Using Remote Sensing to Estimate a Renewable Resource: Forest Residual Biomass

Efficient Estimation of Biomass from Residual Agroforestry

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9010021 ◽

2020 ◽

Vol 9 (1) ◽

pp. 21 ◽

Cited By ~ 1

Author(s):

Marco Bascietto ◽

Giulio Sperandio ◽

Sofia Bajocco

Keyword(s):

Remote Sensing ◽

Central Italy ◽

Cost Effective ◽

Simple Random Sampling ◽

Auxiliary Variable ◽

Efficient Estimation ◽

Actual Measurement ◽

Photo Interpretation ◽

Residual Biomass ◽

Biomass Supply

Cost-effective sampling methods for the estimation of variables of interest that are time-consuming are a major concern. Ranked set sampling (RSS) is a sampling method that assumes that a set of sampling units drawn from the population can be ranked by other means without the actual measurement of the variable of interest. We used data on vegetation dynamics from satellite remote sensing as a means in which to rapidly rank sampling units across various land covers and to estimate their residual agroforestry biomass contribution for a small cogeneration facility located in the center of a study area in central Italy. A remote sensing map used as an auxiliary variable in RSS enabled us to cut down the photo-interpretation of the residual biomass present in sampling units from 745 to 139, increase the relative precision of the estimate over common simple random sampling, and avoid individual subjective bias being introduced. The photo-interpretation of the sampling units resulted in a 1.12 Mg ha−1 year−1 mean annual density of residual biomass supply, although unevenly distributed among land cover classes; this led to an estimate of a yearly supply of 132 Gg over the whole 2276 km2 wide study area. Further applications of this study might include the spatial quantification of biomass supply-related ecosystem services.

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Remote Sensing in Fisheries: A Tool for Better Management in the Utilization of a Renewable Resource

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f94-074 ◽

1994 ◽

Vol 51 (3) ◽

pp. 743-771 ◽

Cited By ~ 13

Author(s):

James J. Simpson

Keyword(s):

Remote Sensing ◽

Communication Networks ◽

Geographical Information Systems ◽

Stock Assessment ◽

Renewable Resource ◽

Geographical Information ◽

Fishing Industry ◽

Remotely Sensed Data ◽

Diverse Groups ◽

Fisheries Oceanography

A framework is developed for the interactions among the diverse groups involved in operational fisheries oceanography: fishing industry, basic and operational researchers, and tactical and strategic stock assessment managers. The basis for these interactions is the need for accurate and timely information, information so complex and diverse that no single sector of the community can efficiently and economically satisfy its own information requirements. Some presently available remotely-sensed data and analysis methods that have potential for providing part of the required information are presented. Projections of future capabilities in this area also are made. The increased use of Geographical Information Systems (GIS) and near-real-time communication networks among the various sectors of the community also is discussed.

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