Jinao Photovoltaic Panel Identification

How to detect PV modules using imaging spectroscopy?

Therefore, PV modules detection using imaging spectroscopy data should focus on the physical characteristics and the spectral uniqueness of PV modules. PV modules commonly consist of several layers, including fully transparent glass covers for protection, highly transparent EVA films, and the core PV cell.

Should imaging spectroscopy data be used for PV identification?

This study aims to create greater awareness of the potential importance of imaging spectroscopy data for PV identification. As a physics-based approach, it is robust, transferable, and can provide data on PV coverage on a regional or global scale in short time.

How to identify photovoltaic panels?

Common methods used to identify photovoltaic panels include participatory cartography , deep learning [21, 22], and the random forest method . The photovoltaic indexes were reported in the latest study .

Can spectral and textural features identify PV panels in coastal China?

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.

What is a photovoltaic panel?

Photovoltaic (PV) technology is an effective means of converting sunlight into electricity and reducing greenhouse gas emissions . The cost of photovoltaic panel installation has gradually decreased with improvements in photovoltaic materials and the expansion of the photovoltaic industry.

What are photovoltaic indexes?

The photovoltaic indexes were reported in the latest study . The data types mainly include aerial RGB images , multispectral images , hyperspectral images , and thermal infrared images . The area of solar panels is small and distributed.