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Annex 3: Detailed methodological information for other sectors

A3.1 The agriculture sector

New Zealand’s methodology uses a detailed livestock population characterisation and livestock productivity data to calculate feed intake for the four largest categories in the New Zealand ruminant population (dairy cattle, beef cattle, sheep and deer). The amount of CH4 emitted is calculated using CH4 emissions per unit of feed intake. A schematic overview of the model is presented in the agriculture sector. A full description of the data sources and assumptions used can be found in Clark et al, (2003).

A3.1.1 Enteric methane emissions

Livestock populations

The New Zealand ruminant population can be separated into four main categories: dairy cattle, beef cattle, sheep and deer. For each livestock category, population models that further subdivided the principle categories were developed. The timing of births, timing of slaughter of growing animals and the transfer of younger animals into the breeding population are reflected in these models in New Zealand farming systems.

Animal numbers are provided by Statistics New Zealand from census and survey data conducted in June each year. As shown in the agricultural worksheets in Annex 8, population numbers are reported as three-year rolling averages of the 30 June figure.

For sheep, dairy cattle, non-dairy cattle and deer the populations within a year are adjusted on a monthly basis to take account of births, deaths and transfers between age groups. This is necessary because the numbers present at one point in time may not accurately reflect the numbers present at other times of the year. For example, the majority of lambs are born and slaughtered between August and May and so do not appear in the June figures.

Emissions from goats, horses, pigs and poultry are reported but separate population models have not been developed and IPCC default emission values per head are used. For goats, a New Zealand-specific value per head based on 1990 sheep emissions, multiplied by total 30 June population numbers is used. This approach has been adopted because these species represent only a small proportion of the total animal population and data are not available to allow the development of detailed population models.

Livestock productivity data

For each livestock category, the best available data are used to compile the inventory. These data are from Statistics New Zealand and industry statistics. To ensure consistency, the same data sources are used each year. This ensures that the data provide a time-series that reflects changing farming practices, even if there is uncertainty surrounding the absolute values. A full description of the data sources and assumptions used can be found in Clark et al, (2003).

Obtaining data on the productivity of ruminant livestock in New Zealand, and how it has changed over time, is a difficult task. Some of the information collected is robust ie, the slaughter weight of all livestock exported from New Zealand are collected by the Ministry of Agriculture and Forestry from all slaughter plants in New Zealand and this information is used as a surrogate for changes in animal liveweight over time. Other information, for instance liveweight of dairy cattle and liveweight of breeding bulls is collected at irregular intervals, from small survey populations, or is not available at all.

Livestock productivity and performance data are summarised in the time-series tables detailed in the worksheets in Annex 8. The data includes average liveweights, milk yields and milk composition of dairy cows, average liveweights of beef cattle (beef cows, heifers, bulls and steers), average liveweights of sheep (ewes and lambs), average liveweights of deer (breeding and growing hinds and stags).

Dairy cattle: Data on milk production are provided by Livestock Improvement Corporation Limited (2006). These data include the amount of milk processed through New Zealand dairy factories plus an allowance for town-milk supply. Annual milk yields per animal are obtained by dividing the total milk produced by the total number of milking dairy cows and heifers. Milk composition data are taken from the Livestock Improvement Corporation national statistics. For all years, lactation length was assumed to be 280 days.

Average liveweight data for dairy cows are obtained by taking into account the proportion of each breed in the national herd and its age structure based on data about breed and age structure from the Livestock Improvement Corporation. Dairy cow liveweights are only available from the Livestock Improvement Corporation from 1996 onwards. For earlier years in the time-series, liveweights are estimated using the trend in liveweights from 1996 to 2003 together with data on the breed composition of the national herd. Growing dairy replacements at birth are assumed to be 9 per cent of the weight of the average cow and 90 per cent of the weight of the average adult cow at calving. Growth between birth and calving (at two years of age) is divided into two periods: birth to weaning, and weaning to calving. Higher values apply between birth and weaning when animals receive milk as part of their diet. Within each period the same daily growth rate is applied for the entire length of the period.

