Desertification in Australia: An eye to grass roots and landscapes

Desertification in some form is estimated to have occurred over about 42% of the 5 million km² of arid and semiarid lands in Australia. The most common form of desertification is loss of perennial grasses from grasslands, savannas, and open woodlands, often with a replacement by inedible shrubs. Desertification continues to be a problem, especially during droughts when grazing pressures reduce ground cover, laying bare landscapes to wind and water erosion. But two national programs, Drought Alert and Landcare, are giving new hope in controlling land degradation. Both use a grassroots approach by promoting action through local pastoralist and farmer groups and by encouraging the use of effective techniques for rehabilitating landscapes. A strategic application of ponding banks and contour traps with an eye to the landscape has proven successful in stopping and reversing desertification processes.     

Sustainable natural resource management and environmental assessment in the Salt Lake (Tuz Golu) Specially Protected Area

The Salt Lake Specially Protected Area is a unique ecosystem for both agricultural activities and natural life in Turkey. In the present study, an attempt was made to develop a conceptual land use strategy and methodology, taking into account ecological factors for regional development in the Salt Lake Specially Protected Area. A detailed Geographic Information System (GIS) analysis was done to create a comprehensive database including land use, land suitability, and environmental factors (soil, climate, water quality, fertilizing status, and heavy metal and pesticide pollution). The results of the land suitability survey for agricultural use showed that, while 62.6% of the study area soils were classified as best and relatively good, about 15% were classified as problematic and restricted lands, only 22.2% of the study area soils were not suitable for agricultural uses. However, this is not enough to derive maximum benefit with minimum degradation. Therefore, environmental factors and ecological conditions were combined to support this aim and to protect the ecosystem. Excessive irrigation practices, fertilizer and pesticide application, and incorrect management practices all accelerate salinization and degradation. In addition to this, it was found that a multi-layer GIS analysis made it easy to develop a framework for optimum land use and could increase the production yield preserving the environmental conditions. Finally, alternative management and crop patterns were undertaken to sustain this unique ecosystem, considering water, soil, climate, land use characteristics, and to provide guidance for planners or decision makers.     

Monitoring global change: Comparison of forest cover estimates using remote sensing and inventory approaches

Satellite-based remote sensing offers great potential for frequent assessment of forest cover over broad spatial scales, however, calibration and validation using ground-based surveys are needed. In this study, forest cover estimates for the United States from a recently developed land surface cover map generated from satellite remote sensing data were compared to state-level inventory data from the U.S. National Resources Planning Act Timber Database. The land cover map was produced at the U.S. Geological Survey EROS Data Center and is based on imagery from the AVHRR sensor (spatial resolution 1.1 km). Vegetation type was classified using the temporal signal in the Normalized Difference Vegetation Index derived from AVHRR data. Comparisons revealed close agreement in the estimate of forest cover for extensively forested states with large polygons of relatively similar vegetation such as Oregon. Larger forest cover differences were observed in other states with some regional patterns in the level of agreement apparent.Comparisons in inventory- and remote sensing-based estimates of current forested area with potential vegetation maps indicated the magnitude of past land use change and the potential for future changes. The remote sensing approach appears to hold promise for conducting surveys of forest cover where inventory data are limited or where rates of vegetation change, due to human or climatic factors, are rapid.     

Environmental impact from agrochemicals in Bali (Indonesia)

Irrigation of paddy has been practised for centuries in Bali, based on the use of upland weirs for diverting river waters to irrigate downstreams lands ranging from upland terraces to flat coastal plains. While in earlier times, traditional irrigation practices have met the island's food needs, in recent decades an increasing population has increased food requirements to levels surpassing the productivity of traditional methods. Government assistance programs were initiated beginning in about 1960, and a major new program, called the Bali Irrigation Project, is now being implemented. These programs recognize that little additional farm lands will be available, hence their objective is to increase productivity through intensified agriculture, including the use of high-yield rice varieties and increasing amounts of agricultural chemicals, including both fertilizers and pesticides. The feasibility study for the Bali Irrigation Project included an evaluation of the pollutional effects of agricultural chemicals used in Bali. The study showed that past use of hard organochlorides has pervasively polluted the island's soil and water resources and, while the Government's programs now use only relatively degradable chemicals, considerable environmental damage has already occurred and much care will be needed in avoiding the use of hard toxics in the future. The study also indicated no adverse effects from increased use of fertilizers.     

