Retrieving multi-scale climatic variations from high dimensional time-series MODIS green vegetation cover in a tropical/subtropical mountainous island

Chang, Chih-Hsiung; Wang, Hsueh-Ching; Huang, Chin Wei

doi:10.1007/s11629-013-2835-x

Cited by 10 publications

(11 citation statements)

References 72 publications

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“…This corresponds to field conditions of the rainy season, as, in JJAS season, minimum temperature decline and NDVI of Teak and Sal increases in the month of August and September due to flush after rainfall resulting in a negative correlation. Chang et al (2014) and Sarmah et al (2018) also reported the similar type of correlations during the monsoon season (JJAS) in forest areas. (Table. 3)…”

Section: Monsoon (Jjas)mentioning

confidence: 58%

“…The NDVI is a potential tool to monitor forest health and infer seasonal dynamics. The recent literature shows that EVI is a better indicator than NDVI for assessment of high biomass vegetation (Chang et al, 2014;Heute at el, 2002). The annual NDVI for both Teak and Sal landscape showed an increasing trend for the period 2000-2015.…”

Section: Resultsmentioning

confidence: 99%

“…The post-monsoon months of October and November correspond to maximum values of NDVI in both teak and Sal forest. This could be attributed to sustained soil moisture of rainy months and increased leaf area index (Nischita et al, 2014, Chang et al, 2014. Both Teak and Sal NDVI was significant and positively correlated with the temperatures except the correlation with minimum temperature was not significant.…”

Section: Post-monsoon (On)mentioning

confidence: 99%

“…Limited incident radiation hinders photosynthesis which is essential for vegetation growth (Song and Ma, 2008) which ultimately reduces NDVI values. There are many studies comparing NDVI and EVI for their discerning ability to detect seasonal and phenological changes which conclude EVI as a better indicator in high canopy areas because NDVI gets asymptotically saturated in high biomass regions (Heaute et al, 2002, Yang et al, 2007and Chang et al, 2014. Thus, in order to study the vegetation dynamics in terms of seasonal and phenological changes, it is important to use both NDVI and EVI.…”

Section: Modis Time Series Analysis (2000-2015)mentioning

confidence: 99%

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Assessing Impacts of Climate Change on Teak and Sal Landscape Using Modis Time Series Data

Patasaraiya

Sinha

Bisaria

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Climate change poses a severe threat to the forest ecosystems by impacting its productivity, species composition and forest biodiversity at global and regional level. The scientific community all over the world is using remote sensing techniques to monitor and assess the impact of climate change on forest ecosystems. The consistent time series data provided by MODIS is immensely used for developing a different type of Vegetation indices like NDVI (Normalized difference vegetation indices) products at different spatial and temporal resolution. These vegetation indices have significant potential to detect forest growth and health, vegetation seasonality and different phenological events like budding and flowering. The current study aims to understand the impact of climate change on Teak and Sal forest of STR (Satpura tiger reserve) in central India by using Landsat and MODIS time series data. The rationale for taking STR as study site was to attribute the changes exclusively to climate change as there is no anthropogenic disturbance in STR. A change detection analysis was carried out to detect changes between the period 2017 and 1990 using Landsat data of October month. To understand the inter-annual and seasonal variation of Teak and Sal forests, freely available MOD13Q1 product (250m, 16 days’ interval) was used to extract NDVI values for each month and four seasons (DJF, JJAS, ON, MAM) for the period 2000 to 2015. The climatic data (rainfall and temperature) was sourced from IMD (India Meteorological Department) at different resolutions (1, 0.5 and 0.25 degree) for the given period of the study. A correlation analysis was done to establish a causal relationship between climate variable (temperature and rainfall) and vegetation health (NDVI) on a different temporal scale of annual, seasonal and month. The study found an increasing trend in annual mean temperature and no consistent trend in total annual rainfall over the period 2000 to 2015. The maximum percentage change was observed in minimum temperature over the period 2000 to 2015. The average annual NDVI of Teak and Sal forests showed an increasing trend however, no trend was observed in seasonal and monthly NDVI over the same period. The maximum and minimum NDVI was found in the post-monsoon months (ON) and summer months (MAM) respectively. As STR is a Teak and Sal dominated landscape, the findings of the current study can also be applied in developing silvicultural and adaptation strategies for other Teak and Sal dominated landscapes of central India.

