scholarly journals Vegetation Indices Do Not Capture Forest Cover Variation in Upland Siberian Larch Forests

2018 ◽  
Vol 10 (11) ◽  
pp. 1686 ◽  
Author(s):  
Michael Loranty ◽  
Sergey Davydov ◽  
Heather Kropp ◽  
Heather Alexander ◽  
Michelle Mack ◽  
...  
Keyword(s):  
Carbon Storage ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Forest Cover ◽  
Global Climate ◽  
Vegetation Indices ◽  
Temporal Trends ◽  
Siberian Larch ◽  
Field Observations ◽  
Larch Forests

Boreal forests are changing in response to climate, with potentially important feedbacks to regional and global climate through altered carbon cycle and albedo dynamics. These feedback processes will be affected by vegetation changes, and feedback strengths will largely rely on the spatial extent and timing of vegetation change. Satellite remote sensing is widely used to monitor vegetation dynamics, and vegetation indices (VIs) are frequently used to characterize spatial and temporal trends in vegetation productivity. In this study we combine field observations of larch forest cover across a 25 km2 upland landscape in northeastern Siberia with high-resolution satellite observations to determine how the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) are related to forest cover. Across 46 forest stands ranging from 0% to 90% larch canopy cover, we find either no change, or declines in NDVI and EVI derived from PlanetScope CubeSat and Landsat data with increasing forest cover. In conjunction with field observations of NDVI, these results indicate that understory vegetation likely exerts a strong influence on vegetation indices in these ecosystems. This suggests that positive decadal trends in NDVI in Siberian larch forests may correspond primarily to increases in understory productivity, or even to declines in forest cover. Consequently, positive NDVI trends may be associated with declines in terrestrial carbon storage and increases in albedo, rather than increases in carbon storage and decreases in albedo that are commonly assumed. Moreover, it is also likely that important ecological changes such as large changes in forest density or variable forest regrowth after fire are not captured by long-term NDVI trends.

scholarly journals Beyond Bioproductivity: Engaging Local Perspectives in Land Degradation Monitoring and Assessment

2018 ◽  
Author(s):  
Stefanie Herrmann ◽  
Abdoul Aziz Diouf ◽  
Ibrahima Sall
Keyword(s):  
Remote Sensing ◽  
Land Degradation ◽  
Vegetation Indices ◽  
Temporal Trends ◽  
Photo Elicitation ◽  
Field Observations ◽  
Crowd Sourcing ◽  
Vegetative Cover ◽  
Degradation Monitoring ◽  
Land Condition

Land degradation monitoring and assessment in the Sahel zone takes advantage of and relies substantially on temporal trends of remote sensing-based vegetation indices, which are proxies for the bioproductivity of the land. However, prior studies have shown that negative or positive trends in bioproductivity are not necessarily associated with degradation or improvement of land condition. We argue that remote sensing-based indices, while having contributed much to dismantling an outdated desertification narrative, are themselves falling short of capturing the whole picture and need to be accompanied by field observations that are relevant to local land users. We used the participatory photo elicitation method in three sites in order to elicit local pastoralists’ perspectives on land degradation and identify the indicators that they use to characterize pasture quality, while empowering them to lead the discussion. The discussion revealed indicators far beyond bioproductivity, including livestock performance as well as composition and quality of the herbaceous and woody vegetative cover, invasive species, soil quality and water availability. We found that the pastoralists’ interest, knowledge and field observations could potentially be harnessed using a crowd-sourcing approach in order to produce a geospatially explicit dataset of land degradation, which would be complementary to the remote sensing-based maps of trends in bioproductivity and could serve as a reference for the development of more targeted remote sensing-based indicators of land degradation

scholarly journals The Ongoing Greening in Southwest China despite Severe Droughts and Drying Trends

2021 ◽  
Vol 13 (17) ◽  
pp. 3374
Author(s):  
Xin Chen ◽  
Tiexi Chen ◽  
Qingyun Yan ◽  
Jiangtao Cai ◽  
Renjie Guo ◽  
...  
Keyword(s):  
Vegetation Change ◽  
Vegetation Index ◽  
Southwest China ◽  
Vegetation Indices ◽  
Climate Extremes ◽  
Global Scale ◽  
Area Index ◽  
Huge Impact ◽  
Increasing Trends

