at the first measurement and further increased from 84.8 to 102.4 tC ha−1, over a period of 10 years. The mean aboveground annual carbon sequestration rate was 1.3 tC ha−1 year−1 in the average forest in Flanders and 1.8 tC ha−1 year−1 in the set-aside forests. The stocks and fluxes depended on the soil conditions and were higher in set-aside forests on silt and sandy silt sites compared to wet and sand sites. The set-aside forests on dry sites showed additionality in in situ aboveground carbon sequestration. We saw no indication of approaching a culmination point in the first decades following set-aside: plots with high carbon pools did not show lower carbon sequestration. In conclusion, set-aside forests can combine high carbon pools with high sequestration rates on suitable sites. Under the current management policy, we expect Flemish forests—regular and set-aside—to further increase their carbon pools in the coming decades.","PeriodicalId":507254,"journal":{"name":"Frontiers in Forests and Global Change","volume":"1 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139859177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-05DOI: 10.3389/ffgc.2024.1356686
Xianliang Zhang, Ruben Manzanedo, Guobao Xu, Andrei G. Lapenis
{"title":"Editorial: Achieving sustainable development goal 13: resilience and adaptive capacity of temperate and boreal forests under climate change","authors":"Xianliang Zhang, Ruben Manzanedo, Guobao Xu, Andrei G. Lapenis","doi":"10.3389/ffgc.2024.1356686","DOIUrl":"https://doi.org/10.3389/ffgc.2024.1356686","url":null,"abstract":"","PeriodicalId":507254,"journal":{"name":"Frontiers in Forests and Global Change","volume":"14 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139805971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-05DOI: 10.3389/ffgc.2024.1356686
Xianliang Zhang, Ruben Manzanedo, Guobao Xu, Andrei G. Lapenis
{"title":"Editorial: Achieving sustainable development goal 13: resilience and adaptive capacity of temperate and boreal forests under climate change","authors":"Xianliang Zhang, Ruben Manzanedo, Guobao Xu, Andrei G. Lapenis","doi":"10.3389/ffgc.2024.1356686","DOIUrl":"https://doi.org/10.3389/ffgc.2024.1356686","url":null,"abstract":"","PeriodicalId":507254,"journal":{"name":"Frontiers in Forests and Global Change","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139865881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As a key ecological function area and a priority area for biodiversity conservation in China, Qilian Mountain National Park is facing a severe test of its ecological environment, and the study of its landscape ecological risk is of great significance to the construction and high-quality development of the Qilian Mountain National Park. In this research, based on land use data from six periods (i.e., year in 1995, 2000, 2005, 2010, 2015, and 2020) in the Qilian Mountain National Park, we divided the ecological risk plots, calculated the landscape pattern, and constructed the landscape ecological risk index to deeply explore the temporal and spatial heterogeneity of landscape ecological risk in Qilian Mountain National Park by using ArcGIS, Fragstats and GeoDa. The results showed that: Grassland is the predominant land use type, the area covered by woodland and grassland have exhibited a significant increase since 1995. Landscape fragmentation and disturbance indices exhibit fluctuations across different years, but showed an overall decreasing trend, and landscape stability was improved in the study area. There were obvious differences in the disturbance indices of different landscape types, with grassland and bare land having the highest values. Ecological risk in the study area is heterogeneous, with an overall low ecological risk and a shift to a lower risk level, and a decreasing trend in ecological risk, which is positively correlated spatially and mainly manifested as a “low-low” aggregation. Global warming and unreasonable human activities have exacerbated the ecological degradation of Qilian Mountain National Park, but a series of ecological restoration strategies after the establishment of the national park have gradually improved the regional ecological environment.