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Section: Monsoon (Jjas)mentioning

confidence: 58%

Section: Resultsmentioning

confidence: 99%

Section: Post-monsoon (On)mentioning

confidence: 99%

Section: Modis Time Series Analysis (2000-2015)mentioning

confidence: 99%

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Assessing Impacts of Climate Change on Teak and Sal Landscape Using Modis Time Series Data

Patasaraiya

Sinha

Bisaria

et al. 2018

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Therefore, as suggested by Peltola et al [32], a three-year moving average window was applied to smooth the time-series data to mitigate effects of short-term climate fluctuations on tree-ring widths. This should be appropriate since the region was wet (mean annual precipitation greater than 3000 mm) [33] and annual temperature fluctuation for this near-tropical humid island was much less pronounced in comparison to other regions [34]. To assess the effects of thinning, the raw tree-ring series was divided into two periods, pre-(1966-1990) and post-(1991-2011) thinning.…”

Section: Tree-ring Data Pre-processingmentioning

confidence: 99%

Determining Ideal Timing of Row Thinning for a Cryptomeria japonica Plantation Using Event History Analysis

Chung

Lin

et al. 2017

Forests

Self Cite

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Effective time of thinning is essential for determining a silvicultural operation schedule. One of the most commonly used methods is the percentage of radial increase to assess the effect of thinning. However, it is difficult to determine the ideal time point due to variation in tree growth rates. Event history analysis was used to quantify the optimal timings for different row thinning types for a 45-year-old Cryptomeria japonica plantation in the mountainous region of Taiwan. The increase in tree-ring size was measured and converted to the basal area increment (BAI) to estimate annual tree growth; derived time-series data were entered into event history analysis to calculate the time to 50% probability of survival. Additionally, an accelerated failure time regression was applied to test the effects of thinning and its timing; model validation was carried out to examine the influence of thinning time variation on plant growth through time. Results showed that thinning modified the temporal dynamics of the BAI, and, in general, a positive trend was observed between strip-width and time of thinning. Simulated tree growth in the model validation corroborated that accurate timing may optimize thinning effects. Combining tree-ring measurement and event history analysis may facilitate determining the timing of row thinning, which can improve carbon sequestration of forest stands.

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Assessment of MODIS-derived indices (2001–2013) to drought across Taiwan’s forests

2017

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Tropical and subtropical ecosystems, the largest terrestrial carbon pools, are very susceptible to the variability of seasonal precipitation. However, the assessment of drought conditions in these regions is often overlooked due to the preconceived notion of the presence of high humidity. Drought indices derived from remotely sensed imagery have been commonly used for large-scale monitoring, but feasibility of drought assessment may vary across regions due to climate regimes and local biophysical conditions. Therefore, this study aims to evaluate the feasibility of 11 commonly used MODIS-derived vegetation/drought index in the forest regions of Taiwan through comparison with the station-based standardized precipitation index with a 3-month time scale (SPI3). The drought indices were further transformed (standardized anomaly, SA) to make them better delineate the spatiotemporal variations of drought conditions. The results showed that the Normalized Difference Infrared Index utilizing the near-infrared and shortwave infrared bands (NDII6) may be more superior to other indices in delineating drought patterns. Overall, the NDII6 SA-SPI3 pair yielded the highest correlation (mean r ± standard deviation = 0.31 ± 0.13) and was most significant in central and south Taiwan (r = 0.50-0.90) during the cold, dry season (January and April). This study illustrated that the NDII6 is suitable to delineate drought conditions in a relatively humid region. The results suggested the better performance of the NDII6 SA-SPI3 across the high climate gradient, especially in the regions with dramatic interannual amplifications of rainfall. This synthesis was conducted across a wide bioclimatic gradient, and the findings could be further generalized to a much broader geographical extent.

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Retrieving multi-scale climatic variations from high dimensional time-series MODIS green vegetation cover in a tropical/subtropical mountainous island

Cited by 10 publications

References 72 publications

Assessing Impacts of Climate Change on Teak and Sal Landscape Using Modis Time Series Data

Assessing Impacts of Climate Change on Teak and Sal Landscape Using Modis Time Series Data

Determining Ideal Timing of Row Thinning for a Cryptomeria japonica Plantation Using Event History Analysis

Assessment of MODIS-derived indices (2001–2013) to drought across Taiwan’s forests

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