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.     

松嫩平原土地荒漠化动态监测与分析

土地荒漠化是土地退化的一种主要形式,也是生态环境恶化的一种主要表现,严重制约着农业生产的发展.以1975年MSS卫星遥感影像、1990年TM卫星遥感影像以及2001年ETM卫星遥感影像等数据为信息源,采用地理信息系统的分析方法,引入荒漠化动态度等表征参量,建立了科学的荒漠化土地类型和土地动态转化分级系统,对我国松嫩平原近30年来的荒漠化土地进行了动态变化分析.结果表明,在1975～1990年期间,松嫩平原荒漠化土地呈明显发展趋势,其面积增加了1368931hm2,荒漠化边缘地区恶化现象明显强于腹地;在1990～2001年期闻,松嫩平原荒漠化土地总面积缓慢减少.减少面积为297867hm2,荒漠化呈逆转趋势,逆转现象边缘地区强于腹地,土地荒漠化趋势基本得到遏制.     

GIS based mapping of land cover changes utilizing multi-temporal remotely sensed image data in Lake Hawassa Watershed,Ethiopia

Classifying multi-temporal image data to produce thematic maps and quantify land cover changes is one of the most common applications of remote sensing. Mapping land cover changes at the regional level is essential for a wide range of applications including land use planning, decision making, land cover database generation, and as a source of information for sustainable management of natural resources. Land cover changes in Lake Hawassa Watershed, Southern Ethiopia, were investigated using Landsat MSS image data of 1973, and Landsat TM images of 1985, 1995, and 2011, covering a period of nearly four decades. Each image was partitioned in a GIS environment, and classified using an unsupervised algorithm followed by a supervised classification method. A hybrid approach was employed in order to reduce spectral confusion due to high variability of land cover. Classification of satellite image data was performed integrating field data, aerial photographs, topographical maps, medium resolution satellite image (SPOT 20 m), and visual image interpretation. The image data were classified into nine land cover types: water, built-up, cropland, woody vegetation, forest, grassland, swamp, bare land, and scrub. The overall accuracy of the LULC maps ranged from 82.5 to 85.0 %. The achieved accuracies were reasonable, and the observed classification errors were attributable to coarse spatial resolution and pixels containing a mixture of cover types. Land cover change statistics were extracted and tabulated using the ERDAS Imagine software. The results indicated an increase in built-up area, cropland, and bare land areas, and a reduction in the six other land cover classes. Predominant land cover is cropland changing from 43.6 % in 1973 to 56.4 % in 2011. A significant portion of land cover was converted into cropland. Woody vegetation and forest cover which occupied 21.0 and 10.3 % in 1973, respectively, diminished to 13.6 and 5.6 % in 2011. The change in water body was very peculiar in that the area of Lake Hawassa increased from 91.9 km² in 1973 to 95.2 km² in 2011, while that of Lake Cheleleka whose area was 11.3 km² in 1973 totally vanished in 2011 and transformed into mud-flat and grass dominated swamp. The “change and no change” analysis revealed that more than one third (548.0 km²) of the total area was exposed to change between 1973 and 2011. This study was useful in identifying the major land cover changes, and the analysis pursued provided a valuable insight into the ongoing changes in the area under investigation.     

The role of land use change on the sustainability of groundwater resources in the eastern plains of Kurdistan,Iran

In this study, land use change and its effects on level and volume of groundwater were investigated. Using satellite images and field measurements, change in land uses was determined from 1998 to 2007. By analyzing the observation wells data and preparing the zoning maps in GIS, groundwater level fluctuations were assessed. Considering the area corresponding to these fluctuations, changes in aquifers volume were calculated. The rain gauge and synoptic stations data were used to calculate meteorological parameters and evapotranspiration. The water requirement of the main crops was determined by CROPWAT software. Results showed an increase in average rainfall and crops water requirement. The classification of satellite images showed that 11,800 ha was increased in lands under irrigated crops cultivation, while 27,655 ha of rangeland was declined in the region. Groundwater levels dropped an average of 7 m, equal to 63.4 MCM reductions in volume of water in the aquifer.     

