Yıl 2022,
, 211 - 222, 20.07.2022
Mst. Mahbuba Khatun
,
Debajani Chakraborty
,
Ifterkharul Alam
Kaynakça
- ARSET Advanced NDVI Webinar Series (2020). Winter 2016, Session 3, MODIS NDVI Time Series. Available online: accessed on November 25, 2020, Retrieved from https://appliedsciences.nasa.gov/sites/default/files/202011/ndvipart3exercise.pdf.
- Becker-Reshef I, Justice C, Sullivan M, Vermote E, Tucker C, Anyamba A, Small J, Pak E, Masuoka E, Schmaltz J, Hansen M, Pittman K, Birkett C, Williams D, Reynolds C & Doorn B (2010). Monitoring Global Croplands with Coarse Resolution Earth Observations: The Global Agriculture Monitoring (GLAM) Project. Remote Sensing, 2(6), 1589–1609.
- Cai Z & Ofterdinger U (2016). Analysis of groundwater-level response to rainfall and estimation of annual recharge in fractured hard rock aquifers, NW Ireland. Journal of Hydrology, 535, 71-84.
- Camberlin P, Martiny N, Philippon N & Richard Y (2007). Determinants of the interannual relationships between remote sensed photosynthetic activity and rainfall in tropical Africa. Remote Sensing of Environment, 106(2), 199–216.
- Chu H, Venevsky S, Wu C & Wang M (2019). NDVI-based vegetation dynamics and its response to climate changes at Amur-Heilongjiang River Basin from 1982 to 2015. Science of the Total Environment, 650, 2051–2062.
- Davenport M L & Nicholson S E (2007). On the relation between rainfall and the normalized difference vegetation index for diverse vegetation types in east Africa. International Journal of Remote Sensing, 14(12), 2369–2389.
- Davis J C (2002). Statistics and Data Analysis in Geology. John Wiley & Sons, Inc., New York, Third Edition, ISBN: 978-0-471-17275-8.
- Delbart N, Kergoat L, Toan T L, Lhermitte J & Picard G (2005). Determination of phenological dates in boreal regions using normalized difference water index. Remote Sensing of Environment, 97(1), 26– 38.
- Eastman J R, Sangermano F, Machado E A, Rogan J & Anyamba A (2013). Global trends in seasonality of normalized difference vegetation index (NDVI), 1982–2011. Remote Sensing, 5(10), 4799–4818.
- Exceluser, 2020: Accessed on 25-6-2020, Retrieved from https://exceluser.com/1069/.
- Feng X, Fu B, Piao S, Wang S, Ciais P, Zeng Z, Lü Y, Zeng Y, Li Y, Jiang X & Wu B (2016). Revegetation in China’s Loess Plateau is approaching sustainable water resource limits. Nature Climate Change, 6, 1019–1022.
- GLAM, 2020: Accessed on 25-6-2020, Retrieved from https://glam1.gsfc.nasa.gov/.
- Gu Y, Brown J F, Verdin J P & Wardlow B (2007). A five-year analysis of MODIS NDVI and NDWI for grasslanddrought assessment over the central Great Plains of the United States. Geophysical ResearchLetters, 34(6).
- Gu Y, Hunt E, Wardlow B, Basara J B, Brown J F & Verdin J P (2008). Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data. Geophysical ResearchLetters, 35(22).
- Islam M N & Al-Amin M (2019). Life behind leaves: Capability, poverty and social vulnerability of tea garden workers in Bangladesh. Labor History, 60(5), 571–587.
- Jackson T J, Chen D, Cosh M, Li F, Anderson M, Walthall C, Doriaswamy P & Hunt E R (2004). Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans. Remote Sensing of Environment, 92(4), 475– 482.
- Jiang C & Wang F (2016). Environmental Change in the Agro-Pastoral Transitional Zone, Northern China: Patterns, Drivers, and Implications. International Journal of Environmental Research and Public Health, 13, 165.
- Kabir M H, Hasan N, Rahman M M, Rahman M A,Khan J A, Hoque N T, Bhuiyan M R Q, Mou S M, Jahan R &Rahmatullah M (2014). A survey of medicinal plants used by the Deb barma clan of the Tripura tribe of Moulvibazar district, Bangladesh. Journal of Ethnobiology and Ethnomedicine, 10(19).
