Solar array placement, electricity generation, and cropland displacement across California's Central Valley

Stid, Jacob T; Shukla, Siddharth; Anctil, Annick; Kendall, A. D.; Rapp, Jeremy; Hyndman, D. W.

doi:10.1016/j.scitotenv.2022.155240

Cited by 6 publications

(8 citation statements)

References 41 publications

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“…We used remote sensing imagery, existing solar PV arrays, and GIS datasets to identify the most complete publicly available dataset of ground-mounted solar PV arrays co-located with agriculture in the CCV through 2018. We extracted all existing non-residential solar PV arrays from two geospatial datasets (Kruitwagen et al 7 and Stid et al 9,88 ) within the bounds of the CCV alluvial boundary 89 . We then removed duplicate arrays with preference given to Stid et al 9 to retain reported panel area and installation year.…”

Section: Identifying Agrisolar Pv Arrays Across the California Centra...mentioning

confidence: 99%

“…The resulting dataset (925 agriculturally co-located solar PV arrays) included 686 ground-mounted arrays from Stid et al 9,88 plus 239 from Kruitwagen et al 7 . For these sites, we calculated solar PV array peak capacity (kWp) by 91 :…”

Section: Identifying Agrisolar Pv Arrays Across the California Centra...mentioning

confidence: 99%

“…While recent research has identified the spatial and temporal extent of solar photovoltaic (PV) installations [4][5][6][7][8][9][10][11] , few studies have incorporated long-term FEW and economic effects of agricultural solar co-location 12 . Such interdisciplinary analyses are important as solar capacity in the United States (US) will need to grow more than 10-fold by 2050 to meet net-zero 1 Solar PV and cropland benefit from similar site characteristics including solar irradiation, topography, and climate, which can lead to land use competition 13 .…”

Section: Mainmentioning

confidence: 99%

“…As society attempts to mitigate these and other threats, in part by transitioning toward a net-zero carbon emissions energy system (hereafter "net-zero"), new energy installations should be deployed with consideration to the complete FEW nexus. All feasible paths to net-zero involve broad deployment of solar electricity generation 1-3 which shows promise for reducing energy and social costs, along with energy end-use, while producing millions of long-term jobs 3 .While recent research has identified the spatial and temporal extent of solar photovoltaic (PV) installations [4][5][6][7][8][9][10][11] , few studies have incorporated long-term FEW and economic effects of agricultural solar co-location 12 . Such interdisciplinary analyses are important as solar capacity in the United States (US) will need to grow more than 10-fold by 2050 to meet net-zero 1 Solar PV and cropland benefit from similar site characteristics including solar irradiation, topography, and climate, which can lead to land use competition 13 .…”

mentioning

confidence: 99%

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From Fields to Photovoltaics: Effects of Agrisolar Co-Location on Food, Energy, Water, and Economic Security

Stid,

Shukla,

Kendall

et al. 2023

Preprint

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Achieving sustainable net-zero energy production requires understanding how solar PV installations affect the landscape and its critical resources. To enhance this understanding, we investigate agrisolar co-location, which is land that is broadly co-managed for agricultural production, solar photovoltaic electricity production, and ecosystem services. We present a food, energy, water, and economic impact analysis of agricultural output offset by agrisolar co-location for 925 arrays (2.53 GWp covering 39.3 km2) spanning the California Central Valley. We find that agrisolar co-location displaces a significant amount of food production. However, agrisolar co-location also increases economic security for farmers and likely enhances water sustainability, and thus future agricultural production, by reducing irrigation water use and facilitating the fallowing of irrigated land. Given the unprecedented pace of solar PV expansion globally, these results highlight the need for a deeper understanding of the multifaceted outcomes of agricultural and solar PV co-location decisions.

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Section: Identifying Agrisolar Pv Arrays Across the California Centra...mentioning

confidence: 99%

Section: Identifying Agrisolar Pv Arrays Across the California Centra...mentioning

confidence: 99%

Section: Mainmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

From Fields to Photovoltaics: Effects of Agrisolar Co-Location on Food, Energy, Water, and Economic Security

Stid,

Shukla,

Kendall

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Common methods used to identify photovoltaic panels include participatory cartography [20], deep learning [21,22], and the random forest method [23]. The photovoltaic indexes were reported in the latest study [24]. The data types mainly include aerial RGB images [25], multispectral images [26], hyperspectral images [27], and thermal infrared images [28].…”

Section: Introductionmentioning

confidence: 99%

Mapping Photovoltaic Panels in Coastal China Using Sentinel-1 and Sentinel-2 Images and Google Earth Engine

et al. 2023

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Photovoltaic (PV) panels convert sunlight into electricity, and play a crucial role in energy decarbonization, and in promoting urban resources and environmental sustainability. The area of PV panels in China’s coastal regions is rapidly increasing, due to the huge demand for renewable energy. However, a rapid, accurate, and robust PV panel mapping approach, and a practical PV panel classification strategy for large-scale applications have not been established. Here, we developed a new approach that uses spectral and textural features to identify and map the PV panels there were in coastal China in 2021 using multispectral instrument (MSI) and synthetic aperture radar (SAR) images, and the Google Earth Engine (GEE), to differentiate PV panels according to their underlying surface properties. Our 10-m-spatial-resolution PV panel map had an overall accuracy of 94.31% in 2021. There was 510.78 km2 of PV panels in coastal China in 2021, which included 254.47 km2 of planar photovoltaic (PPV) panels, 170.70 km2 of slope photovoltaic (SPV) panels, and 85.61 km2 of water photovoltaic (WPV) panels. Our resultant PV panel map provides a detailed dataset for renewable layouts, ecological assessments, and the energy-related Sustainable Development Goals (SDGs).

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Mapping global water-surface photovoltaics with satellite images

Xia,

Li,

Guo

et al. 2023

Renewable and Sustainable Energy Reviews

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Solar array placement, electricity generation, and cropland displacement across California's Central Valley

Cited by 6 publications

References 41 publications

From Fields to Photovoltaics: Effects of Agrisolar Co-Location on Food, Energy, Water, and Economic Security

From Fields to Photovoltaics: Effects of Agrisolar Co-Location on Food, Energy, Water, and Economic Security

Mapping Photovoltaic Panels in Coastal China Using Sentinel-1 and Sentinel-2 Images and Google Earth Engine

Mapping global water-surface photovoltaics with satellite images

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