Guidelines for air quality maintenance planning and analysis.

Vol. 7: second ed., 1975.

The rural land problem, the remedy : a speech delivered by the Right Hon. D. Lloyd George, M.P. at Swindon, on October 18th, 1913.

Mode of access: Internet.

Pioneer settlement in the Asiatic tropics; studies in land utilization and agricultural colonization in southeastern Asia

"This study has been made with the cooperation of the Secretariat of the Institute of Pacific relations and constitutes a report in its International research series."

Land resource analysis /

Research proposal submitted to the National Science Foundation, Research Applied to National Needs (RANN).

Land utilization and rural economy in Korea,

Mode of access: Internet.

Arid and semiarid land stewardship : a 10-year review of accomplishments and contributions of the International Arid Lands Consortium /

"November 2001."

Public Land for Affordable Housing: An Evaluation of a HALA Proposal in Seattle

Thesis (Master's)--University of Washington, 2016-06

Modeling the age of tropical moist forest fragments in heavily-cleared lowland landscapes of Colombia

Increasingly, large areas of native tropical forests are being transformed into a mosaic of human dominated land uses with scattered mature remnants and secondary forests. In general, at the end of the land clearing process, the landscape will have two forest components: a stable component of surviving mature forests, and a dynamic component of secondary forests of different ages. As the proportion of mature forests continues to decline, secondary forests play an increasing role in the conservation and restoration of biodiversity. This paper aims to predict and explain spatial and temporal patterns in the age of remnant mature and secondary forests in lowland Colombian landscapes. We analyse the age distributions of forest fragments, using detailed temporal land cover data derived from aerial photographs. Ordinal logistic regression analysis was applied to model the spatial dynamics of mature and secondary forest patches. In particular, the effect of soil fertility, accessibility and auto-correlated neighbourhood terms on forest age and time of isolation of remnant patches was assessed. In heavily transformed landscapes, forests account for approximately 8% of the total landscape area, of which three quarters are comprised of secondary forests. Secondary forest growth adjacent to mature forest patches increases mean patch size and core area, and therefore plays an important ecological role in maintaining landscape structure. The regression models show that forest age is positively associated with the amount of neighbouring forest, and negatively associated with the amount of neighbouring secondary vegetation, so the older the forest is the less secondary vegetation there is adjacent to it. Accessibility and soil fertility also have a negative but variable influence on the age of forest remnants. The probability of future clearing if current conditions hold is higher for regenerated than mature forests. The challenge of biodiversity conservation and restoration in dynamic and spatially heterogeneous landscape mosaics composed of mature and secondary forests is discussed. (c) 2004 Elsevier B.V. All rights reserved.

Regional-scale, fully coupled modelling of stream-aquifer interaction in a tropical catchment

The planning and management of water resources in the Pioneer Valley, north-eastern Australia requires a tool for assessing the impact of groundwater and stream abstractions on water supply reliabilities and environmental flows in Sandy Creek (the main surface water system studied). Consequently, a fully coupled stream-aquifer model has been constructed using the code MODHMS, calibrated to near-stream observations of watertable behaviour and multiple components of gauged stream flow. This model has been tested using other methods of estimation, including stream depletion analysis and radon isotope tracer sampling. The coarseness of spatial discretisation, which is required for practical reasons of computational efficiency, limits the model's capacity to simulate small-scale processes (e.g., near-stream groundwater pumping, bank storage effects), and alternative approaches are required to complement the model's range of applicability. Model predictions of groundwater influx to Sandy Creek are compared with baseflow estimates from three different hydrograph separation techniques, which were found to be unable to reflect the dynamics of Sandy Creek stream-aquifer interactions. The model was also used to infer changes in the water balance of the system caused by historical land use change. This led to constraints on the recharge distribution which can be implemented to improve model calibration performance. (c) 2006 Elsevier B.V. All rights reserved.

The application of remote sensing to water resources

Techniques are developed for the visual interpretation of drainage features from satellite imagery. The process of interpretation is formalised by the introduction of objective criteria. Problems of assessing the accuracy of maps are recognized, and a method is developed for quantifying the correctness of an interpretation, in which the more important features are given an appropriate weight. A study was made of imagery from a variety of landscapes in Britain and overseas, from which maps of drainage networks were drawn. The accuracy of the mapping was assessed in absolute terms, and also in relation to the geomorphic parameters used in hydrologic models. Results are presented relating the accuracy of interpretation to image quality, subjectivity and the effects of topography. It is concluded that the visual interpretation of satellite imagery gives maps of sufficient accuracy for the preliminary assessment of water resources, and for the estimation of geomorphic parameters. An examination is made of the use of remotely sensed data in hydrologic models. It is proposed that the spectral properties of a scene are holistic, and are therefore more efficient than conventional catchment characteristics. Key hydrologic parameters were identified, and were estimated from streamflow records. The correlation between hydrologic variables and spectral characteristics was examined, and regression models for streamflow were developed, based solely on spectral data. Regression models were also developed using conventional catchment characteristics, whose values were estimated using satellite imagery. It was concluded that models based primarily on variables derived from remotely sensed data give results which are as good as, or better than, models using conventional map data. The holistic properties of remotely sensed data are realised only in undeveloped areas. In developed areas an assessment of current land-use is a more useful indication of hydrologic response.