{"title":"An analysis on the spatial heterogeneity characteristics of landscape ecological risk in Qilian Mountain National Park","authors":"Yanlong Li, Qianqian Qin, Duowen Wang, Wanxiu An, Xiaohui He, Tianquan Yu","doi":"10.3389/ffgc.2024.1308154","DOIUrl":"https://doi.org/10.3389/ffgc.2024.1308154","url":null,"abstract":"As a key ecological function area and a priority area for biodiversity conservation in China, Qilian Mountain National Park is facing a severe test of its ecological environment, and the study of its landscape ecological risk is of great significance to the construction and high-quality development of the Qilian Mountain National Park. In this research, based on land use data from six periods (i.e., year in 1995, 2000, 2005, 2010, 2015, and 2020) in the Qilian Mountain National Park, we divided the ecological risk plots, calculated the landscape pattern, and constructed the landscape ecological risk index to deeply explore the temporal and spatial heterogeneity of landscape ecological risk in Qilian Mountain National Park by using ArcGIS, Fragstats and GeoDa. The results showed that: Grassland is the predominant land use type, the area covered by woodland and grassland have exhibited a significant increase since 1995. Landscape fragmentation and disturbance indices exhibit fluctuations across different years, but showed an overall decreasing trend, and landscape stability was improved in the study area. There were obvious differences in the disturbance indices of different landscape types, with grassland and bare land having the highest values. Ecological risk in the study area is heterogeneous, with an overall low ecological risk and a shift to a lower risk level, and a decreasing trend in ecological risk, which is positively correlated spatially and mainly manifested as a “low-low” aggregation. Global warming and unreasonable human activities have exacerbated the ecological degradation of Qilian Mountain National Park, but a series of ecological restoration strategies after the establishment of the national park have gradually improved the regional ecological environment.","PeriodicalId":507254,"journal":{"name":"Frontiers in Forests and Global Change","volume":"10 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139864995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As a key ecological function area and a priority area for biodiversity conservation in China, Qilian Mountain National Park is facing a severe test of its ecological environment, and the study of its landscape ecological risk is of great significance to the construction and high-quality development of the Qilian Mountain National Park. In this research, based on land use data from six periods (i.e., year in 1995, 2000, 2005, 2010, 2015, and 2020) in the Qilian Mountain National Park, we divided the ecological risk plots, calculated the landscape pattern, and constructed the landscape ecological risk index to deeply explore the temporal and spatial heterogeneity of landscape ecological risk in Qilian Mountain National Park by using ArcGIS, Fragstats and GeoDa. The results showed that: Grassland is the predominant land use type, the area covered by woodland and grassland have exhibited a significant increase since 1995. Landscape fragmentation and disturbance indices exhibit fluctuations across different years, but showed an overall decreasing trend, and landscape stability was improved in the study area. There were obvious differences in the disturbance indices of different landscape types, with grassland and bare land having the highest values. Ecological risk in the study area is heterogeneous, with an overall low ecological risk and a shift to a lower risk level, and a decreasing trend in ecological risk, which is positively correlated spatially and mainly manifested as a “low-low” aggregation. Global warming and unreasonable human activities have exacerbated the ecological degradation of Qilian Mountain National Park, but a series of ecological restoration strategies after the establishment of the national park have gradually improved the regional ecological environment.
{"title":"An analysis on the spatial heterogeneity characteristics of landscape ecological risk in Qilian Mountain National Park","authors":"Yanlong Li, Qianqian Qin, Duowen Wang, Wanxiu An, Xiaohui He, Tianquan Yu","doi":"10.3389/ffgc.2024.1308154","DOIUrl":"https://doi.org/10.3389/ffgc.2024.1308154","url":null,"abstract":"As a key ecological function area and a priority area for biodiversity conservation in China, Qilian Mountain National Park is facing a severe test of its ecological environment, and the study of its landscape ecological risk is of great significance to the construction and high-quality development of the Qilian Mountain National Park. In this research, based on land use data from six periods (i.e., year in 1995, 2000, 2005, 2010, 2015, and 2020) in the Qilian Mountain National Park, we divided the ecological risk plots, calculated the landscape pattern, and constructed the landscape ecological risk index to deeply explore the temporal and spatial heterogeneity of landscape ecological risk in Qilian Mountain National Park by using ArcGIS, Fragstats and GeoDa. The results showed that: Grassland is the predominant land use type, the area covered by woodland and grassland have exhibited a significant increase since 1995. Landscape fragmentation and disturbance indices exhibit fluctuations across different years, but showed an overall decreasing trend, and landscape stability was