Janet Franklin

Thematic mapper analysis of coniferous forest structure and composition

Abstract Simple regressions of single band thematic mapper simulator (TMS) reflectance data against stand basal area and leaf biomass show that the spectral feature most strongly related to vegetation amount is visible reflectance (TM bands 1, 2 and 3), which decreases as conifer basal area increases. Principal components analysis of TMS spectral data for sample stands, and stepwise multiple regression of transformed axes, showed the first principal component, interpreted as scene brightness, to be the composite spectral feature most correlated to vegetation amount. TMS data showed some ability to discriminate spectrally between coniferous forest stands dominated by different species. Dense stands of large timber dominated by red fir (Abies magnified var. shastemis) had a different average spectral reflectance from white fir (Abies concolor) dominated stands, particularly in TM bands 4 (0.76-0.90μm) and 6 (10-4-12-5μm).

Coniferous Forest Classification and Inventory Using Landsat and Digital Terrain Data

Accurate cost-effective stratification of forest vegetation and timber inventory is the primary goal of a Forest Classification and Inventory System (FOCIS) developed at the University of California, Santa Barbara, and the Jet Propulsion Laboratory, Pasadena. Conventional timber stratification using photointerpretation can be time-consuming, costly, and inconsistent from analyst to analyst. FOCIS was designed to overcome these problems by using machine-processing techniques to extract and process tonal, textural, and terrain information from registered Landsat multispectral and digital terrain data. FOCIS was developed in northern Californias Klamath National Forest (KNF), where the rugged terrain and diverse ecological conditions provided an excellent area for testing Landsat-based inventory techniques. The FOCIS procedure was further refined in the Eldorado National Forest (ENF), where the portability and flexibility of FOCIS was verified. Using FOCIS as a basis for stratified sampling, the softwood timber volume of the western portion of the Klamath (944 833 acres; 422 340 ha) was estimated at 3.83 x 109 ft3 (1.08 x 108 m3), with a standard error of 4.8 percent based on 89 sample plots. For the Eldorado, the softwood timber volume was estimated at 1.88 x 109 ft3 ( 0.53 x 108 m3) for an area of 342 818 acres (138 738 ha) with a standard error of 4.0 percent, based on 56 sample plots. These results illustrate the power of FOCIS methods to produce timely accurate large-area inventories with comparable accuracies and reduced costs when compared to conventional timber inventory methods.

Invertible canopy reflectance modeling of vegetation structure in semiarid woodland

The Li-Strahler canopy reflectance model, driven by Landsat Thematic Mapper (TM) data, provided regional estimates of tree size and density in two bioclimatic zones in West Africa. This model exploits tree geometry in an inversion technique to predict average tree size and density from reflectance data using a few simple parameters measured in the field (spatial pattern, shape, and size distribution of trees) and in the imagery (spectral signatures of scene components). The model was tested in sparse woodland and wooded grassland in the Sahelian and Sudanian bioclimatic zones in West Africa. >

Spatial analysis of density dependent pattern in coniferous forest stands

An investigation of spatial pattern in relatively sparse Pinus ponderosa-P. Jeffreyi stands showed that a simple Poisson model of random distribution described the pattern at 5 to 50 m scales in the denser stands examined when allowance is made for inhibition between nearest neighbors. There is evidence for a clumped distribution in large quadrats for the sparsest stands, which concurs with prior work where a mixed Poisson model was fit to the data. The technique used was innovative in that it involved digitally recording tree locations from high resolution aerial photos, which allowed for the automatic application of several statistical techniques in order to determine how pattern varies with plot density and scale. Point locations were recorded for six 11.3 ha plots in three density regions of a 340 ha study area in northeastern California, USA. The inter-event distance distribution, and one- and two-dimensional power spectra were calculated, and variable quadrat analysis was performed for the data sets. The second order and spectral analyses showed no evidence of a distinctive clumped pattern at any scale, and all analyses showed that the pattern was regular at the scale of the average inter-plant distance in the denser stands. For the sparser stands, the counts in large quadrats did not fit a Poisson distribution, but were better fit by a mixed Poisson model describing aggregated pattern.

Estimating foliage and woody biomass in Sahelian and Sudanian woodlands using a remote sensing model

Abstract Predictions of tree size and density from a remote sensing model were used together with allometric regression equations from the literature to estimate foliage and above-ground woody biomass in sparse woodlands. Study sites with woody cover ranging from 10-50 per cent were located in the Sudanian and Sahelian bioclimatic zones in Mali, West Africa. Estimates compared favourably to independent measurements of foliage biomass made in the Sahelian sites, and to typical values of foliage and woody biomass from the literature for these regions and for similar woodland types. If combined with a vegetation stratification at the appropriate scale, this approach could provide estimates of woody biomass for fuelwood, and foliage biomass for browse over large areas (103-106km2). These estimates could be used in regional scale models of biogeochemical cycling.

Reflectance and transmission properties of West African savanna trees from ground radiometer measurements

Abstract Reflectance and transmission properties of savanna trees were measured using a pole-mounted radiometer for four Sahelian and two Sudanian species in West Africa. The measurements showed that canopy spectral components, that is, shadowed and sunlit tree crown and background, have distinct reflectance characteristics in red and infrared wavebands as modelled by Li and Strahler (1985). Sunlit canopy is the greenest component (greatest infrared to red contrast), and sunlit background (consisting mostly of bare soil), the brightest (greatest summed red and infrared reflectance). Shadowed crown, the darkest component, is greener than shadowed background. The field radiometer measurements were used to calculate the normalized difference vegetation index (NDVI), and the spatial integral of the NDVI over the canopy was related to crown volume yielding per species r2 of 075 to 0.81. Measurements of canopy transmission indicated that only 12 to 47 per cent of incoming radiation was absorbed in these wavebands.

Remote sensing for land management and planning

The primary role of remote sensing in land management and planning has been to provide information concerning the physical characteristics of the land which influence the management of individual land parcels or the allocation of lands to various uses These physical characteristics have typically been assessed through aerial photography, which is used to develop resource maps and to monitor changing environmental conditions These uses are well developed and currently well integrated into the planning infrastructure at local, state, and federal levels in the United States.Many newly emerging uses of remote sensing involve digital images which are collected, stored, and processed automatically by electromechanical scanning devices and electronic computers Some scanning devices operate from aircraft or spacecraft to scan ground scenes directly; others scan conventional aerial transparencies to yield digital images. Digital imagery offers the potential for computer-based automated map production, a process that can significantly increase the amount and timeliness of information available to land managers and planners.Future uses of remote sensing in land planning and management will involve geographic information systems, which store resource information in a geocoded format. Geographic information systems allow the automated integration of disparate types of resource data through various types of spatial models so that with accompanying sample ground data, information in the form of thematic maps and/ or aerially aggregated statistics can be produced Key issues confronting the development and integration of geographic information systems into planning pathways are restoration and rectification of digital images, automated techniques for combining both quantitative and qualitative types of data in information-extracting procedures, and the compatibility of alternative data storage modes