- Li C, Wang J, Hu R, Yin S, Bao Y & Ayal D Y (2018). Relationship between vegetation change and extreme climate indices on the Inner Mongolia Plateau, China, from 1982 to 2013. Ecological Indicators, 89, 101–109.
- Li Y, Xie Z, Qin Y & Zheng Z (2019). Estimating Relations of Vegetation, Climate Change, and Human Activity: A Case Study in the 400 mm Annual Precipitation Fluctuation Zone, China. Remote Sensing, 11, 1159.
- Liu S L & Wang T (2012). Climate change and local adaptation strategies in the middle Inner Mongolia, northern China. Environmental Earth Sciences, 66, 1449–1458.
- Liu Y & Lei H (2015). Responses of natural vegetation dynamics to climate drivers in China from 1982 to 2011. Remote Sensing, 7(8), 10243–10268.
- Mao J, Shi X, Thornton P E, Hoffman F M, Zhu Z &Myneni R B (2013). Global Latitudinal-Asymmetric Vegetation Growth Trends and Their Driving Mechanisms: 1982- 2009. Remote Sensing, 5(3), 1484–1497.
- Meng X, Gao X, Li S & Lei J (2020). Spatial and temporal characteristics of vegetation NDVI changes and the driving forces in Mongolia during 1982–2015. Remote Sensing, 12(4), 603.
- Na L, Na R, Zhang J, Tong S, Shan Y, Ying H, Li X &Bao Y (2018). Vegetation Dynamics and Diverse Responses to Extreme Climate Events in Different Vegetation Types of Inner Mongolia. Atmosphere, 9(10), 394.
- Nemani R R, Keeling C D, Hashimoto H, Jolly W M, Piper S C, Tucker C J, Myneni R B & Running S W (2003). Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science, 300, 1560–1563.
- Patra K C (2008). Hydrology and water resources engineering. New Delhi: Narosa Publishing House, Second edition, ISBN:978-81-7319-846-5.
- Pei Z, Fang S, Yang W, Wang L, Wu M, Zhang Q, Han W &Khoi D N (2019). The Relationship between NDVI and Climate Factorsat Different Monthly Time Scales: A Case Study of Grasslands in Inner Mongolia, China (1982–2015). Sustainability, 11(24), 7243.
- Piao S, Tan J, Chen A, Fu Y H, Ciais P, Liu Q, Janssens I A, Vicca S, Zeng Z, Jeong S J, Li Y, Myneni R B, Peng S, Shen M &Penuelas J (2015). Leaf onset in the northern hemisphere triggered by daytime temperature. Nature Communications, 6, 6911.
- Piao S, Wang X, Ciais P, Zhu B, Wang T & Liu J (2011). Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006. Global Change Biology, 17(10), 3228–3239.
- Posavec K, Vukojević P, Ratkaj M & Bedeniković T (2017). Cross-correlation Modelling of Surface Water–Groundwater Interaction Using the Excel Spreadsheet Application. The Mining-Geology-Petroleum Engineering Bulletin, 25-32.
- Rahman M Z, Hossain M S, Kamal A S M M, Siddiqua S, Mustahid F & Farazi A H (2018). Seismic site characterization for Moulvibazar town, Bangladesh. Bulletin of Engineering Geology and the Environment, 77, 1451–1471.
- Rasmus F & Simon R P (2012). Evaluation of Earth Observation based global long term vegetation trends—Comparing GIMMS and MODIS global NDVI time series. Remote Sensing of Environment, 119, 131–147.
- Salmi T, Maatta A, Anttila P, Ruoho-Airola T & Amnell T (2002). Detecting Trends of Annual Values of Atmospheric Pollutants by the Mann-Kendall Test and Sen’s Slope Estimates -The Excel Template Application MAKESENS. User Manual, Air Quality, Finnish Meteorological Institute, Helsinki, Finland. Accessed on 25-9-2020, Retrieved from https://en.ilmatieteenlaitos.fi/documents/30106/335634754/MAKESENS Manual_2002.pdf/25bbe115-7f7e-4de3-97d8-5a96ac88499f.
