Spatiotemporal Variations of Vegetation NPP Based on GF-SG and kNDVI and Its Response to Climate Change and Human Activities: A Case Study of the Zoigê Plateau

Net primary productivity (NPP) is a key metric for evaluating ecosystem carbon sink capacity and defining vegetation. Despite extensive research on vegetation NPP, much relies on coarse spatial resolution data, which often overlooks regional spatial heterogeneity, causing inaccuracies in NPP estimates. Therefore, this study employed the improved CASA model, based on GF-SG and kNDVI methods, to estimate vegetation NPP at a 30 m spatial resolution on the Zoigê Plateau from 2001 to 2020. The effects of anthropogenic and climatic factors on NPP were quantified through residual and partial correlation analyses. These results indicated the following: (1) NDVI derived from the GF-SG fusion method aligns closely with Landsat NDVI (R2 ≈ 0.9). When contrasted with using NDVI alone, incorporating kNDVI into the CASA model enhances NPP assessment accuracy. (2) Vegetation NPP on the Zoigê Plateau has fluctuated upward by 2.09 gC·m−2·a−1 over the last two decades, with higher values centrally and lower at the edges. (3) Monthly partial correlation analysis indicates almost no temporal effects in NPP response to temperature (97.42%) but significant cumulative effects in response to precipitation (80.3%), with longer accumulation periods in the south. Annual analysis reveals that NPP correlates more strongly with temperature than precipitation. (4) NPP changes are jointly influenced by climate change (48.46%) and human activities (51.54%), with the latter being the dominant factor. This study deepens the understanding of NPP dynamics in the Zoigê Plateau and offers insights for estimating NPP at high spatial-temporal resolutions.

Authors

Institutions

Publication Details

Journal
Forests
Published
2024-12-27
DOI
https://doi.org/10.3390/f16010032
Citations
3
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
1.38

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Spatiotemporal Variations of Vegetation NPP Based on GF-SG and kNDVI and Its Response to Climate Change and Human Activities: A Case Study of the Zoigê Plateau

Zhengwei He, Yan Yuan, Li He, Yang Zhao et al.
3 citations
Forests
Remote Sensing in Agriculture
1.38
article

Spatiotemporal Variations of Vegetation NPP Based on GF-SG and kNDVI and Its Response to Climate Change and Human Activities: A Case Study of the Zoigê Plateau

Zhengwei He, Yan Yuan, Li He, Yang Zhao, Yixian Xiao, Wanting Zeng, Jintai Pang, Yuxin Cen
article en
3 citations

Abstract

Net primary productivity (NPP) is a key metric for evaluating ecosystem carbon sink capacity and defining vegetation. Despite extensive research on vegetation NPP, much relies on coarse spatial resolution data, which often overlooks regional spatial heterogeneity, causing inaccuracies in NPP estimates. Therefore, this study employed the improved CASA model, based on GF-SG and kNDVI methods, to estimate vegetation NPP at a 30 m spatial resolution on the Zoigê Plateau from 2001 to 2020. The effects of anthropogenic and climatic factors on NPP were quantified through residual and partial correlation analyses. These results indicated the following: (1) NDVI derived from the GF-SG fusion method aligns closely with Landsat NDVI (R2 ≈ 0.9). When contrasted with using NDVI alone, incorporating kNDVI into the CASA model enhances NPP assessment accuracy. (2) Vegetation NPP on the Zoigê Plateau has fluctuated upward by 2.09 gC·m−2·a−1 over the last two decades, with higher values centrally and lower at the edges. (3) Monthly partial correlation analysis indicates almost no temporal effects in NPP response to temperature (97.42%) but significant cumulative effects in response to precipitation (80.3%), with longer accumulation periods in the south. Annual analysis reveals that NPP correlates more strongly with temperature than precipitation. (4) NPP changes are jointly influenced by climate change (48.46%) and human activities (51.54%), with the latter being the dominant factor. This study deepens the understanding of NPP dynamics in the Zoigê Plateau and offers insights for estimating NPP at high spatial-temporal resolutions.

ForestsVol. 16(1)
Chengdu University of Technology (CN)
National Natural Science Foundation of China
Climate action
Openalex Percentile: Top 17%
Remote Sensing in Agriculture
1.38
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.