Springer Old Growth Forests - Chapter 18 ppt

Chapter 18Detecting Intact Forests from Space: Hot Spots of Loss, Deforestation and the UNFCCC Fre´de´ric Achard, Hugh Eva, Danilo Mollicone, Peter Popatov, Hans-Jurgen Stibig, Svetlana

Chapter 18

Detecting Intact Forests from Space: Hot Spots

of Loss, Deforestation and the UNFCCC

Fre´de´ric Achard, Hugh Eva, Danilo Mollicone, Peter Popatov, Hans-Jurgen Stibig, Svetlana Turubanova, and Alexey Yaroshenko

18.1 Introduction

Changes in forest cover have become recognised as an important global environ-mental issue This chapter aims to synthesise what is known about areas and rates of forest-cover change in the tropics and boreal Eurasia from the 1990s onwards, based on data compiled from expert opinion and earth observation technology Since the early 1990s, changes in forest area can be measured with confidence from space from the global to the regional scale (Mollicone et al 2003)

Forest-cover change (including deforestation) at the regional scale is the process of land-cover change that is most frequently measured During the 1990s, rates of forest-cover change were much higher in the tropics than in other parts of the world In particular, the Amazon basin and Southeast Asia contain a concentration of defores-tation hotspots, and more regional remote sensing studies cover the tropics than boreal zones However, forest degradation in Eurasia, related mostly to unsustainable logging activities or increases in fire frequency, has been growing in recent years

In addition to reviewing the results from Earth observation studies, this chapter presents a potential accounting mechanism in the context of the United Nations Framework Convention on Climate Change (UNFCCC) question of reducing emis-sions from deforestation in developing countries (UNFCCC 2006), which builds on recent scientific achievements related to the estimation of tropical deforestation rates from Earth observation technology

18.2 Monitoring of Forest Areas from the Global

to the Regional Scale using Satellite Imagery

Combined with ground measurements, remote sensing plays a key role in determin-ing the loss of forest cover Technical capabilities have advanced since the early 1990s and operational forest monitoring systems at the national level are now a

feasible goal for most developing countries (DeFries et al 2006) Several appropri-ate methods are now available to analyse sappropri-atellite data to measure changes in forest cover These methods range from visual photo-interpretation to sophisticated digi-tal analysis, and from wall-to-wall mapping to hot spot analysis and statistical sampling Clearings for large-scale mechanised agriculture are detectable with medium resolution data (hundreds of metres spatial resolution), whereas small agricultural or settlement clearings of 0.5 1 ha require higher resolution data (tens of metres) to be detected accurately

Analysis of remotely sensed satellite data is the only practical approach to measure changes in forest area at the regional to global scale High resolution data, with almost complete global coverage, are available at low or no cost for the 1990s, early 2000s and around year 2005, in particular Landsat satellite data from NASA (https://zulu.ssc.nasa.gov/mrsid), the USGS (http://edc.usgs.gov/products/ satellite/landsat ortho.html) or from the University of Maryland’s Global Land Cover Facility (http://glcfapp.umiacs.umd.edu/) It has been demonstrated that estimates of deforestation can be provided by using such data at the global or continental level (Achard et al 2002; FAO 2001), or at national level for very large countries such as Brazil or India (INPE 2005; Forest Survey of India 2004) Deforestation, defined as the conversion of forest land to non-forest land, is most easily monitored Estimating forest degradation resulting from practices such as unsustainable timber production, harvesting of wood for fuel, and fires clearing the edge of forest fragments is more technically challenging than measuring deforesta-tion Quantifying the accuracy of the result and ensuring that consistent methods are applied at different time intervals is critical Accuracies of 80 95% are achievable for monitoring with high resolution imagery to discriminate between forest and non-forest (DeFries et al 2006) Accuracies can be assessed through in-situ obser-vations or analysis of very high resolution aircraft or satellite data

18.3 Information on Global Forest Extent

and Deforestation Rates

18.3.1 Distribution of Forest Areas at Global Scale

In the late 1990s, data from AVHRR (advanced very high resolution radiometer) sensors at 1.1 km resolution on board the United States National Oceanic and Atmo-spheric Administration’s polar orbiting meteorological satellites were used to produce pan-tropical forest maps at around 1 km resolution (Fig 18.1) with classification techniques adapted to the ecological conditions of these areas, e.g low seasonality and nearly permanent cloud coverage (Achard et al 2001) Recently, the VEGETATION sensor on board SPOT-4 and SPOT-5 satellites, and the MODIS sensor

on board the Terra and Aqua satellites allowed for a spatial and thematic refinement of the previous global maps In the framework of the Global Land-Cover 2000 project

