Long-term straw return is an important carbon source for improving soil organic carbon(SOC) stocks in croplands, and straw removal through burning is also a common practice in open fields in South China. However, the ...Long-term straw return is an important carbon source for improving soil organic carbon(SOC) stocks in croplands, and straw removal through burning is also a common practice in open fields in South China. However, the specific effects of long-term rice straw management on SOC fractions, the related enzyme activities and their relationships, and whether these effects differ between crop growing seasons remain unknown. Three treatments with equal nitrogen, phosphorus, and potassium nutrient inputs, including straw/ash and chemical nutrients, were established to compare the effects of straw removal(CK), straw return(SR), and straw burned return(SBR). Compared to CK, long-term SR tended to improve the yield of early season rice(P=0.057), and significantly increased total organic carbon(TOC) and microbial biomass carbon(MBC) in double-cropped rice paddies. While SBR had no effect on TOC, it decreased light fraction organic carbon(LFOC) in early rice and easily oxidizable organic carbon(EOC) in late rice, significantly increased dissolved organic carbon(DOC), and significantly decreased soil p H. These results showed that MBC was the most sensitive indicator for assessing changes of SOC in the double-cropped rice system due to long-term straw return. In addition, the different effects on SOC fraction sizes between SR and SBR were attributed to the divergent trends in most of the soil enzyme activities in the early and late rice that mainly altered DOC, while DOC was positively affected by β-xylosidase in both early and late rice. We concluded that straw return was superior to straw burned return for improving SOC fractions, but the negative effects on soil enzyme activities in late rice require further research.展开更多
Background:Full thickness burns of the chest in childhood are a devastating problem that requires challenging reconstructive options.Integra is a bilaminate artificial dermis composed of shark chondroitin 6-sulfate an...Background:Full thickness burns of the chest in childhood are a devastating problem that requires challenging reconstructive options.Integra is a bilaminate artificial dermis composed of shark chondroitin 6-sulfate and bovine collagen.The dermal matrix serves as a scaffold for fibroblasts and endothelial cells.Vascularization of the matrix begins after 2-3 weeks,and eventually,the matrix incorporates with the tissue to create a new dermis.The main advantage of the Integra is that the neodermis is of the same quality as a native dermis.Case presentation:In this case report,we present post-burn breast reconstruction of a 12-year-old girl using Integra,with a long follow-up of 7 years.To the best of our knowledge,there is no published follow-up of breast development after reconstruction with Integra from its beginning point at the age of puberty until after the growing process has terminated.Conclusions:Integra is a reliable reconstructive tool for burned breast.If done before puberty,it can help in getting normal developing tissue with satisfying esthetic results of size,shape and symmetry.展开更多
In Côte d’Ivoire, the recurring and unregulated use of bushfires, which cause ecological damage, presents a pressing concern for the custodians of protected areas. This study aims to enhance our comprehension of...In Côte d’Ivoire, the recurring and unregulated use of bushfires, which cause ecological damage, presents a pressing concern for the custodians of protected areas. This study aims to enhance our comprehension of the dynamics of burnt areas within the Abokouamékro Wildlife Reserve (AWR) by employing the analysis of spectral indices derived from satellite imagery. The research methodology began with the calculation of mean indices and their corresponding spectral sub-indices, including NDVI, SAVI, NDWI, NDMI, BAI, NBR, TCW, TCG, and TCB, utilizing data from the Sentinel-2A satellite image dated January 17, 2022. Subsequently, a fuzzy classification model was applied to these various indices and sub-indices, guided by the degree of membership α, with the goal of effectively distinguishing between burned and unburned areas. Following the classification, the accuracies of the classified indices and sub-indices were validated using the coordinates of 100 data points collected within the AWR through GPS technology. The results revealed that the overall accuracy of all indices and sub-indices declines as the degree of membership α decreases from 1 to 0. Among the mean spectral indices, NDVI-mean, SAVI-mean, NDMI-mean exhibited the highest overall accuracies, achieving 97%, 95%, and 90%, respectively. These results closely mirrored those obtained by sub-indices using band 8 (NDVI-B8, SAVI-B8, and NDMI-B8), which yield respective overall accuracies of 93%, 92%, and 89%. At a degree of membership α = 1, the estimated burned areas for the most effective indices encompassed 2144.38 hectares for NDVI-mean, 1932.14 hectares for mean SAVI-mean, and 4947.13 hectares for mean NDMI-mean. A prospective approach involving the amalgamation of these three indices could have the potential to yield improved outcomes. This study could be a substantial contribution to the discrimination of bushfires in Côte d’Ivoire.展开更多