improved in the study area. There were obvious differences in the disturbance indices of different landscape types, with grassland and bare land having the highest values. Ecological risk in the study area is heterogeneous, with an overall low ecological risk and a shift to a lower risk level, and a decreasing trend in ecological risk, which is positively correlated spatially and mainly manifested as a “low-low” aggregation. Global warming and unreasonable human activities have exacerbated the ecological degradation of Qilian Mountain National Park, but a series of ecological restoration strategies after the establishment of the national park have gradually improved the regional ecological environment.","PeriodicalId":507254,"journal":{"name":"Frontiers in Forests and Global Change","volume":"5 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139805255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-02DOI: 10.3389/ffgc.2024.1339603
Hongjun Peng, Ping Li, Rong Zhu
Utilizing flowering cherries to enhance suburban landscapes and attract public recreation holds significant economic and social value. However, the current quality of the cherry landscape is compromised due to the absence of variety selection and planning in planting and design. Based on the analysis of public preference, there is significant importance in boosting the sustainability of cherry blossom landscape. However, related research in this domain still needs to be explored. This study examined four representative cherry blossom landscapes in Fujian Province to assess the landscape quality and growth of existing cherry varieties. Subsequently, an improvement model of cherry blossom landscape quality was developed based on image semantic segmentation, aiming to quantify landscape elements. The findings indicated that: (1) There were a total of 46 cherry varieties blooming from January to March in the four representative cherry blossom landscapes. The health grades distribution was as follow: Grade I accounted for 41.3%, Grade II for 39.1%, Grade III for 8.7%, Grade IV for 6.5%, and Grade V for 4.4%. (2) The highest marginal benefit for flake planting was observed when the flowering ratio exceeded 60% or was less than 15%. In contrast, the optimal flowering ratio for the linear cherry blossom landscape for maximum marginal benefit was over 30.0%. (3) The outcomes of the scenic beauty model revealed that the five major factors influencing the scenic beauty were the scene cleanliness (38.04%), plant color composition (25.59%), road (17.79%), plant type (12.88%) and building (2.70%). The results of this study provide valuable objective data references for the planning, design and management of cherry blossom landscapes.
{"title":"Enhancing the sustainability of cherry blossom landscapes-a case study in Fujian Province, China","authors":"Hongjun Peng, Ping Li, Rong Zhu","doi":"10.3389/ffgc.2024.1339603","DOIUrl":"https://doi.org/10.3389/ffgc.2024.1339603","url":null,"abstract":"Utilizing flowering cherries to enhance suburban landscapes and attract public recreation holds significant economic and social value. However, the current quality of the cherry landscape is compromised due to the absence of variety selection and planning in planting and design. Based on the analysis of public preference, there is significant importance in boosting the sustainability of cherry blossom landscape. However, related research in this domain still needs to be explored. This study examined four representative cherry blossom landscapes in Fujian Province to assess the landscape quality and growth of existing cherry varieties. Subsequently, an improvement model of cherry blossom landscape quality was developed based on image semantic segmentation, aiming to quantify landscape elements. The findings indicated that: (1) There were a total of 46 cherry varieties blooming from January to March in the four representative cherry blossom landscapes. The health grades distribution was as follow: Grade I accounted for 41.3%, Grade II for 39.1%, Grade III for 8.7%, Grade IV for 6.5%, and Grade V for 4.4%. (2) The highest marginal benefit for flake planting was observed when the flowering ratio exceeded 60% or was less than 15%. In contrast, the optimal flowering ratio for the linear cherry blossom landscape for maximum marginal benefit was over 30.0%. (3) The outcomes of the scenic beauty model revealed that the five major factors influencing the scenic beauty were the scene cleanliness (38.04%), plant color composition (25.59%), road (17.79%), plant type (12.88%) and building (2.70%). The results of this study provide valuable objective data references for the planning, design and management of cherry blossom landscapes.","PeriodicalId":507254,"journal":{"name":"Frontiers in Forests and Global Change","volume":"102 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139810346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-02DOI: 10.3389/ffgc.2024.1339603
Hongjun Peng, Ping Li, Rong Zhu
