An Artificial Intelligence Dataset for Solar Energy Locations in India

by   Anthony Ortiz, et al.

Rapid development of renewable energy sources, particularly solar photovoltaics, is critical to mitigate climate change. As a result, India has set ambitious goals to install 300 gigawatts of solar energy capacity by 2030. Given the large footprint projected to meet these renewable energy targets the potential for land use conflicts over environmental and social values is high. To expedite development of solar energy, land use planners will need access to up-to-date and accurate geo-spatial information of PV infrastructure. The majority of recent studies use either predictions of resource suitability or databases that are either developed thru crowdsourcing that often have significant sampling biases or have time lags between when projects are permitted and when location data becomes available. Here, we address this shortcoming by developing a spatially explicit machine learning model to map utility-scale solar projects across India. Using these outputs, we provide a cumulative measure of the solar footprint across India and quantified the degree of land modification associated with land cover types that may cause conflicts. Our analysis indicates that over 74% of solar development In India was built on landcover types that have natural ecosystem preservation, and agricultural values. Thus, with a mean accuracy of 92% this method permits the identification of the factors driving land suitability for solar projects and will be of widespread interest for studies seeking to assess trade-offs associated with the global decarbonization of green-energy systems. In the same way, our model increases the feasibility of remote sensing and long-term monitoring of renewable energy deployment targets.


page 2

page 3

page 4

page 5

page 7

page 8

page 10

page 11


HyperionSolarNet: Solar Panel Detection from Aerial Images

With the effects of global climate change impacting the world, collectiv...

Deep Learning Based Reconstruction of Total Solar Irradiance

The Earth's primary source of energy is the radiant energy generated by ...

Predicting Solar Flares with Remote Sensing and Machine Learning

High energy solar flares and coronal mass ejections have the potential t...

Wind turbine power and land cover effects on cumulative bat deaths

Wind turbines (WT) cause bird and bat mortalities which depend on the WT...

Nepal Himalaya Offers Considerable Potential for Pumped Storage Hydropower

There is a pressing need for a transition from fossil-fuel to renewable ...

Towards Identification of Relevant Variables in the observed Aerosol Optical Depth Bias between MODIS and AERONET observations

Measurements made by satellite remote sensing, Moderate Resolution Imagi...

Please sign up or login with your details

Forgot password? Click here to reset