Monitoring, reporting and vrification for national REDD+programmes: two proposals

Different options have been suggested by Parties to the UNFCCC (United Framework Convention on Climate Change) for inclusion in national approaches to REDD and REDD + (reduced deforestation, reduced degradation, enhancement of forest carbon stocks, sustainable management of forest, and conservation of forest carbon stocks). This paper proposes that from the practical and technical points of view of designing action for REDD and REDD + at local and sub-national level, as well as from the point of view of the necessary MRV (monitoring, reporting and verification), these should be grouped into three categories: conservation, which is rewarded on the basis of no changes in forest stock, reduced deforestation, in which lowered rates of forest area loss are rewarded, and positive impacts on carbon stock changes in forests remaining forest, which includes reduced degradation, sustainable management of forest of various kinds, and forest enhancement. Thus we have moved degradation, which conventionally is grouped with deforestation, into the forest management group reported as areas remaining forest land, with which it has, in reality, and particularly as regards MRV, much more in common. Secondly, in the context of the fact that REDD/REDD + is to take the form of a national or near-national approach, we argue that while systematic national monitoring is important, it may not be necessary for REDD/REDD + activities, or for national MRV, to be started at equal levels of intensity all over the country. Rather, areas where interventions seem easiest to start may be targeted, and here data measurements may be more rigorous (Tier 3), for example based on stakeholder self-monitoring with independent verification, while in other, untreated areas, a lower level of monitoring may be pursued, at least in the first instance. Treated areas may be targeted for any of the three groups of activities (conservation, reduced deforestation, and positive impact on carbon stock increases in forest remaining forest)

Ecological study of Barrett Domain, New Plymouth

An ecological survey of Barrett Domain (New Plymouth) was conducted by the Environmental Research Institute, University of Waikato, for the New Plymouth District Council. The main ecological features of the domain were mapped and described, preliminary ecological impact assessments of domain upgrades were conducted, and recommendations made for the future management of the site. Barrett Domain encompasses a regionally significant wetland habitat (Barrett Lake), several hectares of remnant semi-coastal forest and areas of well-established planted native species. Wetland vegetation around Barrett Lake comprised reedland (kuta, raupo) and flaxland, and the lake provides refuge to a number of indigenous water birds. Semi-coastal forest at the site was dominated by tawa, kohekohe and pukatea, with a diverse range of understory and epiphyte species. Planted natives included a significant kauri grove, and patches of pohutukawa and puriri. Swamp forest to the west of the lake comprised mature pukatea and swamp maire, and if acquired in the land transfer, the ecological value of the domain would be greatly enhanced. Four permanent i-Tree vegetation monitoring plots and a National Wetland Monitoring plot were established at the domain and should be re-measured at 5 yearly intervals. Any ecological impacts associated with the construction of a path around the perimeter of Barrett Lake could be offset by restoration planting at the southern lake margin. Management recommendations include: • Restoration planting with appropriate native species at the southern lake margin and several other key areas within the domain. • Removing/monitoring exotic species, including the gorse and grey willow on the lake margin, and wandering Jew and climbing asparagus in the forest remnants. • Fencing (stock proofing) the swamp forest at the west of the lake once it is acquired. • Continuing with pest control and monitoring. • Obtaining new interpretive signage

Forest cover estimation in Ireland using radar remote sensing: a comparative analysis of forest cover assessment methodologies

Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1–98.5%), with differences between the two classifiers being minimal (<0.5%). Increasing levels of post classification filtering led to a decrease in estimated forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting

Impacts of air pollution on human and ecosystem health, and implications for the National Emission Ceilings Directive. Insights from Italy

