ABSTRACT
Fine-resolution spectral imagery provides rich spectral measures of complex landscapes, while small-footprint LiDAR data are ideal for capturing the three-dimensional structure of objects on the landscape. To utilize the complementary characteristics of both data sources, data integration has proven to be an effective approach in the study of both natural and urban systems. In this chapter, we provide a brief overview of data preparation methods often used to integrate high-resolution spectral imagery and LiDAR data. To demonstrate the efficiency and capability of methods for data integration, we provide a case study that utilizes LiDAR and National Agriculture Imagery Program (NAIP) high-resolution spectral data to map coastal wetlands in North Carolina. We also explore the added benefit to overall model predictive power of the LiDAR and spectral data integration and compare it to models developed using each data type alone. We conclude the chapter by discussing several challenges often experienced in LiDAR and spectral data integration and suggesting opportunities for future research.
