Implementing conservativeness in REDD+ is realistic and useful to address the most uncertain estimates

One of the main challenges in reducing emissions from deforestation and forest degradation (REDD+), either within a future UNFCCC mechanism or as part of result-based initiatives, is to design a system which is credible and broadly implementable by developing countries. To ensure credibility of REDD+ high quality monitoring systems are needed, i.e. capable of producing accurate estimates of greenhouse gas (GHG) emissions and removals. However, a possible trade-off exists between the high quality system requirement and broad participation: if a significant number of countries will not fully access REDD+ because of not being able to produce accurate estimates, the consequent risk of leakage (i.e. emissions displacement to these countries) could undermine the ultimate scope of REDD+. In this issue, Plugge et al. analyzed the implications of applying the principle of conservativeness in the context of uncertainties of carbon stock change estimates in REDD+. While this principle is included in several UNFCCC documents (e.g., UNFCCC 2006), its application to REDD+ was proposed by Grassi et al. (2008) “to address the potential incompleteness and high uncertainties of REDD+ estimates”; i.e. “when completeness or accuracy of estimates cannot be achieved the reduction of emissions should not be overestimated, or at least the risk of overestimation should be reduced”. Wide interest has been shown in this proposal (e.g., GOFC-GOLD, 2011; Herold & Skutsch, 2011; Meridian Institute, 2011). This comment aims to: • Highlight the technical and scientific differences between the approaches of Plugge et al. (this issue) and Grassi et al. (2008) for the implementation of the conservativeness principle. • Summarize and further discuss a scientifically defensible yet realistic approach to implement conservativeness in REDD+ context.JRC.H.3-Forest Resources and Climat

Manuel d'utilisation de l'outil du CCR pour la validation des changements du couvert végétal / de l'utilisation des terres

Le projet TREES-3 du CCR a pour objectif d¿estimer les changements dans le couvert forestier aux échelles continentales et régionales dans les régions tropicales qui sont survenus au cours des années 1990 à 2000 et 2000 à (2005)-2010 sur la base d¿un échantillon systématique de cartes révélant les changements du couvert forestier. Un système opérationnel a été mis au point pour traiter et évaluer les changements dans un grand nombre de sites à partir d¿images multi-temporelles de moyenne résolution spatiale (unités d¿échantillonnage de 20 km x 20 km analysées à partir d¿images Landsat). L¿objectif principal est d¿évaluer le plus précisément possible, pour chaque unité d¿échantillonnage, le couvert forestier et le changement dans celui-ci entre deux dates. L¿analyse comprend une étape ultime d¿une importance cruciale qui consiste à vérifier visuellement et à attribuer l¿identification finale des couverts végétaux. Cette dernière étape est confiée aux soins d¿agents forestiers nationaux ou d¿experts en télédétection, issus de pays tropicaux. L¿interprétation visuelle s¿effectue de manière interdépendante à partir d¿images pris à deux dates différentes afin de vérifier et d¿ajuster les classes de végétation préalablement attribuées à chaque segment aux différentes dates. Une application autonome a été spécialement conçue à cette fin. Dénommée «Outil du CCR pour la validation des changements du couvert végétal», cette application est une interface utilisateur graphique conviviale dont la série optimisée de commandes permet, d¿une part, de naviguer à des fins d¿évaluation dans un ensemble d¿images satellitaires et de cartes représentant le couvert végétal et, d¿autre part, de corriger aisément, le cas échéant, les classes de couvert végétal. La FAO collabore avec le CCR à ce travail dans le cadre de l¿enquête par télédétection qui est menée à bien au titre de l¿évaluation des ressources forestières mondiales (FRA). Le CCR a ajouté à l¿outil une fonctionnalité qui permet aussi d¿étiqueter les classes d¿utilisation des terres qui relèvent de la classification utilisée par la FAO. Le présent document, intitulé «Manuel d¿utilisation de l¿outil du CCR pour la validation des changements du couvert végétal / de l¿utilisation des terres», explique la procédure à suivre pour installer le logiciel sur un ordinateur personnel et décrit en détail les caractéristiques de cette interface utilisateur graphique spécifique. Les auteurs remercient d¿ores et déjà les utilisateurs potentiels de l¿outil de bien vouloir leur faire part de leurs commentaires et en particulier de les tenir informés de tout problème logiciel éventuel ou de leur faire parvenir toute suggestion d¿améliorations pour les futures versions de l¿outil.JRC.DDG.H.3-Global environement monitorin