Computer automation of land evaluation procedures

This study was concerned with the computer automation of land evaluation. This is a broad subject with many issues to be resolved, so the study concentrated on three key problems: knowledge based programming; the integration of spatial information from remote sensing and other sources; and the inclusion of socio-economic information into the land evaluation analysis. Land evaluation and land use planning were considered in the context of overseas projects in the developing world. Knowledge based systems were found to provide significant advantages over conventional programming techniques for some aspects of the land evaluation process. Declarative languages, in particular Prolog, were ideally suited to integration of social information which changes with every situation. Rule-based expert system shells were also found to be suitable for this role, including knowledge acquisition at the interview stage. All the expert system shells examined suffered from very limited constraints to problem size, but new products now overcome this. Inductive expert system shells were useful as a guide to knowledge gaps and possible relationships, but the number of examples required was unrealistic for typical land use planning situations. The accuracy of classified satellite imagery was significantly enhanced by integrating spatial information on soil distribution for Thailand data. Estimates of the rice producing area were substantially improved (30% change in area) by the addition of soil information. Image processing work on Mozambique showed that satellite remote sensing was a useful tool in stratifying vegetation cover at provincial level to identify key development areas, but its full utility could not be realised on typical planning projects, without treatment as part of a complete spatial information system.

Background levels of urban land contamination

The research work reported in this thesis is concerned with the development and application of an urban scale sampling methodology for measuring and assessing background levels of heavy metal soil contamination in large and varied urban areas. The policy context of the work is broadly the environmental health problems posed by contaminated land and their implications for urban development planning. Within this wider policy context, the emphasis in the research has been placed on issues, related to the determination and application of 'guidelines' for assessing the significance of contaminated land for environmental planning. In concentrating on background levels of land contamination, the research responds to the need for additional techniques which address both the problems of measuring soil contamination at the urban scale and which are also capable of providing detailed information for use in the assessment of contaminated sites. Therefore, a key component of the work has been the development of a land-use based sampling framework for generating spatially comprehensive data on heavy metals in soil. The utility of the information output of the sampling method is demonstrated in two alternative ways. Firstly, it has been used to map the existing pattern of typical levels of heavy metals in urban soils. Secondly, it can be used to generate both generalised data in the form of 'reference levels' from which the overall significance of .background contamination may be assessed and detailed data, termed 'normal limit levels' for use in the assessment of site specific investigation data. The fieldwork was conducted in the West Midlands Metropolitan County and surface soil has been sampled and analysed for a measure of plant-available' and 'total' lead cadmium, copper and zinc. The research contrasts with much of the previous work on contaminated land which has generally concentrated on either the detailed investigation of individual sites suspected of being contaminated or the appraisal of land contamination resulting from specific point sources.

European biorefineries:implications for land, trade and employment

Biorefineries are expected to play a major role in a future low carbon economy and substantial investments are being made to support this vision. However, it is important to consider the wider socio-economic impacts of such a transition. This paper quantifies the potential trade, employment and land impacts of economically viable European biorefinery options based on indigenous straw and wood feedstocks. It illustrates how there could be potential for 70-80 European biorefineries, but not hundreds. A single facility could generate tens of thousands of man-years of employment and employment creation per unit of feedstock is higher than for biomass power plants. However, contribution to national GDP is unlikely to exceed 1% in European member states, although contributions to national agricultural productivity may be more significant, particularly with straw feedstocks. There is also a risk that biorefinery development could result in reduced rates of straw incorporation into soil, raising concerns that economically rational decisions to sell rather than reincorporate straw could result in increased agricultural land-use or greenhouse gas emissions. © 2013.

An investigation of location effect on trip production using artificial neural networks

As traffic congestion exuberates and new roadway construction is severely constrained because of limited availability of land, high cost of land acquisition, and communities' opposition to the building of major roads, new solutions have to be sought to either make roadway use more efficient or reduce travel demand. There is a general agreement that travel demand is affected by land use patterns. However, traditional aggregate four-step models, which are the prevailing modeling approach presently, assume that traffic condition will not affect people's decision on whether to make a trip or not when trip generation is estimated. Existing survey data indicate, however, that differences exist in trip rates for different geographic areas. The reasons for such differences have not been carefully studied, and the success of quantifying the influence of land use on travel demand beyond employment, households, and their characteristics has been limited to be useful to the traditional four-step models. There may be a number of reasons, such as that the representation of influence of land use on travel demand is aggregated and is not explicit and that land use variables such as density and mix and accessibility as measured by travel time and congestion have not been adequately considered. This research employs the artificial neural network technique to investigate the potential effects of land use and accessibility on trip productions. Sixty two variables that may potentially influence trip production are studied. These variables include demographic, socioeconomic, land use and accessibility variables. Different architectures of ANN models are tested. Sensitivity analysis of the models shows that land use does have an effect on trip production, so does traffic condition. The ANN models are compared with linear regression models and cross-classification models using the same data. The results show that ANN models are better than the linear regression models and cross-classification models in terms of RMSE. Future work may focus on finding a representation of traffic condition with existing network data and population data which might be available when the variables are needed to in prediction.