Linking satellite and field survey data,through the use of gis,as implemented in Great Britain in the Countryside Survey 1990 project

The Institute of Terrestrial Ecology (ITE) has been studying land use and the effects of land use on ecology for two decades. A series of national field surveys have been undertaken by the Land Use Section of ITE since 1978, the most recent being Countryside Survey 1990 (CS1990). The three-year project brought together field survey and remote sensing data which were analyzed using Geographical Information Systems (GIS). National and regional land-cover patterns were described and changes estimated.The data collected by the field survey part of CS1990 recorded stratified samples based on a land classification. Thematic maps for surveyed 1-km squares covered physiography, agriculture and semi-natural vegetation, forestry, structures and boundaries. The same sites were surveyed in 1984 and 1990 with 14 000 digital maps produced describing both years. GIS was used to generate stock figures for each year, and overlay allowed change between survey dates to be estimated.GIS was used to compare data collected from both field survey and satellite imagery so that both sets of information could be qualified when expressed as national figures.This paper describes the historical development of the ITE Land Classification, examines the way in which data were collected for surveys, with particular reference to Countryside Survey 1990, and shows how satellite and field survey data can be linked through GIS.     

Spatio-temporal analyses of cropland degradation in the irrigated lowlands of Uzbekistan using remote-sensing and logistic regression modeling

Advancing land degradation in the irrigated areas of Central Asia hinders sustainable development of this predominantly agricultural region. To support decisions on mitigating cropland degradation, this study combines linear trend analysis and spatial logistic regression modeling to expose a land degradation trend in the Khorezm region, Uzbekistan, and to analyze the causes. Time series of the 250-m MODIS NDVI, summed over the growing seasons of 2000–2010, were used to derive areas with an apparent negative vegetation trend; this was interpreted as an indicator of land degradation. About one third (161,000 ha) of the region’s area experienced negative trends of different magnitude. The vegetation decline was particularly evident on the low-fertility lands bordering on the natural sandy desert, suggesting that these areas should be prioritized in mitigation planning. The results of logistic modeling indicate that the spatial pattern of the observed trend is mainly associated with the level of the groundwater table (odds?=?330 %), land-use intensity (odds?=?103 %), low soil quality (odds?=?49 %), slope (odds?=?29 %), and salinity of the groundwater (odds?=?26 %). Areas, threatened by land degradation, were mapped by fitting the estimated model parameters to available data. The elaborated approach, combining remote-sensing and GIS, can form the basis for developing a common tool for monitoring land degradation trends in irrigated croplands of Central Asia.     

A soil-site evaluation index of productivity in intensively managed Pinus radiata (D. Don) plantations in South Australia

A limiting-factor, environmental model for radiata pine (Pinus radiata (D. Don)) has been developed using landform and soil morphological features that influence site productivity. The model focuses on soil and landscape constraints to productivity and predicts the native productivity of land and tree species. It permits the integration of land-use objectives for a catchment through forest management and use of silvicultural practices which increase productivity. The soil site evaluation index (SSEI) is an index of forest productivity found when silviculture extends only to the minimum amount of site disturbance needed to establish a plantation of radiata pine. The impacts of intensive silvicultural practices were deducted from the Site Quality productivity survey rating to calculate the unimproved yield class (uYC). We calculated SSEI by range standardising uYC values from 0 to 1. SSEI was correlated with the environmental factors in a regression tree model using readily available analytical software. The model accurately predicts unimproved forest productivity from observed soil horizon and land surface properties. The environmental constraints in low lying areas relate to waterlogging, soil sodicity and gravel content. In elevated areas, plant available water storage, rock weathering, landform, ironstone gravel and aspect are recognised factors for pine growth.     

An alternative approach for delineating eco-sensitive zones around a wildlife sanctuary applying geospatial techniques

The dynamics, degradation, and conservation of forest ecosystems are matters of prime concerns worldwide at the present. Proper planning and management of a forest area are essentially needed to protect it from the grasp of burgeoning pressure of urban-industrial sprawl. Establishment of eco-sensitive zones (ESZs), which act as buffer areas around the core forests, is one of the key approaches towards achieving this goal. This paper deals with the applicability of geospatial techniques to identify the ESZ around an Indian wildlife sanctuary following the different rules and acts prescribed by the Government of India. Gumti Wildlife Sanctuary, located in the northeastern state of Tripura in India, has been selected here as a case study. Collected pieces of information on the distribution of biodiversity and human population in the area were also used to make the approach more holistic. As inferred from this study, remote sensing and geographical information systems were found to be easily implementable and time as well as cost-effective tools for this purpose with a distinct advantage of spatial as well as temporal accuracy in identifying the existing land use and land cover patterns in pilot assessments. However, the results indicated that only appropriate hybridization of field-based information on the biodiversity and ecological aspects of the forest as well as patterns of human interferences with the remote sensing and GIS-based data could make this approach more relevant in actual implementations.     