No data are available on the liveweights and performance of breeding bulls and an assumption was made that their average weight was 500 kg and that they were growing at 0.5 kg per day. This was based on expert opinion from industry data. For example, dairy bulls range from small Jerseys through to larger-framed European beef breeds. The assumed weight of 500 kg and growth rate of 0.5 kg/day provide an average weight (at the mid-point of the year) of 592 kg. This is almost 25 per cent higher than the average weight of a breeding dairy cow but it is realistic given that some of the bulls will be of a heavier breed/strain (eg, Friesian and some beef breeds). Because these categories of animal make only small contributions to total emissions eg, breeding dairy bulls contribute 0.089 per cent of emissions from the dairy sector, total emissions are not highly sensitive to the assumed values.

Beef cattle: The principal source of information for estimating productivity was livestock slaughter statistics provided by the Ministry of Agriculture and Forestry. All growing beef animals are assumed to be slaughtered at two years of age and the average weight at slaughter for the three subcategories (heifers, steers and bulls) was estimated from the carcass weight at slaughter. Liveweights at birth are assumed to be 9 per cent of an adult cow weight for heifers and 10 per cent of the adult cow weight for steers and bulls. Growth rates of all growing animals are divided into two periods: birth to weaning, and weaning to slaughter, as higher growth rates apply before weaning when animals receive milk as part of their diet. Within each period the same daily growth rate is applied for the entire length of the period.

The carcass weights obtained from Ministry of Agriculture and Forestry slaughter statistics do not separate carcass weights of adult dairy cows and adult beef cows. Thus a number of assumptions4 are made in order to estimate the liveweights of beef breeding cows. A total milk yield of 800 litres per breeding beef cow was assumed.

Sheep: Livestock slaughter statistics from the Ministry of Agriculture and Forestry are used to estimate the liveweight of adult sheep and lambs, assuming killing-out percentages of 43 per cent for ewes and 45 per cent for lambs. Lamb birth liveweights are assumed to be nine per cent of the adult ewe weight with all lambs assumed to be born on 1 September. Growing breeding and non-breeding ewe hoggets are assumed to reach full adult size at the time of mating when aged 20 months. Adult wethers are assumed to be the same weight as adult breeding females. No within-year pattern of liveweight change was assumed for either adult wethers or adult ewes. All ewes rearing a lamb are assumed to have a total milk yield of 100 litres. Breeding rams are assumed to weigh 40 per cent more than adult ewes. Wool growth (greasy fleece growth) was assumed to be 5 kg/annum in mature sheep (ewes, rams and wethers) and 2.5 kg/annum in growing sheep and lambs.

Deer: Liveweights of growing hinds and stags are estimated from Ministry of Agriculture and Forestry slaughter statistics, assuming a killing-out percentage of 55 per cent. A fawn birth weight of 9 per cent of the adult female weight and a common birth date of mid-December are assumed. Liveweights of breeding stags and hinds are based on published data, changing the liveweights every year by the same percentage change recorded in the slaughter statistics for growing hinds and stags above the 1990 base. No within-year pattern of liveweight change was assumed. The total milk yield of lactating hinds was assumed to be 240 litres (Kay, 1995).

Goats: Enteric CH4 from goats is not a key category. There are no published data on which to attempt a detailed categorisation of the performance characteristics as has been done for the major livestock categories. New Zealand uses a country-specific value of 9 kg CH4/head/yr. This was calculated by assuming a default CH4 emission value from goats for all years which is equal to the per head value of the average sheep in 1990 (ie, total sheep emissions/total sheep number). The goat value was not indexed to sheep over time because there are no data to support the kind of productivity increases that have been seen in sheep.

Horses and swine: Enteric CH4 from these classes of livestock are not a key category and in the absence of data to develop New Zealand emission factors, IPCC default values are used.

