Assessing correlation between Rainfall, normalized difference Vegetation Index (NDVI) and land surface temperature (LST) in Eastern India

Garai, Sanjoy; Khatun, Masjuda; Singh, Ronak; Sharma, Jassi; Pradhan, Minakshi; Ranjan, Ashish; Rahaman, Sk Mujibar; Khan, M. L.; Tiwari, Sharad

doi:10.1007/s42797-022-00056-2

Cited by 29 publications

(15 citation statements)

References 55 publications

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“…On the other hand, correlation between NDVI and temperature was generally negative in most parts of East Africa Figure 4(b). This is not different from the study by (Garai et al, 2022), which also demonstrated inverse correlation between NDVI and land surface temperature. This negative correlation may indicate that NDVI is sensitive to changes in temperature, with higher temperatures potentially causing stress and reduced vigour in plants.…”

Section: Correlation Analysis For Ndvi and Meteorological Parameterscontrasting

confidence: 86%

“…This study used daily NDVI dataset sourced from NOAA-07 GAC at spatial resolution of 0.05˚ by 0.05˚ (Pettorelli et al, 2011;Garai et al, 2022). For rainfall, this study acquired CHIRPS-v2 data set which is generated from satellite ground observations to build high resolution (0.05˚) gridded precipitation climatology (Harrison et al, 2022) while Temperature data was retrieved from ECMWF, which is ERA5 monthly averaged data on single levels (reference).…”

Section: Data Sourcesmentioning

confidence: 99%

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Spatio-Temporal Variability of Rainfall and Temperature and Their Effects on Pasture Variability over East Africa: Implication on the Cattle Grazing Areas

Peter,

Wen,

Matthews

et al. 2024

GEP

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Understanding the spatiotemporal variability of climatic parameters and their effects on pasture variability is vital for pasture management interventions over East Africa. The present study aims to assess the spatial-temporal variability of rainfall, temperature and Normalized Difference Vegetation Index (NDVI) (which is being used to assess pasture quality and productivity) over the region, between the period of 1982 and 2019. This study used annual mean values for rainfall, temperature and NDVI which were calculated for the period mentioned above. NDVI was derived from National Oceanic and Atmospheric Administration (NOAA) Global Area Cover (GAC) (NOAA-07-GAC) data. The rainfall data was acquired from the Climate Hazards Group Infrared Precipitation with Station (CHIRPS) while temperature is ERA5 reanalysis data sourced from the European Centre for Medium-Range Weather Forecasts (ECMWF). The study utilized the empirical orthogonal function (EOF) to identify patterns and dominant relationships between the climate variables. The correlation was calculated between rainfall, temperature and NDVI to assess the relationship among them. A non-parametric Mann-Kendall trends test was used to determine whether annual precipitation, temperature and NDVI had statistically increasing or decreasing trend. Results revealed a positive correlation between rainfall and NDVI while a negative correlation between NDVI and temperature. Positive correlation between rainfall and NDVI indicates that pasture health (quality and productivity), will improve accordingly. A negative correlation between temperature and NDVI indicates that pasture health will decrease with increase in temperature while improv-How to cite this paper:

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Section: Correlation Analysis For Ndvi and Meteorological Parameterscontrasting

confidence: 86%

Section: Data Sourcesmentioning

confidence: 99%

Spatio-Temporal Variability of Rainfall and Temperature and Their Effects on Pasture Variability over East Africa: Implication on the Cattle Grazing Areas

Peter,

Wen,

Matthews

et al. 2024

GEP

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“…1) and is surrounded by Bhutan, Nepal and Bangladesh. The study area features diverse landforms, including hills, plateaus, plains, and the Bay of Bengal coastline (Garai et al 2022). The Great Himalayan Range located in the northern portion and the Sundarbans in the southern portion of the study area are the regions of global importance.…”

Section: Study Areamentioning

confidence: 99%

Buchanania cochinchinensis (Lour.) M.R. Almedia habitat exhibited robust adaptability to diverse socioeconomic scenarios in eastern India