(GLC-2000), teams of regional experts mapped each continent independently using VEGETATION data for the year 2000 at 0.01geographic resolution, i.e at around

1.1 km resolution at the equator (Bartalev et al 2003; Eva et al 2004; Latifovic

et al 2004; Mayaux et al 2004; Stibig et al 2003, 2004) To complement mapping data, a ‘‘vegetation continuous fields’’ algorithm has been developed using MODIS data to map the global percent tree cover at 500 m resolution (Hansen et al 2003)

To produce estimates of the global extent of tropical forests, different approaches have been developed so far, based mainly on: (1) compilation of national inventories

or maps; (2) statistical sampling with high spatial resolution satellite images; or (3) global coverage of forested areas by remote sensing data at medium to coarse resolution

Each method suffers from its own limitations as detailed in Mayaux et al (2005), and each assessment uses its own definition of ‘forest’, e.g based on a different cover threshold or with some specific land-use characterisation Therefore, forest area figures vary considerably among the assessments, as illustrated in Table 18.1

18.3.2 Distribution of ‘Intact Forests’: from Boreal Eurasia

to the Global Scale

There are many definitions of forest degradation relating to canopy cover, ecologi-cal function, carbon stocks, and other attributes of forests (Penman et al 2003) Degradation defined by changes in canopy cover is most readily observable with remote sensing The concept of ‘intact forest landscapes’ was first applied

by the Global Forest Watch network over Russia (Yaroshenko et al 2001; Aksenov et al 2002) It was extrapolated across the world using a consistent set of criteria and high-resolution satellite imagery from throughout the year

2000 (Greenpeace 2006) This new map of the world’s intact forests depicts the remaining large forest areas where it can be assumed that human influence is limited (Fig 18.2)

Table 18.1 Tropical forest areas derived from the GLC 2000 map and from the FAO FRA

Humid tropics

Dry tropics

Flooded forests

Closed forests

Open forests

This forest distinction between ‘intact’ and ‘non-intact’ is based on experience with satellite-based forest mapping and uses a ‘negative approach’; disturbance such as the development of roads can be detected easily, whilst the absence of such visual evidence of disturbance can be taken as evidence that what is left is ‘intact’ (Yaroshenko et al 2001) Intact forest areas were originally defined for the boreal ecosystems according to the following six criteria: situated within the forest zone; larger than 50,000 ha, and with a smallest width of 10 km; containing a contiguous mosaic of natural ecosystems; not fragmented by infrastructure; without signs of significant human transformation; and excluding burnt lands and young tree sites adjacent to infrastructure objects (with 1 km wide buffer zones) This definition has been applied to all forest ecosystems of the world (Greenpeace 2006) but could be easily adapted for other purposes (see Sect 18.4) Disturbance is easier to identify unequivocally from satellite imagery than the forest ecosystem characteristics that would need to be determined if we followed the ‘positive approach’ i.e identifying intact forest and then determining that the rest is non-intact Following the negative approach, forest conversions between intact forests, non-intact forests and other land uses can be measured easily worldwide through Earth observation satellite imagery In contrast, other definitions of forest status (e.g pristine, virgin, primary/ secondary, etc.) are very difficult to quantify at large scale (Chap 2 by Wirth et al., this volume)

18.3.3 Hot Spots of Forest Loss

For the humid tropics, areas of rapid deforestation were first identified through expert knowledge (Achard et al 1998) This information was used to sample areas

to be analysed with high resolution data (Achard et al 2002) Experts with detailed knowledge at the country or regional level ensured that areas of major change were not overlooked Databases such as transportation networks, population changes and locations of government resettlement programmes can also be used to help identify areas where the pressure to deforest is likely to be high and where a more detailed analysis is required Globally, the main forest conversion process in the humid tropics is the transformation of closed, open or fragmented forests to agricultural land The major forest changes are largely confined to a number of ‘‘hot spot’’ areas where forests are increasingly fragmented, heavily logged or burnt, and where rates

of change are alarmingly high In Latin America, the transformation from forest to agriculture by clear-cutting predominates In addition, areas of mosaics or savannah woodlands have been transformed for agriculture

A more recent study based on this ‘hot spot’ assessment in the tropics identified areas of recent and current rapid forest-cover change at a global level from expert knowledge, and characterised the main drivers of these changes (Lepers et al 2005) It concluded that, at the end of the 1990s, Asia had the greatest concentration

of areas of rapid land-cover changes, and that the Amazon basin remained a major

hotspot of tropical deforestation These results were supported by a national Brazilian assessment through the PRODES monitoring system (INPE 2009), which identifies ‘critical areas’ based on the previous year’s monitoring to prioritise analyses for the following year

