Tim Brewer

Improving local estimations and regional trends of glacier equilibrium line altitudes

Abstract Small glaciers have short response times to climate change and therefore offer a powerful means of climate monitoring. Glacier responses to climate, or their mass change, may be suggested by a change in the Equilibrium Line Altitude (ELA). However, regional climatic reconstructions have repeatedly neglected the importance of local variations in ELAs in preference for regional trends. For small glaciers close to the glaciation level, ignoring the importance of local topographic components in mass balance estimates may lead to erroneous climatic reconstructions. Of 510 small valley and cirque glaciers digitised across northern Scandinavia, 284 were objectively deemed suitable for inferring an ELA. The inferred ELA was derived from the median elevation and several local topographic variables using regression analysis. The glacier elevation, area, slope and aspect parameters were found to be the best predictors of the local ELA. ELA estimations improved from 77% up to 94% accuracy when topographic parameters for every grid‐cell within rasters representing glacier surfaces were computed rather than using subjective measurements from topographic maps. Regional ELA trend surfaces, interpolated between the local ELA values, differed in effectively representing the local variability, depending upon the distribution and accuracy of the local ELA values. A second‐order polynomial trend surface most accurately represented ELA variations across the study area, within the initial local measurement accuracy of ±100 m. It is concluded that current subjective topographic map‐based analyses are unlikely to be sufficiently accurate for predicting the regional ELA of small, sensitive and marginal glaciers, unless CIS‐based spatial analyses are made at a reasonable resolution.

Monitoring land use change in the Badia transition zone in Jordan using aerial photography and satellite imagery

Detection of land use change makes a valuable contribution to the planning and monitoring of drylands. Land use changes at four sites within the Badia transition zone of Jordan were investigated and quantified over the period from 1953 to 1992 using black and white aerial photographs and SPOT PAN satellite imagery digitally merged with Landsat TM. Land use interpretation was checked in the field, and analysed using a Geographical Information System (GIS). Results indicated that land use changes have altered the character of the selected study sites. The important land use changes were from rangeland to rain-fed cultivation, irrigated fields and urban settlements. The increased agricultural activity was reflected in the land use maps through the 39-year period with the appearance of irrigated fields between 1978 and 1992. The land use changes are mainly attributed to the high population growth rate in Jordan and in the Badia, socio-economic change amongst Beduoin and farmers, the land tenure system and to a minor extent environmental factors.

Monitoring landscape change in the National Parks of England and Wales using aerial photo interpretation and GIS

Aerial photographic interpretation was carried out to extract information on 50 types of landscape feature in the National Parks of England and Wales for two time periods, the mid 1970s and the late 1980s. The aim of the work was to identify and quantify changes at different administrative levels (National Park, County, District, and Parish). To facilitate this investigation, data were converted to digital format and analysed with a Geographic Information System (GIS). The work was carried out under commerical contract but required considerable research and development input to achieve the results. In this paper we report on the methodological developments. We present some of the main results at national level and give an example of how the GIS can be used to analyse landscape change in specific locations. The work for this Project was completed in 1991. At the beginning of a new millenium, we reflect on appropriate modifications to the approach in the context of current technical developments.

Soil erosion survey of the central part of the Swaziland Middleveld

Abstract Soil erosion has worsened considerably in the Middleveld of Swaziland over the last 20 years. Most of the erosion has occurred on deep colluvial and saprolitic materials and is associated with convex-slope breaks and rejuvenation shoulders on valley sides. Although the risk of erosion seems to reflect natural instability in the landscape, the way in which the land is used determines the ultimate severity of the problem. Land systems can serve as functional units as far as erosion assessment is concerned. The most severely eroded land occurs within the Manzini, Jabuleni, Lobamba and Chibidze land systems. The universal soil loss equation (USLE) and the soil loss estimator for southern Africa (SLEMSA) give vastly different estimates of the rate of soil loss but no information is available to validate or refute the predictions.

Survey and monitoring of opium poppy and wheat in Afghanistan: 2003–2009

An integrated application of remote-sensing technology was devised and applied in Afghanistan during 2003–2009 providing critical information on cereal and poppy cultivation and poppy eradication. The results influenced UK and international policy and counter-narcotics actions in Afghanistan.

Monitoring British Upland Ecosystems With the Use of Landscape Structure as an Indicator for State-and-Transition Models