Utilizing flowering cherries to enhance suburban landscapes and attract public recreation holds significant economic and social value. However, the current quality of the cherry landscape is compromised due to the absence of variety selection and planning in planting and design. Based on the analysis of public preference, there is significant importance in boosting the sustainability of cherry blossom landscape. However, related research in this domain still needs to be explored. This study examined four representative cherry blossom landscapes in Fujian Province to assess the landscape quality and growth of existing cherry varieties. Subsequently, an improvement model of cherry blossom landscape quality was developed based on image semantic segmentation, aiming to quantify landscape elements. The findings indicated that: (1) There were a total of 46 cherry varieties blooming from January to March in the four representative cherry blossom landscapes. The health grades distribution was as follow: Grade I accounted for 41.3%, Grade II for 39.1%, Grade III for 8.7%, Grade IV for 6.5%, and Grade V for 4.4%. (2) The highest marginal benefit for flake planting was observed when the flowering ratio exceeded 60% or was less than 15%. In contrast, the optimal flowering ratio for the linear cherry blossom landscape for maximum marginal benefit was over 30.0%. (3) The outcomes of the scenic beauty model revealed that the five major factors influencing the scenic beauty were the scene cleanliness (38.04%), plant color composition (25.59%), road (17.79%), plant type (12.88%) and building (2.70%). The results of this study provide valuable objective data references for the planning, design and management of cherry blossom landscapes.
{"title":"Enhancing the sustainability of cherry blossom landscapes-a case study in Fujian Province, China","authors":"Hongjun Peng, Ping Li, Rong Zhu","doi":"10.3389/ffgc.2024.1339603","DOIUrl":"https://doi.org/10.3389/ffgc.2024.1339603","url":null,"abstract":"Utilizing flowering cherries to enhance suburban landscapes and attract public recreation holds significant economic and social value. However, the current quality of the cherry landscape is compromised due to the absence of variety selection and planning in planting and design. Based on the analysis of public preference, there is significant importance in boosting the sustainability of cherry blossom landscape. However, related research in this domain still needs to be explored. This study examined four representative cherry blossom landscapes in Fujian Province to assess the landscape quality and growth of existing cherry varieties. Subsequently, an improvement model of cherry blossom landscape quality was developed based on image semantic segmentation, aiming to quantify landscape elements. The findings indicated that: (1) There were a total of 46 cherry varieties blooming from January to March in the four representative cherry blossom landscapes. The health grades distribution was as follow: Grade I accounted for 41.3%, Grade II for 39.1%, Grade III for 8.7%, Grade IV for 6.5%, and Grade V for 4.4%. (2) The highest marginal benefit for flake planting was observed when the flowering ratio exceeded 60% or was less than 15%. In contrast, the optimal flowering ratio for the linear cherry blossom landscape for maximum marginal benefit was over 30.0%. (3) The outcomes of the scenic beauty model revealed that the five major factors influencing the scenic beauty were the scene cleanliness (38.04%), plant color composition (25.59%), road (17.79%), plant type (12.88%) and building (2.70%). The results of this study provide valuable objective data references for the planning, design and management of cherry blossom landscapes.","PeriodicalId":507254,"journal":{"name":"Frontiers in Forests and Global Change","volume":"52 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139870106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-02DOI: 10.3389/ffgc.2024.1300060
Imran Md Jelas, M. A. Zulkifley, Mardina Abdullah, Martin Spraggon
Deforestation poses a critical global threat to Earth’s ecosystem and biodiversity, necessitating effective monitoring and mitigation strategies. The integration of deep learning with remote sensing offers a promising solution for precise deforestation segmentation and detection. This paper provides a comprehensive review of deep learning methodologies applied to deforestation analysis through satellite imagery. In the face of deforestation’s ecological repercussions, the need for advanced monitoring and surveillance tools becomes evident. Remote sensing, with its capacity to capture extensive spatial data, combined with deep learning’s prowess in recognizing complex patterns to enable precise deforestation assessment. Integration of these technologies through state-of-the-art models, including U-Net, DeepLab V3, ResNet, SegNet, and FCN, has enhanced the accuracy and efficiency in detecting deforestation patterns. The review underscores the pivotal role of satellite imagery in capturing spatial information and highlights the strengths of various deep learning architectures in deforestation analysis. Multiscale feature learning and fusion emerge as critical strategies enabling deep networks to comprehend contextual nuances across various scales. Additionally, attention mechanisms combat overfitting, while group and shuffle convolutions further enhance accuracy by reducing dominant filters’ contribution. These strategies collectively fortify the robustness of deep learning models in deforestation analysis. The integration of deep learning techniques into remote sensing applications serves as an excellent tool for deforestation identification and monitoring. The synergy between these fields, exemplified by the reviewed models, presents hope for preserving invaluable forests. As technology advances, insights from this review will drive the development of more accurate, efficient, and accessible deforestation detection methods, contributing to the sustainable management of the planet’s vital resources.