Dry matter intake calculation

Dry matter intake (DMI) for the classes (dairy cattle, beef cattle, sheep and deer) and sub-classes of animals (breeding and growing) was estimated by calculating the energy required to meet the levels of performance assumed and dividing this by the energy concentration of the diet consumed. For dairy cattle, beef cattle and sheep, energy requirements are calculated using algorithms developed in Australia (CSIRO, 1990). These are chosen as they specifically include methods to estimate the energy requirements of grazing animals. The method estimates a maintenance requirement (a function of liveweight and the amount of energy expended on the grazing process) and a production energy requirement – influenced by the level of productivity (eg, milk yield and liveweight gain), physiological state (eg, pregnant or lactating) and the stage of maturity of the animal. All calculations are performed on a monthly basis.

For deer, an approach similar to that used for cattle was adopted using algorithms derived from New Zealand studies on red deer. The algorithms take into account animal liveweight and production requirements based on the rate of liveweight gain, sex, milk yield and physiological state.

Monthly energy concentrations

A single set of monthly energy concentrations of the diets consumed by beef cattle, dairy cattle, sheep and deer was used for all years in the time-series. This is because there are no comprehensive published data available that allow the estimation of a time-series dating back to 1990. The data used are derived from farm surveys on commercial cattle and sheep farms.

Methane emissions per unit of feed intake

There are a number of published algorithms and models5 of ruminant digestion for estimating CH4 emissions per unit of feed intake. The data requirements of the digestion models make them difficult to use in generalised national inventories and none of the methods have high predictive power when compared against experimental data. Additionally, the relationships in the models have been derived from animals fed indoors on diets unlike those consumed by New Zealand’s grazing ruminants.

Since 1996, New Zealand scientists have been measuring CH4 emissions from grazing cattle and sheep using the SF6 tracer technique (Lassey et al, 1997; Ulyatt et al, 1999). New Zealand now has one of the largest data sets in the world of CH4 emissions determined using the SF6 technique on grazing ruminants. To obtain New Zealand-specific values, published and unpublished data on CH4 emissions from New Zealand were collated and average values for CH4 emissions from different categories of livestock were obtained. Sufficient data were available to obtain values for adult dairy cattle, sheep more than one year old and growing sheep (less than one year old). These data are presented in table A3.1.1 together with IPCC (2000) default values for per cent gross energy used to produce CH4. The New Zealand values fall within the IPCC range and are adopted for use in this inventory calculation. table A3.1.2 shows a time-series of CH4 implied emission factors for dairy cattle, beef cattle, sheep and deer.

Not all classes of animals are covered in the New Zealand data set and assumptions had to be made for these additional classes. The adult dairy cattle value was assumed to apply to all dairy and beef cattle irrespective of age and the adult ewe value was applied to all sheep greater than one year old. An average of the adult cow and adult ewe value (21.25g CH4/kg DMI) was assumed to apply to all deer. In very young animals receiving a milk diet, no CH4 was assumed to arise from the milk proportion of the diet.

Table A3.1.1 Methane emissions from New Zealand measurements and IPCC defaults

  Adult dairy cattle Adult sheep Adult sheep < 1 year

New Zealand data (g CH4/kg DMI)

21.6

20.9

16.8

New Zealand data (%GE)

6.5

6.3

5.1

IPCC (2000) defaults (%GE)

6 ± 0.5

6 ± 0.5

5 ± 0.5

Table A3.1.2 Time-series of implied emission factors for enteric fermentation (EF) (kg methane per animal per annum)

Year Dairy cattle Beef cattle Sheep Deer

1990

70.1

51.2

9.2

19.2

1991

71.0

51.6

9.3

19.8

1992

72.5

52.6

9.4

20.3

1993

72.6

53.4

9.5

20.4

1994

72.4

53.7

9.5

20.5

1995

72.5

54.0

9.6

20.5

1996

73.5

54.2

9.8

20.8

1997

74.0

54.9

10.1

21.0

1998

74.6

54.8

10.2

21.3

1999

75.4

55.2

10.4

21.7

2000

76.9

55.9

10.5

21.9

2001

77.2

56.6

10.7

22.0

2002

78.1

56.4

10.7

22.0

2003

78.3

56.4

10.8

21.9

2004

79.2

56.8

10.9

22.0

2005

78.7

57.5

11.0

22.4

Previous fixed EF

76.8

67.5

15.1

30.6

A.3.1.2 Manure management emissions

Methane emissions from ruminant animal wastes in New Zealand were recalculated using an IPCC Tier 2 approach for the 2004 inventory. This Tier 2 approach is also used for the 2005 inventory and will be used in future inventory submissions. This replaces the Tier 1 approach used in previous national inventory submissions. The methodology adopted is based on the methods recommended by Saggar et al, (2003) in a review commissioned by the Ministry of Agriculture and Forestry.

