MODIS Derived Vegetation Index for Drought Detection on the San Carlos Apache Reservation

Wu, Zhuoting; Velasco, Miguel G.; McVay, Jason; Middleton, Barry R.; Vogel, John M.; Dye, Dennis G.

doi:10.23953/cloud.ijarsg.44

Cited by 10 publications

(6 citation statements)

References 62 publications

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“…[57,58]. MSAVI2 is especially useful for quantifying the photosynthetic biomass in landscapes characterized by high percentages of bare surfaces [62][63][64]. It ranges from −1 (absence of vegetation biomass) to 1 (maximum of vegetation biomass), with higher values indicating higher percentages of photosynthetic biomass [63,65].…”

Section: Data Collection Field Data Collectionmentioning

confidence: 99%

Measuring Alpha and Beta Diversity by Field and Remote-Sensing Data: A Challenge for Coastal Dunes Biodiversity Monitoring

et al. 2021

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Combining field collected and remotely sensed (RS) data represents one of the most promising approaches for an extensive and up-to-date ecosystem assessment. We investigated the potential of the so called spectral variability hypothesis (SVH) in linking field-collected and remote-sensed data in Mediterranean coastal dunes and explored if spectral diversity provides reliable information to monitor floristic diversity, as well as the consistency of such information in altered ecosystems due to plant invasions. We analyzed alpha diversity and beta diversity, integrating floristic field and Remote-Sensing PlanetScope data in the Tyrrhenian coast (Central Italy). We explored the relationship among alpha field diversity (species richness, Shannon index, inverse Simpson index) and spectral variability (distance from the spectral centroid index) through linear regressions. For beta diversity, we implemented a distance decay model (DDM) relating field pairwise (Jaccard similarities index, Bray–Curtis similarities index) and spectral pairwise (Euclidean distance) measures. We observed a positive relationship between alpha diversity and spectral heterogeneity with richness reporting the higher R score. As for DDM, we found a significant relationship between Bray–Curtis floristic similarity and Euclidean spectral distance. We provided a first assessment of the relationship between floristic and spectral RS diversity in Mediterranean coastal dune habitats (i.e., natural or invaded). SVH provided evidence about the potential of RS for estimating diversity in complex and dynamic landscapes.

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Section: Data Collection Field Data Collectionmentioning

confidence: 99%

Measuring Alpha and Beta Diversity by Field and Remote-Sensing Data: A Challenge for Coastal Dunes Biodiversity Monitoring

et al. 2021

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“…Applications of remote sensing using both satellite-and aerialbased imagery sources have been widely used for the semicontinuous monitoring of the vegetation at a broad-scale on the San Carlos Apache Reservation (Petrakis et al, 2016;Wu et al, 2016;Norman et al, 2018;Middleton and Norman, 2021). However, riparian zones are extremely dynamic and complex systems structurally, and cover only a small portion of the landscape (Naiman and Décamps, 1997).…”

Section: Challenges and Benefits Of Remote Sensing Within Riparian Zonesmentioning

confidence: 99%

Advances in characterizing and monitoring land cover/use and associated ecosystem changes using remote sensing data

2024

Frontiers Research Topics

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Frontiers is more than just an open access publisher of scholarly articles: it is a pioneering approach to the world of academia, radically improving the way scholarly research is managed. The grand vision of Frontiers is a world where all people have an equal opportunity to seek, share and generate knowledge. Frontiers provides immediate and permanent online open access to all its publications, but this alone is not enough to realize our grand goals. Frontiers journal seriesThe Frontiers journal series is a multi-tier and interdisciplinary set of openaccess, online journals, promising a paradigm shift from the current review, selection and dissemination processes in academic publishing. All Frontiers journals are driven by researchers for researchers; therefore, they constitute a service to the scholarly community. At the same time, the Frontiers journal series operates on a revolutionary invention, the tiered publishing system, initially addressing specific communities of scholars, and gradually climbing up to broader public understanding, thus serving the interests of the lay society, too. Dedication to qualityEach Frontiers article is a landmark of the highest quality, thanks to genuinely collaborative interactions between authors and review editors, who include some of the world's best academicians. Research must be certified by peers before entering a stream of knowledge that may eventually reach the public -and shape society; therefore, Frontiers only applies the most rigorous and unbiased reviews. Frontiers revolutionizes research publishing by freely delivering the most outstanding research, evaluated with no bias from both the academic and social point of view. By applying the most advanced information technologies, Frontiers is catapulting scholarly publishing into a new generation. What are Frontiers Research Topics?Frontiers Research Topics are very popular trademarks of the Frontiers journals series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area.

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“…The improved modified soil-adjusted vegetation index (MSAVI2) [84] was included in the analysis to account for potential soil effects. It has been applied for LAI estimation and drought detection on different grassland sites [85,86]. Because MSAVI2 is a broadband index, it was calculated from the hyperspectral data based on Sentinel-2 band specifications.…”

Section: Evaluation With Spectral Indices and Geophysical Measurementsmentioning

confidence: 99%

Inferring Grassland Drought Stress with Unsupervised Learning from Airborne Hyperspectral VNIR Imagery

et al. 2021

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The 2018–2019 Central European drought had a grave impact on natural and managed ecosystems, affecting their health and productivity. We examined patterns in hyperspectral VNIR imagery using an unsupervised learning approach to improve ecosystem monitoring and the understanding of grassland drought responses. The main objectives of this study were (1) to evaluate the application of simplex volume maximisation (SiVM), an unsupervised learning method, for the detection of grassland drought stress in high-dimensional remote sensing data at the ecosystem scale and (2) to analyse the contributions of different spectral plant and soil traits to the computed stress signal. The drought status of the research site was assessed with a non-parametric standardised precipitation–evapotranspiration index (SPEI) and soil moisture measurements. We used airborne HySpex VNIR-1800 data from spring 2018 and 2019 to compare vegetation condition at the onset of the drought with the state after one year. SiVM, an interpretable matrix factorisation technique, was used to derive typical extreme spectra (archetypes) from the hyperspectral data. The classification of archetypes allowed for the inference of qualitative drought stress levels. The results were evaluated using a set of geophysical measurements and vegetation indices as proxy variables for drought-inhibited vegetation growth. The successful application of SiVM for grassland stress detection at the ecosystem canopy scale was verified in a correlation analysis. The predictor importance was assessed with boosted beta regression. In the resulting interannual stress model, carotenoid-related variables had among the highest coefficient values. The significance of the photochemical reflectance index that uses 512 nm as reference wavelength (PRI512) demonstrates the value of combining imaging spectrometry and unsupervised learning for the monitoring of vegetation stress. It also shows the potential of archetypical reflectance spectra to be used for the remote estimation of photosynthetic efficiency. More conclusive results could be achieved by using vegetation measurements instead of proxy variables for evaluation. It must also be investigated how the method can be generalised across ecosystems.

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MODIS Derived Vegetation Index for Drought Detection on the San Carlos Apache Reservation

Cited by 10 publications

References 62 publications

Measuring Alpha and Beta Diversity by Field and Remote-Sensing Data: A Challenge for Coastal Dunes Biodiversity Monitoring

Measuring Alpha and Beta Diversity by Field and Remote-Sensing Data: A Challenge for Coastal Dunes Biodiversity Monitoring

Advances in characterizing and monitoring land cover/use and associated ecosystem changes using remote sensing data

Inferring Grassland Drought Stress with Unsupervised Learning from Airborne Hyperspectral VNIR Imagery

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