Vegetation greening, which refers to the interannual increasing trends of vegetation greenness, has been widely found on the regional to global scale. Meanwhile, climate extremes, especially several drought, significantly damage vegetation. The Southwest China (SWC) region experienced massive drought from 2009 to 2012, which severely damaged vegetation and had a huge impact on agricultural systems and life. However, whether these extremes have significantly influenced long-term (multiple decades) vegetation change is unclear. Using the latest remote sensing-based records, including leaf area index (LAI) and gross primary productivity (GPP) for 1982–2016 and enhanced vegetation index (EVI) for 2001–2019, drought events of 2009–2012 only leveled off the greening (increasing in vegetation indices and GPP) temporally and long-term greening was maintained. Meanwhile, drying trends were found to unexpectedly coexist with greening.

scholarly journals Evaluating Post-Fire Vegetation Recovery in Cajander Larch Forests in Northeastern Siberia Using UAV Derived Vegetation Indices

2020 ◽  
Vol 12 (18) ◽  
pp. 2970
Author(s):  
Anna C. Talucci ◽  
Elena Forbath ◽  
Heather Kropp ◽  
Heather D. Alexander ◽  
Jennie DeMarco ◽  
...  
Keyword(s):  
Boreal Forests ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Visible Spectrum ◽  
Basal Area ◽  
Vegetation Recovery ◽  
Climate Conditions ◽  
Northeastern Siberia ◽  
Larch Forests

The ability to monitor post-fire ecological responses and associated vegetation cover change is crucial to understanding how boreal forests respond to wildfire under changing climate conditions. Uncrewed aerial vehicles (UAVs) offer an affordable means of monitoring post-fire vegetation recovery for boreal ecosystems where field campaigns are spatially limited, and available satellite data are reduced by short growing seasons and frequent cloud cover. UAV data could be particularly useful across data-limited regions like the Cajander larch (Larix cajanderi Mayr.) forests of northeastern Siberia that are susceptible to amplified climate warming. Cajander larch forests require fire for regeneration but are also slow to accumulate biomass post-fire; thus, tall shrubs and other understory vegetation including grasses, mosses, and lichens dominate for several decades post-fire. Here we aim to evaluate the ability of two vegetation indices, one based on the visible spectrum (GCC; Green Chromatic Coordinate) and one using multispectral data (NDVI; Normalized Difference Vegetation Index), to predict field-based vegetation measures collected across post-fire landscapes of high-latitude Cajander larch forests. GCC and NDVI showed stronger linkages with each other at coarser spatial resolutions e.g., pixel aggregated means with 3-m, 5-m and 10-m radii compared to finer resolutions (e.g., 1-m or less). NDVI was a stronger predictor of aboveground carbon biomass and tree basal area than GCC. NDVI showed a stronger decline with increasing distance from the unburned edge into the burned forest. Our results show NDVI tended to be a stronger predictor of some field-based measures and while GCC showed similar relationships with the data, it was generally a weaker predictor of field-based measures for this region. Our findings show distinguishable edge effects and differentiation between burned and unburned forests several decades post-fire, which corresponds to the relatively slow accumulation of biomass for this ecosystem post-fire. These findings show the utility of UAV data for NDVI in this region as a tool for quantifying and monitoring the post-fire vegetation dynamics in Cajander larch forests.

scholarly journals Spatiotemporal Assessment of Vegetation Indices and Land Cover for Erbil City and Its Surrounding Using Modis Imageries

2017 ◽  
Vol 10 (1-2) ◽  
pp. 31-39 ◽  
Author(s):  
Shwan O. Hussein ◽  
Ferenc Kovács ◽  
Zalán Tobak
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Natural Vegetation ◽  
Visual Interpretation ◽  
Surrounding Areas ◽  
The Impact

