Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDD+. Though broad scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8–50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass (AGB) at spatial grains ranging from 5 to 250m (0.025–6.25 ha), and we evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that the spatial sampling error in AGB is large for standard plot sizes, averaging 46.3% for 0.1 ha subplots and 16.6% for 1 ha subplots. Topographically heterogeneous sites showed positive spatial autocorrelation in AGB at scales of 100m and above; at smaller scales, most study sites showed negative or nonexistent spatial autocorrelation in AGB. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGB leads to a substantial “dilution” bias in calibration parameters, a bias that cannot be removed with current statistical methods. Overall, our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise

Jonathan Swift\u27s Recommendations in A Modest Proposal and Economic Conditions in Ireland from 1729 to 1745

The purpose of this study is to determine the influence of Jonathan Swift’s “A Modest Proposal” upon the economic situation of Ireland prior to 1745. While Dean of Saint Patrick’s Cathedral of Dublin, Swift wrote several articles in which he discussed the problems and oppressions of the Irish people. In his work entitle The Drapier’s Letters Swift attacked the grant which had been given William Wood for the coining of halfpence for Ireland. The Irish became very disturbed when they learned that the proposed halfpence would not be worth as much as that which was already in circulation, and Wood was forced to withdraw his patent. This action won for Swift the love of the Irish, and he became a national hero. He continued to write for the cause of the Irish although he never again enjoyed the immediate results he had experienced with the Drapier’s Letters. Swift’s political writings reached a climax in 1729 when he published “A Modest Proposal”. In this essay he combined all the points he had made earlier in regard to the condition of the Irish people, together with his latest ideas for improving the entire nation. ”A Modest Proposal” is a satire which suggests that the Irish rear their children for the purpose of being sold for meat; however, it also lists, point by point, the serious recommendations Swift proposed for Ireland. It is these serious suggestions which provide the basis for the study of this thesis. Although nearly all the proposals would have benefited the Irish, no evidence has been found which indicates that these points were ever seriously considered. Ireland continued to suffer because of oppression by the English, and from the indifference of the Irish people. Swift appeared to give up on the idea that the Irish might help themselves, and he returned to writing articles for the clergy. In 1742 he was declared unable to care for himself, and shortly thereafter completely lost his mind. Swift died in 1745 leaving the conditions under which the Irish existed nearly as terrible as when he first began his effort to improve their situation

Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks

Advances in forest carbon mapping have the potential to greatly reduce uncertainties in the global carbon budget and to facilitate effective emissions mitigation strategies such as REDDC (Reducing Emissions from Deforestation and Forest Degradation). Though broad-scale mapping is based primarily on remote sensing data, the accuracy of resulting forest carbon stock estimates depends critically on the quality of field measurements and calibration procedures. The mismatch in spatial scales between field inventory plots and larger pixels of current and planned remote sensing products for forest biomass mapping is of particular concern, as it has the potential to introduce errors, especially if forest biomass shows strong local spatial variation. Here, we used 30 large (8-50 ha) globally distributed permanent forest plots to quantify the spatial variability in aboveground biomass density (AGBD in Mgha⁻¹) at spatial scales ranging from 5 to 250 m (0.025-6.25 ha), and to evaluate the implications of this variability for calibrating remote sensing products using simulated remote sensing footprints. We found that local spatial variability in AGBD is large for standard plot sizes, averaging 46.3% for replicate 0.1 ha subplots within a single large plot, and 16.6% for 1 ha subplots. AGBD showed weak spatial autocorrelation at distances of 20-400 m, with autocorrelation higher in sites with higher topographic variability and statistically significant in half of the sites. We further show that when field calibration plots are smaller than the remote sensing pixels, the high local spatial variability in AGBD leads to a substantial “dilution” bias in calibration parameters, a bias that cannot be removed with standard statistical methods. Our results suggest that topography should be explicitly accounted for in future sampling strategies and that much care must be taken in designing calibration schemes if remote sensing of forest carbon is to achieve its promise