Remote sensing monitoring of photovoltaic panels

Can remote sensing data be used to monitor PV modules?

Especially spaceborne satellite remote sensing images offer numerous benefits, including rapid data acquisition, frequent updates, and independence from ground conditions [ 9 ]. Therefore, a lot of potential and a new research field is seen in the large-scale monitoring of PV modules through remote sensing data [ 13 ].

Why is remote sensing important for solar photovoltaics in China?

Solar photovoltaics (PV) are rapidly expanding in China as a popular renewable energy technology. Medium resolution remote sensing (RS) plays an important role in monitoring the spatial distribution of PV. As China is a country with vast and diverse landscapes, the classifier trained in small areas may have poor performance, to a large extent.

Can remote sensing data detect PV installation in urbanized coastal areas?

The performance of PV detection using medium resolution satellite images in highly urbanized coastal areas remains to be explored. Therefore, this study aims to detect PV installation in diverse landscapes using open multi-source remote sensing data.

Can remote sensing be used to detect PV in diverse landscapes?

However, the complexity of land cover types can bring much difficulty in PV identification. This study investigated detecting PV in diverse landscapes using freely accessible remote sensing data, aiming to evaluate the transferability of PV detection between rural and urbanized coastal area.

Can remote sensing detect PV installation?

Remote sensing can play an important role in detecting PV installation. Conventional methods, including household surveys and utility interconnection filings, are limited in their completeness and spatial resolution in collecting the distribution of PV plants .

Can hyperspectral imagery be used to identify solar PV modules?

Hyperspectral imagery provides crucial information to identify PV modules based on their physical absorption and reflection properties. This study investigated spectral signatures of spaceborne PRISMA data of 30 m low resolution for the first time, as well as airborne AVIRIS-NG data of 5.3 m medium resolution for the detection of solar PV.