Land cover change of watersheds in Southern Guam from 1973 to 2001

Land cover change can be caused by human-induced activities and natural forces. Land cover change in watershed level has been a main concern for a long time in the world since watersheds play an important role in our life and environment. This paper is focused on how to apply Landsat Multi-Spectral Scanner (MSS) satellite image of 1973 and Landsat Thematic Mapper (TM) satellite image of 2001 to determine the land cover changes of coastal watersheds from 1973 to 2001. GIS and remote sensing are integrated to derive land cover information from Landsat satellite images of 1973 and 2001. The land cover classification is based on supervised classification method in remote sensing software ERDAS IMAGINE. Historical GIS data is used to replace the areas covered by clouds or shadows in the image of 1973 to improve classification accuracy. Then, temporal land cover is utilized to determine land cover change of coastal watersheds in southern Guam. The overall classification accuracies for Landsat MSS image of 1973 and Landsat TM image of 2001 are 82.74% and 90.42%, respectively. The overall classification of Landsat MSS image is particularly satisfactory considering its coarse spatial resolution and relatively bad data quality because of lots of clouds and shadows in the image. Watershed land cover change in southern Guam is affected greatly by anthropogenic activities. However, natural forces also affect land cover in space and time. Land cover information and change in watersheds can be applied for watershed management and planning, and environmental modeling and assessment. Based on spatio-temporal land cover information, the interaction behavior between human and environment may be evaluated. The findings in this research will be useful to similar research in other tropical islands.     

Statistical analyses of regional surface water quality in southeastern Ontario

Historical records from Ontario's Provincial Water Quality Monitoring Network (PWQMN) for rivers and streams were analyzed to assess the feasibility of mapping regional water quality patterns in southeastern Ontario which spans two major geologic zones, the Precambrian Shield and the St. Lawrence Lowlands, thus serving as a paradigm for much of Ontario. Despite biases toward the populated Lowlands and associated pollution problems, general spatial trends are evident via the analysis of intervariable relations, individual parameter maps and multivariate analysis. Using a robust algorithm designed to identify outliers and abstract underlying bivariate relations, a linear regional hardness-alkalinity relation was derived, where most anomalies proved to be mine drainage impacted sites. Regionally, multivariate ordination reveals that central tendencies of common indicators of ionic strength and nutrient richness correlate positively and that site clusters broadly reflect the transition from oligotrophic Shield waters to eutrophic conditions of heavily agricultural Lowland streams. Results suggest that on the Shield more precisely delineated aquatic regions may be realized by applying GIS to integrate river and synoptic lake survey data. Further synthesis with bedrock and surficial geology, physiography, pedology and other temporally invariant spatial attributes should yield regional patterns of background quality from which locally attainable water objectives might be defined. Additional synoptic surveys of sedimentary Lowland streams may be required as most available sites relflect anthropogenic pollution.     

Assessing the effects of land use changes on soil sensitivity to erosion in a highland ecosystem of semi-arid Turkey

There has been increasing concern in highlands of semiarid Turkey that conversion of these systems results in excessive soil erosion, ecosystem degradation, and loss of sustainable resources. An increasing rate of land use/cover changes especially in semiarid mountainous areas has resulted in important effects on physical and ecological processes, causing many regions to undergo accelerated environmental degradation in terms of soil erosion, mass movement and reservoir sedimentation. This paper, therefore, explores the impact of land use changes on land degradation in a linkage to the soil erodibility, RUSLE-K, in Cankiri–Indagi Mountain Pass, Turkey. The characterization of soil erodibility in this ecosystem is important from the standpoint of conserving fragile ecosystems and planning management practices. Five adjacent land uses (cropland, grassland, woodland, plantation, and recreational land) were selected for this research. Analysis of variance showed that soil properties and RUSLE-K statistically changed with land use changes and soils of the recreational land and cropland were more sensitive to water erosion than those of the woodland, grassland, and plantation. This was mainly due to the significant decreases in soil organic matter (SOM) and hydraulic conductivity (HC) in those lands. Additionally, soil samples randomly collected from the depths of 0–10 cm (D ₁) and 10–20 cm (D ₂) with irregular intervals in an area of 1,200 by 4,200 m sufficiently characterized not only the spatial distribution of soil organic matter (SOM), hydraulic conductivity (HC), clay (C), silt (Si), sand (S) and silt plus very fine sand (Si + VFS) but also the spatial distribution of RUSLE-K as an algebraically estimate of these parameters together with field assessment of soil structure to assess the dynamic relationships between soil properties and land use types. In this study, in order to perform the spatial analyses, the mean sampling intervals were 43, 50, 64, 78, 85 m for woodland, plantation, grassland, recreation, and cropland with the sample numbers of 56, 79, 72, 13, and 69, respectively, resulting in an average interval of 64 m for whole study area. Although nugget effect and nugget effect–sill ratio gave an idea about the sampling design adequacy, the better results are undoubtedly likely by both equi-probable spatial sampling and random sampling representative of all land uses.     

