Remote sensing of alpine treeline ecotone dynamics and phenology in Arunachal Pradesh Himalaya

Mohapatra, Jakesh; Singh, Chandra Prakash; Tripathi, Om Prakash; Pandya, Himanshu

doi:10.1080/01431161.2019.1608383

Cited by 26 publications

(16 citation statements)

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“…Phenological data derived from direct observations have also been conducted for several decades at permanent research sites [343]. The beginning of remote sensing data acquisition dates back to the early 1970s when the Landsat satellite mission began, and this is the period of origin of the oldest remote sensing data obtainable [111]. AVHRR data acquisition started at the beginning of the 1980s [375], and the MODIS sensor was introduced a decade later [258].…”

Section: Discussionmentioning

confidence: 99%

Remote Sensing in Studies of the Growing Season: A Bibliometric Analysis

2022

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Analyses of climate change based on point observations indicate an extension of the plant growing season, which may have an impact on plant production and functioning of natural ecosystems. Analyses involving remote sensing methods, which have added more detail to results obtained in the traditional way, have been carried out only since the 1980s. The paper presents the results of a bibliometric analysis of papers related to the growing season published from 2000–2021 included in the Web of Science database. Through filtering, 285 publications were selected and subjected to statistical processing and analysis of their content. This resulted in the identification of author teams that mostly focused their research on vegetation growth and in the selection of the most common keywords describing the beginning, end, and duration of the growing season. It was found that most studies on the growing season were reported from Asia, Europe, and North America (i.e., 32%, 28%, and 28%, respectively). The analyzed articles show the advantage of satellite data over low-altitude and ground-based data in providing information on plant vegetation. Over three quarters of the analyzed publications focused on natural plant communities. In the case of crops, wheat and rice were the most frequently studied plants (i.e., they were analyzed in over 30% and over 20% of publications, respectively).

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Section: Discussionmentioning

confidence: 99%

Remote Sensing in Studies of the Growing Season: A Bibliometric Analysis

2022

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“…In a recent study on Greenland's glacial cap, the researchers note that ‘… collecting historical data sets is probably more important at this point than having yet another satellite do more of the same stuff… ’ (Schiermeier, 2016). In terms of spatial resolution, contemporary satellite and airborne images are perfectly appropriate to track, for example, tree leafing phenology and tree line shifts across open landscapes (Mohapatra et al, 2019), but they are often not suitable to track flowering phenology of herbaceous vegetation, range shifts of individual plants or in forests where below‐canopy biodiversity is not visible from above the canopy. Ground‐based photography is thus often able to provide more accurate and long‐term information of spatial and temporal vegetation change compared to remote sensing data (Fitzgerald et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

The use of photos to investigate ecological change

et al. 2022

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Global change is causing ecosystems to change at unprecedented rates and the urgency to quantify ecological change is high. We therefore need all possible sources of ecological data to address key knowledge gaps. Ground‐based photos are a form of remote sensing and an unconventional data source with a high potential to improve our understanding of ecological change. They can provide invaluable information on ecological conditions in the past and present at relevant spatiotemporal scales that is very difficult to obtain with other approaches. Here we review the use of ground‐based photos in a set of relevant ecological research topics, such as biodiversity and community ecology, phenology, global change ecology and landscape ecology. We highlight three main photo‐based methods in ecological research (repeat photography, time‐lapse photography and public archives), alongside which we discuss three case studies to demonstrate novel applications of these methods, to answer fundamental ecological questions. Synthesis. Photos can significantly support ecological research to improve our understanding of biotic responses in a rapidly changing world. Photos cover relatively large temporal and spatial scales, and can provide large amounts of information with limited time investment. To exploit their full potential, we need to invest not only in technological advances to compile, process and analyse images but also in proper data management.

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“…At present, the analysis of drivers affecting vegetation patterns in the Tibetan Plateau region is mostly concentrated in the analysis of climatic factors, and relatively little research has been conducted on topographic control mechanisms [24; 26; 27]. Given the inaccessibility of most mountainous regions, remote sensing (RS) and geographic information system (GIS) technology stand out as powerful tools for monitoring vegetation cover changes in mountainous areas by providing continuous, spatially detailed satellite data on mountainous vegetation cover [28]. With the development of RS technology, the types of remote sensing sensors have become more and more diversified, and the large-scale long time series vegetation dynamics has gradually developed into a hot spot for global change research, among which MODIS vegetation cover product data is regarded as one of the most effective data products for vegetation productivity analysis [29].…”

Section: Introductionmentioning

confidence: 99%

Multiple Effects of Topographic Factors on Spatio-temporal Variations of Vegetation Patterns in the Three Parallel Rivers Region, Southeast Tibet

Wang¹,

Wang²,

Naudiyal³

et al. 2021

Preprint

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Topographic factors are recognized as one of the key factors influencing vegetation distribution patterns, and studying the interactions between them can contribute to enhancing our understanding of future vegetation dynamics. We used the Moderate-resolution Imaging Spectroradiometer Normalized Differential Vegetation Index (MODIS NDVI) image dataset (2000-2019), combined with Digital Elevation Model (DEM), and vegetation type data for trend analysis, and explored NDVI variation and its relationship with topographic factors through an integrated geographically-weighted model in the Three Parallel Rivers Region (TPRR) of southeastern Tibetan plateau in the past 20 years. Our results indicated that there was no significant increase of NDVI in the entire basin between 2000-2019, except for the Lancang River basin. In the year 2004, abrupt changes in NDVI were observed across the whole basin and each sub-basin. During 2000-2019, the mean NDVI value of the whole basin increased initially and then decreased with the increasing elevation. However, it changed marginally with changes in slope and aspect. We observed a distinct spatial heterogeneity in vegetation patterns with elevation, with vegetation in the southern regions showing higher NDVI than the north as a whole. Most of the vegetation cover was concentrated in the slope range of 8~35°, with no significant difference in distribution except flat-land. Furthermore, from 2000 to 2019, the vegetation cover in the TPRR showed an improving trend with the changes of various topographic factors, with the largest improvement area (36.10%) in the slightly improved category. The improved region was mainly distributed in the source area of the Jinsha River basin and the southern part of the whole basin. Geographically weighted regression (GWR) analysis showed that elevation was negatively correlated with NDVI trends in most areas, especially in the middle reaches of Nujiang River basin and Jinsha River basin, where the influence of slope and aspect on NDVI change was considerably much smaller than elevation.

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Remote sensing of alpine treeline ecotone dynamics and phenology in Arunachal Pradesh Himalaya

Cited by 26 publications

References 50 publications

Remote Sensing in Studies of the Growing Season: A Bibliometric Analysis

Remote Sensing in Studies of the Growing Season: A Bibliometric Analysis

The use of photos to investigate ecological change

Multiple Effects of Topographic Factors on Spatio-temporal Variations of Vegetation Patterns in the Three Parallel Rivers Region, Southeast Tibet

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