Monthly projections of maximum temperature,relative humidity,precipitation,and wind speed were made based on the model of HadCM3 and the climatic change scenarios of IPCC SRES A2a and B2a for the future scenario perio...Monthly projections of maximum temperature,relative humidity,precipitation,and wind speed were made based on the model of HadCM3 and the climatic change scenarios of IPCC SRES A2a and B2a for the future scenario periods of 2010–2039（referred to as 2020s）,2040–2069（referred to as 2050s）,and 2070–2099（referred to as 2080s）.The period 1961–1990 was chosen as the baseline period.The observed and projected weather data were downscaled using delta change methods and historical relationships between weather data,area burned,and the seasonal severity rating（SSR） code of the Canadian Fire Weather Index System were examined.The variations of area burned as influenced by climate change were assessed quantitative and qualitative for the study region,assuming that the fire regimes had the similar responses to the warming climate as during the 20th century.Our results indicated that a linear regression relationship existing between the historical area burned and the mean SSR values with regression coefficient in the significant range of 0.16 to 0.61.It was evident that the increased SSR values could result in more area burned;the area burned in the study region would have an increasing pattern during the 21st century under scenarios A2a and B2a scenarios and the area burned would be doubled.Also,the future area burned would have a strong seasonal pattern that more fires would occur in summer and autumn fire season,especially in summer.The area burned in summer fire season would increase by 1.5 times compared to that in the baseline period in 2080s under A2a scenarios.展开更多
The Sentinel-2 satellites are providing an unparalleled wealth of high-resolution remotely sensed information with a short revisit cycle, which is ideal for mapping burned areas both accurately and timely. This paper ...The Sentinel-2 satellites are providing an unparalleled wealth of high-resolution remotely sensed information with a short revisit cycle, which is ideal for mapping burned areas both accurately and timely. This paper proposes an automated methodology for mapping burn scars using pairs of Sentinel-2 imagery, exploiting the state-of-the-art eXtreme Gradient Boosting (XGB) machine learning framework. A large database of 64 reference wildfire perimeters in Greece from 2016 to 2019 is used to train the classifier. An empirical methodology for appropriately sampling the training patterns from this database is formulated, which guarantees the effectiveness of the approach and its computational efficiency. A difference (pre-fire minus post-fire) spectral index is used for this purpose, upon which we appropriately identify the clear and fuzzy value ranges. To reduce the data volume, a super-pixel segmentation of the images is also employed, implemented via the QuickShift algorithm. The cross-validation results showcase the effectiveness of the proposed algorithm, with the average commission and omission errors being 9% and 2%, respectively, and the average Matthews correlation coefficient (MCC) equal to 0.93.展开更多
Burned area mapping is an essential step in the forest fire research to investigate the relationship between forest fire and cli- mate change and the effect of forest fire on carbon budgets. This study proposed an alg...Burned area mapping is an essential step in the forest fire research to investigate the relationship between forest fire and cli- mate change and the effect of forest fire on carbon budgets. This study proposed an algorithm to map forest fire burned area using the Moderate-Resolution Imaging Spectroradiameter （MODIS） time series data in Heilongjiang Province, China. The algorithm is divided into two steps： Firstly, the ＇core＇ pixels were extracted to represent the most possible burned pixels based on the comparison of the tem- poral change of Global Environmental Monitoring Index （GEMI）, Burned Area Index （BAI） and MODIS active fire products between pre- and post-fires. Secondly, a 15-km distance was set to extract the entire burned areas near the ＇core＇ pixels as more relaxed conditions were used to identify the fire pixels for reducing the omission error as much as possible. The algorithm comprehensively considered the thermal characteristics and the spectral change between pre- and post-fires, which are represented by the MODIS fire products and the spectral index, respectively. Tahe, Mohe and Huma counties of Heilongjiang Province, China were chosen as the study area for burned area mapping and a time series of burned maps were produced from 2000 to 2011. The results show that the algorithm can extract burned areas more accurately with the hiehest accuracy of 96.61%.展开更多
