Integration of Landsat time-series vegetation indices improves consistency of change detection-Reference-Cited by-同舟云学术

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Integration of Landsat time-series vegetation indices improves consistency of change detection

Published:2023-04-13 Issue:1 Volume:16 Page:1276-1299
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Zhou Mingxing¹²³^ORCID,Li Dengqiu¹²,Liao Kuo⁴,Lu Dengsheng¹²^ORCID

Affiliation:

1. Institute of Geography, Fujian Normal University, Fuzhou, People’s Republic of China

2. Fujian Provincial Key Laboratory for Subtropical Resources and Environment, Fujian Normal University, Fuzhou, People’s Republic of China

3. School of Environmental & Resource Sciences, Zhejiang A&F University, Hangzhou, People’s Republic of China

4. Wuyi Mountain National Meteorological Observation Station, Wuyishan, People’s Republic of China

Funder

Natural Science Foundation of Fujian Province

Public welfare projects of Fujian Provincial Science and Technology Department

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,Computer Science Applications,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2023.2200040

Reference71 articles.

1. Forecasting Solar Power Using Hybrid Firefly and Particle Swarm Optimization (HFPSO) for Optimizing the Parameters in a Wavelet Transform-Adaptive Neuro Fuzzy Inference System (WT-ANFIS)

2. Spatial and temporal trends of drought effects in a heterogeneous semi-arid forest ecosystem

3. An Evaluation and Comparison of Four Dense Time Series Change Detection Methods Using Simulated Data

4. Canopy near-infrared reflectance and terrestrial photosynthesis

5. Satellite observations document trends consistent with a boreal forest biome shift

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4. Accurate vegetation destruction detection using remote sensing imagery based on the three-band difference vegetation index (TBDVI) and dual-temporal detection method;International Journal of Applied Earth Observation and Geoinformation;2024-03

5. A Novel Spectral Index for Vegetation Destruction Event Detection Based on Multispectral Remote Sensing Imagery;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

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