Road dust biases NDVI and alters edaphic properties in Alaskan arctic tundra

Ackerman, Daniel; Finlay, Jacques C.

doi:10.1038/s41598-018-36804-3

Cited by 15 publications

(14 citation statements)

References 49 publications

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“…For example, the NDVI and NDMI, as shown in this study, decreased substantially in the 0-100 m and 100-500 m buffers, whereas the LST increased progressively during the study period. A decrease in the NDVI and NDMI could be attributed to the direct removal of vegetation, similar to that of urbanization [75,76], and indirect influences from highway construction, such as changes of moisture and temperature conditions and deposition of dust on vegetation [77,78]. The dust deposited on leaf surfaces could reduce NDVI values by blocking reflectance properties of the underlying leaves in the regions nearest the road [77], therefore reducing photosynthetic activities of vegetation.…”

Section: The Effect Distance Of Highwaymentioning

confidence: 99%

“…A decrease in the NDVI and NDMI could be attributed to the direct removal of vegetation, similar to that of urbanization [75,76], and indirect influences from highway construction, such as changes of moisture and temperature conditions and deposition of dust on vegetation [77,78]. The dust deposited on leaf surfaces could reduce NDVI values by blocking reflectance properties of the underlying leaves in the regions nearest the road [77], therefore reducing photosynthetic activities of vegetation. Nitrogen from vehicular NO X emission could affect vegetation up to 400 m from highway [79,80].…”

Section: The Effect Distance Of Highwaymentioning

confidence: 99%

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Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach

et al. 2021

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Highways provide key social and economic functions but generate a wide range of environmental consequences that are poorly quantified and understood. Here, we developed a before–during–after control-impact remote sensing (BDACI-RS) approach to quantify the spatial and temporal changes of environmental impacts during and after the construction of the Wujing Highway in China using three buffer zones (0–100 m, 100–500 m, and 500–1000 m). Results showed that land cover composition experienced large changes in the 0–100 m and 100–500 m buffers while that in the 500–1000 m buffer was relatively stable. Vegetation and moisture conditions, indicated by the normalized difference vegetation index (NDVI) and the normalized difference moisture index (NDMI), respectively, demonstrated obvious degradation–recovery trends in the 0–100 m and 100–500 m buffers, while land surface temperature (LST) experienced a progressive increase. The maximal relative changes as annual means of NDVI, NDMI, and LST were about −40%, −60%, and 12%, respectively, in the 0–100m buffer. Although the mean values of NDVI, NDMI, and LST in the 500–1000 m buffer remained relatively stable during the study period, their spatial variabilities increased significantly after highway construction. An integrated environment quality index (EQI) showed that the environmental impact of the highway manifested the most in its close proximity and faded away with distance. Our results showed that the effect distance of the highway was at least 1000 m, demonstrated from the spatial changes of the indicators (both mean and spatial variability). The approach proposed in this study can be readily applied to other regions to quantify the spatial and temporal changes of disturbances of highway systems and subsequent recovery.

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Section: The Effect Distance Of Highwaymentioning

confidence: 99%

Section: The Effect Distance Of Highwaymentioning

confidence: 99%

Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach

et al. 2021

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“…Within Alaska, oil and gas development and associated infrastructure directly and indirectly compromise shorebird habitat (Meehan 1986, 1988, Andres et al 2012). The construction of gravel pads fills in tundra, wetlands, and other landscape types that are important for nesting birds (Meehan 1986), while widely dispersed dust fallout associated with gravel pads and roads alters soil chemistry, increases permafrost thaw depth, and significantly changes vegetation communities (Walker and Everett 1987, Auerbach et al 1997, Myers‐Smith et al 2006, Ackerman and Finlay 2019). Beyond geophysical impacts on habitat quality and extent, specific activities associated with oil and gas development have the potential to disturb individual birds (Miller et al 1994).…”

Section: Introductionmentioning

confidence: 99%

Simulation modeling accounts for uncertainty while quantifying ecological effects of development alternatives