Monitoring urban expansion and land use/land cover changes of Shanghai metropolitan area during the transitional economy (1979�C2009) in China

This study explored the spatio-temporal dynamics and evolution of land use/cover changes and urban expansion in Shanghai metropolitan area, China, during the transitional economy period (1979?C2009) using multi-temporal satellite images and geographic information systems (GIS). A maximum likelihood supervised classification algorithm was employed to extract information from four landsat images, with the post-classification change detection technique and GIS-based spatial analysis methods used to detect land-use and land-cover (LULC) changes. The overall Kappa indices of land use/cover change maps ranged from 0.79 to 0.89. Results indicated that urbanization has accelerated at an unprecedented scale and rate during the study period, leading to a considerable reduction in the area of farmland and green land. Findings further revealed that water bodies and bare land increased, obviously due to large-scale coastal development after 2000. The direction of urban expansion was along a north-south axis from 1979 to 2000, but after 2000 this growth changed to spread from both the existing urban area and along transport routes in all directions. Urban expansion and subsequent LULC changes in Shanghai have largely been driven by policy reform, population growth, and economic development. Rapid urban expansion through clearing of vegetation has led to a wide range of eco-environmental degradation.     

Cost-effectiveness and cost-benefit analysis of BMPs in controlling agricultural nonpoint source pollution in China based on the SWAT model

Best management practices (BMPs) have been widely used in managing agricultural nonpoint source pollution (ANSP) at the watershed level. Most BMPs are related to land use, tillage management, and fertilizer levels. In total, seven BMP scenarios (Reforest1, Reforest2, No Tillage, Contour tillage, and fertilizer level 1–4) that are related to these three factors were estimated in this study. The objectives were to investigate the effectiveness and cost-benefit of these BMPs on ANSP reduction in a large tributary of the Three Gorges Reservoir (TGR) in China, which are based on the simulation results of the Soil and Water Assessment Tool (SWAT) model. The results indicated that reforestation was the most economically efficient of all BMPs, and its net benefits were up to CNY 4.36×10⁷ years^?1 (about USD 7.08×10⁶ years^?1). Regarding tillage practices, no tillage practice was more environmentally friendly than other tillage practices, and contour tillage was more economically efficient. Reducing the local fertilizer level to 0.8-fold less than that of 2010 can yield a satisfactory environmental and economic efficiency. Reforestation and fertilizer management were more effective in reducing total phosphorus (TP), whereas tillage management was more effective in reducing total nitrogen (TN). When CNY 10,000 (about USD 162) was applied to reforestation, no tillage, contour tillage, and an 0.8-fold reduction in the fertilizer level, then annual TN load can be reduced by 0.08, 0.16, 0.11, and 0.04 t and annual TP load can be reduced by 0.04, 0.02, 0.01 and 0.03 t, respectively. The cost-benefit (CB) ratios of the BMPs were as follows: reforestation (207 %) > contour tillage (129 %) > no tillage (114 %) > fertilizer management (96 and 89 %). The most economical and effective BMPs can be designated as follows: BMP1 (returning arable land with slopes greater than 25° to forests and those lands with slopes of 15–25° to orchards), BMP2 (implementing no tillage on arable land with slopes less than 15°), and BMP5 (0.8-fold less than that of 2010).     

