scholarly journals Land cover and vegetation data from an ecological survey of "key habitat" landscapes in England, 1992–1993

2018 ◽  
Vol 10 (2) ◽  
pp. 899-918
Author(s):  
Claire M. Wood ◽  
Robert G. H. Bunce ◽  
Lisa R. Norton ◽  
Simon M. Smart ◽  
Colin J. Barr

Abstract. Since 1978, a series of national surveys (Countryside Survey, CS) have been carried out by the Centre for Ecology and Hydrology (CEH) (formerly the Institute of Terrestrial Ecology, ITE) to gather data on the natural environment in Great Britain (GB). As the sampling framework for these surveys is not optimised to yield data on rarer or more localised habitats, a survey was commissioned by the then Department of the Environment (DOE, now the Department for Environment, Food and Rural Affairs, DEFRA) in the 1990s to carry out additional survey work in English landscapes which contained semi-natural habitats that were perceived to be under threat, or which represented areas of concern to the ministry. The landscapes were lowland heath, chalk and limestone (calcareous) grasslands, coasts and uplands. The information recorded allowed an assessment of the extent and quality of a range of habitats defined during the project, which can now be translated into standard UK broad and priority habitat classes. The survey, known as the "Key Habitat Survey", followed a design which was a series of gridded, stratified, randomly selected 1 km squares taken as representative of each of the four landscape types in England, determined from statistical land classification and geological data ("spatial masks"). The definitions of the landscapes are given in the descriptions of the spatial masks, along with definitions of the surveyed habitats. A total of 213 of the 1 km2 square sample sites were surveyed in the summers of 1992 and 1993, with information being collected on vegetation species, land cover, landscape features and land use, applying standardised repeatable methods. The database contributes additional information and value to the long-term monitoring data gathered by the Countryside Survey and provides a valuable baseline against which future ecological changes may be compared, offering the potential for a repeat survey. The data were analysed and described in a series of contract reports and are summarised in the present paper, showing for example that valuable habitats were restricted in all landscapes, with the majority located within protected areas of countryside according to different UK designations. The dataset provides major potential for analyses, beyond those already published, for example in relation to climate change, agri-environment policies and land management. Precise locations of the plots are restricted, largely for reasons of landowner confidentiality. However, the representative nature of the dataset makes it highly valuable for evaluating the status of ecological elements within the associated landscapes surveyed. Both land cover data and vegetation plot data were collected during the surveys in 1992 and 1993 and are available via the following DOI: https://doi.org/10.5285/7aefe6aa-0760-4b6d-9473-fad8b960abd4. The spatial masks are also available from https://doi.org/10.5285/dc583be3-3649-4df6-b67e-b0f40b4ec895.

2017 ◽  
Author(s):  
Claire M. Wood ◽  
Robert G. H. Bunce ◽  
Lisa R. Norton ◽  
Simon M. Smart ◽  
Colin J. Barr

Abstract. Since 1978, a series of national surveys (Countryside Surveys) have been carried out by the Centre for Ecology and Hydrology (formerly the Institute of Terrestrial Ecology) to gather data on the natural environment in Great Britain. As the sampling framework for these surveys is not optimised to yield data on rarer or more specialised habitats, a survey was commissioned by the then Department of the Environment (DOE, now the Department for Environment Food & Rural Affairs, DEFRA), in the 1990s to carry out additional survey work in English landscapes which contained semi-natural habitats that were perceived to be under threat, or which represented areas of concern to the Ministry. The landscapes were: lowland heath, chalk and limestone grasslands, coasts and uplands. These landscapes were chosen from a list identified as `key habitats' in the Countryside Stewardship Scheme, an agri-environment scheme initiated in 1991. The survey design was a series of gridded, stratified, randomly selected 1 km squares taken as representative of classes derived from environmental classifications (or spatial masks) for each of the four landscape types in England determined from a statistical land classification. This resulted in a total of 213 of these squares being surveyed in the summers of 1992 and 1993, with information being collected regarding vegetation species, land cover, landscape features and land use. Data from the survey were collected using standardised, repeatable methods, with the database now providing a valuable baseline against which future ecological changes, resulting from a range of different drivers, may be compared. Following the surveys, the data were analysed and described in a series of contract reports showing that valuable habitats were restricted in all landscapes and that the majority were within designated land. The data set provides major potential for analyses, beyond those published in the reports published in 1996, for example in relation to climate change, agri-environment policies and land management. Precise locations of the plots are restricted, largely for reasons of landowner confidentiality. However, the representative nature of the data set makes it highly valuable for evaluating the status of the associated landscapes and vegetation covered. Both land cover data and vegetation plot data were collected during the surveys in 1992 and 1993, and are available via the following DOI: https://doi.org/10.5285/7aefe6aa-0760-4b6d-9473-fad8b960abd4. The spatial masks are also available from: https://doi.org/10.5285/dc583be3-3649-4df6-b67e-b0f40b4ec895.


