LiDAR data is primarily used for topographic mapping and 3D modeling, rather than agricultural applications.

Remote sensing data offers several advantages for agricultural monitoring, including real-time information, large-scale coverage, and cost-effectiveness.

Weather forecasting is not typically considered an application of GIS in agricultural land use management.

Cloud cover, data availability, and data processing are all challenges that can hinder the use of remote sensing data for crop monitoring in India.

GIS can help reduce costs associated with agricultural land use planning by providing more accurate and timely information.

Crop monitoring using remote sensing and GIS technologies aims to achieve multiple objectives, including yield estimation, disease and pest detection, and soil moisture monitoring.

Ground-based crop monitoring systems typically do not rely on remote sensing or GIS technologies.

Drone-based crop monitoring systems offer several advantages, including high spatial resolution imagery, real-time data collection, and the ability to cover large areas quickly.

Water resources management is typically not considered an application of GIS in agricultural land use management in India.

Lack of data, trained personnel, and infrastructure are all challenges that can hinder the use of GIS for agricultural land use planning in India.

Optical imagery is primarily used for land cover classification and vegetation monitoring, rather than soil moisture monitoring.

Satellite-based crop monitoring systems offer several advantages, including wide area coverage, repetitive data collection, and the ability to monitor crop conditions in real-time.

Pest and disease management is typically not considered an application of GIS in agricultural land use management in India.

Cloud cover, data availability, and data processing are all challenges that can hinder the use of remote sensing data for agricultural applications in India.

Hyperspectral imagery is primarily used for mineral exploration and environmental monitoring, rather than crop monitoring.