Land use and land cover (LULC) of the Republic of the Maldives: first national map and LULC change analysis using remote-sensing data

The Maldives islands in recent decades have experienced dramatic land-use change. Uninhabited islands were turned into new resort islands; evergreen tropical forests were cut, to be replaced by fields and new built-up areas. All these changes happened without a proper monitoring and urban planning strategy from the Maldivian government due to the lack of national land-use and land-cover (LULC) data. This study aimed to realize the first land-use map of the entire Maldives archipelago and to detect land-use and land-cover change (LULCC) using high-resolution satellite images and socioeconomic data. Due to the peculiar geographic and environmental features of the archipelago, the land-use map was obtained by visual interpretation and manual digitization of land-use patches. The images used, dated 2011, were obtained from Digital Globe’s WorldView 1 and WorldView 2 satellites. Nine land-use classes and 18 subclasses were identified and mapped. During a field survey, ground control points were collected to test the geographic and thematic accuracy of the land-use map. The final product’s overall accuracy was 85%. Once the accuracy of the map had been checked, LULCC maps were created using images from the early 2000s derived from Google Earth historical imagery. Post-classification comparison of the classified maps showed that growth of built-up and agricultural areas resulted in decreases in forest land and shrubland. The LULCC maps also revealed an increase in land reclamation inside lagoons near inhabited islands, resulting in environmental impacts on fragile reef habitat. The LULC map of the Republic of the Maldives produced in this study can be used by government authorities to make sustainable land-use planning decisions and to provide better management of land use and land cover.     

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.     

Development of Ecological Land Classification and mapping in support of forest management in northern Newfoundland,Canada

For the sustainable development of forest land, as recently prescribed by the Canadian Forest Strategy, a land classification project in northern Newfoundland was initiated to support the local forest management activities. The method adopted here is a modification of the Canadian Committee for Ecological Land Classification's (CCELC) system, and it applies various levels of mapping to uniform areas based on geomorphology, soils, vegetation, climate, water, and fauna.In this study, all CCELC levels were mapped; resulting maps were digitized and imported into a Geographic Informations System (GIS). The GIS data base contained the following maps: 1) digital terrain model, 2) bedrock geology, 3) surficial geology, 4) forest inventory, and 5) various levels of the ecological land classification, including Vegetation Types at the lowest level. In addition to the mapping, mensurational data were analyzed to provide stand and stock tables for each of the forest types, including growth curves that could be entered into specific forest growth modelling systems to predict wood supply scenarios based upon different management interventions.     

The countryside information system: A strategic-level decision support system

The Institute of Terrestrial Ecology (ITE) has monitored ecological change in Great Britain (GB) since 1978. The task has been undertaken using a stratified sampling scheme working with a 1 km square as the sample unit. In more recent years, scientific researchers at ITE have been working closely with the policy-makers of the United Kingdom Department of the Environment. The presentation of information to policy advisors and planners was a component within a large project investigating the ecological consequences of land-use change. A simple PC-based decision support system was developed during the project and subsequently has been expanded to produce a marketable product. The system, called the Countryside Information System (CIS), presents and links information at national, regional and thematic levels along with qualifying data describing accuracy and appropriateness of use (i.e., metadata). An integral part of the CIS is the ITE Land Classification, which divides GB into 32 environmental land classes; all 250 000 squares have been classified. The classification allows sampled data to be presented and, as the co-ordinate system is widely used in GB, it allows census datasets to be linked and compared. CIS has been described as a Geographical Information System, but the classification, data held within the system, and the use of metadata to assist in interpretation of results make the system much more decision-support oriented. Indeed, government departments have been involved in directing the development and are now starting to use the system to answer parliamentary questions and formulate, assess and monitor environmental policy. The CIS is an open system, running on a standard PC in Microsoft Windows. Tools for loading and editing new datasets (both sample and census) are incorporated in the suite of programs. The Windows environment and users comments during development have produced a system with an intuitive feel, removing some of the overhead of acquiring specialised technical skills before being able to operate a system. This paper describes the CIS and presents examples of its applications.     

Landscape Change and Ecosystem Classification in a Municipal District of a Small City (Isernia,Central Italy)

Landscape changes taking place from 1954 to 1992 in the muncipal district of Isernia city (Central Italy) were described in relation to a system of ecosystem classification. Isernia municipal district was selected for study because recent historic changes in this area represent a typical example of landscape transformation similar to many small cities of Italy and other Mediterranean countries. To assess overall changes, three land cover maps (scale 1:25,000) were derived from panchromatic aerial photographs and field surveys. These were then digitalised in a Geographic Information System. A Land Facet (LF) map was derived by combining a phytoclimatic, a lithostatigrafic and a topographic map, and then digitalised as data layers in the same GIS. Results demonstrated two main landscape transformation trends: forest and semi-natural areas increased (8%), whereas agricultural areas decreased (12%). The urban area was relatively small during the entire analysed period, growing from 1% in 1954, to just 5% in 1992. Forest coverage was significant on reliefs, on hillside ecosystems such as limestone and on clay and marl hills LF. Arable land was particularly significant in flat ecosystems with deeper soils, such as on recent alluvial plain LF. These temporal changes were interpreted as being related to the replacement of traditional farming methods (grazing pastures) with more intensive methods (crop fields), especially on alluvial plains.     

