T. Tran, Mon Danh, M. Duong, Tung H. Luu, Dung Nguyen
{"title":"利用时间序列LAI-MODIS图像估算越南中部高地叶面积指数变化的长期趋势","authors":"T. Tran, Mon Danh, M. Duong, Tung H. Luu, Dung Nguyen","doi":"10.25303/1601da023029","DOIUrl":null,"url":null,"abstract":"This study examined changes in leaf area index (LAI) patterns corresponding to vegetation cover dynamics across space and time in the Vietnamese Central Highlands. We generated the mean annual LAI values during the 2002–2021 period using the MCD15A3H MODIS time-series based on the Google Earth Engine platform. Afterwards, a spatial linear regression was applied to examine spatiotemporal LAI variations in the study area. Results show that the mean LAI values between 2 and 3 covered almost all of the study area. The significant decreasing and increasing patterns in LAI trends were discovered for all provinces, but a decreasing pattern mainly distributed in Dak Nong and Gia Lai provinces. Besides, in terms of vegetation categories, an increasing LAI trend was explored in perennial croplands, while a decreasing LAI trend was found in forests and shrubs. These trends considered a conversion in land use purposes in the study area from forests to croplands over the past two decades. Additionally, the discovered information contributed to highlighting forest degradation and deforestation associated with anthropogenic activities in the region. Our study of LAI variations could assist future investigations into the affecting factors of deforestation and forest degradation and it also enables policy makers, planners and foresters to propose potential strategies for sustainable management in the future. Notably, our study shows the efficiency of the LAI MCD15A3H MODIS application for vegetation cover at a regional analysis.","PeriodicalId":50576,"journal":{"name":"Disaster Advances","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimating Long-term Trend in Leaf Area Index Variations in the Vietnamese Central Highlands using Time Series LAI MODIS Imagery\",\"authors\":\"T. Tran, Mon Danh, M. Duong, Tung H. Luu, Dung Nguyen\",\"doi\":\"10.25303/1601da023029\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study examined changes in leaf area index (LAI) patterns corresponding to vegetation cover dynamics across space and time in the Vietnamese Central Highlands. We generated the mean annual LAI values during the 2002–2021 period using the MCD15A3H MODIS time-series based on the Google Earth Engine platform. Afterwards, a spatial linear regression was applied to examine spatiotemporal LAI variations in the study area. Results show that the mean LAI values between 2 and 3 covered almost all of the study area. The significant decreasing and increasing patterns in LAI trends were discovered for all provinces, but a decreasing pattern mainly distributed in Dak Nong and Gia Lai provinces. Besides, in terms of vegetation categories, an increasing LAI trend was explored in perennial croplands, while a decreasing LAI trend was found in forests and shrubs. These trends considered a conversion in land use purposes in the study area from forests to croplands over the past two decades. Additionally, the discovered information contributed to highlighting forest degradation and deforestation associated with anthropogenic activities in the region. Our study of LAI variations could assist future investigations into the affecting factors of deforestation and forest degradation and it also enables policy makers, planners and foresters to propose potential strategies for sustainable management in the future. Notably, our study shows the efficiency of the LAI MCD15A3H MODIS application for vegetation cover at a regional analysis.\",\"PeriodicalId\":50576,\"journal\":{\"name\":\"Disaster Advances\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Disaster Advances\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25303/1601da023029\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Disaster Advances","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25303/1601da023029","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
Estimating Long-term Trend in Leaf Area Index Variations in the Vietnamese Central Highlands using Time Series LAI MODIS Imagery
This study examined changes in leaf area index (LAI) patterns corresponding to vegetation cover dynamics across space and time in the Vietnamese Central Highlands. We generated the mean annual LAI values during the 2002–2021 period using the MCD15A3H MODIS time-series based on the Google Earth Engine platform. Afterwards, a spatial linear regression was applied to examine spatiotemporal LAI variations in the study area. Results show that the mean LAI values between 2 and 3 covered almost all of the study area. The significant decreasing and increasing patterns in LAI trends were discovered for all provinces, but a decreasing pattern mainly distributed in Dak Nong and Gia Lai provinces. Besides, in terms of vegetation categories, an increasing LAI trend was explored in perennial croplands, while a decreasing LAI trend was found in forests and shrubs. These trends considered a conversion in land use purposes in the study area from forests to croplands over the past two decades. Additionally, the discovered information contributed to highlighting forest degradation and deforestation associated with anthropogenic activities in the region. Our study of LAI variations could assist future investigations into the affecting factors of deforestation and forest degradation and it also enables policy makers, planners and foresters to propose potential strategies for sustainable management in the future. Notably, our study shows the efficiency of the LAI MCD15A3H MODIS application for vegetation cover at a regional analysis.