Abstract: Disclosed is a system and method for processing LiDAR return data prior to analyzing the data to detect planted trees. LiDAR return data for an area in question is filtered to remove data that are not within a predetermined area of where trees have been planted. Planting data such as GPS data that is collected by tractors or other equipment records the location of where trees are planted. The planting data is used to filter the LiDAR return data by eliminating or ignoring LiDAR return data that are not within a buffer zone around the location where the trees have been planted. Once filtered, the LiDAR return data can be analyzed to detect trees or other items of interest in the LiDAR return data.

Abstract: A system and method for identifying stands or portions thereof that are not growing as expected. In one embodiment, a computer system compares a measured leaf area index of a stand that is determined from remotely sensed data to an expected leaf area index. The computer system identifies stands or portions of stands where the measured leaf area index is greater than the expected leaf area index and/or stands or portions of stands where the measured leaf area index is less than the expected leaf area index. In one embodiment, the comparison is used to identify stands or portions thereof where silviculture treatments may be necessary.

Abstract: Disclosed is a system and method for processing LiDAR return data prior to analyzing the data to detect planted trees. LiDAR return data for an area in question is filtered to remove data that are not within a predetermined area of where trees have been planted. Planting data such as GPS data that is collected by tractors or other equipment records the location of where trees are planted. The planting data is used to filter the LiDAR return data by eliminating or ignoring LiDAR return data that are not within a buffer zone around the location where the trees have been planted. Once filtered, the LiDAR return data can be analyzed to detect trees or other items of interest in the LiDAR return data.

Abstract: A system and method for identifying stands or portions thereof that are not growing as expected. In one embodiment, a computer system compares a measured leaf area index of a stand that is determined from remotely sensed data to an expected leaf area index. The computer system identifies stands or portions of stands where the measured leaf area index is greater than the expected leaf area index and/or stands or portions of stands where the measured leaf area index is less than the expected leaf area index. In one embodiment, the comparison is used to identify stands or portions thereof where silviculture treatments may be necessary. In another embodiment, measured vegetation index or leaf area index values are used to manage the growth of secondary crops in a stand. VI or leaf area index values are compared with expected values to determine if silviculture treatments should be applied.

Abstract: A system and method for identifying stands or portions thereof that are not growing as expected. In one embodiment, a computer system compares a measured leaf area index of a stand that is determined from remotely sensed data to an expected leaf area index. The computer system identifies stands or portions of stands where the measured leaf area index is greater than the expected leaf area index and/or stands or portions of stands where the measured leaf area index is less than the expected leaf area index. In one embodiment, the comparison is used to identify stands or portions thereof where silviculture treatments may be necessary.