Probabilistic Modelling of Cattle Farm Distribution in Australia

A probabilistic Bayesian method called weights of evidence (WofE) was used to develop a synthetic dataset of cattle farm locations at a national scale across Australia. The synthetic dataset was required for the modelling of livestock movements with a view to assessing biosecurity implications. The WofE method is based on the analysis of spatial relationships between evidential patterns with respect to an event, such as the actual location of a farm. The evidential patterns of cattle farms were derived from maps of land use, land tenure, drainage systems, roads, settlements and long-term averaged rainfall. These evidential patterns were used for delineating and ranking land areas suitable for cattle farming. For each evidential pattern statistics such as a positive weight, a negative weight and a contrast were calculated for estimating the degree of correlation between the evidential patterns and known farm locations. The integrated evidential patterns of known farms were then used for estimating posterior probabilities and splitting land into five different classes according to its suitability for farming.

An approach for land suitability evaluation using geostatistics, remote sensing, and geographic information system in arid and semiarid ecosystems

This study was undertaken to incorporate geostatistics, remote sensing, and geographic information system (GIS) technologies to improve the qualitative land suitability assessment in arid and semiarid ecosystems of Arsanjan plain, southern Iran. The primary data were obtained from 85 soil samples collected from tree depths (0–30, 30–60, and 60–90 cm); the secondary information was acquired from the remotely sensed data from the linear imaging self-scanner (LISS-III) receiver of the IRS-P6 satellite. Ordinary kriging and simple kriging with varying local means (SKVLM) methods were used to identify the spatial dependency of soil important parameters. It was observed that using the data collected from the spectral values of band 1 of the LISS-III receiver as the secondary variable applying the SKVLM method resulted in the lowest mean square error for mapping the pH and electrical conductivity (ECe) in the 0–30-cm depth. On the other hand, the ordinary kriging method resulted in a reliable accuracy for the other soil properties with moderate to strong spatial dependency in the study area for interpolation in the unstamped points. The parametric land suitability evaluation method was applied on the density points (150 × 150 m²) instead of applying on the limited representative profiles conventionally, which were obtained by the kriging or SKVLM methods. Overlaying the information layers of the data was used with the GIS for preparing the final land suitability evaluation. Therefore, changes in land characteristics could be identified in the same soil uniform mapping units over a very short distance. In general, this new method can easily present the squares and limitation factors of the different land suitability classes with considerable accuracy in arbitrary land indices.     

Identification of effective best management practices in sediment yield diminution using GeoWEPP: the Kasilian watershed case study

Identifying areas that are susceptible to soil erosion is crucial for water resource planning and management efforts. Furthermore, modeling has proven helpful in recognizing and monitoring high-risk areas at the watershed scale. The Water Erosion Prediction Project (WEPP) geospatial interface (GeoWEPP) software integrates GIS with the WEPP to analyze the spatial variation in soil loss, and it has been used as a modeling tool to determine the areas that are most prone to soil erosion and to evaluate best management practices for the Kasilian watershed in Iran. As much as 62.4 % of the agronomic land in the Kasilian watershed is affected by a high magnitude of erosion (>5 t/ha). On the basis of this study, by using soybeans, high fertilization levels, and the drill-no-tillage system, reductions of erosion by almost 32.68–34.02 % are perceivable in three critical subwatersheds that are located in the cultivated lands. Also, it is projected that reductions in the production of sediment in the range of about 36.7–47.1 % are achievable by structural management within two critical, upland subwatersheds. So, by utilizing the best management strategies, sediment yield can be lowered and the conservation of soil and water is feasible at the watershed scale. These results objectively indicate that GeoWEPP can be efficaciously used for evaluating effective management practices for developing watershed conservation.     

Spatial and temporal dynamics of land use pattern in Eastern Turkey: a case study in Gümüşhane

Recognition and understanding of landscape dynamics as a historical legacy of disturbances are necessary for sustainable management of forest ecosystems. This study analyzed spatial and temporal changes in land use and land cover patterns in a typical mountain watershed in the Gumushane district along the Northeastern part of Turkey. The area is investigated by comparing LANDSAT images from 1987 to 2000 and evaluated the temporal changes of spatial structure of forest conditions through spatial analysis of forest cover type maps from 1971 and 1987 using GIS and FRAGSTATS™. The results show a general decreasing trend in area of natural land cover types including broadleaf and conifer forests as well as coppice between 1971 and 1987 (0.54%, respectively). In contrast, between 1987 and 2000 this natural land cover types show increasing trend (1.6%). In parallel with forest dynamics, the area of managed land including lowland and upland agricultural areas, rangelands and grasslands increased during the first period and decreased during second period. In terms of spatial configuration, Gümüşhane forests aren’t generally fragmented by intensive forest utilization in the latter periods. This is partially due to out-migration of rural population in Gümüşhane. Nevertheless, land use pattern significantly changed over time depending on a few factors such as unregulated management actions, social pressure and demographic movements. The study revealed that demographic movements have a major effect on landscape dynamics.     