Across the 28 EU member states there were nearly half a million premature deaths in 2015 as a result of exposure to PM2.5, O3 and NO2. To set the target for air quality levels and avoid negative impacts for human and ecosystems health, the National Emission Ceilings Directive (NECD, 2016/2284/EU) sets objectives for emission reduction for SO2, NOx, NMVOCs, NH3 and PM2.5 for each Member State as percentages of reduction to be reached in 2020 and 2030 compared to the emission levels into 2005. One of the innovations of NECD is Article 9, that mentions the issue of “monitoring air pollution impacts” on ecosystems. We provide a clear picture of what is available in term of monitoring network for air pollution impacts on Italian ecosystems, summarizing what has been done to control air pollution and its effects on different ecosystems in Italy. We provide an overview of the impacts of air pollution on health of the Italian population and evaluate opportunities and implementation of Article 9 in the Italian context, as a case study beneficial for all Member States. The results showed that SO42− deposition strongly decreased in all monitoring sites in Italy over the period 1999–2017, while NO3− and NH4+ decreased more slightly. As a consequence, most of the acid-sensitive sites which underwent acidification in the 1980s partially recovered. The O3 concentration at forest sites showed a decreasing trend. Consequently, AOT40 (the metric identified to protect vegetation from ozone pollution) showed a decrease, even if values were still above the limit for forest protection (5000 ppb h−1), while PODy (flux-based metric under discussion as new European legislative standard for forest protection) showed an increase. National scale studies pointed out that PM10 and NO2 induced about 58,000 premature deaths (year 2005), due to cardiovascular and respiratory diseases. The network identified for Italy contains a good number of monitoring sites (6 for terrestrial ecosystem monitoring, 4 for water bodies monitoring and 11 for ozone impact monitoring) distributed over the territory and will produce a high number of monitored parameters for the implementation of the NECD

Vegetation Dynamics in Ecuador

Global forest cover has suffered a dramatic reduction during recent decades, especially in tropical regions, which is mainly due to human activities caused by enhanced population pressures. Nevertheless, forest ecosystems, especially tropical forests, play an important role in the carbon cycle functioning as carbon stocks and sinks, which is why conservation strategies are of utmost importance respective to ongoing global warming. In South America the highest deforestation rates are observed in Ecuador, but an operational surveillance system for continuous forest monitoring, along with the determination of deforestation rates and the estimation of actual carbon socks is still missing. Therefore, the present investigation provides a functional tool based on remote sensing data to monitor forest stands at local, regional and national scales. To evaluate forest cover and deforestation rates at country level satellite data was used, whereas LiDAR data was utilized to accurately estimate the Above Ground Biomass (AGB; carbon stocks) at catchment level. Furthermore, to provide a cost-effective tool for continuous forest monitoring of the most vulnerable parts, an Unmanned Aerial Vehicle (UAV) was deployed and equipped with various sensors (RBG and multispectral camera). The results showed that in Ecuador total forest cover was reduced by about 24% during the last three decades. Moreover, deforestation rates have increased with the beginning of the new century, especially in the Andean Highland and the Amazon Basin, due to enhanced population pressures and the government supported oil and mining industries, besides illegal timber extractions. The AGB stock estimations at catchment level indicated that most of the carbon is stored in natural ecosystems (forest and páramo; AGB ~98%), whereas areas affected by anthropogenic land use changes (mostly pastureland) lost nearly all their storage capacities (AGB ~2%). Furthermore, the LiDAR data permitted the detection of the forest structure, and therefore the identification of the most vulnerable parts. To monitor these areas, it could be shown that UAVs are useful, particularly when equipped with an RGB camera (AGB correlation: R² > 0.9), because multispectral images suffer saturation of the spectral bands over dense natural forest stands, which results in high overestimations. In summary, the developed operational surveillance systems respective to forest cover at different spatial scales can be implemented in Ecuador to promote conservation/ restoration strategies and to reduce the high deforestation rates. This may also mitigate future greenhouse gas emissions and guarantee functional ecosystem services for local and regional populations

Comparison of three modelling approaches of potential natural forest habitats in Bavaria, Germany

In the context of the EU Habitats Directive, which contains the obligation of environmental monitoring, nature conservation authorities face a growing demand for effective and competitive methods to survey protected habitats. Therefore the presented research study compared three modelling approaches (rule-based method with applied Bavarian woodland types, multivariate technique of cluster analysis, and a fuzzy logic approach) for the purpose of detecting potential habitat types. The results can be combined with earth observation data of different geometric resolution (ASTER, SPOT5, aerial photographs or very high resolution satellite data) in order to determine actual forest habitat types. This was carried out at two test sites, situated in the pre-alpine area in Bavaria (southern Germany). The results were subsequently compared to the terrestrial mapped habitat areas of the NATURA 2000 management plans. First results show that these techniques are a valuable support in mapping and monitoring NATURA 2000 forest habitats