2018 ◽  
Vol 192 ◽  
pp. 02017 ◽  
Author(s):  
Jatuwat Wattanasetpong ◽  
Uma Seeboonruang ◽  
Uba Sirikaew ◽  
Walter Chen

Soil loss due to surface erosion has been a global problem not just for developing countries but also for developed countries. One of the factors that have greatest impact on soil erosion is land cover. The purpose of this study is to estimate the long-term average annual soil erosion in the Lam Phra Phloeng watershed, Nakhon Ratchasima, Thailand with different source of land cover by using the Universal Soil Loss Equation (USLE) and GIS (30 m grid cells) to calculate the six erosion factors (R, K, L, S, C, and P) of USLE. Land use data are from Land Development Department (LDD) and ESA Climate Change Initiative (ESA/CCI) in 2015. The result of this study show that mean soil erosion by using land cover from ESA/CCI is less than LDD (29.16 and 64.29 ton/ha/year respectively) because soil erosion mostly occurred in the agricultural field and LDD is a local department that survey land use in Thailand thus land cover data from this department have more details than ESA/CCI.


2014 ◽  
Vol 40 (2) ◽  
pp. 137-148 ◽  
Author(s):  
Dragan Čakmak ◽  
Jelena Beloica ◽  
Veljko Perović ◽  
Ratko Kadović ◽  
Vesna Mrvić ◽  
...  

Abstract Acidification, as a form of soil degradation is a process that leads to permanent reduction in the quality of soil as the most important natural resource. The process of soil acidification, which in the first place implies a reduction in soil pH, can be caused by natural processes, but also considerably accelerated by the anthropogenic influence of excessive S and N emissions, uncontrolled deforestation, and intensive agricultural processes. Critical loads, i.e. the upper limit of harmful depositions (primarily of S and N) which will not cause damages to the ecosystem, were determined in Europe under the auspices of the Executive Committee of the CLRTAP in 1980. These values represent the basic indicators of ecosystem stability to the process of acidification. This paper defines the status of acidification for the period up to 2100 in relation to the long term critical and target loading of soil with S and N on the territory of Krupanj municipality by applying the VSD model. The Inverse Distance Weighting (IDW) geostatistic module was used as the interpolation method. Land management, particularly in areas susceptible to acidification, needs to be focused on well-balanced agriculture and use of crops/seedlings to achieve the optimum land use and sustainable productivity for the projected 100-year period.


Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 881 ◽  
Author(s):  
Richard Ampomah ◽  
Hossein Hosseiny ◽  
Lan Zhang ◽  
Virginia Smith ◽  
Kristin Sample-Lord

Urbanization typically results in increased imperviousness which alters suspended sediment yield and impacts geomorphic and ecological processes within urban streams. Therefore, there is an increasing interest in the ability to predict suspended sediment yield. This study assesses the combined impact of urban development and increased precipitation on suspended sediment yield in the Cuyahoga River using statistical modeling. Historical satellite-based land-cover data was combined with precipitation and suspended sediment yield data to create a Multiple Linear Regression (MLR) model for the Cuyahoga watershed. An R2 value of 0.71 was obtained for the comparison between the observed and predicted results based on limited land-use and land-cover data. The model also shows that every 1 mm increase in the mean annual precipitation has the potential to increase the mean annual suspended sediment yield by 860 tons/day. Further, a 1 km2 increase in developed land area has the potential to increase mean annual suspended sediment yield by 0.9 tons/day. The framework proposed in this study provides decision makers with a measure for assessing the potential impacts of future development and climate alteration on water quality in the watershed and implications for stream stability, dam and flood management, and in-stream and near-stream infrastructure life.


