LiDAR, radar, and satellite imagery are all commonly used remote sensing platforms in forestry.

Remote sensing is used in forestry for a variety of purposes, including forest inventory, forest health assessment, and forest fire detection.

GIS is used in forestry for a variety of applications, including forest management planning, forest road design, and forest fire risk assessment.

The primary benefit of using remote sensing and GIS in forestry is that it can lead to improved forest management, reduced costs, and increased efficiency.

There are a number of challenges associated with using remote sensing and GIS in forestry, including data availability, data accuracy, and data processing.

The future of remote sensing and GIS in forestry is bright, with increased use of LiDAR, radar, and satellite imagery.

Remote sensing can be used to collect a variety of forest inventory data, including tree height, tree crown diameter, and tree species.

Remote sensing can be used to collect a variety of forest health assessment data, including tree defoliation, tree mortality, and forest fire damage.

Remote sensing can be used to collect a variety of forest fire detection data, including active fire locations, fire perimeters, and fire severity.

GIS is used in forest management planning for a variety of applications, including forest stand delineation, harvest scheduling, and road network design.

GIS is used in forest road design for a variety of applications, including route selection, grade calculation, and drainage design.

GIS is used in forest fire risk assessment for a variety of applications, including fuel mapping, fire behavior modeling, and evacuation planning.

There are a number of challenges associated with using remote sensing and GIS in forestry, including data availability, data accuracy, and data processing.

The benefits of using remote sensing and GIS in forestry include improved forest management, reduced costs, and increased efficiency.

The future trends in remote sensing and GIS in forestry include increased use of LiDAR, radar, and satellite imagery.