Abstract Remote sensing and landscape ecology concepts can provide a useful framework for state-and-transition models (STM) in order to quantify thresholds at different scales, and provide useful information for scientists, land managers, and conservationists in relation to resilience management. The overall aim of this research was to develop a spatially explicit STM to quantify thresholds based on the scale of disturbance processes impacting a grazing system. Specific objectives were to develop a conceptual STM framework for upland grazing ecosystems, to quantify spatial dynamics of stable and degraded pastures, and to assess threshold occurrence. Color aerial photography from Armboth Fell in the English Lake District National Park (United Kingdom) was classified into bare rock, dwarf shrub heath (DSH), and grassland/degraded wet heath (GDWH) in four pastures with different degrees of grazing pressure. Vegetation communities from these pastures were combined with soils, climate, and landform data to create a conceptual STM framework. Each pasture was sampled with 2-ha plots to quantify DSH and GDWH spatial structure. The proposed STM consisted of two reference and three alternative states. Low–grazing-pressure areas showed significantly higher percentage of DSH cover with larger contiguous patches and lower patch density than high–grazing-pressure areas. Breakpoints, considered to be thresholds, in mean patch area were identified in our data when DSH percentage cover was < 63% and GDWH, > 77%. The present study has shown the value of a robust, reliable, and repeatable approach to identify landscape dynamics and integrate it with field data to inform a conceptual STM framework for upland grazing ecosystems. It also demonstrates the importance of selecting scales relevant to the predominant disturbance process to test for threshold occurrence, and how this approach can be integrated with current assessment methods for resilience management.

Land cover attributes and their utility within land cover mapping: a practical example

A disaggregated approach to land cover survey is developed utilising data primitives. A field methodology is developed to characterise five attributes: species composition, cover, height, structure and density. The utility of these data primitives, as land cover ‘building blocks’ is demonstrated via classification of the field data to multiple land cover schema. Per-pixel classification algorithms, trained on the basis of the classified field data, are utilised to classify a SPOT 5 satellite image. The resultant land cover maps have overall accuracies approaching 80%. However, significantly lower validation accuracies are demonstrated to be a function of sample fraction. The aggregation of attributes to classes under-utilises the potential of remote sensing data to describe variability in vegetation composition across the landscape. Consequently, land cover attribute parameterisation techniques are discussed. In conclusion, it is demonstrated that data primitives provide a flexible field data source proven to support multiple land cover classification schemes and scales.

Monitoring landscape change--the role for GIS

Abstract Geographic information systems (GIS) have made major contributions to landscape mapping and analysis, but they must be used carefully in relation to the properties of particular sets of landscape data and the types of query to be asked. This paper describes two projects undertaken to assess the types and amounts of landscape change occurring in the countryside, using aerial photograph sets from different dates. One project relates to the national parks of England and Wales, the other to the county of Bedfordshire. Results are presented, and the benefits of GIS in processing vast quantities of data and permitting specific queries are reviewed.

A review of potential methods for monitoring rangeland degradation in Libya

Natural and human factors exert a profound impact on the degradation of rangelands, human effects being the most significant factor in increasing the severity of deterioration. This occurs through agricultural expansion at the expense of rangelands, and with the number of domestic and wildlife animals exceeding the natural carrying capacity. This raises concerns about the ongoing sustainability of these land resources, as well as the sustainability of traditional pastoral land practices. Rangelands require effective management, which is dependent upon accurate and timely monitoring data to support the assessment of rangeland deterioration. Natural rangelands provide one of the significant pillars of support for the Libyan national economy. Despite the important role of rangeland in Libya from both economic and environmental perspectives, the vegetation cover of Libyan rangeland has changed adversely qualitatively and quantitatively over the past four decades.Ground-based observation methods are widely used to assess rangeland degradation in Libya. However, multi-temporal observations are often not integrated nor repeatable, making it difficult for rangeland managers to detect degradation consistently. Field study costs are also significantly high in comparison with their accuracy and reliability, both in terms of the time and resources required. Remote-sensing approaches offer the advantage of spanning large geographical areas with multiple spatial, spectral and temporal resolutions. These data can play a significant role in rangeland monitoring, permitting observation, monitoring and prediction of vegetation changes, productivity assessment, fire extent, vegetation and soil moisture measurement and quantifying the proliferation of invasive plant species. This paper reviews the factors causing rangeland degradation in Libya, identifying appropriate remote-sensing methods that can be used to implement appropriate monitoring procedures.

Image segmentation for improved consistency in image-interpretation of opium poppy

ABSTRACT The image-interpretation of opium poppy crops from very high resolution satellite imagery forms part of the annual Afghanistan opium surveys conducted by the United Nations Office on Drugs and Crime and the United States Government. We tested the effect of generalization of field delineations on the final estimates of poppy cultivation using survey data from Helmand province in 2009 and an area frame sampling approach. The sample data was reinterpreted from pan-sharpened IKONOS scenes using two increasing levels of generalization consistent with observed practice. Samples were also generated from manual labelling of image segmentation and from a digital object classification. Generalization was found to bias the cultivation estimate between 6.6% and 13.9%, which is greater than the sample error for the highest level. Object classification of image-segmented samples increased the cultivation estimate by 30.2% because of systematic labelling error. Manual labelling of image-segmented samples gave a similar estimate to the original interpretation. The research demonstrates that small changes in poppy interpretation can result in systematic differences in final estimates that are not included within confidence intervals. Segmented parcels were similar to manually digitized fields and could provide increased consistency in field delineation at a reduced cost. The results are significant for Afghanistan’s opium monitoring programmes and other surveys where sample data are collected by remote sensing.