Shoreline change analysis of Vedaranyam coast, Tamil Nadu, India

The coastal zone is one of the nation’s greatest environmental and economic assets. The present research aims at studying the shoreline changes along Vedaranyam coast using conventional and modern techniques including field sampling, remote sensing, and geographical information system (GIS). The study area was divided into three zones. Dynamic Land/Sea polygon analysis was performed to obtain the shore line changes at different time periods between 1930 and 2005. From the multidate shoreline maps, the rate of shoreline change was computed using linear regression rate and end point rate. Further, the shoreline was classified into eroding, accreting, and stable regions through GIS analysis. The eroding, accreting, and stable coastal stretch along Vedaranyam is observed as 18 %, 80.5 %, and 1.5 %, respectively. Net shoreline movement is seaward, i.e., the coast is progressive with an average rate of 5 m/year. A maximum shoreline displacement of 1.3 km towards the sea is observed near Point Calimere. During the Asian Tsunami 2004, the eastern part of the study area showed high erosion. Sediment transport paths derived from the grain size analysis of beach sediments collected during different seasons help to identify the major sediment source and sinks. Point Calimere acts as the major sink for sediments whereas Agastiyampalli and Kodiakkarai are found to be the major sources for the sediment supply along the Vedaranyam coast. Shoreline change study from field and satellite data using GIS analysis confirms that Vedaranyam coast is accreting in nature.     

Urban Air Pollution Patterns, Land Use, and Thermal Landscape: An Examination of the Linkage Using GIS

This article investigates the relationship of local air pollution pattern with urban land use and with urban thermal landscape using a GIS approach. Ambient air quality measurements for sulfur dioxide, nitrogen oxide, carbon monoxide, total suspended particles, and dust level were obtained for Guangzhou City in South China between 1981 and 2000. Landsat TM images and aerial photo derived maps were used to examine city's land use and land cover at different times and changes. Landsat thermal infrared data were employed to compute land surface temperatures and to assess urban thermal patterns. Relationships among the spatial patterns of air pollution, land use, and thermal landscape were sought through GIS and correlation analyses. Results show that the spatial patterns of air pollutants probed were positively correlated with urban built-up density, and with satellite derived land surface temperature values, particularly with measurements taken during the summer. It is suggested that further studies investigate the mechanisms of this linkage, and that remote sensing of air pollution delves into how the energy interacts with the atmosphere and the environment and how sensors see pollutants. Thermal infrared imagery could play a unique role in monitoring and modeling atmospheric pollution.     

The LUCAS topsoil database and derived information on the regional variability of cropland topsoil properties in the European Union

Approximately 20,000 topsoil samples were collected in 25 European Union (EU) Member States (EU-27 except Bulgaria and Romania) with the aim to produce the first coherent pan-European physical and chemical topsoil database, which can serve as baseline information for an EU wide harmonized soil monitoring. The soil sampling was undertaken within the frame of the Land Use/Land Cover Area Frame Survey (LUCAS), a project to monitor changes in the management and character of the land surface of the EU. Soil samples have been analysed for basic soil properties, including particle size distribution, pH, organic carbon, carbonates, NPK, cation exchange capacity (CEC) and multispectral signatures. Preliminary studies show the outstanding potential of the dataset for enhancing the knowledge base on soils in the EU. The current paper provides an introduction to the LUCAS Topsoil 2009 project and provides an example of data applicability for cropland assessment by highlighting initial results for regional and national comparisons.     

Dynamics of aeolian desertification and its driving forces in the Horqin Sandy Land,Northern China

Aeolian desertification is one of the most serious environmental and socioeconomic problems in arid, semi-arid, and dry subhumid zones. Understanding desertification processes and causes is important to provide reasonable and effective control measures for preventing desertification. With satellite remote sensing images as data source to assess the temporal and spatial dynamics of desertification from 1975 to 2010 in the Horqin Sandy Land, dynamic changes of aeolian desertification were detected using the human–machine interactive interpretation method. The driving factors of local desertification were analyzed based on natural and socioeconomic data. The results show that aeolian desertified land in the study area covered 30,199 km² in 2010, accounting for 24.1 % of the study area. The total area of aeolian desertified land obviously expanded from 30,884 km² in 1975 to 32,071 km² in 1990, and gradually decreased to 30,199 km² in 2010; aeolian desertified land represented an increasing trend firstly and then decreased. During the past 35 years, the gravity centers of desertified lands that are classified as extremely severe and severe generally migrated to the northeast, whereas those that are moderate and slight migrated to the northwest. The migration distance of severely desertified land was the largest, which indicated the southern desertified lands were improved during the last few decades. In addition, the climatic variation in the past 35 years has been favorable to desertification in the Horqin Sandy Land. Aeolian desertified land rapidly expanded from 1975 to 1990 under the combined effects of climate changes and unreasonable human activities. After the 1990s, the main driving factors responsible for the decrease in desertification were positive human activities, such as the series of antidesertification and ecological restoration projects.     