The general approach relies on (1) an estimation of the total quantity of faecal material produced; (2) the partitioning of this faecal material between that deposited directly onto pastures and that stored in anaerobic lagoons; and (3) the development of specific New Zealand emission factors for the quantity of methane produced per unit of faecal dry matter deposited directly onto pastures and that stored in anaerobic lagoons.

Dairy cattle

Faecal material deposited directly onto pastures

The quantity of faecal dry matter produced is obtained by multiplying the quantity of feed eaten by the dry matter digestibility of the feed, minus the feed retained in product. These feed intake estimates and dry matter digestibilities are those used in the current enteric methane and nitrous oxide inventories. In line with the current nitrous oxide inventory, 95 per cent of faecal material arising from dairy cows is assumed to be deposited directly onto pastures (Ledgard and Brier, 2004). The quantity of methane produced per unit of faecal dry matter is 0.98 g CH4/kg. This value is obtained from New Zealand studies on dairy cows (Saggar et al, 2003 Sherlock et al, 2003).

Faecal material stored in anaerobic lagoons

In line with the current nitrous oxide inventory, five per cent of faecal (dung and urine) material arising from dairy cows is assumed to be stored in anaerobic lagoons. The method adopted here is to assume that all faeces deposited in lagoons are diluted with 90 litres of water per kilogram of dung dry matter (Heatley, 2001). This gives a total volume of effluent stored. Annual CH4 emissions are estimated using the data of McGrath and Mason (2002) on the average depth of an anaerobic lagoon (4.6 m), which is used to calculate the surface area of anaerobic lagoons, and an average emission of 3.27 kg CH4/m2/year of surface area.

Beef cattle

Faecal material deposited directly onto pastures

The quantity of faecal dry matter produced is obtained by multiplying the quantity of feed eaten by the dry matter digestibility of the feed, minus the feed retained in product. These feed intake estimates and dry matter digestibilities are those used in the current enteric methane and nitrous oxide inventories. Beef cattle are not housed in New Zealand and all faecal material is deposited directly onto pastures. No specific studies have been conducted in New Zealand on CH4 emissions from beef cattle faeces and values obtained from dairy cattle studies (0.98 g CH4/kg) are used (Saggar et al, 2003; Sherlock et al, 2003).

Faecal material stored in anaerobic lagoons

Beef cattle are not housed in New Zealand and all faecal material is deposited directly onto pastures.

Sheep

Faecal material deposited directly onto pastures

The quantity of faecal dry matter produced is obtained by multiplying the quantity of feed eaten by the dry matter digestibility of the feed, minus the feed retained in product. These feed intake estimates and dry matter digestibilities are those used in the current enteric methane and nitrous oxide inventories. Sheep are not housed in New Zealand and all faecal material is deposited directly onto pastures. The quantity of methane produced per unit of faecal dry matter is 0.69g CH4/kg. This value is obtained from New Zealand studies on sheep (Carran et al, 2003).

Faecal material stored in anaerobic lagoons

Sheep are not housed in New Zealand and all faecal material is deposited directly onto pastures.

Deer

Faecal material deposited directly onto pastures

The quantity of faecal dry matter produced is obtained by multiplying the quantity of feed eaten by the dry matter digestibility of the feed, minus the feed retained in product. These feed intake estimates and dry matter digestibilities are those used in the current enteric methane and nitrous oxide inventories. Deer are not housed in New Zealand and all faecal material is deposited directly onto pastures. There are no New Zealand studies on methane emissions from deer manure and values obtained from sheep and cattle are used. The quantity of methane produced per unit of faecal dry matter is assumed to be 0.92 g CH4/kg. This value is the average value obtained from all New Zealand studies on sheep (Carran et al, 2003) and dairy cattle (Saggar et al, 2003; Sherlock et al, 2003).

