Ecosystem functional assessment based on the "optical type" concept and self-similarity patterns: An application using MODIS-NDVI time series autocorrelation
Huesca, Margarita ; Merino-de-Miguel, Silvia ; Eklundh, Lars LU
; Litago, Javier
; Cicuendez, Victor
; Rodriguez-Rastrero, Manuel
; Ustin, Susan L.
and Palacios-Orueta, Alicia
(2015)
In International Journal of Applied Earth Observation and Geoinformation
43.
p.132-148
- Abstract
- Remote sensing (RS) time series are an excellent operative source for information about the land surface across several scales and different levels of landscape heterogeneity. Ustin and Gamon (2010) proposed the new concept of "optical types" (OT), meaning "optically distinguishable functional types", as a way to better understand remote sensing signals related to the actual functional behavior of species that share common physiognomic forms but differ in functionality. Whereas the OT approach seems to be promising and consistent with ecological theory as a way to monitor vegetation derived from RS, it received little implementation. This work presents a method for implementing the OT concept for efficient monitoring of ecosystems based on... (More)
- Remote sensing (RS) time series are an excellent operative source for information about the land surface across several scales and different levels of landscape heterogeneity. Ustin and Gamon (2010) proposed the new concept of "optical types" (OT), meaning "optically distinguishable functional types", as a way to better understand remote sensing signals related to the actual functional behavior of species that share common physiognomic forms but differ in functionality. Whereas the OT approach seems to be promising and consistent with ecological theory as a way to monitor vegetation derived from RS, it received little implementation. This work presents a method for implementing the OT concept for efficient monitoring of ecosystems based on RS time series. We propose relying on an ecosystem's repetitive pattern in the temporal domain (self-similarity) to assess its dynamics. Based on this approach, our main hypothesis is that distinct dynamics are intrinsic to a specific OT. Self-similarity level in the temporal domain within a broadleaf forest class was quantitatively assessed using the auto-correlation function (ACF), from statistical time series analysis. A vector comparison classification method, spectral angle mapper, and principal component analysis were used to identify general patterns related to forest dynamics. Phenological metrics derived from MOD IS NDVI time series using the TIMESAT software, together with information from the National Forest Map were used to explain the different dynamics found. Results showed significant and highly stable self-similarity patterns in OTs that corresponded to forests under non-moisture-limited environments with an adaptation strategy based on a strong phenological synchrony with climate seasonality. These forests are characterized by dense closed canopy deciduous forests associated with high productivity and low biodiversity in terms of dominant species. Forests in transitional areas were associated with patterns of less temporal stability probably due to mixtures of different adaptation strategies (i.e., deciduous, marcescent and evergreen species) and higher functional diversity related to climate variability at long and short terms. A less distinct seasonality and even a double season appear in the OT of the broadleaf Mediterranean forest characterized by an open canopy dominated by evergreen-sclerophyllous formations. Within this forest, understory and overstory dynamics maximize functional diversity resulting in contrasting traits adapted to summer drought, winter frosts, and high precipitation variability. (C) 2015 Elsevier B.V. All rights reserved. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8220768
- author
- Huesca, Margarita
; Merino-de-Miguel, Silvia
; Eklundh, Lars
LU
; Litago, Javier
; Cicuendez, Victor
; Rodriguez-Rastrero, Manuel
; Ustin, Susan L.
and Palacios-Orueta, Alicia
- organization
- publishing date
- 2015
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- MODIS time series, Autocorrelation function, Phenometrics, Optical type, Ecosystem dynamics
- in
- International Journal of Applied Earth Observation and Geoinformation
- volume
- 43
- pages
- 132 - 148
- publisher
- Elsevier
- external identifiers
-
- wos:000362144000011
- scopus:84943654104
- ISSN
- 1569-8432
- DOI
- 10.1016/j.jag.2015.04.008
- language
- English
- LU publication?
- yes
- id
- 3b1bbe70-bda5-4c6a-98b7-bf18688347b5 (old id 8220768)
- date added to LUP
- 2016-04-01 14:24:18
- date last changed
- 2022-04-14 17:38:50
@article{3b1bbe70-bda5-4c6a-98b7-bf18688347b5,
abstract = {{Remote sensing (RS) time series are an excellent operative source for information about the land surface across several scales and different levels of landscape heterogeneity. Ustin and Gamon (2010) proposed the new concept of "optical types" (OT), meaning "optically distinguishable functional types", as a way to better understand remote sensing signals related to the actual functional behavior of species that share common physiognomic forms but differ in functionality. Whereas the OT approach seems to be promising and consistent with ecological theory as a way to monitor vegetation derived from RS, it received little implementation. This work presents a method for implementing the OT concept for efficient monitoring of ecosystems based on RS time series. We propose relying on an ecosystem's repetitive pattern in the temporal domain (self-similarity) to assess its dynamics. Based on this approach, our main hypothesis is that distinct dynamics are intrinsic to a specific OT. Self-similarity level in the temporal domain within a broadleaf forest class was quantitatively assessed using the auto-correlation function (ACF), from statistical time series analysis. A vector comparison classification method, spectral angle mapper, and principal component analysis were used to identify general patterns related to forest dynamics. Phenological metrics derived from MOD IS NDVI time series using the TIMESAT software, together with information from the National Forest Map were used to explain the different dynamics found. Results showed significant and highly stable self-similarity patterns in OTs that corresponded to forests under non-moisture-limited environments with an adaptation strategy based on a strong phenological synchrony with climate seasonality. These forests are characterized by dense closed canopy deciduous forests associated with high productivity and low biodiversity in terms of dominant species. Forests in transitional areas were associated with patterns of less temporal stability probably due to mixtures of different adaptation strategies (i.e., deciduous, marcescent and evergreen species) and higher functional diversity related to climate variability at long and short terms. A less distinct seasonality and even a double season appear in the OT of the broadleaf Mediterranean forest characterized by an open canopy dominated by evergreen-sclerophyllous formations. Within this forest, understory and overstory dynamics maximize functional diversity resulting in contrasting traits adapted to summer drought, winter frosts, and high precipitation variability. (C) 2015 Elsevier B.V. All rights reserved.}},
author = {{Huesca, Margarita and Merino-de-Miguel, Silvia and Eklundh, Lars and Litago, Javier and Cicuendez, Victor and Rodriguez-Rastrero, Manuel and Ustin, Susan L. and Palacios-Orueta, Alicia}},
issn = {{1569-8432}},
keywords = {{MODIS time series; Autocorrelation function; Phenometrics; Optical type; Ecosystem dynamics}},
language = {{eng}},
pages = {{132--148}},
publisher = {{Elsevier}},
series = {{International Journal of Applied Earth Observation and Geoinformation}},
title = {{Ecosystem functional assessment based on the "optical type" concept and self-similarity patterns: An application using MODIS-NDVI time series autocorrelation}},
url = {{http://dx.doi.org/10.1016/j.jag.2015.04.008}},
doi = {{10.1016/j.jag.2015.04.008}},
volume = {{43}},
year = {{2015}},
}