Keyword

land use

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  • Gridded land use map of Peninsular Malaysia with a resolution of approximate 25 meters for the year 2018. The map includes nine different classes: 1) non-paddy agriculture, 2) paddy fields, 3) rural residential, 4) urban residential, 5) commercial/institutional, 6) industrial/infrastructure, 7) roads, 8) urban and 9) others. The land use map was created as part of the project “Malaysia - Flood Impact Across Scales”. The project is funded under the Newton-Ungku Omar Fund ‘Understanding of the Impacts of Hydrometeorological Hazards in South East Asia’ call. The grant was jointly awarded by the Natural Environment Research Council and the MYPAIR Scheme under the Ministry of Higher Education of Malaysia. Full details about this dataset can be found at https://doi.org/10.5285/36df244e-11c8-44bc-aa9b-79427123c42c

  • This dataset is the 2018 Corine Land Cover map, consisting of 44 classes in the hierarchical three level Corine nomenclature. Corine Land Cover (CLC) 2018, CLC change 2012-2018 and CLC 2012 revised are three of the datasets produced within the frame of the Copernicus programme on land monitoring. Corine Land Cover (CLC) provides consistent information on land cover and land cover changes across Europe; these two maps are the UK component of Europe. This inventory was initiated in 1985 (reference year 1990) and established a time series of land cover information with updates in 2000, 2006 and 2012 being the last iteration. CLC products are based on photointerpretation of satellite images by national teams of participating countries – the EEA member and cooperating countries – following a standard methodology and nomenclature with the following base parameters: 44 classes in the hierarchical three level Corine nomenclature; minimum mapping unit (MMU) of status layers is 25 hectares; minimum width of linear elements is 100 metres; minimum mapping unit (MMU) for Land Cover Changes (LCC) for the change layers is 5 hectares. The resulting national land cover inventories are further integrated into a seamless land cover map of Europe. Land cover and land use (LCLU) information is important not only for land change research, but also more broadly for the monitoring of environmental change, policy support, the creation of environmental indicators and reporting. CLC datasets provide important datasets supporting the implementation of key priority areas of the Environment Action Programmes of the European Union as protecting ecosystems, halting the loss of biological diversity, tracking the impacts of climate change, assessing developments in agriculture and implementing the EU Water Framework Directive, among others. More information about the Corine Land Cover (CLC) and Copernicus land monitoring data in general can be found at http://land.copernicus.eu/. Full details about this dataset can be found at https://doi.org/10.5285/084e0bc6-e67f-4dad-9de6-0c698f60e34d

  • This dataset is the 2012 revised Corine Land Cover (CLC) map, consisting of 44 classes in the hierarchical three level Corine nomenclature, produced during the CLC2018 production to improve the CLC2012 inventory. CLC 2018, CLC change 2012-2018 and CLC 2012 revised are three of the datasets produced within the frame of the Copernicus programme on land monitoring. Corine Land Cover (CLC) provides consistent information on land cover and land cover changes across Europe; these two maps are the UK component of Europe. This inventory was initiated in 1985 (reference year 1990) and established a time series of land cover information with updates in 2000, 2006 and 2012 being the last iteration. CLC products are based on photointerpretation of satellite images by national teams of participating countries – the EEA member and cooperating countries – following a standard methodology and nomenclature with the following base parameters: 44 classes in the hierarchical three level Corine nomenclature; minimum mapping unit (MMU) of status layers is 25 hectares; minimum width of linear elements is 100 metres; minimum mapping unit (MMU) for Land Cover Changes (LCC) for the change layers is 5 hectares. The resulting national land cover inventories are further integrated into a seamless land cover map of Europe. Land cover and land use (LCLU) information is important not only for land change research, but also more broadly for the monitoring of environmental change, policy support, the creation of environmental indicators and reporting. CLC datasets provide important datasets supporting the implementation of key priority areas of the Environment Action Programmes of the European Union as protecting ecosystems, halting the loss of biological diversity, tracking the impacts of climate change, assessing developments in agriculture and implementing the EU Water Framework Directive, among others. More information about the Corine Land Cover (CLC) and Copernicus land monitoring data in general can be found at http://land.copernicus.eu/. Full details about this dataset can be found at https://doi.org/10.5285/9bb7caab-764d-407b-9a81-0d758722d900

