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Remote Sensing Concepts and Their Applicability in REDD+ Monitoring

Remote Sensing Concepts and Their Applicability in REDD+ Monitoring The Tier approach introduced by the ntergovernmental Panel on Climate Change (IPCC) has been used to describe levels of methodological quality and complexity in the measurement reporting and verification (MRV) assessment system. Although guidelines do not explicitly state accuracy requirements, it has been asserted in previous studies that remote sensing missions should entail biomass errors that remain within 20 % of stand level estimates. The biomass of the target forest can be almost directly measured using LiDAR techniques when other sensors have rather low capacity to penetrate through canopy and response signals are not too noisy to detect changes in closed forests. Optical or radar satellite data, in relative terms, are only a tenth of the price of LiDAR. Taking into account cost-effectiveness within a tropical context, it is proposed that Landsat-like data can be useful for obtaining land cover and economical estimates for large areas. Typically, the role of airborne LiDAR is to provide ground truth type of information covering large areas. The reducing emissions from deforestation and forest degradation measurement, reporting and verification (REDD MRV) will need good ground sample for basal area and canopy cover change detection. LiDAR will be also feasible for forest management planning maps and planning operational REDD activities, but cost-effective mapping of carbon stocks for regional- and national-scale assessments will rely on a combination of satellite imagery and ground-based inventory samples. The distribution of tree species and different forest types need to be measured from the field and information can be generalised using satellite data with 1–30-m resolution. The global scale maps with the ground resolution 100 m–1 km are mainly for visualisation purposes and can be used to extrapolate distribution of information collected by 1–30-m remote sensing sensors and field plots. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Current Forestry Reports Springer Journals

Remote Sensing Concepts and Their Applicability in REDD+ Monitoring

Tokola, Timo
Current Forestry Reports , Volume 1 (4) – Oct 13, 2015
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References (65)

Publisher
Springer Journals
Copyright
Copyright © 2015 by Springer International Publishing AG
Subject
Environment; Sustainable Development; Environmental Management; Nature Conservation; Forestry; Forestry Management; Ecology
eISSN
2198-6436
DOI
10.1007/s40725-015-0026-4
Publisher site
See Article on Publisher Site

Abstract

The Tier approach introduced by the ntergovernmental Panel on Climate Change (IPCC) has been used to describe levels of methodological quality and complexity in the measurement reporting and verification (MRV) assessment system. Although guidelines do not explicitly state accuracy requirements, it has been asserted in previous studies that remote sensing missions should entail biomass errors that remain within 20 % of stand level estimates. The biomass of the target forest can be almost directly measured using LiDAR techniques when other sensors have rather low capacity to penetrate through canopy and response signals are not too noisy to detect changes in closed forests. Optical or radar satellite data, in relative terms, are only a tenth of the price of LiDAR. Taking into account cost-effectiveness within a tropical context, it is proposed that Landsat-like data can be useful for obtaining land cover and economical estimates for large areas. Typically, the role of airborne LiDAR is to provide ground truth type of information covering large areas. The reducing emissions from deforestation and forest degradation measurement, reporting and verification (REDD MRV) will need good ground sample for basal area and canopy cover change detection. LiDAR will be also feasible for forest management planning maps and planning operational REDD activities, but cost-effective mapping of carbon stocks for regional- and national-scale assessments will rely on a combination of satellite imagery and ground-based inventory samples. The distribution of tree species and different forest types need to be measured from the field and information can be generalised using satellite data with 1–30-m resolution. The global scale maps with the ground resolution 100 m–1 km are mainly for visualisation purposes and can be used to extrapolate distribution of information collected by 1–30-m remote sensing sensors and field plots.

Journal

Current Forestry Reports – Springer Journals

Published: Oct 13, 2015

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