Investigation of NDVI in relation to the growth phases of beech leaves in forest

Hashemi, Seyed Armin; Chai, Mir Mozaffar Fallah

doi:10.1007/s12517-012-0565-y

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…This study, furthermore, provided empirical evidence that SIF, EVI and NDVI also capture complementary stages of the progressive leaf senescence process. Specifically, the autumn phenology extracted from SIF corresponds with the attenuation of photosynthetic activity, while EVI is prone to track leaf color changes from greenness perspective (X. Zhang, 2015), and NDVI is more sensitive to structural changes such as leaf fall (Hashemi & Chai, 2013; Nagai et al., 2010). This indicated that the neglect of the specific definition of different satellite proxies is one of the main reasons resulting in diverse satellite‐derived autumn phenology.…”

Section: Discussionmentioning

confidence: 99%

Divergence in Autumn Phenology Extracted From Different Satellite Proxies Reveals the Timetable of Leaf Senescence Over Deciduous Forests

Wang,

Yang,

Yin

et al. 2024

Geophysical Research Letters

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Remote sensing detection of autumn phenology is challenging and highly uncertain, as exemplified by the observed divergence in autumn phenology extracted from different proxies. Here, we compared the autumn phenology derived from Solar‐Induced chlorophyll Fluorescence (SIF), Chlorophyll/Carotenoid Index (CCI), Enhanced Vegetation Index (EVI), and Normalized Difference Vegetation Index (NDVI) over deciduous forest sites. We observed a clear temporal sequence in the derived autumn phenology from various proxies: SIF < CCI < EVI < NDVI. Comparison with field measurements supported that SIF, EVI, and NDVI can successfully capture the attenuation of photosynthetic activity, leaf coloration, and leaf fall, respectively. The sequence among the autumn phenology derived from those proxies was also consistent with their responses to climate cues, where SIF had the highest partial correlation coefficient to solar radiation in autumn, followed by CCI, EVI, and NDVI, while NDVI was more correlated with temperature, followed by EVI, CCI, and SIF.

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Section: Discussionmentioning

confidence: 99%

Divergence in Autumn Phenology Extracted From Different Satellite Proxies Reveals the Timetable of Leaf Senescence Over Deciduous Forests

Wang,

Yang,

Yin

et al. 2024

Geophysical Research Letters

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“…Having timeliness information and statistics is essential for the proper management of natural realms. One of the principles of natural resource management is the information about land use change maps (Hashemi and Fallah Chai 2013). According to the high cost and lack of timeliness in preparation of these maps by ground operations, in recent years, the use of satellite images has been proposed as a method for doing this work.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of deciduous broadleaf forests mountain using satellite data using neural network method near Caspian Sea in North of Iran

Hashemi

2016

An. Acad. Bras. Ciênc.

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During the recent decades, deciduous forests have been molested by human intervention. Easy access, abundance and diversity of valuable forest products have led to increased population density, creating new residential areas and deforestation activities. Revealing changes is one of the fundamental methods in management and assessment of natural resources. This study is evaluated changes in forests area of 2013 using satellite images. In order to mapping the forest extent condition 2013, images of the mentioned years were digitized and geo-referenced by using the ground control points and the maps of mapping organization. After selecting the best set of band using the Bhattacharya distance index, the image classification was performed by using artificial neural network algorithm. Classification by neural network method 2013 in showed that it has a high overall accuracy equal to 95.96%.

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Monitoring deforestation in Iran, Jangal-Abr Forest using multi-temporal satellite images and spectral mixture analysis method

Karimi

Golian

Karimi³

2016

Arab J Geosci

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Investigation of NDVI in relation to the growth phases of beech leaves in forest

Cited by 3 publications

References 7 publications

Divergence in Autumn Phenology Extracted From Different Satellite Proxies Reveals the Timetable of Leaf Senescence Over Deciduous Forests

Divergence in Autumn Phenology Extracted From Different Satellite Proxies Reveals the Timetable of Leaf Senescence Over Deciduous Forests

Evaluation of deciduous broadleaf forests mountain using satellite data using neural network method near Caspian Sea in North of Iran

Monitoring deforestation in Iran, Jangal-Abr Forest using multi-temporal satellite images and spectral mixture analysis method

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