- Shen X J, Liu B H & Zhou D W (2016). Using GIMMS NDVI time series to estimate the impacts of grassland vegetation cover on surface air temperatures in the temperate grassland region of China. Remote Sensing Letters, 7, 229–238.
- Shilong P, Wang X, Ciais P, ZHU B, Wang T & Liu J (2011). Changes in satellite-derived vegetation growth trend in temperate and Boreal Eurasia from 1982 to 2006. Global Change Biology, 17(10), 3228–3239.
- Shi X, Wang W & Shi W (2016). Progress on quantitative assessment of the impacts of climate change and human activities on cropland change. Journal of Geophysical Sciences, 26, 339–354.
- Sun H, Wang J, Xiong J, Bian J, Jin H, Cheng W & Li A (2021). Vegetation Change and Its Response to Climate Change in Yunnan Province, China. Advances in Meteorology, 2021, 1-20.
- Sun W Y, Song X Y, Mu X M, Gao P, Wang F & Zhao G J (2015). Spatiotemporal vegetation cover variations associated with climate change and ecological restoration in the Loess Plateau. Agricultural and Forest Meteorology, 209, 87–99.
- Tucker C J (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), 127–150.
- USDA FAS (2020). GLAM-Global Agricultural Monitoring. Accessed on 21-9-2020, Retrieved from http://www.pecad.fas.usda.gov/glam.cfm (accessed on November 21, 2020).
- Wan S, Hui D, Wallace L & Luo Y (2005). Direct and indirect effects of experimental warming on ecosystem carbon processes in a tallgrass prairie. Global Biogeochemical, Cycles, 19(2), GB2014, doi:10.1029/2004GB002315.
- Wang X, Chen F H, Dong Z & Xia D (2005). Evolution of the southern Mu Us Desert in north China over the past 50 years: An analysis using proxies of human activity and climate parameters. Land Degradation & Development, 16(4), 351–366.
- Wang Y, Shen X, Jiang M & Lu X (2020). Vegetation change and its response to climate change between 2000 and 2016 in marshes of the Songnen plain, northeast China. Sustainability, 12(9), 3569.
- Wikipedia, 2020: Moulvibazar. Accessed on 25-6-2020, Retrieved from https://en.wikipedia.org/wiki/Moulvibazar.
- Wu D, Zhao X, Liang S, Zhou T, Huang K, Tang B & Zhao W (2015). Time-lag effects of global vegetation responses to climate change. Global Change Biology, 21(9), 3520–3531.
- Xu Y, Yang J & Chen Y (2015). NDVI-based vegetation responses to climate change in an arid area of China. Theoretical and Applied Climatology, 126, 213–222.
- Yu X, Ding S, Zou Y, Xue Z, Lyu X & Wang G (2018). Review of rapid transformation of floodplain wetlands in northeast China: roles of human development and global environmental change. Chinese Geographical Science, 28(4), 654–664.
- Zhang Y, Gao J, Liu L, Wang Z, Ding M & Yang X (2013). NDVI-based vegetation changes and their responses to climate change from 1982 to 2011: a case study in the Koshi river basin in the middle Himalayas. Global and Planetary Change, 108, 139–148.
- Zhao X, Hu H, Shen H, Zhou D, Zhou L, Myneni R B & Fang J (2015). Satellite-indicated long-term vegetation changes and their drivers on the Mongolian Plateau. Landscape Ecology, 30, 1599–1611.
Clarifying the impact of climatic parameters on vegetation in Moulvibazar district
Yıl 2022,
, 211 - 222, 20.07.2022
Mst. Mahbuba Khatun
,
Debajani Chakraborty
,
Ifterkharul Alam
Öz
In this research, the temporal trends of vegetation from 2000 to 2019 as well as meteorological variables contribution to vegetation change were investigated using the GLAM NDVI, rainfall and temperature data. The MAKESENS revealed that the vegetation growth rate was slow, particularly on a yearly time scale. On the other hand, the rainfall and temperature had a major impact on vegetation growth on a monthly-time scale with a time lag. The lagged effect of rainfall and temperature on vegetation was shown to be a promotion (based on cross-correlation analysis). There was high value of r (0.804) between vegetation and rainfall for a certain lag period, which was significant (P ≤ 0.05) as per the cross-correlation. Rainfall had a 4-month lag effect on vegetation development, while temperature had a 5 (r = 0.74), - 2 (r = 0.84), - 3 (r = 0.68) month lag effect on vegetation growth. This study's findings revealed changes in vegetation and highlighted the importance of rainfall and temperature in regulating vegetation dynamics. Finally, this study recommended that the effect of more climatic variables on vegetation should be investigated in the context of human activities to better conserve the environment.