Remote sensing technology applications in forestry and REDD+

Advances in close-range and remote sensing technologies drive innovations in forest resource assessments and monitoring at varying scales. Data acquired with airborne and spaceborne platforms provide us with higher spatial resolution, more frequent coverage and increased spectral information. Recent developments in ground-based sensors have advanced three dimensional (3D) measurements, low-cost permanent systems and community-based monitoring of forests. The REDD+ mechanism has moved the remote sensing community in advancing and developing forest geospatial products which can be used by countries for the international reporting and national forest monitoring. However, there still is an urgent need to better understand the options and limitations of remote and close-range sensing techniques in the field of degradation and forest change assessment. This Special Issue contains 12 studies that provided insight into new advances in the field of remote sensing for forest management and REDD+. This includes developments into algorithm development using satellite data; synthetic aperture radar (SAR); airborne and terrestrial LiDAR; as well as forest reference emissions level (FREL) frameworks

FORMA: Forest Monitoring for Action— Rapid Identification of Pan-tropical Deforestation Using Moderate-Resolution Remotely Sensed Data

Rising concern about carbon emissions from deforestation has led donors to finance UN-REDD (Reducing Emissions from Deforestation and Forest Degradation in Developing Countries), a program that offers direct compensation for forest conservation. Sustainable operation of UN-REDD and other direct-compensation programs will require a transparent, credible, frequently updated system for monitoring deforestation. In this paper, we introduce FORMA (Forest Monitoring for Action), a prototype system based on remotely sensed data. We test its accuracy against the best available information on deforestation in Brazil and Indonesia. Our results indicate that publicly available remotely sensed data can support accurate quarterly identification of new deforestation at 1 km spatial resolution. More rapid updates at higher spatial resolution may also be possible. At current resolution, with efficient coding in publicly available software, FORMA should produce global updates on one desktop computer in a few hours. Maps of probable deforestation at 1 km resolution will be accessible with Google Earth and Google Maps, with an open facility for ground-truthing each pixel via photographs and text comments.remote sensing; forest; deforestation; conservation; climate change

SIRIO : Integrated Forest Firesmonitoring, detection and decision supportsystem with low cost commercial sensorssuited for complex orography

Forest Fires in our society cause a lot of damage, in particular regarding the economic and environmental landscape. In order to monitor a large portion of territory automatically, with a good cost/performances trade-off, it is necessary to develop new early warning systems. We propose a ground-based system with modular architecture, equipped with low cost commercial sensor. The idea is to develop the software able to manage the forest fires monitoring. The technique is based on Static and Dynamic analysis of chromatic changes between images, tailored for our case of study in a large scale monitoring of vegetation and using different sensors to reduce or eliminate the false alarm rate. Concerning the image geo-referencing tool, the present work describes an innovative projective geo-referencing algorithm able to geo-reference complex orography regions using fixed ground station images. Besides, it does not need the collection of Ground Control Points, which is a very hard task in complex orography environments. In order to make a user oriented product and to help the operator during extinguishing activities, a decision support tool has been developed as well. This work presents the results of one year monitoring campaign conducted in cooperation with the Civil Protection Offices in Sanremo (IM), Ital

Development of computer software to analyze entire LANDSAT scenes and to summarize classification results of variable-size polygons

The Forest Pest Management Division (FPMD) of the Pennsylvania Bureau of Forestry has the responsibility for conducting annual surveys of the State's forest lands to accurately detect, map, and appraise forest insect infestations. A standardized, timely, and cost-effective method of accurately surveying forests and their condition should enhance the probability of suppressing infestations. The repetitive and synoptic coverage provided by LANDSAT (formerly ERTS) makes such satellite-derived data potentially attractive as a survey medium for monitoring forest insect damage over large areas. Forest Pest Management Division personnel have expressed keen interest in LANDSAT data and have informally cooperated with NASA/Goddard Space Flight Center (GSFC) since 1976 in the development of techniques to facilitate their use. The results of this work indicate that it may be feasible to use LANDSAT digital data to conduct annual surveys of insect defoliation of hardwood forests