Data ◽  
2017 ◽  
Vol 2 (2) ◽  
pp. 16 ◽  
Author(s):  
Amin Tayyebi ◽  
Samuel Smidt ◽  
Bryan Pijanowski

2010 ◽  
Vol 5 (5) ◽  
pp. 526-534 ◽  
Author(s):  
Jung Eun Kang ◽  
◽  
Walter Gillis Peacock ◽  
Rahmawati Husein ◽  

The U.S. Federal EmergencyManagement Agency requires jurisdictions to develop hazardmitigation plans (HMPs) to be eligible for hazard mitigation grants based on the 2000 Disaster Mitigation Act. As of May 2007, over 14,000 local jurisdictions in the US have developed single or multi-jurisdiction local hazard mitigation plans. However, little empirical research has examined the quality of local HMPs. This study develops a comprehensive HMP assessment protocol and then assesses the status of twelve HMPs within the Texas coastal management zone. The components of these plans are systematically examined in order to highlight their strengths and weaknesses. The average plan quality score (PǪS) was only 41.6 on a 100-point scale, with a high of 53.3 and a low of 28.7. Regional and county plans displayed higher PSQs than city plans. Most disconcerting was the finding of very low component quality scores forfact basisat 33.6 and mitigationpolicies & actionsat only 28.2. These two components are at the heart of HMPs. The relatively lowPǪSandCǪSresults suggest that there are significant improvements that should be undertaken in future iterations of HMPs to better insure long-term disaster resilience of local jurisdictions along the Texas coast.


2020 ◽  
Vol 12 (18) ◽  
pp. 2888 ◽  
Author(s):  
Nishanta Khanal ◽  
Mir Abdul Matin ◽  
Kabir Uddin ◽  
Ate Poortinga ◽  
Farrukh Chishtie ◽  
...  

Time series land cover data statistics often fluctuate abruptly due to seasonal impact and other noise in the input image. Temporal smoothing techniques are used to reduce the noise in time series data used in land cover mapping. The effects of smoothing may vary based on the smoothing method and land cover category. In this study, we compared the performance of Fourier transformation smoothing, Whittaker smoother and Linear-Fit averaging smoother on Landsat 5, 7 and 8 based yearly composites to classify land cover in Province No. 1 of Nepal. The performance of each smoother was tested based on whether it was applied on image composites or on land cover primitives generated using the random forest machine learning method. The land cover data used in the study was from the years 2000 to 2018. Probability distribution was examined to check the quality of primitives and accuracy of the final land cover maps were accessed. The best results were found for the Whittaker smoothing for stable classes and Fourier smoothing for other classes. The results also show that classification using a properly selected smoothing algorithm outperforms a classification based on its unsmoothed data set. The final land cover generated by combining the best results obtained from different smoothing approaches increased our overall land cover map accuracy from 79.18% to 83.44%. This study shows that smoothing can result in a substantial increase in the quality of the results and that the smoothing approach should be carefully considered for each land cover class.


Author(s):  
Djan'na H. Koubodana ◽  
Bernd Diekkrüger ◽  
Kristian Näschen ◽  
Julien Adounkpe ◽  
Kossi Atchonouglo

The results reveal CILSS as the most accurate data set with a Kappa coefficient of 68% and an overall accuracy of 83%. CILSS data shows a decrease of savanna and forest whereas an increase of cropland over the period 1975 to 2013. The increase of cropland area of 30.97% from 1975 to 2013 can be related to the increase in population and their food demand, while the losses of forest area and the decrease of savanna are further amplified by using wood as energy sources and the lack of forest management. The three datasets were used to simulate future LULC changes using the Terrset Land Change Modeler. The validation of the model using CILSS data for 2013 showed a quality of 50.94%, it is only 40.04% for ESA and 20.13% for Globeland30. CILSS data was utilized to simulate the LULC distribution for the years 2020 and 2027 because of its satisfactory performances. The results show that a high spatial resolution is not a guarantee of high quality. The results of this study can be used for impact studies and to develop management strategies for mitigating negative effects of land use and land cover change.


2018 ◽  
Vol 71 ◽  
pp. 00016
Author(s):  
Jakub Łuczak

OpenStreetMap (OSM) is an open source, freely available spatial database, co-created by users from around the world in the idea of volunteered geographic information. The functioning of the project as an open community geographic information system is its great advantage, however, it is associated with many flaws, like heterogeneity of collected data. The presented work focuses on the assessment of completeness and quality of land cover data. The reference data used in analysis were objects stored in the Baza Danych Obiektów Topograficznych (BDOT10k), which is an element of the Polish National Geodetic and Cartographic Resource. The analysis was carried out for the area of the Lower Silesia Voivodship. Despite the achievement of quite unsatisfactory results of the analysis, OpenStreetMap project has information potential and is useful in selected spatial analyses.


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