{"title":"Deforestation detection using deep learning-based semantic segmentation techniques: a systematic review","authors":"Imran Md Jelas, M. A. Zulkifley, Mardina Abdullah, Martin Spraggon","doi":"10.3389/ffgc.2024.1300060","DOIUrl":"https://doi.org/10.3389/ffgc.2024.1300060","url":null,"abstract":"Deforestation poses a critical global threat to Earth’s ecosystem and biodiversity, necessitating effective monitoring and mitigation strategies. The integration of deep learning with remote sensing offers a promising solution for precise deforestation segmentation and detection. This paper provides a comprehensive review of deep learning methodologies applied to deforestation analysis through satellite imagery. In the face of deforestation’s ecological repercussions, the need for advanced monitoring and surveillance tools becomes evident. Remote sensing, with its capacity to capture extensive spatial data, combined with deep learning’s prowess in recognizing complex patterns to enable precise deforestation assessment. Integration of these technologies through state-of-the-art models, including U-Net, DeepLab V3, ResNet, SegNet, and FCN, has enhanced the accuracy and efficiency in detecting deforestation patterns. The review underscores the pivotal role of satellite imagery in capturing spatial information and highlights the strengths of various deep learning architectures in deforestation analysis. Multiscale feature learning and fusion emerge as critical strategies enabling deep networks to comprehend contextual nuances across various scales. Additionally, attention mechanisms combat overfitting, while group and shuffle convolutions further enhance accuracy by reducing dominant filters’ contribution. These strategies collectively fortify the robustness of deep learning models in deforestation analysis. The integration of deep learning techniques into remote sensing applications serves as an excellent tool for deforestation identification and monitoring. The synergy between these fields, exemplified by the reviewed models, presents hope for preserving invaluable forests. As technology advances, insights from this review will drive the development of more accurate, efficient, and accessible deforestation detection methods, contributing to the sustainable management of the planet’s vital resources.","PeriodicalId":507254,"journal":{"name":"Frontiers in Forests and Global Change","volume":"61 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139810832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-02DOI: 10.3389/ffgc.2024.1301086
Farkhanda Naz, Muhammad Arif, Tan Xue, Changxiao Li
River ecosystem biodiversity and biogeochemical processes are shaped largely by riverside vegetation and soil. Moreover, river ecosystems provide ecological services influenced by the surrounding vegetation and soil interactions. However, the mechanisms by which artificially remediated plants (ARPs) and riparian soil interact to provide these benefits are still unclear among various ARPs. This study fills this gap and examines the impact of ARPs along the riparian zones of Three Gorges Dam (TGD) in Chongqing City, China. We sampled four varieties of ARPs from the Ruxi River Basin in the TGD. These varieties included Cynodon dactylon, Hemarthria altissima, Taxodium disticum, and Salix mastudana. Our results indicated substantial changes in soil physicochemical parameters. Comparably, T. distigum contains significantly higher soil chemical contents. Interestingly, principal component analysis explained almost 100% of the variance for all plant species in this study. Moreover, different vegetation types and soil chemical properties were positively correlated using Pearson correlation analysis (p < 0.05). Furthermore, all plant species exhibited strong negative correlations with physical characteristics (up to r = −1.00). Specifically, these mechanisms explain the interactions between ARPs and soil from riparian areas in the TGD. Hence, this study may facilitate ecological restoration and land management in degraded riparian areas.
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