Fullman¹,

Sullender

Cameron

et al. 2021

Ecosphere

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Wildlife management often involves trade-offs between protecting species and allowing human activities and development. Ideally, these decisions are guided by scientific studies that quantify the impacts of proposed actions on the environment. However, critical information to assess impacts of proposed activities may be lacking, such as certainty in where actions will take place, which may hinder a robust impact assessment. To address this issue, we present the Development Impacts Analysis (DIA), which employs Monte Carlo simulation modeling to quantify the environmental consequences of proposed development scenarios, while accounting for uncertainty in the exact location of future development. We applied the DIA to five proposed oil leasing management scenarios under a revised management plan for the National Petroleum Reserve-Alaska. For each management scenario with differing levels of proposed development ("alternatives"), oil production pads and roads were randomly simulated in proportion to estimated undiscovered oil and following alternative-specific restrictions. We assessed habitat displacement for two caribou (Rangifer tarandus) herds, eight shorebird species, and black brant (Branta bernicla) based on reported responses to development, repeating the process 100 times for each alternative. Some habitat loss was reported for each proposed alternative, but the amount of impact varied by alternative and species. One caribou herd and most bird species indicated greatest effects in the alternative with the least restrictions on development and lesser impacts under more protective alternatives. Our results emphasized the importance of considering spatial variation in development effects and species-specific differences when evaluating management proposals. The DIA quantified potential impacts on a suite of species under proposed management alternatives, while accounting for uncertainty in where development will occur and providing confidence intervals on estimated impacts. This illustrates that uncertainty need not preclude management decisions about establishment of broad land use restrictions prior to submission of project-level proposals but can instead be explicitly incorporated into decision making. While no single management approach will likely benefit all species, use of tools such as the DIA allows managers to quantify trade-offs among species and pursue approaches that balance the needs of various taxa and other management objectives.

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“…Accurate vegetation reflectance is critical for reliably estimating vegetation parameters based on empirical methods. However, sometimes an accurate reflectance of the target cannot be obtained due to the spectral masking caused by dust or weathering residues on the target [28]. This problem has drawn geologists' attention [29].…”

Section: Introductionmentioning

confidence: 99%

“…According to the relationship between spectra and dusty leaves, reflectance spectroscopy could be used as an effective tool for monitoring soot pollution in urban suburbs [32]. Spectra-based VIs change with the dust amount [28]. Based on this, foliar dustfall amount was estimated by establishing models using multivariate linear regression, principal component regression, and partial least squares regression [33,34].…”

Section: Introductionmentioning

confidence: 99%

Experimental and Numerical Investigation of Dustfall Effect on Remote Sensing Retrieval Accuracy of Chlorophyll Content

Liang

et al. 2019

Sensors

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Chlorophyll is the dominant pigment in the photosynthetic light-harvesting complexes that is related to the physiological function of leaves and is responsible for light absorption and energy transfer. Dust pollution has become an environmental problem in many areas in China, indicating that accurately estimating chlorophyll content of vegetation using remote sensing for assessing the vegetation growth status in dusty areas is vital. However, dust deposited on the leaf may affect the chlorophyll content retrieval accuracy. Thus, quantitatively studying the dustfall effect is essential. Using selected vegetation indices (VIs), the medium resolution imaging spectrometer terrestrial chlorophyll index (MTCI), and the double difference index (DD), we studied the retrieval accuracy of chlorophyll content at the leaf scale under dusty environments based on a laboratory experiment and spectra simulation. First, the retrieval accuracy under different dustfall amounts was studied based on a laboratory experiment. Then, the relationship between dustfall amount and fractional dustfall cover (FDC) was experimentally analyzed for spectra simulation of dusty leaves. Based on spectral data simulated using a PROSPECT-based mixture model, the sensitivity of VIs to dust under different chlorophyll contents was analyzed comprehensively, and the MTCI was modified to reduce its sensitivity to dust. The results showed that (1) according to experimental investigation, the DD model provides low retrieval accuracy, the MTCI model is highly accurate when the dustfall amount is less than 80 g/m2, and the retrieval accuracy decreases significantly when the dustfall amount is more than 80 g/m2; (2) a logarithmic relationship exists between FDC and dustfall amount, and the PROSPECT-based mixture model can simulate the leaf spectra under different dustfall amounts and different chlorophyll contents with a root mean square error of 0.015; and (3) according to numerical investigation, MTCI’s sensitivity to dust in the chlorophyll content range of 25 to 60 μg/cm2 is lower than in other chlorophyll content ranges; DD’s sensitivity to dust was generally high throughout the whole chlorophyll content range. These findings may contribute to quantitatively understanding the dustfall effect on the retrieval of chlorophyll content and would help to accurately retrieve chlorophyll content in dusty areas using remote sensing.

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Road dust biases NDVI and alters edaphic properties in Alaskan arctic tundra

Cited by 15 publications

References 49 publications

Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach

Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach

Simulation modeling accounts for uncertainty while quantifying ecological effects of development alternatives

Experimental and Numerical Investigation of Dustfall Effect on Remote Sensing Retrieval Accuracy of Chlorophyll Content

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