Kaynakça
- ARSET Advanced NDVI Webinar Series (2020). Winter 2016, Session 3, MODIS NDVI Time Series. Available online: accessed on November 25, 2020, Retrieved from https://appliedsciences.nasa.gov/sites/default/files/202011/ndvipart3exercise.pdf.
- Becker-Reshef I, Justice C, Sullivan M, Vermote E, Tucker C, Anyamba A, Small J, Pak E, Masuoka E, Schmaltz J, Hansen M, Pittman K, Birkett C, Williams D, Reynolds C & Doorn B (2010). Monitoring Global Croplands with Coarse Resolution Earth Observations: The Global Agriculture Monitoring (GLAM) Project. Remote Sensing, 2(6), 1589–1609.
- Cai Z & Ofterdinger U (2016). Analysis of groundwater-level response to rainfall and estimation of annual recharge in fractured hard rock aquifers, NW Ireland. Journal of Hydrology, 535, 71-84.
- Camberlin P, Martiny N, Philippon N & Richard Y (2007). Determinants of the interannual relationships between remote sensed photosynthetic activity and rainfall in tropical Africa. Remote Sensing of Environment, 106(2), 199–216.
- Chu H, Venevsky S, Wu C & Wang M (2019). NDVI-based vegetation dynamics and its response to climate changes at Amur-Heilongjiang River Basin from 1982 to 2015. Science of the Total Environment, 650, 2051–2062.
- Davenport M L & Nicholson S E (2007). On the relation between rainfall and the normalized difference vegetation index for diverse vegetation types in east Africa. International Journal of Remote Sensing, 14(12), 2369–2389.
- Davis J C (2002). Statistics and Data Analysis in Geology. John Wiley & Sons, Inc., New York, Third Edition, ISBN: 978-0-471-17275-8.
- Delbart N, Kergoat L, Toan T L, Lhermitte J & Picard G (2005). Determination of phenological dates in boreal regions using normalized difference water index. Remote Sensing of Environment, 97(1), 26– 38.
- Eastman J R, Sangermano F, Machado E A, Rogan J & Anyamba A (2013). Global trends in seasonality of normalized difference vegetation index (NDVI), 1982–2011. Remote Sensing, 5(10), 4799–4818.
- Exceluser, 2020: Accessed on 25-6-2020, Retrieved from https://exceluser.com/1069/.
- Feng X, Fu B, Piao S, Wang S, Ciais P, Zeng Z, Lü Y, Zeng Y, Li Y, Jiang X & Wu B (2016). Revegetation in China’s Loess Plateau is approaching sustainable water resource limits. Nature Climate Change, 6, 1019–1022.
- GLAM, 2020: Accessed on 25-6-2020, Retrieved from https://glam1.gsfc.nasa.gov/.
- Gu Y, Brown J F, Verdin J P & Wardlow B (2007). A five-year analysis of MODIS NDVI and NDWI for grasslanddrought assessment over the central Great Plains of the United States. Geophysical ResearchLetters, 34(6).
- Gu Y, Hunt E, Wardlow B, Basara J B, Brown J F & Verdin J P (2008). Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data. Geophysical ResearchLetters, 35(22).
- Islam M N & Al-Amin M (2019). Life behind leaves: Capability, poverty and social vulnerability of tea garden workers in Bangladesh. Labor History, 60(5), 571–587.
- Jackson T J, Chen D, Cosh M, Li F, Anderson M, Walthall C, Doriaswamy P & Hunt E R (2004). Vegetation water content mapping using Landsat data derived normalized difference water index for corn and soybeans. Remote Sensing of Environment, 92(4), 475– 482.