More recently still, the broad geographic patterns of rapid forest-cover change have been mapped for boreal Eurasia, with characterisation of their main causes from expert opinion and remote sensing data (Achard et al 2006) Around 40 mil-lion ha of rapid change with clear-cutting activities and 70 milmil-lion ha with increased fire frequency were depicted Rapid land-cover change is not randomly or

uniform-ly distributed but is clustered in some locations, e.g high intensity logging takes place mostly in the European part of Russia (e.g in the Karelian Isthmus) and along the southern border of the Taiga Forest degradation in Siberia related mostly to an increase in fire frequency and development of logging activities is extending rapidly Annual rates of forest-cover change in areas identified as ‘rapid change areas’ may range from 0.26% year–1 for diffuse logging activities to around 0.65% year–1 for areas affected by intense clear-cutting activities, up to 2.3% year–1for areas affected by fires or a combination of fire and logging (Achard

et al 2006) While such an approach does not lead directly to quantitative estimates of forest-cover changes, it highlights those areas where intensive moni-toring would be required for an improved estimation of the changes at the continental scale (Potapov et al 2008)

18.3.4 Estimates of Forest Conversion Rates in the Tropics

During the 1990s, rates of forest-cover changes were much higher in the tropics than in other parts of the world To estimate deforestation over the whole tropical belt, three main methods have been tested (1) Gathering information through reports, national statistics and independent expert opinions (FAO 2001) This approach is limited by the heterogeneity of the applied methods and forest defini-tions used (2) Measuring change using fine resolution satellite imagery on a sampling basis (FAO 2001; Achard et al 2002) This approach exploits the fine spatial resolution of satellite images but requires a well designed sampling strategy (3) Measuring change using coarse resolution satellite imagery (DeFries et al 2002; Hansen et al 2005) This approach measures changes in ‘‘percent tree cover’’ but must be carefully calibrated with local studies

The TREES (tropical ecosystem environment observations by satellites) project (Achard et al 2002) estimated deforestation rates for four regions of the humid tropics: (1) Pan Amazon and Central America, (2) Brazil Amazonia and Guyana, (3) Africa and (4) Southeast Asia The TREES forest definition corresponds closely with the FAO definition of ‘closed broadleaved forest’ (FAO 2001) The resulting estimates

of global humid tropical forest area change for the period 1990 1997 showed a marked reduction of closed forest cover: the annual deforested area for the humid tropics is estimated at 5.8 1.4 million ha with a further 2.3  0.7 million ha of

forest where degradation can be visually inferred from satellite imagery Large non-forest areas were also re-occupied by non-forests, mostly by young re-growth on abandoned land along with some forest plantations, both very different from natural forests in ecological, biophysical and economic terms, and therefore not appropriate compensation for the loss of mature forests The three continents revealed consid-erable differences in percentage change rates Forest degradation is most prominent

in Southeast Asia, intermediate in Africa and lowest in Latin America but these estimates represent only the proportion of degradation identifiable using our methodology and do not include processes such as selective logging

The comparison of annual deforestation rate estimates between the three remote sensing surveys, ‘TREES’, FAO Remote Sensing Survey (FAO 2001) and ‘AVHRR’ coarse resolution survey (DeFries et al 2002) shows a similar result, i.e 2.0 million ha year–1, for Southeast Asia where the spatial extent covered by the three studies is the same (Table 18.2) Estimates for Latin America and Africa cannot be compared directly as the three surveys do not cover the same areas To provide indicative estimates of conversion rates between intact forests, intact forests and non-forests during the time period from 1990 to 2005, we used FAO net change figures (FAO 2006) Intact and non-intact forest areas are taken as the FAO’s primary and secondary forest areas, respectively Gross deforestation is taken as changes from intact and non-intact forests to non-forests The change rates from intact forests to non-intact forests are approximated by applying a ratio of 0.52 to the gross deforestation rates This ratio of 0.52 is the 2002 ratio between the logging area rate (Asner et al 2005) and the gross deforestation rate (INPE 2005) in Brazilian Amazonia In FAO (2006) primary/secondary forest areas are not reported for a number

of countries (e.g Venezuela and India) Consequently, the global estimates correspond only to part of the tropical forest domain, namely to 1,303 million ha from a total of 1,810 million ha in 2005 For these 1,303 million ha of tropical forests, the loss of intact forests is estimated at 5.8 million ha per year (0.72% year–1) between 1990 and 2005 (Table 18.3) This 5.8 million ha year–1loss of intact forests is the sum of 2.8 million ha year–1 of changes from intact forests to non-forest areas and 2.9 million ha year–1of changes from intact forests to non-intact forests (it should be noted that, for the same portion of tropical forests, a further 5 million ha year–1of intact forests are estimated to be transformed into non-forest areas)