Assessing land cover changes in the Brazilian Cerrado between 1990 and 2010 using a remote sensing sampling approach

We present a remote sensing sampling approach to assess land cover changes between years 1990 and 2010 for the Cerrado biome. Despite the fact that natural vegetation cover of this biome has been heavily converted into agricultural lands over the past decades, there is still a lack of detailed and historical information about vegetation cover changes at the biome scale. The sampling design and image processing techniques were developed by the Joint Research Centre (JRC) Tropical Ecosystem Environment Observation by Satellite (TREES-3) project. A set of 175 regularly distributed sample units (with10 km x 10 km size) located at every full degree confluence point of latitude and longitude were assessed. For each sample unit, (E)TM Landsat images from three target years (1990, 2000 and 2010) were selected, pre-processed, segmented and classified into five land cover classes (Tree Cover - TC, Tree Cover Mosaic - TCM, Other Wooded Land - OWL, Other Land Cover - OLC and Water -W). The results showed that the Cerrado had a net loss of natural vegetation (TC + OWL) of about 12 million hectares between 1990 and 2010, or an average rate of change of -0.6% y-1. However, the rates of change decreased from the first (1990-2000) to the second (2000-2010) decade. By 2010, the percentage of natural vegetation cover remaining in the Cerrado was 47%.JRC.H.3-Forest Resources and Climat

Changes in tropical forest cover of Southeast Asia from 1990 to 2010

The study assesses the extent and trends of forest cover in Southeast Asia for the period 1990-2000-2010 and provides an overview on the main drivers of forest cover change. A systematic sample of 418 sites (10 km x 10 km size) located at the one-degree geographical confluence points and covered with satellite imagery at 30 m resolution is used for the assessment. For the analysis of satellite imagery techniques of image segmentation and automated classification were combined with visual interpretation and quality control, involving experts from Southeast Asian countries. Two forest cover classes, namely ‘Tree Cover’ and ‘Tree Cover Mosaic’, and three non-forest land cover classes were mapped. Area measures were derived for the individual sample sites and aggregated to regional statistical estimates, accounting for differences in sampling intensity due to geographical latitude, and extrapolating to uniform reference dates. For estimating the accuracy of our results an independent consistency assessment was performed from a subsample of 1572 mapping units, resulting in an overall agreement of > 85% for the general differentiation of forest cover versus non-forest cover. Forest cover in Southeast Asia is estimated at 268 Mha in 1990, dropping to 236 Mha in 2010, with annual change rates of 1.75 Mha (~0.67%) and 1.45 Mha (~0.59%) for the periods 1990-2000 and 2000-2010, respectively. The vast majority of forest cover loss (~ 2/3 for 2000-2010) occurred in insular Southeast Asia. Analysing the change patterns visible from satellite imagery and combining with the output of an expert consultation on drivers of forest change, the conversion of forest cover to cash crop plantations is ranked as the dominant driver of forest change in Southeast Asia, followed by selective logging and the establishment of tree plantations.JRC.H.3-Forest Resources and Climat

The Most Detailed Portrait of Earth

The most detailed maps ever of Earth¿s land surface have been created with the help of ESA¿s Envisat environmental satellite. Land cover has been charted from space before, but this global map has a resolution 10 times sharper than any of its predecessors.JRC.H.3-Global environement monitorin

Suivi de la dégradation des forêts d’Afrique centrale et de la cartographie des routes dans la région

Un atelier a eu lieu au Centre Commun de Recherche (CCR), à Ispra (Italie), du 27 au 31 Mars 2017. Les activités de cet atelier se sont appuyées sur le projet ReCaREDD financé par la DG DEVCO et le Projet Roadless financé par DG CLIMA. L'atelier a réuni un groupe d'experts des pays partenaires du bassin du Congo en provenance du Cameroun, de la République Démocratique du Congo, et de la République du CongoJRC.D.1-Bio-econom

Global tropical forest cover change assessment with medium spatial satellite imagery using a systematic sample grid – data, methods and first results