- Jiang C & Wang F (2016). Environmental Change in the Agro-Pastoral Transitional Zone, Northern China: Patterns, Drivers, and Implications. International Journal of Environmental Research and Public Health, 13, 165.
- Kabir M H, Hasan N, Rahman M M, Rahman M A,Khan J A, Hoque N T, Bhuiyan M R Q, Mou S M, Jahan R &Rahmatullah M (2014). A survey of medicinal plants used by the Deb barma clan of the Tripura tribe of Moulvibazar district, Bangladesh. Journal of Ethnobiology and Ethnomedicine, 10(19).
- Li C, Wang J, Hu R, Yin S, Bao Y & Ayal D Y (2018). Relationship between vegetation change and extreme climate indices on the Inner Mongolia Plateau, China, from 1982 to 2013. Ecological Indicators, 89, 101–109.
- Li Y, Xie Z, Qin Y & Zheng Z (2019). Estimating Relations of Vegetation, Climate Change, and Human Activity: A Case Study in the 400 mm Annual Precipitation Fluctuation Zone, China. Remote Sensing, 11, 1159.
- Liu S L & Wang T (2012). Climate change and local adaptation strategies in the middle Inner Mongolia, northern China. Environmental Earth Sciences, 66, 1449–1458.
- Liu Y & Lei H (2015). Responses of natural vegetation dynamics to climate drivers in China from 1982 to 2011. Remote Sensing, 7(8), 10243–10268.
- Mao J, Shi X, Thornton P E, Hoffman F M, Zhu Z &Myneni R B (2013). Global Latitudinal-Asymmetric Vegetation Growth Trends and Their Driving Mechanisms: 1982- 2009. Remote Sensing, 5(3), 1484–1497.
- Meng X, Gao X, Li S & Lei J (2020). Spatial and temporal characteristics of vegetation NDVI changes and the driving forces in Mongolia during 1982–2015. Remote Sensing, 12(4), 603.
- Na L, Na R, Zhang J, Tong S, Shan Y, Ying H, Li X &Bao Y (2018). Vegetation Dynamics and Diverse Responses to Extreme Climate Events in Different Vegetation Types of Inner Mongolia. Atmosphere, 9(10), 394.
- Nemani R R, Keeling C D, Hashimoto H, Jolly W M, Piper S C, Tucker C J, Myneni R B & Running S W (2003). Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science, 300, 1560–1563.
- Patra K C (2008). Hydrology and water resources engineering. New Delhi: Narosa Publishing House, Second edition, ISBN:978-81-7319-846-5.
- Pei Z, Fang S, Yang W, Wang L, Wu M, Zhang Q, Han W &Khoi D N (2019). The Relationship between NDVI and Climate Factorsat Different Monthly Time Scales: A Case Study of Grasslands in Inner Mongolia, China (1982–2015). Sustainability, 11(24), 7243.
- Piao S, Tan J, Chen A, Fu Y H, Ciais P, Liu Q, Janssens I A, Vicca S, Zeng Z, Jeong S J, Li Y, Myneni R B, Peng S, Shen M &Penuelas J (2015). Leaf onset in the northern hemisphere triggered by daytime temperature. Nature Communications, 6, 6911.
- Piao S, Wang X, Ciais P, Zhu B, Wang T & Liu J (2011). Changes in satellite-derived vegetation growth trend in temperate and boreal Eurasia from 1982 to 2006. Global Change Biology, 17(10), 3228–3239.
- Posavec K, Vukojević P, Ratkaj M & Bedeniković T (2017). Cross-correlation Modelling of Surface Water–Groundwater Interaction Using the Excel Spreadsheet Application. The Mining-Geology-Petroleum Engineering Bulletin, 25-32.
- Rahman M Z, Hossain M S, Kamal A S M M, Siddiqua S, Mustahid F & Farazi A H (2018). Seismic site characterization for Moulvibazar town, Bangladesh. Bulletin of Engineering Geology and the Environment, 77, 1451–1471.
