Satellites Reveal Spatial Heterogeneity in Dryland Photovoltaic Plants' Effects on Vegetation Dynamics

Author:

Xia Zilong12,Li Yingjie3,Guo Shanchuan12ORCID,Chen Ruishan4,Zhang Wei125,Guo Xiaona4,Zhang Xingang12,Du Peijun12

Affiliation:

1. Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Nanjing China

2. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing China

3. Natural Capital Project Woods Institute for the Environment Stanford University Stanford CA USA

4. School of Design Shanghai Jiaotong University Shanghai China

5. National Key Laboratory of Water Disaster Prevention Nanjing Hydraulic Research Institute Nanjing China

Abstract

AbstractLarge‐scale photovoltaic (PV) plants are growing rapidly in drylands because of the rich solar radiation and vast unutilized land. The transformation of landscapes in dryland has threatened local fragile vegetation. Existing studies have investigated the issue by field observations and satellite data, yet the spatial differences in vegetation changes due to dryland PV plants deployment and underlying driving mechanisms remain poorly understood. In this study, Landsat Normalized Difference Vegetation Index data were used to assess the vegetation changes disturbed by PV plants in China's drylands. We further identified environmental factors affecting vegetation changes based on random forest regression model. Our findings reveal the spatial heterogeneity in the impact of PV plants on vegetation dynamics—PV plant deployment promoted the growth of vegetation in the vast majority of arid and hyper‐arid drylands, while it tends to cause vegetation decline in the sub‐humid and semi‐arid drylands. The impact of PV plants on vegetation dynamics depends on local environmental conditions. We found that deploying PV plants in areas with sparse vegetation, low humidity, and long sunshine duration is more likely to promote vegetation restoration. The findings and data maps with highly detailed information can help guide solar energy operators in siting and ecological restoration to enhance techno–ecological synergies in the future.

Funder

National Natural Science Foundation of China

Publisher

American Geophysical Union (AGU)

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