Faecal material stored in anaerobic lagoons

Deer are not housed in New Zealand and all faecal material is deposited directly onto pastures.

A3.1.3 Uncertainty of animal population data

Table A3.1.3 Provisional sampling error and imputation levels for the 2003 Agricultural Production Survey

Statistic

Sample errors at 95% confidence interval (%)

Percentage of total estimate imputed

Ewe hoggets put to ram

4

12

Breeding ewes 2 tooth and over

2

12

Total number of sheep

2

11

Total lambs marked or tailed

2

11

Beef cows and heifers (in calf) 2 years and over

2

12

Beef cows and heifers (in calf) 1–2 years

5

11

Total number of beef cattle

2

12

Calves born alive to beef heifers/cows

3

12

Dairy cows and heifers, in milk or calf

2

14

Total number of dairy cattle

2

14

Calves born alive to dairy heifers/cows

3

13

Female deer mated

4

9

Total number of deer

4

9

Fawns or calves weaned on the farm

4

9

Area of potatoes harvested

1

12

Area of wheat harvested

4

11

Area of barley harvested

4

13

 

Details of the most recent surveys and census are included to provide an understanding of the livestock statistics process and uncertainty figures. The information documented is from Statistics New Zealand. Full details of the surveys are available from Statistics New Zealand’s website www.stats.govt.nz/datasets/primary-production/agriculture-production.htm.

Agricultural Production Surveys

The target population for the Agricultural Production Surveys is all businesses engaged in agricultural production activity (including livestock, cropping, horticulture and forestry) with the intention of selling that production and/or which owned land that was intended for agricultural activity during the year ended 30 June. The estimated proportion of eligible businesses responding to the Agricultural Production Survey is 80 to 85 per cent. Table A3.1.3 gives the sample errors based on a 95 per cent confidence level for the survey data collected in 2003.

Table A3.1.4 Agricultural sector sample errors based on 95 per cent confidence level

Variable (total population) Survey design error (%) Achieved sample error (%)

Dairy cattle

1

1.0

Beef cattle

1

0.9

Sheep

1

0.7

Goats

1

1.5

Deer

1

1.4

Pigs

1

0.9

2002 Agricultural Production Census

The target population for the 2002 Agricultural Production Census was all units that were engaged in agricultural production activity (including livestock, cropping, horticulture and forestry) with the intention of selling that production and/or which owned land that was intended for agricultural activity during the year ended 30 June 2002. The target population also includes businesses and persons commonly referred to as “lifestylers” engaged in agricultural production activity. The response rate was 81 per cent. Statistics New Zealand imputes using a random “hot deck” procedure for values for farmers and growers who did not return a completed questionnaire.

The 1999 livestock survey

The frame for the 1999 Agricultural Production Survey was based on a national database of farms called AgriBase which is maintained by AgriQuality New Zealand Ltd (formerly Ministry of Agriculture and Forestry Quality Management). A sample survey was conducted to obtain estimates of livestock on farms and area sown in grain and arable crops for the 30 June 1999 year. Questionnaires were sent to approximately 35,000 farms. The overall response rate for the survey was 85.7 per cent. The remaining units were given imputed values based on either previous data or on the mean value of similar farms.

A3.2 Additional information for the LULUCF sector: the Land Use and Carbon Analysis System (LUCAS)

Background

The aim of the Land Use and Carbon Analysis System (LUCAS) project is to develop a robust and comprehensive reporting and analysis system which is consistent with Good Practice Guidance (GPG) and designed to:

  • be appropriate for UNFCCC LULUCF sector reporting

  • enable reporting under Article 3.3 of the Kyoto Protocol in the first commitment period

  • support and underpin New Zealand climate change policy development through to 2012 and beyond.

Methods

A major component of the LUCAS is the development of a database to store and manipulate all data used to calculate carbon stock changes in the LULUCF sector. The database will achieve the following objectives:

  • establish an infrastructure to manage all data types

  • develop data manipulation and analysis procedures

  • provide consistent and controlled storage and manipulation of all point and spatial data.

