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Analyzing Ecological Vulnerability and Vegetation Phenology Response Using NDVI Time Series Data and the BFAST Algorithm

https://doi.org/10.3390/rs12203371
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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TIMESAT—a program for analyzing time-series of satellite sensor data
inferredcites →https://doi.org/10.1016/j.ecolind.2013.02.004openalex-snapshot
Phenology-based, remote sensing of post-burn disturbance windows in rangelands
inferredcites →https://doi.org/10.1016/j.ecolind.2016.05.028openalex-snapshot
Establishing an ecological vulnerability assessment indicator system for spatial recognition and management of ecologically vulnerable areas in highly urbanized regions: A case study of Shenzhen, China
inferredcites →https://doi.org/10.1016/j.ecolind.2017.10.044openalex-snapshot
Method for evaluating ecological vulnerability under climate change based on remote sensing: A case study
inferredcites →https://doi.org/10.1016/j.ecolind.2018.05.065openalex-snapshot
Vegetation changes in the Three-River Headwaters Region of the Tibetan Plateau of China
inferredcites →https://doi.org/10.1016/j.ecolind.2018.07.060openalex-snapshot
Assessment of vegetation degradation in mountainous pastures of the Western Tien-Shan, Kyrgyzstan, using eMODIS NDVI
inferredcites →https://doi.org/10.1016/j.ecolind.2020.106456openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.ecolind.2020.106642openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.rse.2014.08.023openalex-snapshot
Effectiveness of the BFAST algorithm for detecting vegetation response patterns in a semi-arid region
inferredcites →https://doi.org/10.1016/j.rse.2016.01.001openalex-snapshot
The vegetation greenness trend in Canada and US Alaska from 1984–2012 Landsat data
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Remote sensing of vegetation dynamics in drylands: Evaluating vegetation optical depth (VOD) using AVHRR NDVI and in situ green biomass data over West African Sahel
inferredcites →https://doi.org/10.1016/j.rse.2017.11.017openalex-snapshot
Large-scale detection of vegetation dynamics and their potential drivers using MODIS images and BFAST: A case study in Quebec, Canada
inferredcites →https://doi.org/10.1016/j.rse.2018.11.011openalex-snapshot
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Abrupt Change in Ecological Systems: Inference and Diagnosis
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Climate change in Europe. 1. Impact on terrestrial ecosystems and biodiversity. A review
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inferredcites →https://doi.org/10.1088/1748-9326/aacf6fopenalex-snapshot
Using an integrated social-ecological analysis to detect effects of household herding practices on indicators of rangeland resilience in Mongolia
inferredcites →https://doi.org/10.1093/jxb/erp156openalex-snapshot
Scientific and technical challenges in remote sensing of plant canopy reflectance and fluorescence
inferredcites →https://doi.org/10.1109/tgrs.2002.802519openalex-snapshot
Seasonality extraction by function fitting to time-series of satellite sensor data
inferredcites →https://doi.org/10.1109/tgrs.2008.921412openalex-snapshot
TiSeG: A Flexible Software Tool for Time-Series Generation of MODIS Data Utilizing the Quality Assessment Science Data Set
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Transient population dynamics impede restoration and may promote ecosystem transformation after disturbance
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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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inferred← citeshttps://doi.org/10.1002/eco.2726openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-031-90163-8_6openalex-snapshot
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