The burning of crop residues in fields is a significant global biomass burning activity which is a key element of the terrestrial carbon cycle,and an important source of atmospheric trace gasses and aerosols.Accurate ...The burning of crop residues in fields is a significant global biomass burning activity which is a key element of the terrestrial carbon cycle,and an important source of atmospheric trace gasses and aerosols.Accurate estimation of cropland burned area is both crucial and challenging,especially for the small and fragmented burned scars in China.Here we developed an automated burned area mapping algorithm that was implemented using Sentinel-2 Multi Spectral Instrument(MSI)data and its effectiveness was tested taking Songnen Plain,Northeast China as a case using satellite image of 2020.We employed a logistic regression method for integrating multiple spectral data into a synthetic indicator,and compared the results with manually interpreted burned area reference maps and the Moderate-Resolution Imaging Spectroradiometer(MODIS)MCD64A1 burned area product.The overall accuracy of the single variable logistic regression was 77.38%to 86.90%and 73.47%to 97.14%for the 52TCQ and 51TYM cases,respectively.In comparison,the accuracy of the burned area map was improved to 87.14%and 98.33%for the 52TCQ and 51TYM cases,respectively by multiple variable logistic regression of Sentind-2 images.The balance of omission error and commission error was also improved.The integration of multiple spectral data combined with a logistic regression method proves to be effective for burned area detection,offering a highly automated process with an automatic threshold determination mechanism.This method exhibits excellent extensibility and flexibility taking the image tile as the operating unit.It is suitable for burned area detection at a regional scale and can also be implemented with other satellite data.展开更多
The restoration of forest landscape has drawn much attention since thecatastrophic fire took place on the northern slope of Great Xing'an Mountains in 1987. Forest canopydensity, which has close relation to forest...The restoration of forest landscape has drawn much attention since thecatastrophic fire took place on the northern slope of Great Xing'an Mountains in 1987. Forest canopydensity, which has close relation to forest productivity, was selected as a key factor to find howmuch the forest quality was changed 13 years after fire, and how fire severity, regeneration way andterrain factors influenced the restoration of forest canopy density, based on forest inventory datain China, and using Kendall Bivariate Correlation Analysis, and Distances Correlation Analysis. Theresults showed that fire severity which was inversely correlated with forest canopy density gradewas an initial factor among all that selected. Regeneration way which did not remarkably affectforest canopy density restoration in short period, may shorten the cycle of forest succession andpromote the forest productivity of conophorium in the future. Among the three terrain factors, theeffect of slope was the strongest, the position on slope was the second and the aspect was the last.展开更多
Daxing抋n Mountains was one of the most important forest areas in China, but it was also an area which was prone to suffering forest fire. The catastrophic forest fire that occurred in Daxing抋n Mountains on May 6, 19...Daxing抋n Mountains was one of the most important forest areas in China, but it was also an area which was prone to suffering forest fire. The catastrophic forest fire that occurred in Daxing抋n Mountains on May 6, 1987 devastated more than 1.33?06 hm2 of natural forests, which leaded to the formation of some mosaic areas with different burn intensities. Two forest farms of Tuqiang Forest Bureau (124?5-122?8E, 53?4-52?5N) were chosen as a typical area to analyze the post-fire landscape change by drawing and comparing the two digital forest stand maps of 1987 and 2000. The landscape lands of forest were classi-fied into 12 types: coniferous forest, broadleaf forest, needle-broadleaf mixed forest, shrub, nursery, harvested area, burned blanks, agricultural land, swamp, water, built-up, grass. The results showed that: 1) The burned blanks was almost restored, some of them mainly converted into broadleaf forest land during the process of natural restoration, and coniferous forest land by the artificial re-forestation, and the others almost changed into swamp or grass land; 2) The proportion of forest area increased from 47.6% in 1987 to 81.3% in 2002. Therefore, a few management countermeasures, such as the enhancing peoples consciousness of fire-proofing and constructing species diversity, were put forward for forest sustainable development.展开更多
