A study of forest vegetation dynamics in the south of the Krasnoyarskii Krai in spring

Chernetskiy, Maxim; Pasko, Irina; Shevyrnogov, A.; Slyusar, N.; Khodyayev, A.

doi:10.1016/j.asr.2011.04.032

Cited by 11 publications

(4 citation statements)

References 13 publications

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“…In contrast, agricultural land has the lowest EVI and the highest LST. This finding is similar to those of previous studies that non-forested areas have higher temperatures than forested lands [19,23,26]. This indicates that if vegetation cover is reduced due to clearance, it can contribute to an increase in heat energy transferred from the land surface.…”

Section: Discussionsupporting

confidence: 82%

“…Several studies have applied these indices successfully to detect vegetation dynamics in broad landscapes including boreal, semiarid, arid and temperate forests [6,7,11,18,[22][23][24]. Several studies suggest that the combination of measurements of temperature and vegetation indices provides a better classification and observation of land covers in the African continent [25,26], Sub-Saharan Africa [27] and over the continental United States [28].…”

Section: Introductionmentioning

confidence: 99%

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MODIS EVI and LST Temporal Response for Discrimination of Tropical Land Covers

et al. 2015

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MODIS enhanced vegetation index (EVI) and land surface temperature (LST) are key indicators for monitoring vegetation cover changes in broad ecosystems. However, there has been little evaluation of these indices for detecting changes in a range of land covers in tropical regions. In this study, we investigated the characteristics and seasonal responses of LST and EVI for four different land covers in Lao tropical forests: native forest, rubber plantation, mixed wooded/cleared areas and agriculture. We calculated long-term averages of MODIS LST and EVI 16-day time series and compared their monthly transitions over the seven-year period from 2006 to 2012. We also tested whether these indices can be used to classify these four land covers. The findings demonstrate the complex interrelationship of LST and EVI and their monthly transitions for different land covers: they each showed distinctly different intra-annual LST and EVI variations. Native forests have the highest EVI, and the lowest LST throughout the year. In contrast, agricultural areas with little or no vegetation cover have the highest LST. The transition of LST/EVI for the land covers other than native forests showed marked seasonality. Linear discriminant analysis (LDA) showed that there was high overall accuracy of separation of land covers by these indices (86%). The encouraging results indicate that the combined use of MODIS LST and EVI holds promise for improving monitoring of changes in a Lao tropical forest. OPEN ACCESSRemote Sens. 2015, 7 6027

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Section: Discussionsupporting

confidence: 82%

Section: Introductionmentioning

confidence: 99%

MODIS EVI and LST Temporal Response for Discrimination of Tropical Land Covers

et al. 2015

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“…In 2019, areas with NDVI values between 0.5 and 1.0 are already above the 2006 values. Such differences are explained by the lower biomass and photosynthetic activity of pine forests compared to meadow vegetation and the emerging secondary broadleaved forests (Chernetskiy et al, 2011;Adamovich et al, 2018;Pisman et al, 2018). (2006, 2008, 2014, 2019 -years; NDVI values: -1.0-0.1 -bare soil, roads; 0.1-0.3 -thin meadow vegetation; 0.3-0.5 -pine forest with a dense woodland; 0.5-0.6 -sparse pine forest dominated by broad-leaved species; 0.6-1.0 -broad-leaved forests)…”

Section: Resultsmentioning

confidence: 99%

Transformation of plant and soil covers of the Botanical nature monument “Pine forest near Venetsiya village” (Russia) as a result of a windfall

Suleymanov¹,

Yakimov²,

Liebelt³

et al. 2021

Eurasian Journal of Soil Science (Ejss)

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Article InfoThe article presents the results of complex research (research was conducted in 2019) of the Botanical natural monument territory "Pine forest near Venetsiya village" (Russia). In 2007, part of the nature monument territory was destroyed by a hurricane, resulting in massive windfall. The purpose of the research was to study the processes of evolution of natural complexes (vegetation and soil cover) in the areas affected by the hurricane. Classification of vegetation was done according to the Braun-Blanquet and Kopečký and Hejný approaches. NDVI (Normalized Difference Vegetation Index) was used to estimate the amount of photosynthetically active biomass. Changes in morphological, physical and chemical properties were studied in the soil cover. The conducted research showed that the vegetation of the natural monument is represented by relict pine and broad-leaved pine forests. Under the pine canopy linden and birch are dominated. In the herb layer grow in various combinations of nemoral and boreal species. Soil cover is represented by Gray-humus (Umbric Luvisol). There is a strong transformation of vegetation in the areas damaged by the hurricane in 12 years (2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019). There is an active formation of highly productive herbaceous vegetation and renewal of deciduous stands, which leads to an increase in biomass (confirmed by changes in NDVI). The terminal stage of the restoration succession will be the formation of secondary deciduous and mixed nemoral forests. The active development of grass vegetation leads to the formation of a sod horizon on the surface of the soil with a thickness of about 14 cm. There is also an increase in the content of organic carbon, alkaline-hydrolyzable nitrogen and mobile phosphorus, the value of electrical resistivity increases and acidification of the soil solution.

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“…Global measures of land cover change are important for global terrestrial ecosystem carbon schemes, climate and biosphere exchange modeling [1]- [3], and for improving our understanding of human and environmental interactions [4]- [6] with vegetation condition and structure [7]. Biodiversity loss due to land cover change is one of the core management challenges at both global and regional scale [8] [9].…”

Section: Introductionmentioning

confidence: 99%

Applying the Global Disturbance Index for Detecting Vegetation Changes in Lao Tropical Forests

Phompila¹,

Lewis²,

Clarke³

et al. 2015

ARS

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Land cover change is a major challenge for many developing countries. Spatiotemporal information on this change is essential for monitoring global terrestrial ecosystem carbon, climate and biosphere exchange, and land use management. A combination of LST and the EVI indices in the global disturbance index (DI) has been proven to be useful for detecting and monitoring of changes in land covers at continental scales. However, this model has not been adequately applied or assessed in tropical regions. We aimed to demonstrate and evaluate the DI algorithm used to detect spatial change in land covers in Lao tropical forests. We used the land surface temperature and enhanced vegetation index of the Moderate Resolution Imaging Spectroradiometer time-series products from 2006-2012. We used two dates Google Earth TM images in 2006 and 2012 as ground truth data for accuracy assessment of the model. This research demonstrated that the DI was capable of detecting vegetation changes during seven-year periods with high overall accuracy; however, it showed low accuracy in detecting vegetation decrease.

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A study of forest vegetation dynamics in the south of the Krasnoyarskii Krai in spring

Cited by 11 publications

References 13 publications

MODIS EVI and LST Temporal Response for Discrimination of Tropical Land Covers

MODIS EVI and LST Temporal Response for Discrimination of Tropical Land Covers

Transformation of plant and soil covers of the Botanical nature monument “Pine forest near Venetsiya village” (Russia) as a result of a windfall

Applying the Global Disturbance Index for Detecting Vegetation Changes in Lao Tropical Forests

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