Abstract The rate of global urbanization is exponentially increasing and reducing areas of natural vegetation. Remote sensing can determine spatiotemporal changes in vegetation and urban land cover. The aim of this work is to assess spatiotemporal variations of two vegetation indices (VI), the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), in addition land cover in and around Erbil city area between the years 2000 and 2015. MODIS satellite imagery and GIS techniques were used to determine the impact of urbanization on the surrounding quasi-natural vegetation cover. Annual mean vegetation indices were used to determine the presence of a spatiotemporal trend, including a visual interpretation of time-series MODIS VI imagery. Dynamics of vegetation gain or loss were also evaluated through the study of land cover type changes, to determine the impact of increasing urbanization on the surrounding areas of the city. Monthly rainfall, humidity and temperature changes over the 15-year-period were also considered to enhance the understanding of vegetation change dynamics. There was no evidence of correlation between any climate variable compared to the vegetation indices. Based on NDVI and EVI MODIS imagery the spatial distribution of urban areas in Erbil and the bare around it has expanded. Consequently, the vegetation area has been cleared and replaced over the past 15 years by urban growth.

scholarly journals Assessing Typhoon-Induced Canopy Damage Using Vegetation Indices in the Fushan Experimental Forest, Taiwan

2020 ◽  
Vol 12 (10) ◽  
pp. 1654
Author(s):  
Jonathan Peereman ◽  
James Aaron Hogan ◽  
Teng-Chiu Lin
Keyword(s):  
Vegetation Cover ◽  
Forest Canopy ◽  
Vegetation Index ◽  
Forest Cover ◽  
Spatial Scales ◽  
Landsat Imagery ◽  
Vegetation Indices ◽  
Vegetation Heterogeneity ◽  
Induced Changes ◽  
Fushan Experimental Forest

Cyclonic windstorms profoundly affect forest structure and function throughout the tropics and subtropics. Remote sensing techniques and vegetation indices (VIs) have improved our ability to characterize cyclone impacts over broad spatial scales. Although VIs are useful for understanding changes in forest cover, their consistency on detecting changes in vegetation cover is not well understood. A better understanding of the similarities and differences in commonly used VIs across disturbance events and forest types is needed to reconcile the results from different studies. Using Landsat imagery, we analyzed the change between pre- and post-typhoon VI values (ΔVIs) of four VIs for five typhoons (local name of cyclones in the North Pacific) that affected the Fushan Experimental Forest of Taiwan. We found that typhoons varied in their effect on forest canopy cover even when they had comparable trajectories, wind speeds, and rainfall. Most VIs measured a decrease in forest cover following typhoons, ranging from −1.18% to −19.87%; however, the direction of ΔVI–topography relationships varied among events. All typhoons significantly increased vegetation heterogeneity, and ΔVI was negatively related to pre-typhoon VI across all typhoons. Four of the five typhoons showed that more frequently affected sites had greater VI decreases. VIs ranged in their sensitivity to detect typhoon-induced changes in canopy coverage, and no single VI was most sensitive across all typhoons. Therefore, we recommend using VIs in combination—for example Normalized Difference Infrared Index (NDII) and Enhanced Vegetation Index (EVI), when comparing cyclone-disturbance-induced changes in vegetation cover among disturbances and across forests.

scholarly journals Contrasting 20-year trends in NDVI at two Siberian larch forests with and without multiyear waterlogging-induced disturbances

2022 ◽  
Author(s):  
Hirohiko Nagano ◽  
Ayumi Kotani ◽  
Hiroki Mizuochi ◽  
Kazuhito Ichii ◽  
Hironari Kanamori ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Meteorological Data ◽  
Siberian Larch ◽  
Understory Vegetation ◽  
The Past ◽  
Significant Relationships ◽  
Larch Forests ◽  
Tree Dieback ◽  
Flooding Events