基金supported by the National Key Research and Development Program of China (2017YFD0301601)the China Postdoctoral Science Foundation (2016M600512)+1 种基金the Open Project Program of State Key Laboratory of Rice Biology, Ministry of Science and Technology, China (20190401)the Jiangxi Province Postdoctoral Research Project Preferential Grant, China (2017KY16)。
文摘Long-term straw return is an important carbon source for improving soil organic carbon(SOC) stocks in croplands, and straw removal through burning is also a common practice in open fields in South China. However, the specific effects of long-term rice straw management on SOC fractions, the related enzyme activities and their relationships, and whether these effects differ between crop growing seasons remain unknown. Three treatments with equal nitrogen, phosphorus, and potassium nutrient inputs, including straw/ash and chemical nutrients, were established to compare the effects of straw removal(CK), straw return(SR), and straw burned return(SBR). Compared to CK, long-term SR tended to improve the yield of early season rice(P=0.057), and significantly increased total organic carbon(TOC) and microbial biomass carbon(MBC) in double-cropped rice paddies. While SBR had no effect on TOC, it decreased light fraction organic carbon(LFOC) in early rice and easily oxidizable organic carbon(EOC) in late rice, significantly increased dissolved organic carbon(DOC), and significantly decreased soil p H. These results showed that MBC was the most sensitive indicator for assessing changes of SOC in the double-cropped rice system due to long-term straw return. In addition, the different effects on SOC fraction sizes between SR and SBR were attributed to the divergent trends in most of the soil enzyme activities in the early and late rice that mainly altered DOC, while DOC was positively affected by β-xylosidase in both early and late rice. We concluded that straw return was superior to straw burned return for improving SOC fractions, but the negative effects on soil enzyme activities in late rice require further research.
文摘Background:Full thickness burns of the chest in childhood are a devastating problem that requires challenging reconstructive options.Integra is a bilaminate artificial dermis composed of shark chondroitin 6-sulfate and bovine collagen.The dermal matrix serves as a scaffold for fibroblasts and endothelial cells.Vascularization of the matrix begins after 2-3 weeks,and eventually,the matrix incorporates with the tissue to create a new dermis.The main advantage of the Integra is that the neodermis is of the same quality as a native dermis.Case presentation:In this case report,we present post-burn breast reconstruction of a 12-year-old girl using Integra,with a long follow-up of 7 years.To the best of our knowledge,there is no published follow-up of breast development after reconstruction with Integra from its beginning point at the age of puberty until after the growing process has terminated.Conclusions:Integra is a reliable reconstructive tool for burned breast.If done before puberty,it can help in getting normal developing tissue with satisfying esthetic results of size,shape and symmetry.
文摘In Côte d’Ivoire, the recurring and unregulated use of bushfires, which cause ecological damage, presents a pressing concern for the custodians of protected areas. This study aims to enhance our comprehension of the dynamics of burnt areas within the Abokouamékro Wildlife Reserve (AWR) by employing the analysis of spectral indices derived from satellite imagery. The research methodology began with the calculation of mean indices and their corresponding spectral sub-indices, including NDVI, SAVI, NDWI, NDMI, BAI, NBR, TCW, TCG, and TCB, utilizing data from the Sentinel-2A satellite image dated January 17, 2022. Subsequently, a fuzzy classification model was applied to these various indices and sub-indices, guided by the degree of membership α, with the goal of effectively distinguishing between burned and unburned areas. Following the classification, the accuracies of the classified indices and sub-indices were validated using the coordinates of 100 data points collected within the AWR through GPS technology. The results revealed that the overall accuracy of all indices and sub-indices declines as the degree of membership α decreases from 1 to 0. Among the mean spectral indices, NDVI-mean, SAVI-mean, NDMI-mean exhibited the highest overall accuracies, achieving 97%, 95%, and 90%, respectively. These results closely mirrored those obtained by sub-indices using band 8 (NDVI-B8, SAVI-B8, and NDMI-B8), which yield respective overall accuracies of 93%, 92%, and 89%. At a degree of membership α = 1, the estimated burned areas for the most effective indices encompassed 2144.38 hectares for NDVI-mean, 1932.14 hectares for mean SAVI-mean, and 4947.13 hectares for mean NDMI-mean. A prospective approach involving the amalgamation of these three indices could have the potential to yield improved outcomes. This study could be a substantial contribution to the discrimination of bushfires in Côte d’Ivoire.
