The Dynamic Habitat Indices (DHIs) from MODIS and global biodiversity

Radeloff, Volker C.; Dubinin, Maxim; Coops, Nicholas C.; Allen, Andrew M.; Brooks, Thomas M.; Clayton, Murray K.; Costa, Gabriel C.; Graham, Catherine H.; Helmers, David P.; Ives, Anthony R.; Kolesov, D.; Pidgeon, Anna M.; Rapacciuolo, Giovanni; Razenkova, Elena; Suttidate, Naparat; Young, Bruce E.; Zhu, Likai; Hobi, Martina L.

doi:10.1016/j.rse.2018.12.009

Cited by 102 publications

(112 citation statements)

References 74 publications

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“…Phenology also influences ecosystem productivity, carbon cycling, succession, and migration strategies [4][5][6][7]. In addition, it has been classified as one of the essential biodiversity variables (EBV) and addresses goals 13 (climate action) and 15 (life on land) of the Sustainable Development Goals (SDG), which makes the study of phenological patterns and drivers crucial to plan adaptation and mitigation strategies [8,9]. The advancing of spring events, the lengthening of the growing season, the shifting of tree lines, the decreasing sensitivity to warming and the uniformity of spring across elevations are a few of the important evidences of trends in plant phenology [2,[10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Status of Phenological Research Using Sentinel-2 Data: A Review

2020

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Remote sensing of plant phenology as an indicator of climate change and for mapping land cover has received significant scientific interest in the past two decades. The advancing of spring events, the lengthening of the growing season, the shifting of tree lines, the decreasing sensitivity to warming and the uniformity of spring across elevations are a few of the important indicators of trends in phenology. The Sentinel-2 satellite sensors launched in June 2015 (A) and March 2017 (B), with their high temporal frequency and spatial resolution for improved land mapping missions, have contributed significantly to knowledge on vegetation over the last three years. However, despite the additional red-edge and short wave infra-red (SWIR) bands available on the Sentinel-2 multispectral instruments, with improved vegetation species detection capabilities, there has been very little research on their efficacy to track vegetation cover and its phenology. For example, out of approximately every four papers that analyse normalised difference vegetation index (NDVI) or enhanced vegetation index (EVI) derived from Sentinel-2 imagery, only one mentions either SWIR or the red-edge bands. Despite the short duration that the Sentinel-2 platforms have been operational, they have proved their potential in a wide range of phenological studies of crops, forests, natural grasslands, and other vegetated areas, and in particular through fusion of the data with those from other sensors, e.g., Sentinel-1, Landsat and MODIS. This review paper discusses the current state of vegetation phenology studies based on the first five years of Sentinel-2, their advantages, limitations, and the scope for future developments.

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Section: Introductionmentioning

confidence: 99%

Status of Phenological Research Using Sentinel-2 Data: A Review

2020

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“…There are many ways to delimit species’ habitats types 15 – 17 , which can be represented as either continuous variables 17 , 18 or discrete classes 19 . The International Union for Conservation of Nature (IUCN) Red List of Threatened Species uses a global standard typology ( https://www.iucnredlist.org/resources/habitat-classification-scheme ) that aims to categorize all species-relevant habitats into a system of pre-defined habitat classes 16 .…”

Section: Background and Summarymentioning

confidence: 99%

A global map of terrestrial habitat types

et al. 2020

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We provide a global, spatially explicit characterization of 47 terrestrial habitat types, as defined in the International Union for Conservation of Nature (IUCN) habitat classification scheme, which is widely used in ecological analyses, including for quantifying species' area of Habitat. We produced this novel habitat map for the year 2015 by creating a global decision tree that intersects the best currently available global data on land cover, climate and land use. We independently validated the map using occurrence data for 828 species of vertebrates (35152 point plus 8181 polygonal occurrences) and 6026 sampling sites. Across datasets and mapped classes we found on average a balanced accuracy of 0.77 (+0.14 SD) at Level 1 and 0.71 (+0.15 SD) at Level 2, while noting potential issues of using occurrence records for validation. the maps broaden our understanding of habitats globally, assist in constructing area of habitat refinements and are relevant for broad-scale ecological studies and future IUCN Red List assessments. Periodic updates are planned as better or more recent data becomes available.

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“…Основные климатические показатели, такие как температура воздуха, количество атмосферных осадков и индекс динамики местообитаний [21], получены из ГИС-портала WorldClim -Global Climate Data [25]. Сведения о продолжительности безледного периода, озерности бассейна, скорости течения и густоте речной сети получены из гидрологических справочников [9,10].…”

Section: материалы и методы исследованийunclassified

Assessment of important environmental factors in formation of spatial structure of phytoplankton in large subarctic rivers (Eastern Siberia)

Габышев

Габышева

2019

Водные ресурсы

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On the basis of data-array analysis (2000–2011) of phytoplankton in large subarctic rivers; the rivers’ hydrochemical, hydrological, and morphological parameters; and climatic properties of the catchment-basin areas and by using stepwise discriminant analysis and clustering, it was determined that formation of phytoplankton spatial structure is mostly affected by climate rather than by physical-chemical properties of the river waters in northeastern Siberia. Floristic structure of phytoplankton is mostly connected to abiotic factors among phytoplankton-development indicators. The duration of vegetation-growth period is another important environmental factor.

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The Dynamic Habitat Indices (DHIs) from MODIS and global biodiversity

Cited by 102 publications

References 74 publications

Status of Phenological Research Using Sentinel-2 Data: A Review

Status of Phenological Research Using Sentinel-2 Data: A Review

A global map of terrestrial habitat types

Assessment of important environmental factors in formation of spatial structure of phytoplankton in large subarctic rivers (Eastern Siberia)

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