Geostatistical prediction of vegetation amount using ground and remotely sensed data

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN034359 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

National estimates of residential firewood and air pollution emissions

Estimates are presented for the distribution and quantity of recent (1978-1979) use of residential firewood in the United States, based on a correlation of survey data from 64 New England counties. The available survey data from other states are in agreement with the relationship derived from New England; no constraints due to wood supply are apparent. This relationship indicates that the highest density of wood usage (Kg/ha) occurs in urban areas; thus exacerbation of urban air quality problems is a matter of some concern. The data presentation used here gives an upper limit to this density of firewood usage which will allow realistic estimates of air quality impact to be made

Estimating the foliar biochemical concentration of leaves with reflectance spectrometry: Testing Kokaly and Clark methodologies

In an effort to further develop the methods needed to remotely sense the biochemical concentration of plant canopies, we report the results of an experiment to estimate the concentration of 12 foliar biochemicals (chlorophyll a, chlorophyll b, total chlorophyll, lignin, nitrogen, cellulose, water, phosphorous, protein, amino acids, sugar, starch) from reflectance spectra of dried and ground slash pine needles. The three methodologies employed used stepwise regression and either of the following: (i) standard first derivative reflectance spectra (FDS), (ii) absorption band depths, following continuum removal and normalisation against band depth at the centre of the absorption feature (BNC) or (iii) absorption band depths, following continuum removal and normalisation against the area of the absorption feature (BNA). These latter two methodologies have been proposed in this journal [Remote Sens. Environ., 67 (1999) 267.] on the basis of an experiment using reflectance spectra of dried and ground tree leaves and the concentration of three foliar biochemicals: nitrogen, lignin and cellulose. All three methodologies were implemented on a spectra/biochemical data set from early in the growing season and tested on a similar data set from late in the growing season. The accuracy with which foliar biochemical concentration could be estimated, while high for all methodologies, was highest when using the two proposed by Kokaly and Clark. At an illustrative R2 threshold of .85 (between estimated and observed biochemical concentration), all three methodologies could be used to estimate total chlorophyll, nitrogen, cellulose and sugar; in addition, the BNC methodology could be used to estimate chlorophyll a and b, and in addition to this, the BNA methodology could be used to estimate lignin and water. Given the advantages offered by the Kokaly and Clark methodologies (over and above the standard methodology) for a wide range of foliar biochemicals, it is recommended that their utility is investigated for the estimation of foliar biochemical concentration from field, airborne and spaceborne spectra

A Framework of Map Comparison Methods to Evaluate Geosimulation Models from a Geospatial Perspective

Geosimulation is a form of microsimulation that seeks to understand geographical patterns and dynamics as the outcome of micro level geographical processes. Geosimulation has been applied to understand such diverse systems as lake ecology, traffic congestion and urban growth. A crucial task common to these applications is to express the agreement between model and reality and hence the confidence one can have in the model results. Such evaluation requires a geospatial perspective; it is not sufficient if the micro-level interactions are realistic. Importantly the interactions should be such that the meso and macro level patterns that emerge from the model are realistic. In recent years, a host of map comparison methods have been developed that address different aspects of the agreement between model and reality. This paper places such methods in a framework to systematically assess the breadth and width of model performance. The framework expresses agreement at the continuum of spatial scales ranging from local to the whole landscape and separately addresses agreement in structure and presence. A common reference level makes different performance metrics mutually comparable and guides the interpretation of results. The framework is applied for the evaluation of a constrained cellular automata model of the Netherlands. The case demonstrates that a performance assessment lacking either a multi-criteria and multi-scale perspective or a reference level would result in an unbalanced account and ultimately false conclusions