基金supported by the "Eleventh Five-Year" National Science and Technology Support Project (2006BAD23B04)National Forestry Public Benefit Research Founda-tion (No200804002)the Youth Foundation of Northeast Forestry University (No09051)
文摘Monthly projections of maximum temperature,relative humidity,precipitation,and wind speed were made based on the model of HadCM3 and the climatic change scenarios of IPCC SRES A2a and B2a for the future scenario periods of 2010–2039（referred to as 2020s）,2040–2069（referred to as 2050s）,and 2070–2099（referred to as 2080s）.The period 1961–1990 was chosen as the baseline period.The observed and projected weather data were downscaled using delta change methods and historical relationships between weather data,area burned,and the seasonal severity rating（SSR） code of the Canadian Fire Weather Index System were examined.The variations of area burned as influenced by climate change were assessed quantitative and qualitative for the study region,assuming that the fire regimes had the similar responses to the warming climate as during the 20th century.Our results indicated that a linear regression relationship existing between the historical area burned and the mean SSR values with regression coefficient in the significant range of 0.16 to 0.61.It was evident that the increased SSR values could result in more area burned;the area burned in the study region would have an increasing pattern during the 21st century under scenarios A2a and B2a scenarios and the area burned would be doubled.Also,the future area burned would have a strong seasonal pattern that more fires would occur in summer and autumn fire season,especially in summer.The area burned in summer fire season would increase by 1.5 times compared to that in the baseline period in 2080s under A2a scenarios.
文摘The Sentinel-2 satellites are providing an unparalleled wealth of high-resolution remotely sensed information with a short revisit cycle, which is ideal for mapping burned areas both accurately and timely. This paper proposes an automated methodology for mapping burn scars using pairs of Sentinel-2 imagery, exploiting the state-of-the-art eXtreme Gradient Boosting (XGB) machine learning framework. A large database of 64 reference wildfire perimeters in Greece from 2016 to 2019 is used to train the classifier. An empirical methodology for appropriately sampling the training patterns from this database is formulated, which guarantees the effectiveness of the approach and its computational efficiency. A difference (pre-fire minus post-fire) spectral index is used for this purpose, upon which we appropriately identify the clear and fuzzy value ranges. To reduce the data volume, a super-pixel segmentation of the images is also employed, implemented via the QuickShift algorithm. The cross-validation results showcase the effectiveness of the proposed algorithm, with the average commission and omission errors being 9% and 2%, respectively, and the average Matthews correlation coefficient (MCC) equal to 0.93.
基金Under the auspices of Strategic Pilot Science and Technology Projects of Chinese Academic Sciences(No.XDA05090310)
文摘Burned area mapping is an essential step in the forest fire research to investigate the relationship between forest fire and cli- mate change and the effect of forest fire on carbon budgets. This study proposed an algorithm to map forest fire burned area using the Moderate-Resolution Imaging Spectroradiameter （MODIS） time series data in Heilongjiang Province, China. The algorithm is divided into two steps： Firstly, the ＇core＇ pixels were extracted to represent the most possible burned pixels based on the comparison of the tem- poral change of Global Environmental Monitoring Index （GEMI）, Burned Area Index （BAI） and MODIS active fire products between pre- and post-fires. Secondly, a 15-km distance was set to extract the entire burned areas near the ＇core＇ pixels as more relaxed conditions were used to identify the fire pixels for reducing the omission error as much as possible. The algorithm comprehensively considered the thermal characteristics and the spectral change between pre- and post-fires, which are represented by the MODIS fire products and the spectral index, respectively. Tahe, Mohe and Huma counties of Heilongjiang Province, China were chosen as the study area for burned area mapping and a time series of burned maps were produced from 2000 to 2011. The results show that the algorithm can extract burned areas more accurately with the hiehest accuracy of 96.61%.
