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Varying sensitivities of RED-NIR-based vegetation indices to the input reflectance affect the detected long-term trends

Tian, Qing ; Jin, Hongxiao LU ; Fensholt, Rasmus ; Tagesson, Torbern LU ; Feng, Luwei and Tian, Feng LU (2026) In ISPRS Journal of Photogrammetry and Remote Sensing 233. p.247-265
Abstract

Widespread vegetation changes have been evidenced by satellite-observed long-term trends over decades in vegetation indices (VIs). However, many issues can affect the derived VIs trends, among which the inherent difference between VIs calculated from the same input reflectance has not been investigated. Here, we compared global long-term trends in six widely used RED-NIR (near-infrared)-based VIs calculated from the MODIS nadir bidirectional reflectance distribution function (BRDF) adjusted product (MCD43A4) during 2000–2023, including normalized difference vegetation index (NDVI), kernel NDVI (kNDVI), 2-band enhanced vegetation index (EVI2), near-infrared reflectance of vegetation (NIRv), difference vegetation index (DVI), and plant... (More)

Widespread vegetation changes have been evidenced by satellite-observed long-term trends over decades in vegetation indices (VIs). However, many issues can affect the derived VIs trends, among which the inherent difference between VIs calculated from the same input reflectance has not been investigated. Here, we compared global long-term trends in six widely used RED-NIR (near-infrared)-based VIs calculated from the MODIS nadir bidirectional reflectance distribution function (BRDF) adjusted product (MCD43A4) during 2000–2023, including normalized difference vegetation index (NDVI), kernel NDVI (kNDVI), 2-band enhanced vegetation index (EVI2), near-infrared reflectance of vegetation (NIRv), difference vegetation index (DVI), and plant phenology index (PPI). We identified two distinct groups of VIs, i.e., (1) NDVI and kNDVI, and (2) EVI2, NIRv, DVI, and PPI, which shared similar trends within the group but showed significant directional differences between groups in 17.4% of the studied area. Only 20.5% of the global land surface showed consistent trends. Based on the radiation transfer model and remote sensing observations, we demonstrated that the two groups of VIs differed in their sensitivities to RED and NIR reflectance. These differences lead to inconsistent long-term trends arising from variations in vegetation type, mixed pixel effects, saturation, and asynchronous changes in vegetation chlorophyll content and structural attributes. Comparisons with ground-observed leaf area index (LAI), flux tower gross primary productivity (GPP), and PhenoCam green chromatic coordinate (GCC) further revealed that the EVI2, NIRv, DVI, and PPI trends corresponded more closely with LAI and GPP trends, whereas the NDVI and kNDVI trends were more strongly associated with GCC trends. Our results highlight that long-term vegetation trends derived from different RED–NIR-based VIs must be interpreted by considering their intrinsic sensitivities to biophysical properties, which is essential for reliable assessments of vegetation dynamics.

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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Red and near-infrared reflectance, Vegetation biophysical properties, Vegetation indices, Vegetation long-term trend
in
ISPRS Journal of Photogrammetry and Remote Sensing
volume
233
pages
19 pages
publisher
Elsevier
external identifiers
  • scopus:105028956348
ISSN
0924-2716
DOI
10.1016/j.isprsjprs.2026.01.028
language
English
LU publication?
yes
id
7a5ac7ee-3284-4493-b476-70f9ab12c3ce
date added to LUP
2026-02-18 12:21:44
date last changed
2026-02-19 09:27:56
@article{7a5ac7ee-3284-4493-b476-70f9ab12c3ce,
  abstract     = {{<p>Widespread vegetation changes have been evidenced by satellite-observed long-term trends over decades in vegetation indices (VIs). However, many issues can affect the derived VIs trends, among which the inherent difference between VIs calculated from the same input reflectance has not been investigated. Here, we compared global long-term trends in six widely used RED-NIR (near-infrared)-based VIs calculated from the MODIS nadir bidirectional reflectance distribution function (BRDF) adjusted product (MCD43A4) during 2000–2023, including normalized difference vegetation index (NDVI), kernel NDVI (kNDVI), 2-band enhanced vegetation index (EVI2), near-infrared reflectance of vegetation (NIRv), difference vegetation index (DVI), and plant phenology index (PPI). We identified two distinct groups of VIs, i.e., (1) NDVI and kNDVI, and (2) EVI2, NIRv, DVI, and PPI, which shared similar trends within the group but showed significant directional differences between groups in 17.4% of the studied area. Only 20.5% of the global land surface showed consistent trends. Based on the radiation transfer model and remote sensing observations, we demonstrated that the two groups of VIs differed in their sensitivities to RED and NIR reflectance. These differences lead to inconsistent long-term trends arising from variations in vegetation type, mixed pixel effects, saturation, and asynchronous changes in vegetation chlorophyll content and structural attributes. Comparisons with ground-observed leaf area index (LAI), flux tower gross primary productivity (GPP), and PhenoCam green chromatic coordinate (GCC) further revealed that the EVI2, NIRv, DVI, and PPI trends corresponded more closely with LAI and GPP trends, whereas the NDVI and kNDVI trends were more strongly associated with GCC trends. Our results highlight that long-term vegetation trends derived from different RED–NIR-based VIs must be interpreted by considering their intrinsic sensitivities to biophysical properties, which is essential for reliable assessments of vegetation dynamics.</p>}},
  author       = {{Tian, Qing and Jin, Hongxiao and Fensholt, Rasmus and Tagesson, Torbern and Feng, Luwei and Tian, Feng}},
  issn         = {{0924-2716}},
  keywords     = {{Red and near-infrared reflectance; Vegetation biophysical properties; Vegetation indices; Vegetation long-term trend}},
  language     = {{eng}},
  pages        = {{247--265}},
  publisher    = {{Elsevier}},
  series       = {{ISPRS Journal of Photogrammetry and Remote Sensing}},
  title        = {{Varying sensitivities of RED-NIR-based vegetation indices to the input reflectance affect the detected long-term trends}},
  url          = {{http://dx.doi.org/10.1016/j.isprsjprs.2026.01.028}},
  doi          = {{10.1016/j.isprsjprs.2026.01.028}},
  volume       = {{233}},
  year         = {{2026}},
}