Phenological Characteristics of Global Ecosystems Based on Optical, Fluorescence, and Microwave Remote Sensing
Growing seasons of vegetation generally start earlier and last longer due to anthropogenic warming. To facilitate the detection and monitoring of these phenological changes, we developed a discrete, hierarchical set of global “phenoregions” using self-organizing maps and three sa...
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doaj-7d1931ac84124b6fa63171c3294cd7f82020-11-25T02:33:56ZengMDPI AGRemote Sensing2072-42922020-02-0112467110.3390/rs12040671rs12040671Phenological Characteristics of Global Ecosystems Based on Optical, Fluorescence, and Microwave Remote SensingMatthew Dannenberg0Xian Wang1Dong Yan2William Smith3Department of Geographical and Sustainability Sciences, University of Iowa, Iowa City, IA 52242, USASchool of Natural Resources and the Environment, University of Arizona, Tucson, AZ 85721, USASchool of Natural Resources and the Environment, University of Arizona, Tucson, AZ 85721, USASchool of Natural Resources and the Environment, University of Arizona, Tucson, AZ 85721, USAGrowing seasons of vegetation generally start earlier and last longer due to anthropogenic warming. To facilitate the detection and monitoring of these phenological changes, we developed a discrete, hierarchical set of global “phenoregions” using self-organizing maps and three satellite-based vegetation indices representing multiple aspects of vegetation structure and function, including the normalized difference vegetation index (NDVI), solar-induced chlorophyll fluorescence (SIF), and vegetation optical depth (VOD). Here, we describe the distribution and phenological characteristics of these phenoregions, including their mean temperature and precipitation, differences among the three satellite indices, the number of annual growth cycles within each phenoregion and index, and recent changes in the land area of each phenoregion. We found that the phenoregions “self-organized” along two primary dimensions: degree of seasonality and peak productivity. The three satellite-based indices each appeared to provide unique information on land surface phenology, with SIF and VOD improving the ability to detect distinct annual and subannual growth cycles in some regions. Over the nine-year study period (limited in length by the short satellite SIF record), there was generally a decrease in the spatial extent of the highest productivity phenoregions, though whether due to climate or land use change remains unclear.https://www.mdpi.com/2072-4292/12/4/671phenoregionssolar-induced fluorescence (sif)normalized difference vegetation index (ndvi)vegetation optical depth (vod)time series analysisself-organizing maps (som)classification |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Matthew Dannenberg Xian Wang Dong Yan William Smith |
spellingShingle |
Matthew Dannenberg Xian Wang Dong Yan William Smith Phenological Characteristics of Global Ecosystems Based on Optical, Fluorescence, and Microwave Remote Sensing Remote Sensing phenoregions solar-induced fluorescence (sif) normalized difference vegetation index (ndvi) vegetation optical depth (vod) time series analysis self-organizing maps (som) classification |
author_facet |
Matthew Dannenberg Xian Wang Dong Yan William Smith |
author_sort |
Matthew Dannenberg |
title |
Phenological Characteristics of Global Ecosystems Based on Optical, Fluorescence, and Microwave Remote Sensing |
title_short |
Phenological Characteristics of Global Ecosystems Based on Optical, Fluorescence, and Microwave Remote Sensing |
title_full |
Phenological Characteristics of Global Ecosystems Based on Optical, Fluorescence, and Microwave Remote Sensing |
title_fullStr |
Phenological Characteristics of Global Ecosystems Based on Optical, Fluorescence, and Microwave Remote Sensing |
title_full_unstemmed |
Phenological Characteristics of Global Ecosystems Based on Optical, Fluorescence, and Microwave Remote Sensing |
title_sort |
phenological characteristics of global ecosystems based on optical, fluorescence, and microwave remote sensing |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2020-02-01 |
description |
Growing seasons of vegetation generally start earlier and last longer due to anthropogenic warming. To facilitate the detection and monitoring of these phenological changes, we developed a discrete, hierarchical set of global “phenoregions” using self-organizing maps and three satellite-based vegetation indices representing multiple aspects of vegetation structure and function, including the normalized difference vegetation index (NDVI), solar-induced chlorophyll fluorescence (SIF), and vegetation optical depth (VOD). Here, we describe the distribution and phenological characteristics of these phenoregions, including their mean temperature and precipitation, differences among the three satellite indices, the number of annual growth cycles within each phenoregion and index, and recent changes in the land area of each phenoregion. We found that the phenoregions “self-organized” along two primary dimensions: degree of seasonality and peak productivity. The three satellite-based indices each appeared to provide unique information on land surface phenology, with SIF and VOD improving the ability to detect distinct annual and subannual growth cycles in some regions. Over the nine-year study period (limited in length by the short satellite SIF record), there was generally a decrease in the spatial extent of the highest productivity phenoregions, though whether due to climate or land use change remains unclear. |
topic |
phenoregions solar-induced fluorescence (sif) normalized difference vegetation index (ndvi) vegetation optical depth (vod) time series analysis self-organizing maps (som) classification |
url |
https://www.mdpi.com/2072-4292/12/4/671 |
work_keys_str_mv |
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