Variations of NDVI and Its Association with Rainfall and Evapotranspiration over Bangladesh

Islam, Md. Monirul; Mamun, Mainul Islam

doi:10.3329/rujse.v43i0.26160

Cited by 19 publications

(10 citation statements)

References 18 publications

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“…ese findings are consistent with studies [15][16][17][18] which suggest high correlation of evapotranspiration and normalized difference vegetation index (NDVI). e results also indicated higher values for both NDVI and evapotranspiration for daily and monthly comparison for November.…”

Section: Discussionsupporting

confidence: 92%

Mapping Evapotranspiration of Agricultural Areas in Ghana

Aidoo

Klutse

Asare

et al. 2021

The Scientific World Journal

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Climate change is having an adverse effect on the environment especially in sub-Sahara Africa, where capacity for natural resource management such as water is very low. The scope of the effect on land use types have to be estimated to inform proper remedy. A combined estimation of transpiration and evaporation from plants and soil is critical to determine annual water requirement for different land use. Evapotranspiration (ET) is a major component in the world hydrological cycle, and understanding its spatial dimensions is critical in evaluating the effects it has on regional land use. A measure of this component is challenging due to variation in rainfall and environmental changes. The mapping evapotranspiration with high resolution and internalized calibration (METRIC) method is employed to create evapotranspiration map for land use, using remotely sensed data by satellite, processed, and analyzed in ArcGIS. Normalized difference vegetation index (NDVI) was related to the availability of water for vegetation on different land use, and the results indicate a high evapotranspiration for vegetated land use with high NDVI than land use with low NDVI.

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Section: Discussionsupporting

confidence: 92%

Mapping Evapotranspiration of Agricultural Areas in Ghana

Aidoo

Klutse

Asare

et al. 2021

The Scientific World Journal

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“…SA is one of the most vulnerable regions to climate change in the world; it is home to approximately 1.7 billion people and includes three rich biodiversity hotspots: the eastern Himalayas in Nepal, northeastern India and Bhutan; the Western and Eastern Ghats of India and Sri Lanka; and the Indo-Burma hotspot in India and Myanmar [9]. Numerous studies have recognized the well-connected relationship between vegetation growth and climate in this region [10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Satellite view of seasonal greenness trends and controls in South Asia

Sarmah

Jia

Zhang

2018

Environ. Res. Lett.

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South Asia (SA) has been considered one of the most remarkable regions for changing vegetation greenness, accompanying its major expansion of agricultural activities, especially irrigated farming. The influence of the monsoon climate on the seasonal trends and anomalies of vegetation greenness is poorly understood in this area. Herein, we used the satellite-based Normalized Difference Vegetation Index (NDVI) to investigate various spatiotemporal patterns in vegetation activity during summer and winter monsoon (SM and WM) seasons and among irrigated croplands (IC), rainfed croplands (RC), and natural vegetation (NV) areas during 1982-2013. Seasonal NDVI variations with climatic factors (precipitation and temperature) and land use and cover changes (LUCC) have also been investigated. This study demonstrates that the seasonal dynamics of vegetation could improve the detailed understanding of vegetation productivity over the region. We found distinct greenness trends between two monsoon seasons and among the major land use/cover classes. Winter monsoons contributed greater variability to the overall vegetation dynamics of SA. Major greening occurred due to the increased productivity over irrigated croplands during the winter monsoon season; meanwhile, browning trends were prominent over NV areas during the same season. Maximum temperatures had been increasing tremendously during the WM season; however, the precipitation trend was not significant over SA. Both the climate variability and LUCC revealed coupled effects on the long term NDVI trends in NV areas, especially in the hilly regions, whereas anthropogenic activities (agricultural advancements) played a pivotal role in the rest of the area. Until now, advanced cultivation techniques have proven to be beneficial for the region in terms of the productivity of croplands. However, the crop productivity is at risk under climate change.

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“…Vegetation cover over Bangladesh shows spatial and temporal variations. In a recent study of vegetation variability over Bangladesh using the Moderate Resolution Imaging Spectroradiometer's (MODIS's) normalized difference vegetation index (NDVI) data, Islam and Mamun (2015) found higher NDVI in the western part and relatively lower NDVI in the eastern part. Fog and mist are common features of the weather from November to March.…”

Section: Study Areamentioning

confidence: 98%

Pattern analysis of trace gases over Bangladesh using satellite remote sensing

Islam

Mamun

Rasel

et al. 2015

International Journal of Remote Sensing

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Trace gases are important components for climate change process, and Earth's climate is sensitive to change in their atmospheric concentrations; therefore, proper assessment of trace gases is essential for ongoing global climate simulation. The spatio-temporal variations of four trace gases, namely carbon monoxide (CO), nitrogen dioxide (NO 2 ), ozone (O 3 ), and carbon dioxide (CO 2 ), over Bangladesh during the last decade are analysed using the remote-sensing data sets of the Atmospheric Infrared Sounder (AIRS) and Ozone Monitoring Instrument (OMI). Monthly, seasonal, and annual mean variations of trace gases were assessed. Higher CO, O 3 , and CO 2 concentrations show west-to-east gradient, indicating the impact of both local meteorology and emissions on variations in trace gases. On the other hand, total NO 2 concentration increases over Dhaka because of large population density, high traffic emission, larger industrial activities, and highly polluted air. The inter-annual variations of trace gases are mainly due to large-scale climatic phenomena such as El Niño and La Niña conditions. All the trace gases show strong seasonality, with higher levels during pre-monsoon season and lower levels during monsoon season, which are caused by the seasonal variations in biomass burning (BB), long-range transportation, and rainfall in South and Southeast Asia (S-SE Asia). However, O 3 concentration reveals minimum loading during winter season, associated with the reduction of O 3 formation in cold days due to insufficient heat. These findings are important to estimate regional climate variability due to trace gases.

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Variations of NDVI and Its Association with Rainfall and Evapotranspiration over Bangladesh

Cited by 19 publications

References 18 publications

Mapping Evapotranspiration of Agricultural Areas in Ghana

Mapping Evapotranspiration of Agricultural Areas in Ghana

Satellite view of seasonal greenness trends and controls in South Asia

Pattern analysis of trace gases over Bangladesh using satellite remote sensing

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