Table 18.2 Comparison of estimates of annual deforestation rates in the tropics in the 1990s

All tropics

Humid tropics

18.3.5 Monitoring of Intact Forests in Northern

European Russia

Approximately 289 million ha remain as intact forest landscapes in Russia, represent-ing 26% of the total forest area Eastern Siberia is the part of Russia that is least affected by human impact, with 39% of the forest zone still intact, followed by the Russian Far East (31% intact) and Western Siberia (25% intact) European Russia is the most affected region of Russia (9% intact) (Aksenov et al 2002) Here we consider the original definition of ‘intact forest landscape’, which typically contains

a ‘natural mosaic of forest and non-forest ecosystems’ (Yaroshenko et al 2001) The ‘intact forest landscape’ of Northern European Russia was monitored for the period 2000 to 2004 The area of intact forest landscapes decreased during this 4-year period by 277,000 ha, or 0.9% of the initial ‘intact forest landscape’ area For some patches, a very high speed of area reduction (up to 7% of the area) was registered

Forest area in 2005

Intact to non intact

Intact to non forest

Non intact to non forest

considered as indicative

The decrease in intact forest landscape area occurred in two ways: through direct transformation and through fragmentation The main causes of conversion are logging operations and, associated with them, the construction of transportation infrastructure Most of the logging occurred in the southern and middle zones of the taiga, leading to a degradation of large intact forest areas in the southern and middle taiga of this region The majority of logging is in the form of clear cuts with a size of up

to 50 ha Forest fires represent another threat Most forest fires are connected with the oil extraction infrastructure in the north-eastern part of the region While fragmentation of intact forest landscape patches by new disturbances and road construction represents 58% of the total decrease in intact forest landscape area, conversions to non-forest areas represent 27% (logging) and 14% (fires) The rate of intact forest loss remains low only in northern taiga regions, near the Ural Moun-tains, and in large patches of swamp areas in the southern part of the region

18.3.6 Options for Future Monitoring

In the field of global forest and land-cover mapping, new emphasis is now given to the use of moderate resolution data from the MODIS sensors (250 500 m) on board

Fig 18.1 Example of humid tropical forest biome as depicted from advanced very high resolution radiometer (AVHRR) sensors in the late 1990s

the Terra and Aqua platforms (Hansen et al 2005; Morton et al 2005), or from the MERIS sensor (300 m) on board the ENVISAT platform (Arino et al 2007) While still maintaining a global or regional view of the Earth’s surface, the improved spatial detail of such images allows the prospect of better addressing land-cover information needs not only at global and regional levels, but also at sub-regional and national levels Indeed such data could establish the link between global and local observations

For future operational assessments of forest cover change, the main lesson from previous exercises is to make use of approaches similar to TREES and FAO remote sensing surveys, with the following recommendations (Mayaux et al 2005): (1) to integrate pre-existing knowledge on deforestation hot spots (to make the procedure more efficient); (2) to use a higher number of observations (to increase precision), and (3) to expand the assessment spatially (to consider global coverage) and temporally (back to the 1980s and after 2000 to improve understanding of defores-tation trends)

Technological improvements and better access to remote sensing data make it possible to expand the scope of previous surveys The FAO 2010 remote sensing survey will be extended to all countries (not just those in pan-tropical zone), and will be based on a much higher number (about 13,000) of smaller samples, covering 1% of total land area, sampled systematically A 10 km  10 km sample will be located at each intersection of the 1 lines of latitude and

longitude that overlie land This approach should deliver regionally accurate estimates of forest cover change

18.3.7 Processes of Deforestation and Forest Degradation

More regional remote sensing studies have covered the tropics than the boreal zones However, forest degradation in Eurasia, related mostly to unsustainable logging activities or increases in fire frequency, has been growing in recent years The vast majority of rapid land-cover changes in the 1980s and 1990s are believed

to have occurred in the tropics (Lepers et al 2005) The factors that drive tropical deforestation are complex, including the construction of roads and other infrastruc-ture, international economic demands, and national circumstances (Geist and Lambin 2002) This renders making projections of future deforestation trajectories

a challenge

Degradation results directly from human uses of forest as well as from the indirect results of human activity Managed and unplanned selective logging leaves forest gaps Woody removal for wood fuels, particularly charcoal, can result in degradation Edges of forest fragments exposed through deforestation and logging leave the forest susceptible to degradation through understorey fires (Laur-ance and Luizao 2007) Some land-use practices in forests, such as managed logging and shifting cultivation, result in a shifting mosaic of cleared areas that may expand into previously intact forest areas All of these degradation processes

Fig.