  • This dataset is the Corine Land Cover (CLC) change map between 2012 and 2018, consisting of 44 classes in the hierarchical three level Corine nomenclature. The Corine land cover changes between 2012 and 2018 for the UK, Isle of Man, Jersey and Guernsey dataset forms part of the Corine Land Cover Maps collection and is produced within the frame of the Copernicus programme on land monitoring. Corine Land Cover (CLC) provides consistent information on land cover and land cover changes across Europe; this change map is the UK component of the European coverage. This inventory was initiated in 1985 (reference year 1990) and established a time series of land cover information with updates in 2000, 2006 and 2012 being the last iteration. CLC products are based on photointerpretation of satellite images by national teams of participating countries – the EEA member and cooperating countries – following a standard methodology and nomenclature with the following base parameters: 44 classes in the hierarchical three level Corine nomenclature; minimum mapping unit (MMU) of status layers is 25 hectares; minimum width of linear elements is 100 metres; minimum mapping unit (MMU) for Land Cover Changes (LCC) for the change layers is 5 hectares. The resulting national land cover inventories are further integrated into a seamless land cover map of Europe. Land cover and land use (LCLU) information is important not only for land change research, but also more broadly for the monitoring of environmental change, policy support, the creation of environmental indicators and reporting. CLC datasets provide important datasets supporting the implementation of key priority areas of the Environment Action Programmes of the European Union as protecting ecosystems, halting the loss of biological diversity, tracking the impacts of climate change, assessing developments in agriculture and implementing the EU Water Framework Directive, among others. More information about the Corine Land Cover (CLC) and Copernicus land monitoring data in general can be found at http://land.copernicus.eu/. Full details about this dataset can be found at https://doi.org/10.5285/027b6432-f44d-41ab-b349-89fae673d5f5

  • This data collection results from abundance surveys of 7 species of weeds in ca. 500 lowland arable fields in 49 farms over three years. Each field was divided into large grids of 20x20 metre cells, and the density of seven species was estimated three times a year. The study is part of the NERC Rural Economy and Land Use (RELU) programme. In the context of changing external and internal pressures on UK agriculture, particularly those associated with the ongoing reform of the EU Common Agricultural Policy, it is imperative to determine whether all of the various dimensions of sustainability - including the relevant economic and environmental objectives as well as social and cultural values - can be integrated successfully at the farm and landscape levels. Although the ways in which economic, technological, and regulatory changes are likely to affect the profitability and management of farms of varying size are reasonably well understood, there is not the knowledge or understanding to predict the resulting effects on biodiversity. For example, the effect of changes in arable farming practices on field weeds and, in turn, on habitats and food supply required to sustain farm birds is a case in point. This knowledge is critical, however, if we are to understand the ecological consequences of changes in agricultural policy. Furthermore, it is also important if we are to design and justify changes in farming methods that can not only enhance nature conservation, but do this is ways that are practical and appealing from a farmer's point of view. This understanding is essential if we are to achieve an agriculture that is sustainable in both economic and environmental terms and is widely perceived to have social and cultural value. A consistent theme in all components of this research project is to understand the behaviour (of farmers, weeds or birds) and then use this information to produce predictive models. Whilst there have been a number of models of economic behaviour, weed populations and bird populations - including many by the research team here - the really novel component of this research is to integrate these within one framework. Farmer interviews on economic attitudes and preferences associated with and importance of different land-use objectives to lowland arable farmers are available at the UK Data Archive under study number 6728 (see online resources). Further documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see online resources).

  • This dataset consists in a collection of remotely sensed drought indicators time series. The data was extracted from CEH's gridded remotely sensed drought indicators product (Tanguy et al., 2016; http://doi.org/10.5285/4e0d0e50-2f9c-4647-864d-5c3b30bb5f4b), which has gridded data for Europe for three drought indicators: - the Vegetation Condition Index (VCI) based on satellite product NDVI (Normalised Difference Vegetation Index); - the Temperature Condition Index (TCI) based on remotely sensed LST (Land Surface Temperature); - the Vegetation Health Index (VHI) which is a combination of VCI and TCI. These three drought indicators have been extracted for European NUTS regions (level 0, 1, 2 and 3). These have been masked with a land use land cover map to be able to study different responses for various land cover types. A simplified LULC was created, with only four classes: forest, crop, shrub and grass. One extra time series was created for all classes together. Full details about this dataset can be found at https://doi.org/10.5285/5b3fcf9f-19d4-4ad3-a8bb-0a5ea02c857e

  • This dataset consists of an ecology-focused survey of stillwaters along the rivers Yure and Swale and sediment flux measurements recorded at sites along the river Esk. The dataset results from a study which was part of the Rural Economy and Land Use (RELU) programme. The project analysed the complex network of natural and socio-economic relationships around angling in the river environment, including institutions of governance and land use practices at a range of interconnected scales. The sustainability, integrity and ecological value of river catchments are currently major issues for science. The management of freshwaters and their ecologies requires addressing processes that work across the boundaries between the natural environment, economy and society. This research focused upon these cross-cutting processes in an interdisciplinary, holistic assessment of river environments through the case of angling. Angling benefits from and influences river quality, design and management. It also links urban and rural environments and is an economic driver for the rural economy, involving about 4 million people in England and Wales and contributing 6 billion pounds to the economy through freshwater angling alone. This research aimed to provide insights into how environmental and socio-economic drivers for rural change work. This project therefore aimed to identify and analyse the complex network of influences and feedbacks around angling in the rural environment. These include natural and socio-economic influences, interdisciplinary research from both natural and social science disciplines (aquatic ecology, geomorphology, anthropology, sociology, human geography), as well as stakeholders from government, NGOs and the local community. This project focused upon three rivers in northern England - the Esk, Ure and Swale - in the course of an integrated and fine-grained study. The postal survey and business interviews from this study are available at the UK Data Archive under study number 6580 (see online resources). Further documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see online resources).