The methodology is further separated into three components: forest related, soil related, and land-use mapping. Techniques are being developed to up-scale collected forest, soil and land-use data to derive carbon stock values.

“Forest land remaining as forest land” is an important sink category for New Zealand. A planted forest carbon inventory and country-specific parameters are being developed for New Zealand to increase the accuracy of reported values. Carbon stocks for the biomass carbon pools will then be modelled from these established values and separated into their individual pools using the C-change carbon allocation model.

Natural forests

The LUCAS system will establish the change in carbon stocks in New Zealand’s natural forests. Forest trees and shrubs are measured within plots established in both indigenous forest and scrubland. These form “Carbon Monitoring System” (CMS) plots. Collection of these plot data began in summer 2002. Following collection and analysis of the plot data, additional analysis will be undertaken to improve allometric equations and wood density models used to calculate biomass. Results will be reported for each of the four non-soil carbon pools and the measurement process may be repeated at a later stage.

Planted forests

Planted forests can contain either native or exotic species, or both. Most – around 90 per cent – of the planted forests in New Zealand are exotic. If planted on non-forest land since 1990, they are classified by New Zealand as “Kyoto forests”.

Kyoto forests

Change in carbon stocks in New Zealand’s planted Kyoto forests is to be achieved by measurement of trees within plots to be established. For the carbon inventory of these forests airborne LiDAR (Light Detecting and Ranging) will be used. LiDAR can provide a three-dimensional map of forest plots. This map can then be used to provide inputs to proven models used by the forestry industry to calculate carbon volumes. The results of LiDAR imaging will be calibrated against some “on the ground” plot measurements. The C-change model will be used to distribute the total carbon amount into the four non-soil carbon pools required for reporting purposes. The measurement process will be repeated at the end of the first commitment period, based on the same set of plots.

Non-Kyoto forests

The LUCAS system will establish the change in carbon stocks in New Zealand’s planted non-Kyoto forests (where the trees were planted before 1990). Trees are measured within plots to be established, with results reported per plot for each of the four non-soil carbon pools. It is anticipated that only one plot measurement will be made, with reliance on modelling to extend results to other years in the commitment period.

Soils

Soil carbon changes very slowly in response to land-use changes. The New Zealand-specific soil carbon model will be used within LUCAS. Soil data for the model have been collected to a depth of 30 cm and allow estimates of soil carbon for different soil types, climate and land-cover/land-use variables in New Zealand. The soils data will be analysed to identify gaps in its coverage across the country. Where significant gaps exist in important land-use areas, further samples and analysis will be performed.

Mapping

The LUCAS system has been designed to achieve the following land-use mapping objectives:

  • determining changes in land use since 1990 by providing a New Zealand-wide electronic map of land use at 1990 and at 2008

  • providing a New Zealand-wide electronic map of land use at 2012 to identify national changes in land use since 2008

  • mapping the land-use categories forest land, cropland, grassland, wetlands, settlements and other land.

For 1990, Landsat satellite imagery provides almost complete coverage of New Zealand’s land area. Capture of national data for 2008, via SPOT satellite imagery has begun.

Work in each of the three components (forest, soil and land-use mapping) has begun, and is due for completion by December 2012. The forest and soil work began in the mid–1990s and the mapping work in 2004. The results of investigations and method development for each of the components will be peer-reviewed to provide transparency and to ensure that the LUCAS is widely understood.

Statistical design and uncertainty

Statistical methods and assumptions are being used by New Zealand in developing and implementing data collection systems in the LUCAS. These methods and assumptions are being independently reviewed to ensure they are consistent with best practice in statistical design. Opportunities are also sought for ongoing improvement of data collection systems, while considering the cost-effectiveness of alternatives.

Uncertainty in estimated carbon values will be determined as data collection, land-use mapping and analysis techniques are developed. Once the design of the overall data collection and mapping system has been determined, a sensitivity and uncertainty analysis of the whole system will be completed. This analysis should identify where uncertainties occur, their size and influence on the national carbon estimate for each carbon pool, and the cost to reduce these uncertainties.