A landscape approach to quantifying land cover changes in Yulin, Northwest China

In this study we quantified land cover changes in the arid region of Yulin City, Northwest China between 1985 and 2000 using remote sensing and GIS in conjunction with landscape modeling. Land covers were mapped into 20 categories from multitemporal Landsat TM images. Five landscape indices were calculated from these maps at the land cover patches level. It was found that fallow land decreased by 125,148 ha while grassland and woodland increased by 107,975 and 17,157 ha, respectively. Landscape heterogeneity, dominance and fractal dimension changed little during the 15-year period while landscape became more fragmented, with an index rising from 0.56 to 0.58. The major factors responsible for these changes are identified as the change in the government policy on preserving the environment, continued growth in mining, and urbanization.     

Land desertification monitoring and assessment in Yulin of Northwest China using remote sensing and geographic information systems (GIS)

The objective of this study is to develop techniques for assessing and analysing land desertification in Yulin of Northwest China, as a typical monitoring region through the use of remotely sensed data and geographic information systems (GIS). The methodology included the use of Landsat TM data from 1987, 1996 and 2006, supplemented by aerial photos in 1960, topographic maps, field work and use of other existing data. From this, land cover, the Normalised Difference Vegetation Index (NDVI), farmland, woodland and grassland maps at 1:100,000 were prepared for land desertification monitoring in the area. In the study, all data was entered into a GIS using ILWIS software to perform land desertification monitoring. The results indicate that land desertification in the area has been developing rapidly during the past 40 years. Although land desertification has to some extent been controlled in the area by planting grasses and trees, the issue of land desertification is still serious. The study also demonstrates an example of why the integration of remote sensing with GIS is critical for the monitoring of environmental changes in arid and semi-arid regions, e.g. in land desertification monitoring in the Yulin pilot area. However, land desertification monitoring using remote sensing and GIS still needs to be continued and also refined for the purpose of long-term monitoring and the management of fragile ecosystems in the area.     

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.     

The validation analysis of the INSHORE system��a precise and efficient coastal survey system

Government and environmental entities are becoming increasingly concerned with qualifying and quantifying the erosion effects that are observed in sandy shores. Correspondingly, survey methodologies that gather data for such erosion studies are increasingly being demanded. The responsible entities are continually broadening their areas of interest, are concerned in the establishment of regular monitoring programmes and are demanding high accuracy from the geo-spatial data that is collected. The budget available for such monitoring activities, however, does not parallel the trend in the increasing demand for quality specifications. Survey methodologies need improvement to meet these requirements. We have developed a new land-based survey system--the INSHORE system--that is ideal for low cost, highly efficient and highly precise coastal surveys. The INSHORE system uses hi-tech hardware that is based on high-grade global positioning system (GPS) receivers and a laser distance sensor combined with advanced software algorithms. This system enables the determination of the ground coordinates of the surveyed areas with a precision of 1 to 2 cm, without having a sensor in contact with the ground surface. The absence of physical contact with the ground makes this system suitable for high-efficiency surveys. The accuracy of the positioning, which is based on advanced differential GPS processing, is enhanced by considering the estimated attitude of the GPS receiver holding structure and eliminates undesirable offsets. This paper describes the INSHORE survey system and presents the results of validation tests that were performed in a sandy shore environment.     

Retrospective assessment of dryland soil stability in relation to grazing and climate change

Accelerated soil erosion is an aspect of dryland degradation that is affected by repeated intense drought events and land management activities such as commercial livestock grazing. A soil stability index (SSI) that detects the erosion status and susceptibility of a landscape at the pixel level, i.e., stable, erosional, or depositional pixels, was derived from the spectral properties of an archived time series (from 1972 to 1997) of Landsat satellite data of a commercial ranch in northeastern Utah. The SSI was retrospectively validated with contemporary field measures of soil organic matter and erosion status that was surveyed by US federal land management agencies. Catastrophe theory provided the conceptual framework for retrospective assessment of the impact of commercial grazing and soil water availability on the SSI. The overall SSI trend was from an eroding landscape in the early drier 1970s towards stable conditions in the wetter mid-1980s and late 1990s. The landscape catastrophically shifted towards an extreme eroding state that was coincident with the “The Great North American Drought of 1988”. Periods of landscape stability and trajectories toward stability were coincident with extremely wet El Niño events. Commercial grazing had less correlation with soil stability than drought conditions. However, the landscape became more susceptible to erosion events under multiple droughts and grazing. Land managers now have nearly a year warning of El Niño and La Niña events and can adjust their management decisions according to predicted landscape erosion conditions.     

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.