Garai

Mishra

Malakar

et al. 2023

Preprint

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One of the greatest challenges to ecosystems is the rapidity of climate change, and their ability to adjust swiftly will be constrained. Climate change will disrupt the ecological balances, causing species to track suitable habitats for survival. Consequently, understanding the species' response to climate change is crucial for its conservation and management, and for enhancing biodiversity through effective management. This research intends to examine the response of the vulnerable Buchanania cochinchinensis species to climate change. We modeled the potential suitable habitats of B. cochinchinensis for the present and future climatic scenario proxies based on the Shared Socioeconomic Pathways (SSP) i.e. SSP126, 245, 370 and 585. Maxent was used to simulate the potential habitats of B. cochinchinensis. The study found ~ 28313 sq km (~ 10.7% of the study area) was a potentially suitable habitat of B. cochinchinensis for the current scenario. The majority of the suitable habitat area ~ 25169 sq km occurred in the central and southern part of the study area. The future projection shows that the suitable habitat to largely increase in the range of 10.5–20% across all the SSPs, with maximum gain ~ 20% for SSP 126. The mean temperature of the wettest quarter (Bio_08) was the most influential contributing variable in limiting the distribution of B. cochinchinensis. The majority of the suitable habitat area occurred in the vegetation landscape. The study shows southward shifting of B. cochinchinensis habitat by 2050. The phytosociological research determined B. cochinchinensis as Shorea robusta's primary associate. Our research provides significant insight into the prospective distribution scenario of B. cochinchinensis habitat and its response to diverse socioeconomic scenarios, and offers a solid foundation for management of this extremely important species.

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“…The drivers of woody encroachment in African protected areas remain a topic of ongoing debate (Devine et al, 2017). Climate uctuations are thought to signi cantly in uence the dynamics of vegetation because of its effect on the biophysical processes of plants such as respiration and photosynthesis (Garai et al, 2022). In CNP, woody vegetation has considerable impacts on tourism by reducing primary and secondary production in the ecosystem by shading and competing with other plants for light, water and food.…”

Section: Introductionmentioning

confidence: 99%

Examining spatiotemporal land cover dynamics in relation to rainfall and temperature: 1992-2022. Case of Chizarira National Park, Zimbabwe

Jeche,

Mwedzi

2023

Preprint

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Understanding the spatiotemporal dynamics of land cover is crucial for establishing effective monitoring and evaluation programs to assess ecosystem changes. This study explores the intricate land cover dynamics within Chizarira National Park (CNP), Zimbabwe, spanning the period from 1992 to 2022. It seeks to elucidate the complex interplay between climate variables, land cover changes, and human impacts within the park’s ecosystem. Utilizing Google Earth Engine (GEE), we acquired time series data for Normalized Difference Vegetation Index (NDVI), rainfall, and temperature, enabling us to map changes in five key land cover classes: water, trees, shrubs, grass, and bare land. Quantum Geographic Information System (QGIS) software facilitated further classification and the computation of area changes for each land cover class. Our analysis produced intriguing results. Mean annual Normalized Difference Vegetation Index (NDVI) exhibited fluctuations, reaching its peak in 2017 and lowest in 1995. Notably, we found no significant correlation between rainfall and NDVI (rho = 0.32, p = 0.77) or between temperature and NDVI (rho = -0.16, p = 0.45). These findings indicate that climate variables alone may not be sufficient to explain NDVI variations. Notably, CNP experienced woody encroachment, with shrubs developing into trees, potentially altering ecosystem services and land cover. Additionally, the study identified bare land in areas impacted by illegal anthropogenic activities, underscoring the need for stronger conservation enforcement. This research serves as a critical baseline for understanding CNP's complex ecological system, informing strategies for conservation, and guiding future studies aimed at preserving this unique national park. It emphasizes the importance of monitoring and addressing human-induced changes, exploring fine-scale temporal dynamics, and investigating the impacts of fires and wildlife population density on vegetation cover.

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Assessing correlation between Rainfall, normalized difference Vegetation Index (NDVI) and land surface temperature (LST) in Eastern India

Cited by 29 publications

References 55 publications

Spatio-Temporal Variability of Rainfall and Temperature and Their Effects on Pasture Variability over East Africa: Implication on the Cattle Grazing Areas

Spatio-Temporal Variability of Rainfall and Temperature and Their Effects on Pasture Variability over East Africa: Implication on the Cattle Grazing Areas

Buchanania cochinchinensis (Lour.) M.R. Almedia habitat exhibited robust adaptability to diverse socioeconomic scenarios in eastern India

Examining spatiotemporal land cover dynamics in relation to rainfall and temperature: 1992-2022. Case of Chizarira National Park, Zimbabwe

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