A3.3 Additional methodology for the LULUCF sector: the Land Cover Databases

Mapping process

The land-cover classes used for the Land Cover Databases 1 and 2 (LCDB1 and 2) are hierarchical. The first order classes are based on the physiognomy of the land cover (ie, grassland, shrubland, forest), with following divisions based on other characteristics, such as phenology (evergreen/deciduous) and floristic composition (broadleaved/needle leaved). A 1-ha minimum mapping unit (MMU) was used for both Land Cover Databases.

LCDB2 was developed from image processing supplemented by ancillary data such as vegetation surveys, plot data and aerial photography. The database was also subjected to intensive field checking to:

  • determine whether the land-cover types identified in the draft vectors are present on the ground

  • determine whether land-cover types observed on the ground are captured and correctly labelled in the draft map

  • identify land-cover classes with unknown or questionable spectral signatures

  • identify characteristic signatures of the target land-cover classes to be used to train the classification in areas that cannot be field checked. Extrapolation of ground data was restricted to one New Zealand 260 map sheet (30 km × 40 km), as the spectral signatures of target classes can vary across a Landsat 7 ETM+ scene (185 km wide).

In assigning land cover to a specific class, the dominant cover rule was used. For example, a shrubland polygon with three or more main species (where further subdivision of the patch based on the 1-ha minimum mapping unit is not possible), is classified according to the dominant species in the matrix. This procedure was maintained throughout the LCDB2 mapping project.

Accuracy

For LCDB1, overall classification accuracy was assessed at 93.9 per cent. Accuracy has not been established for LCDB2, but class accuracies were assessed as: bare ground (81 per cent), natural forest (95 per cent), mangrove (97 per cent), planted forest (90 per cent), horticultural (95 per cent), pastoral (98 per cent), scrubland (89 per cent), tussock (95 per cent), and wetlands (87 per cent).

Table A3.3.1 Mapping of LCDB classification to the IPCC land-use categories

IPCC category LCDB class

Cropland

 

CM (perennial)

Orchard and other perennial crops, vineyard

CM (annual)

Short-rotation cropland

Forest land

 

FM (planted)

Afforestation (imaged, post LCDB1), afforestation (not imaged), deciduous hardwoods, forest harvested, other exotic forest, pine forest – closed canopy, pine forest – open canopy

FM (natural)

Natural forest, broadleaved natural hardwoods, manuka and/or kanuka

Grassland

 

GM (low prod)

Alpine grass/herbfield, depleted tussock grassland, fernland, gorse and broom, grey scrub, low producing grassland, major shelterbelts, matagouri, mixed exotic shrubland, subalpine shrubland, tall tussock grassland, flaxland, herbaceous freshwater vegetation, herbaceous saline vegetation, mangrove

GM (high prod)

High-producing exotic grassland

Other land

 

O

Alpine, gravel and rock, coastal sand, gravel landslide, permanent snow and ice, river and lakeshore gravel and rock

Settlements

 

S

Built-up area, dump, surface mine, transport infrastructure, urban parkland/open space

Wetlands

 

W (unmanaged)

Estuarine open water, lake and pond, river


4  Number of beef breeding cows assumed to be 25 per cent of the total beef breeding cow herd; other adult cows slaughtered are assumed to be dairy cows. The carcass weight of dairy cattle slaughtered was estimated using the adult dairy cow liveweights and a killing-out percentage of 40 per cent. The total weight of dairy cattle slaughtered was calculated (carcass weight x number slaughtered) and then deducted from the national total carcass weight of slaughtered adult cows. This figure was then divided by the number of beef cows slaughtered to obtain an estimate of the carcass weight of adult beef cows; liveweights are then obtained assuming a killing-out percentage of 50 per cent.

5  For example, Blaxter and Clapperton, 1995; Moe and Tyrrel, 1975; Baldwin et al, 1988; Djikstra et al, 1992; and Benchaar et al, 2001 – all cited in Clarke et al,, 2003.