- Rasmus F & Simon R P (2012). Evaluation of Earth Observation based global long term vegetation trends—Comparing GIMMS and MODIS global NDVI time series. Remote Sensing of Environment, 119, 131–147.
- Salmi T, Maatta A, Anttila P, Ruoho-Airola T & Amnell T (2002). Detecting Trends of Annual Values of Atmospheric Pollutants by the Mann-Kendall Test and Sen’s Slope Estimates -The Excel Template Application MAKESENS. User Manual, Air Quality, Finnish Meteorological Institute, Helsinki, Finland. Accessed on 25-9-2020, Retrieved from https://en.ilmatieteenlaitos.fi/documents/30106/335634754/MAKESENS Manual_2002.pdf/25bbe115-7f7e-4de3-97d8-5a96ac88499f.
- Shen X J, Liu B H & Zhou D W (2016). Using GIMMS NDVI time series to estimate the impacts of grassland vegetation cover on surface air temperatures in the temperate grassland region of China. Remote Sensing Letters, 7, 229–238.
- Shilong P, Wang X, Ciais P, ZHU B, Wang T & Liu J (2011). Changes in satellite-derived vegetation growth trend in temperate and Boreal Eurasia from 1982 to 2006. Global Change Biology, 17(10), 3228–3239.
- Shi X, Wang W & Shi W (2016). Progress on quantitative assessment of the impacts of climate change and human activities on cropland change. Journal of Geophysical Sciences, 26, 339–354.
- Sun H, Wang J, Xiong J, Bian J, Jin H, Cheng W & Li A (2021). Vegetation Change and Its Response to Climate Change in Yunnan Province, China. Advances in Meteorology, 2021, 1-20.
- Sun W Y, Song X Y, Mu X M, Gao P, Wang F & Zhao G J (2015). Spatiotemporal vegetation cover variations associated with climate change and ecological restoration in the Loess Plateau. Agricultural and Forest Meteorology, 209, 87–99.
- Tucker C J (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), 127–150.
- USDA FAS (2020). GLAM-Global Agricultural Monitoring. Accessed on 21-9-2020, Retrieved from http://www.pecad.fas.usda.gov/glam.cfm (accessed on November 21, 2020).
- Wan S, Hui D, Wallace L & Luo Y (2005). Direct and indirect effects of experimental warming on ecosystem carbon processes in a tallgrass prairie. Global Biogeochemical, Cycles, 19(2), GB2014, doi:10.1029/2004GB002315.
- Wang X, Chen F H, Dong Z & Xia D (2005). Evolution of the southern Mu Us Desert in north China over the past 50 years: An analysis using proxies of human activity and climate parameters. Land Degradation & Development, 16(4), 351–366.
- Wang Y, Shen X, Jiang M & Lu X (2020). Vegetation change and its response to climate change between 2000 and 2016 in marshes of the Songnen plain, northeast China. Sustainability, 12(9), 3569.
- Wikipedia, 2020: Moulvibazar. Accessed on 25-6-2020, Retrieved from https://en.wikipedia.org/wiki/Moulvibazar.
- Wu D, Zhao X, Liang S, Zhou T, Huang K, Tang B & Zhao W (2015). Time-lag effects of global vegetation responses to climate change. Global Change Biology, 21(9), 3520–3531.
- Xu Y, Yang J & Chen Y (2015). NDVI-based vegetation responses to climate change in an arid area of China. Theoretical and Applied Climatology, 126, 213–222.
- Yu X, Ding S, Zou Y, Xue Z, Lyu X & Wang G (2018). Review of rapid transformation of floodplain wetlands in northeast China: roles of human development and global environmental change. Chinese Geographical Science, 28(4), 654–664.
- Zhang Y, Gao J, Liu L, Wang Z, Ding M & Yang X (2013). NDVI-based vegetation changes and their responses to climate change from 1982 to 2011: a case study in the Koshi river basin in the middle Himalayas. Global and Planetary Change, 108, 139–148.
- Zhao X, Hu H, Shen H, Zhou D, Zhou L, Myneni R B & Fang J (2015). Satellite-indicated long-term vegetation changes and their drivers on the Mongolian Plateau. Landscape Ecology, 30, 1599–1611.