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Remote Sensing of Land Surface Phenology

Land surface phenology (LSP) uses remote sensing to monitor seasonal dynamics in vegetated land surfaces and retrieve phenological metrics (transition dates, rate of change, annual integrals, etc.). LSP has developed rapidly in the last few decades. Both regional and global LSP products have been ro...

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Bibliographic Details
Main Author: Ma, Xuanlong
Other Authors: Jin, Jiaxin, Zhu, Xiaolin, Zhou, Yuke
Format: eBook
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2022
Subjects:
Qinghai-tibetan Plateau
Carbon Cycle
Seasonally Dry Tropical Forest
Digital Camera
The Loess Plateau
Soil Moisture
Contribution
Yield Potential
N/a
Enhanced Vegetation Index
Urban Heat Island Effect
Photosynthesis
Yield Gap
History Of Engineering And Technology / Bicssc
Random Forest Model
Development Stage
Autumn Phenology
High Elevation
Different Drivers
Turning Point
Climatic Limitation
Crop Sowing Date
Technology: General Issues / Bicssc
Urbanization
Solar-induced Chlorophyll Fluorescence
Structural Equation Model
Mongolian Oak
Water Use Efficiency
Qilian Mountains
Vegetation Indexes
Gross Primary Production
Carbon Exchange
Driving Factors
Plant Phenology
Gpp
Snow Cover
Environmental Science, Engineering And Technology / Bicssc
Evapotranspiration
Google Earth Engine
Three-river Headwaters Region
Spatiotemporal Dynamics
Land Surface Phenology
Remote Sensing
Land Surface Temperature
Phenology
Satellite Data
Sap Flow
Process-based Model
Spatiotemporal Variations
Hangzhou
Climate Change
Snow Phenology
Data Suitability
Human Activities
Northeast China
Ndpi
Climate Changes
Spatiotemporal Patterns
Spatial Scaling Effects
Vegetation Dynamics
Modis
Vegetation Phenology
Arctic
Ndvi
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary:Land surface phenology (LSP) uses remote sensing to monitor seasonal dynamics in vegetated land surfaces and retrieve phenological metrics (transition dates, rate of change, annual integrals, etc.). LSP has developed rapidly in the last few decades. Both regional and global LSP products have been routinely generated and play prominent roles in modeling crop yield, ecological surveillance, identifying invasive species, modeling the terrestrial biosphere, and assessing impacts on urban and natural ecosystems. Recent advances in field and spaceborne sensor technologies, as well as data fusion techniques, have enabled novel LSP retrieval algorithms that refine retrievals at even higher spatiotemporal resolutions, providing new insights into ecosystem dynamics. Meanwhile, rigorous assessment of the uncertainties in LSP retrievals is ongoing, and efforts to reduce these uncertainties represent an active research area. Open source software and hardware are in development, and have greatly facilitated the use of LSP metrics by scientists outside the remote sensing community. This reprint covers the latest developments in sensor technologies, LSP retrieval algorithms and validation strategies, and the use of LSP products in a variety of fields. It aims to summarize the ongoing diverse LSP developments and boost discussions on future research prospects.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (276 p.)
ISBN:books978-3-0365-5326-9
9783036553269
9783036553252

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