Abstract The fate of a boreal forest may depend on the trend in its normalized difference vegetation index (NDVI), such as whether the NDVI has been increasing significantly over the past few decades. In this study, we analyzed the responses of two Siberian larch forests at Spasskaya Pad and Elgeeii in eastern Siberia to various waterlogging-induced disturbances, using satellite-based NDVI and meteorological data for the 2000–2019 period. The forest at Spasskaya Pad experienced waterlogging (i.e., flooding events caused by abnormal precipitation) during 2005–2008 that damaged canopy-forming larch trees and increased the abundance of water-resistant understory vegetation. By contrast, the forest at Elgeeii did not experience any remarkable disturbance, such as tree dieback or changes in the vegetation community. Significant increasing NDVI trends were found in May and June–August at Elgeeii (p < 0.05), whereas no significant trends were found at Spasskaya Pad (p > 0.05). NDVI anomalies in May and June–August at Elgeeii were significantly associated with precipitation or temperature depending on the season (p < 0.05), whereas no significant relationships were found at Spasskaya Pad (p > 0.05). Thus, the 20-year NDVI trend and NDVI–temperature–precipitation relationship differed between the two larch forests, although no significant trends in temperature or precipitation were observed. These findings indicate that nonsignificant NDVI trends for Siberian larch forests may reflect waterlogging-induced dieback of larch trees, with a concomitant increase in water-resistant understory vegetation.

scholarly journals Development of forest cover mask to monitor the health condition of forests in Poland using long-term satellite observations

2016 ◽  
Vol 77 (2) ◽  
pp. 141-150
Author(s):  
Maciej Bartold
Keyword(s):  
Vegetation Index ◽  
Forest Cover ◽  
Normalized Difference Vegetation Index ◽  
Meteorological Data ◽  
Vegetation Indices ◽  
Forest Health ◽  
Remote Sensing Data ◽  
Forest Regions ◽  
The Impact

Abstract The work presented here aims at developing cover mask for monitoring forest health in Poland using remote sensing data. The main objective was to assess the impact of using the mask on forest condition monitoring combined with vegetation indices obtained from long-term satellite data. In this study, a new mask developed from the CORINE Land Cover 2012 (CLC2012) database is presented and its one-kilometer pixel size matched to low-resolution data derived from SPOT VEGETATION satellite registrations. For vegetation mapping, only pixels with a cover ≥ 50% of broad-leaved and mixed forests defined by CLC2012 were taken into account. The masked pixels were used to evaluate spatial variability in eight Natural-Forest Regions (NFRs). The largest coverages by masked forests were obtained in Sudetian (65.7%), Carpathian (65.9%) and Baltic (51.3%) regions. For other forest regions the coverage was observed to be around 30-50%. Time-series of the Normalized Difference Vegetation Index (NDVI) comprising SPOT VEGETATION images from 1998 until 2014 were computed and cross-comparison analyses on ≥ 50% and < 50% forest cover masks brought up frequent differences at a level higher than 0.05 NDVI in seven out of eight NFRs. An exception is the Sudetian region, where the data was highly consistent. Furthermore, the Mann-Whitney U non-parametric test revealed statistically significant differences in two regions: Baltic and Masurian-Podlasie NFR. The comparative analysis of NDVI confirmed that there is a need for additional investigation of the quality of newly developed forest mask combined with vegetation and meteorological data.

scholarly journals A unified vegetation index for quantifying the terrestrial biosphere

2021 ◽  
Vol 7 (9) ◽  
pp. eabc7447
Author(s):  
Gustau Camps-Valls ◽  
Manuel Campos-Taberner ◽  
Álvaro Moreno-Martínez ◽  
Sophia Walther ◽  
Grégory Duveiller ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Global Climate ◽  
Vegetation Indices ◽  
Canopy Structure ◽  
Terrestrial Biosphere ◽  
Area Index ◽  
Photosynthetic Potential ◽  
Source Sink ◽  
Spectral Channels

Empirical vegetation indices derived from spectral reflectance data are widely used in remote sensing of the biosphere, as they represent robust proxies for canopy structure, leaf pigment content, and, subsequently, plant photosynthetic potential. Here, we generalize the broad family of commonly used vegetation indices by exploiting all higher-order relations between the spectral channels involved. This results in a higher sensitivity to vegetation biophysical and physiological parameters. The presented nonlinear generalization of the celebrated normalized difference vegetation index (NDVI) consistently improves accuracy in monitoring key parameters, such as leaf area index, gross primary productivity, and sun-induced chlorophyll fluorescence. Results suggest that the statistical approach maximally exploits the spectral information and addresses long-standing problems in satellite Earth Observation of the terrestrial biosphere. The nonlinear NDVI will allow more accurate measures of terrestrial carbon source/sink dynamics and potentials for stabilizing atmospheric CO2 and mitigating global climate change.

scholarly journals Will Human-Induced Vegetation Regreening Continually Decrease Runoff in the Loess Plateau of China?

Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 906 ◽  
Author(s):  
Yanzhong Li ◽  
Dehua Mao ◽  
Aiqing Feng ◽  
Tayler Schillerberg
Keyword(s):  
Loess Plateau ◽  
Vegetation Change ◽  
Climate Models ◽  
Global Climate ◽  
Temporal Trends ◽  
Global Climate Models ◽  
The Loess Plateau ◽  
Runoff Variation ◽  
The Future ◽  
Grain For Green Project

China has become the largest contributing country to global vegetation regreening. However, the regreening pattern and subsequent impact on arid areas have not been comprehensively evaluated. Therefore, we selected the Loess Plateau, a representative arid region that has undergone evident vegetation restoration, to investigate the spatial patterns and temporal trends, as well as the drivers of vegetation change. This study primarily focused on 12 afforested watersheds during 2000–2018. Furthermore, both the impacts of vegetation regreening on runoff for the past two decades and the future projections were quantified based on the fraction of photosynthetically active radiation (fPAR), the Budyko model, and the global climate models (GCMs). fPAR for the last two decades indicates that vegetation in the Loess Plateau has experienced a continuous increasing trend during the growing season, primarily in response to the implementation of the Grain for Green Project (GFGP). Of the 12 watersheds, 9 experienced significant fPAR change with a change rate above 50%, and 11 exhibited a significant increase (p < 0.05) in runoff sensitivity to vegetation regreening, which indicates that vegetation regreening plays an increasingly important role in controlling runoff variation. The decline in runoff caused by vegetation regreening was particularly noticeable before 2011 or 2012; afterwards, runoff tended to vary with precipitation. In the future (2020–2049 and 2050–2099), decrease in runoff by regreening will be limited, as runoff is anticipated to decrease by 3.5% in 2020–2049 and 4.1% in 2050–2099 with a 20% increase in fPAR. These results indicate that runoff tends to be stable even with continuous vegetation regreening. While the reduction of runoff by regreening will be limited in the future, rapid human-induced vegetation regreening may aggravate water scarcity when flash droughts occur and may result in disasters in water-limited regions to the socio-economic stability and agriculture. Our study will provide an applicable theoretical foundation for water resources decision-making and ecological restoration.

scholarly journals Investigation on Zagros forests cover changes under the recent droughts using satellite imagery

2019 ◽  
Vol 65 (No. 1) ◽  
pp. 9-17 ◽  
Author(s):  
Marjan Goodarzi ◽  
Mehdi Pourhashemi ◽  
Zahra Azizi
Keyword(s):  
Vegetation Index ◽  
Forest Cover ◽  
Landsat Imagery ◽  
Vegetation Indices ◽  
Annual Rainfall ◽  
Forest Cover Change ◽  
Water Index ◽  
Forest Dieback ◽  
Zagros Forests ◽  
Average Annual Temperature

Oak decline phenomenon has recently led to considerable dieback within Zagros forests, western Iran. In the present study, Landsat imagery (2005 to 2016) and synoptic station data were used to study the forest dieback in Dorood, Lorestan province. Sixteen vegetation indices were calculated and values in each year were obtained. The correlations between the index and climatic parameters of rainfall, temperature and relative humidity were investigated. Results showed that the correlation of some indices with rainfall and the correlation of other indices with temperature were more than 70%. Optimized soil adjusted vegetation index had 80% correlation with annual rainfall and the modification of normalized difference water index was correlated with average annual temperature by 75%. Using the numerical value changes of the indices, a map of forest cover change was prepared in four classes; healthy, weak, moderate and severe dieback and the process of its change were compared with the trend of variations in regard with rainfall values in the study period. There was a close relationship between changes in the area of forest cover dieback and rainfall and temperature values.

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