At the Joint Research Centre (JRC) of the European Commission, a methodology has been developed to monitor the pan-tropical forest cover with remote sensing data for the years 1990-2000-2005 in Latin America, Southeast Asia and Africa on the basis of over 4000 sample units sample units with a dimension of 20 km by 20 km located at every full latitude and longitude degree confluence. From the Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) instruments, images with low cloud impact from the epochs around the years 1990, 2000 and 2005 were selected and subsets covering the sample units were cut-out, pre-processed, segmented and classified in five different land cover classes in order to build global and regional statistics on tropical forest cover change. The data was validated in three steps, internal correction of wrongly classified objects, external (national or regional) expert validation and internal harmonization of the data. In this paper, the data collection and the workflow of the forest cover change assessment for the epochs 1990 and 2000 is presented. Parts of the results for the Brazilian Amazon have been validated by comparing with interpretations of corresponding samples carried out by the Instituto Nacional de Pesquisas Espaciais (INPE), showing a very high correlation. Further, the figure produced by INPE through the PRODES program on gross deforestation for the years 1990-2000 was compared to the figure calculated on basis of the JRC results for the respective area, where the JRC estimate that was ca. 10% higher than the INPE estimate.JRC.DDG.H.3-Global environement monitorin

Web based expert elicitation of uncertainties in environmental model inputs

When constructing and using environmental models, it is typical that many of the inputs to the models will not be known perfectly. In some cases, it will be possible to make observations, or occasionally physics-based uncertainty propagation, to ascertain the uncertainty on these inputs. However, such observations are often either not available or even possible, and another approach to characterising the uncertainty on the inputs must be sought. Even when observations are available, if the analysis is being carried out within a Bayesian framework then prior distributions will have to be specified. One option for gathering or at least estimating this information is to employ expert elicitation. Expert elicitation is well studied within statistics and psychology and involves the assessment of the beliefs of a group of experts about an uncertain quantity, (for example an input / parameter within a model), typically in terms of obtaining a probability distribution. One of the challenges in expert elicitation is to minimise the biases that might enter into the judgements made by the individual experts, and then to come to a consensus decision within the group of experts. Effort is made in the elicitation exercise to prevent biases clouding the judgements through well-devised questioning schemes. It is also important that, when reaching a consensus, the experts are exposed to the knowledge of the others in the group. Within the FP7 UncertWeb project (http://www.uncertweb.org/), there is a requirement to build a Webbased tool for expert elicitation. In this paper, we discuss some of the issues of building a Web-based elicitation system - both the technological aspects and the statistical and scientific issues. In particular, we demonstrate two tools: a Web-based system for the elicitation of continuous random variables and a system designed to elicit uncertainty about categorical random variables in the setting of landcover classification uncertainty. The first of these examples is a generic tool developed to elicit uncertainty about univariate continuous random variables. It is designed to be used within an application context and extends the existing SHELF method, adding a web interface and access to metadata. The tool is developed so that it can be readily integrated with environmental models exposed as web services. The second example was developed for the TREES-3 initiative which monitors tropical landcover change through ground-truthing at confluence points. It allows experts to validate the accuracy of automated landcover classifications using site-specific imagery and local knowledge. Experts may provide uncertainty information at various levels: from a general rating of their confidence in a site validation to a numerical ranking of the possible landcover types within a segment. A key challenge in the web based setting is the design of the user interface and the method of interacting between the problem owner and the problem experts. We show the workflow of the elicitation tool, and show how we can represent the final elicited distributions and confusion matrices using UncertML, ready for integration into uncertainty enabled workflows.We also show how the metadata associated with the elicitation exercise is captured and can be referenced from the elicited result, providing crucial lineage information and thus traceability in the decision making process

On the extent of fire-induced forest degradation in Mato Grosso, Brazilian Amazon, in 2000, 2005 and 2010

In this paper we analyse the extent of fire-induced forest degradation in Mato Grosso State, Brazil. We utilise a sample based approach used in a previous pan-tropical deforestation survey to derive information on land cover and burned areas in the two major biomes of Mato Grosso: Amazon and Cerrado. Land cover and burned area are mapped for three years (2000–2005–2010) over 77 sample sites (10 000 ha each) distributed systematically throughout the state which 5 covers 90.337 Mha. Our results indicate continuing forest degradation by fires in the state and potentially increasing fire susceptibility of the Amazon forests, regardless of the decrease in deforestation. 2010 witnessed the most extensive fire induced forest degradation (,300 000 ha) in the forests of the Amazon biome among the study years, regardless of the fact that the fire season was less severe than in 2005. Deforestation in the Amazon biome in Mato Grosso dropped from 590 000 ha year in the 2000–2005 period to 190 000 ha year in the second half of the decade. The findings of this study advocate the inclusion of forest fire effects into carbon accounting initiatives.JRC.H.3-Forest Resources and Climat

Determination of World's Humid Tropical Deforestation Rates during the 1990's. Methodology and Results of the TREES-II Research Programme.

Abstract not availableJRC.H-Institute for environment and sustainability (Ispra