Jiang Mei s photovoltaic panels

How to extract PV panel area from crystalline silicon photovoltaic modules?

Both studies demonstrated that accurate PV panels area can be extracted using red, green, and blue band images. Therefore, we used RGB band information to extract PV panel information. The core part of crystalline silicon photovoltaic modules is the solar cell, which mostly appears in a deep blue color to enhance the absorption of sunlight [ 37 ].

How has the photovoltaic market changed over the past two years?

The photovoltaic (PV) market has experienced rapid growth over the past two decades owing to the reduced cost of PV modules and support programs from governments (La Monaca and Ryan, 2017; Yan et al., 2019). Between 2000 and 2020, worldwide installed capacity increased from 4 W to 714 GW, consistently exceeding expectations (IRENA, 2021).

Does rcham improve the accuracy of PV panel extraction?

The higher value of IoU suggests that RCHAM enhances the completeness of the PV panel extraction, resulting in better alignment between the extracted PV panels and the ground truth, as shown in the second column and the fourth column of Figure 6.

Can pkgpvn extract photovoltaic panels from high-resolution optical remote sensing images?

Moreover, most previous studies have overlooked the unique color characteristics of PV panels. To alleviate these deficiencies and limitations, a method for extracting photovoltaic panels from high-resolution optical remote sensing images guided by prior knowledge (PKGPVN) is proposed.