基金Under the auspices of National Natural Science Foundation of China(No.42101414)Natural Science Found for Outstanding Young Scholars in Jilin Province(No.20230508106RC)。
文摘The burning of crop residues in fields is a significant global biomass burning activity which is a key element of the terrestrial carbon cycle,and an important source of atmospheric trace gasses and aerosols.Accurate estimation of cropland burned area is both crucial and challenging,especially for the small and fragmented burned scars in China.Here we developed an automated burned area mapping algorithm that was implemented using Sentinel-2 Multi Spectral Instrument(MSI)data and its effectiveness was tested taking Songnen Plain,Northeast China as a case using satellite image of 2020.We employed a logistic regression method for integrating multiple spectral data into a synthetic indicator,and compared the results with manually interpreted burned area reference maps and the Moderate-Resolution Imaging Spectroradiometer(MODIS)MCD64A1 burned area product.The overall accuracy of the single variable logistic regression was 77.38%to 86.90%and 73.47%to 97.14%for the 52TCQ and 51TYM cases,respectively.In comparison,the accuracy of the burned area map was improved to 87.14%and 98.33%for the 52TCQ and 51TYM cases,respectively by multiple variable logistic regression of Sentind-2 images.The balance of omission error and commission error was also improved.The integration of multiple spectral data combined with a logistic regression method proves to be effective for burned area detection,offering a highly automated process with an automatic threshold determination mechanism.This method exhibits excellent extensibility and flexibility taking the image tile as the operating unit.It is suitable for burned area detection at a regional scale and can also be implemented with other satellite data.
基金This paper was supported by the National Natural Science Foundation of China (No. 30270225, 40331008)
文摘The restoration of forest landscape has drawn much attention since thecatastrophic fire took place on the northern slope of Great Xing'an Mountains in 1987. Forest canopydensity, which has close relation to forest productivity, was selected as a key factor to find howmuch the forest quality was changed 13 years after fire, and how fire severity, regeneration way andterrain factors influenced the restoration of forest canopy density, based on forest inventory datain China, and using Kendall Bivariate Correlation Analysis, and Distances Correlation Analysis. Theresults showed that fire severity which was inversely correlated with forest canopy density gradewas an initial factor among all that selected. Regeneration way which did not remarkably affectforest canopy density restoration in short period, may shorten the cycle of forest succession andpromote the forest productivity of conophorium in the future. Among the three terrain factors, theeffect of slope was the strongest, the position on slope was the second and the aspect was the last.
基金Under the auspices of the National Science Foundation of China (No. 30270225 40331008) and the Chinese Academy of Sciences (SCXZY0102).
文摘Daxing抋n Mountains was one of the most important forest areas in China, but it was also an area which was prone to suffering forest fire. The catastrophic forest fire that occurred in Daxing抋n Mountains on May 6, 1987 devastated more than 1.33?06 hm2 of natural forests, which leaded to the formation of some mosaic areas with different burn intensities. Two forest farms of Tuqiang Forest Bureau (124?5-122?8E, 53?4-52?5N) were chosen as a typical area to analyze the post-fire landscape change by drawing and comparing the two digital forest stand maps of 1987 and 2000. The landscape lands of forest were classi-fied into 12 types: coniferous forest, broadleaf forest, needle-broadleaf mixed forest, shrub, nursery, harvested area, burned blanks, agricultural land, swamp, water, built-up, grass. The results showed that: 1) The burned blanks was almost restored, some of them mainly converted into broadleaf forest land during the process of natural restoration, and coniferous forest land by the artificial re-forestation, and the others almost changed into swamp or grass land; 2) The proportion of forest area increased from 47.6% in 1987 to 81.3% in 2002. Therefore, a few management countermeasures, such as the enhancing peoples consciousness of fire-proofing and constructing species diversity, were put forward for forest sustainable development.