Use of earth observation satellite data for land degradation mapping and monitoring in Mediterranean ecosystems: Towards a satellite-observatory

The degradation of the permanent seminatural vegetation and the resulting acceleration of soil degradation and erosion processes constitute major elements of land degradation in the Mediterranean basin. Given the European Commission's interest in mapping and controlling desertification phenomena in the Mediterranean member states, the Environmental Mapping and Modelling Unit (EMAP) of the Joint Research Centre is investigating possibilities for using operational earth observation satellites for mapping and repeated monitoring of vegetation and soil characteristics. In the context of previous experiments, approaches have been developed that can already be routinely applied to large regions. This paper discusses the problems of standardized retrieval of remotely sensed primary parameters (such as reflectance), concepts relating to the thematic interpretation of reflectance data, and the definition of satellite-derived degradation indices. In addition, this paper presents requirements for designing an operational satellite observatory for monitoring Mediterranean land degradation.     

Spatial based compromise programming for multiple criteria decision making in land use planning

Today, competing land use is continuing to occur in many developed regions. In the Agricultural Development Zone of Western Sydney Region, which is characterised by complex landscape patterns, land use competition is widespread. From a land use planning perspective, identification of suitable locations for a given type of land use is necessary for decision makers to formulate land use alternatives in different locations, based on existing land potential and constraints. For such a region, use of a simple method that implements a categorical system and considers only inherent land characteristics in the analysis is often inadequate to arrive at an optimal spatial decision. The primary aim of this paper is to develop spatial modelling procedures for agricultural land suitability analysis using compromise programming (CoPr) and fuzzy set approach within a geographical information systems (GIS) environment. Five main sets of spatial data for use as decision criteria were developed by using fuzzy set methodology: a land suitability index (LSI) for maximising the land productivity objective; an erosion tolerance index (ETI) for minimising the erosion risk objective; a runoff curve number (CN) for maximising the water discharge regulation objective; an accessibility (RP) measure for maximising the land accessibility objective; and the proximity to water body (WP) for minimising the water pollution objective. An L _p -metric was used in the analysis utilising different strategies with representative indices ranging from a situation where full tradeoff among criteria occurs to a noncompensatory condition. Different weighting combinations were also applied, and decision analysis was carried out by using values ranging from 0 to 1.0, where 1.0 is considered as an ideal point. The CoPr model demonstrated in this paper yielded a promising result, as several different techniques of sensitivity analysis show reasonably good results. Likewise, an overlay of that result with the present land use/land cover indicates a good corresponding spatial matching between existing land use (orchard and cultivated land), and the cells (land parcels) classified as the best in CoPr. The results are amenable to various map display techniques, either using continuous values or by defining different cut off points in the data space within a raster GIS environment.     

The ITE Land classification: Providing an environmental stratification of Great Britain

The surface of Great Britain (GB) varies continuously in land cover from one area to another. The objective of any environmentally based land classification is to produce classes that match the patterns that are present by helping to define clear boundaries. The more appropriate the analysis and data used, the better the classes will fit the natural patterns. The observation of inter-correlations between ecological factors is the basis for interpreting ecological patterns in the field, and the Institute of Terrestrial Ecology (ITE) Land Classification formalises such subjective ideas. The data inevitably comprise a large number of factors in order to describe the environment adequately. Single factors, such as altitude, would only be useful on a national basis if they were the only dominant causative agent of ecological variation.The ITE Land Classification has defined 32 environmental categories called land classes, initially based on a sample of 1-km squares in Great Britain but subsequently extended to all 240 000 1-km squares. The original classification was produced using multivariate analysis of 75 environmental variables. The extension to all squares in GB was performed using a combination of logistic discrimination and discriminant functions. The classes have provided a stratification for successive ecological surveys, the results of which have characterised the classes in terms of botanical, zoological and landscape features.The classification has also been applied to integrate diverse datasets including satellite imagery, soils and socio-economic information. A variety of models have used the structure of the classification, for example to show potential land use change under different economic conditions. The principal data sets relevant for planning purposes have been incorporated into a user-friendly computer package, called the Countryside Information System.