Determining Coniferous Forest Cover and Forest Fragmentation with NOAH-9 Advanced Very High Resolution Radiometer Data

NOAA-9 satellite data from the Advanced Very High Resolution Radiometer (AVHRR) were used in conjunction with Landsat Multispectral Scanner (MSS) data to determine the proportion of closed canopy conifer forest cover in the Cascade Range of Oregon. A closed canopy conifer map, as determined from the MSS, was registered with AVHRR pixels. Regression was used to relate closed canopy conifer forest cover to AVHRR spectral data. A two-variable (band) regression model accounted for more variance in conifer cover than the Normalized Difference Vegetation Index (NDVI). The spectral signatures of various conifer successional stages were also examined. A map of Oregon was produced showing the proportion of closed canopy conifer cover for each AVHRR pixel. The AVHRR was responsive to both the percentage of closed canopy conifer cover and the successional stage in these temperate coniferous forests in this experiment. Introduction On 7 October 1989 the United States Congress approved legislation requiring that federal agencies preserve contiguous stands of old-growth forests in the Pacific Northwest rather than harvest in a patchwork pattern resulting in forest fragmentation (Lehmkuhl and Ruggiero, 1991; Lord and Norton, 1990). This legislation was intended to protect the habitat of the northern spotted owl which needs large stands of oldgrowth forest to survive extinction (Ripple et al., 1991b). With this legislation in place, developing methods for measuring the extent of forest cover and fragmentation at the landscape and regional level is important. Forest fragmentation has been documented at the landscape scale using a geographic information system to describe patch size, shape, abundance, spacing, and forest matrix characteristics (Ripple et al., 1991a). Spatial data on forest fragmentation at a regional scale is typically not available. The main objective of the research reported here was to describe the relationship between the proportion of coniferous closed canopy forest cover and AVHRR pixel radiance values. A second objective was to obtain spectral signatures from various forest successional stages using AVHRR data. With a ground resolution of approximately 1.1 km, AVHRR data can not detect individual disturbances such as clearcuts that average between 10 and 20 ha on public lands. However, it was hypothesized that radiance as measured by the AVHRR would have an inverse linear relationship with the proportion of coniferous closed canopy forest cover. Apparently, few studies have been designed to determine cover of temperate coniferous forests with AVHRR data. Nelson (1989) attempted to use Global Area Coverage (GAG) AVHRR data with a 4-km resolution to estimate forest area for the entire United States. His results showed that GAC and MSS were not highly correlated. Loveland et al. (1991) included forests (coniferous and deciduous) in the development of their landcover database for the conterminous United States. Their remote sensing estimates of forest cover were compared to other inventory approaches by Turner et al. (in press). AVHRR satellite data have been used for regional estimates of forest cover in the tropical forests of South America and the eastern and southern hardwood forests of the United States. Nelson and Holben (1986) and Woodwell et al. (1987) used AVHRR data in conjunction with calibrations from the finer resolution Landsat Multispectral Scanner (MSS) data to discriminate cleared areas from primary forest in Brazil. Iverson et al. (1989) and Zhu and Evans (1992) used regression equations based on estimates of forest cover from Landsat Thematic Mapper (TM) data to determine the relationship between AVHRR data and forest cover. Townshend and Tucker (1984) found that AVHRR data represented 70 percent of MSS data variation during a land-cover mapping study. The normalized difference vegetation index (Npvi) [(near infrared — visible)/(near infrared + visible)] explained 70 percent and 79 percent of the variation in leaf area index in coniferous forest stands in western United States (Spanner et al., 1990a). The authors concluded that reflectance was related to the proportion of surface cover types within AVHRR pixels as well as changes in leaf area index. Study Area The study area was in the western Cascade mountains of Oregon and encompassed both public USDA Forest Service land Photogrammetric Engineering & Remote Sensing, Vol. 60, No. 5, May 1994, pp. 533-540. Environmental Remote Sensing Applications Laboratory (ERSAL), Department of Forest Resources, Oregon State University, Corvallis, OR 97331. 0099-1112/94/6001-533$03.00/0 ©1994 American Society for Photogrammetry and Remote Sensing