scholarly journals Enhanced Historical Land-Use and Land-Cover Data Sets of the U.S. Geological Survey

Data Series ◽  
10.3133/ds240 ◽  
2007 ◽  
Author(s):  
Curtis V. Price ◽  
Naomi Nakagaki ◽  
Kerie J. Hitt ◽  
Rick M. Clawges
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Geological Survey ◽  
Data Sets ◽  
Land Cover Data ◽  
Historical Land Use ◽  
The U.S

A Simple Reclassification Method for Correcting Uncertainty in Land Use/Land Cover Data Sets Used with Land Surface Models

2007 ◽  
Vol 164 (8-9) ◽  
pp. 1789-1809 ◽  
Author(s):  
Joseph G. Alfieri ◽  
Dev Niyogi ◽  
Margaret A. LeMone ◽  
Fei Chen ◽  
Souleymane Fall
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Data Sets ◽  
Land Use Land Cover ◽  
Land Surface Models ◽  
Land Cover Data ◽  
Surface Models

scholarly journals Granica państwa a spójność danych dla potrzeb analiz hydrologicznych. Studium przypadku dla zlewni Wiaru na pograniczu polsko-ukraińskim = A state border and the integrity of data for hydrological analysis. A case study of the River Wiar catchment on the Poland-Ukraine borderland

2020 ◽  
Vol 92 (1) ◽  
pp. 69-92
Author(s):  
Rafał Kroczak ◽  
Tomasz Bryndal ◽  
Szymon Biały ◽  
Olga Pylypovych ◽  
Yurij Andreychuk ◽  
...  
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Land Cover ◽  
Large Scale ◽  
Satellite Images ◽  
Chemical Components ◽  
Data Sets ◽  
Eu Directive ◽  
Land Cover Data

Hydrological investigations require the development of a geodatabase allowing for the calculation of physiographic catchment parameters, as well as the analysis of amounts of water resources and changes therein. Such a geodatabase usually consists of meteorological, hydrological and cartographic data. The present study offers a review of datasets that may be used for geodatabase development in the interests of hydrological research, in catchments located in the Polish-Ukrainian borderland. The catchment of the Wiar River – selected to serve as a case study – is in fact divided by the state border into two equal sub-catchments (395.5 km2 in Poland and 398.9 km2 in Ukraine).The results reveal disparities in the spatial distribution of stream and meteorological gauges. For the Polish part of the catchment datasets include many parameters (in accordance with EU Directive and Regulations) and the results from monitoring are available online as yearly reports. For the Ukrainian part, only chemical components are monitored, and these data are not made available publicly. Consistent data sets such as DEM can be obtained from globally available ASTER and SRTM models. Datasets, such as LiDAR, which are important for medium and large-scale analyses allowing for the development of high-resolution DEMs, do not exist. Use of TanDEM-X data is restricted for the Ukrainian territory. However, comparison between the SRTM and LiDAR models (for the Polish part) revealed that the SRTM model may be optimised to serve the whole area. Land-use and land-cover data (LULC) are important in many hydrological analyses. the authors propose using satellite images in the development of a comparable layer describing land cover of the whole catchment.

scholarly journals A Comparative Analysis of Spatial Data and Land Use/Land Cover Classification in Urbanized Areas and Areas Subjected to Anthropogenic Pressure for the Example of Poland

2021 ◽  
Vol 13 (6) ◽  
pp. 3070
Author(s):  
Patrycja Szarek-Iwaniuk
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Classification ◽  
Classification Systems ◽  
Anthropogenic Pressure ◽  
Land Use Land Cover ◽  
Land Use Classification ◽  
Land Cover Data ◽  
Spatial Changes ◽  
Land Use Types

Urbanization processes are some of the key drivers of spatial changes which shape and influence land use and land cover. The aim of sustainable land use policies is to preserve and manage existing resources for present and future generations. Increasing access to information about land use and land cover has led to the emergence of new sources of data and various classification systems for evaluating land use and spatial changes. A single globally recognized land use classification system has not been developed to date, and various sources of land-use/land-cover data exist around the world. As a result, data from different systems may be difficult to interpret and evaluate in comparative analyses. The aims of this study were to compare land-use/land-cover data and selected land use classification systems, and to determine the influence of selected classification systems and spatial datasets on analyses of land-use structure in the examined area. The results of the study provide information about the existing land-use/land-cover databases, revealing that spatial databases and land use and land cover classification systems contain many equivalent land-use types, but also differ in various respects, such as the level of detail, data validity, availability, number of land-use types, and the applied nomenclature.

Reply to “Comment on ‘Which Earthquake Accounts Matter?’ by Susan E. Hough and Stacey S. Martin” by David J. Wald

2021 ◽  
Author(s):  
Susan E. Hough ◽  
Stacey S. Martin
Keyword(s):  
Scientific Community ◽  
Recent Article ◽  
Geological Survey ◽  
Data Sets ◽  
Macroseismic Data ◽  
Education Programs ◽  
Socioeconomic Groups ◽  
Science Projects ◽  
Community Science ◽  
The U.S

Abstract We thank David Wald (Wald, 2021; henceforth, W21) for his interest in our recent article (Hough and Martin, 2021; henceforth, HM21). Although different perspectives are vital in science, we are concerned that W21 misrepresents HM21 as an oblique criticism of the U.S. Geological Survey “Did You Feel It?” (DYFI) system, calling for HM21 to be retracted. Readers who are interested in the issues raised by HM21 and the statements made by us therein are referred to that article. In this brief reply, we respond to specific accusations made by W21 and return to the focus of HM21, calling attention to the extent to which macroseismic data sets and inferences drawn from them can be shaped by a lack of representation among individuals whose observations are available to science. HM21 never questioned the benefits of the community science DYFI project to science. HM21 noted, however, and we reiterate here, that community science also potentially benefits the community. Whether or not it matters for science, if participation in community science projects is unrepresentative across socioeconomic groups, it underscores the need for the scientific community to be proactive in its efforts to reach out to groups that have been underserved by current outreach and education programs. We appreciate this opportunity to continue the important conversation about representation.

scholarly journals Land use and land cover mapping and identification of misuse in the permanent preservation areas in the Tailândia Municipality - PA

2017 ◽  
Vol 38 (3) ◽  
pp. 1145 ◽  
Author(s):  
Rosana Sumiya Gurgel ◽  
Paulo Roberto Silva Farias ◽  
Sandro Nunes de Oliveira
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Palm Oil ◽  
Regulatory Agencies ◽  
Visual Interpretation ◽  
Livestock Farming ◽  
Land Cover Data ◽  
The Government ◽  
Remote Sensing Techniques ◽  
Bodies Of Water

The objective of this study is to expand the mapping of land use and land cover, as well as of the permanent preservation areas (PPAs), and identify land misuse areas in the PPAs in the Tailândia municipality in the state of Pará, which is part of the Amazon biome. Remote sensing techniques and geographic information systems (GIS) were used to achieve these goals. Mapping and classification for the year 2012 were made by visual interpretation of images obtained from the RapidEye satellite, which has a 5 m spatial resolution. In this work, we identified nine classes of land use and land cover. From the hydrography vectors it was possible to determinate the Permanent Preservation Areas of the bodies of water according to the environmental legislation. Analysis of misuse in the PPAs was made by crossing-checking the land use and land cover data with that of the PPAs. The results show that 53 % of the municipality (2,347.64 km²) is occupied by human activities. Livestock farming is the activity that has most increased the use of area (30 %), followed by altered vegetation (14.6 %) and palm oil (7.2 %). The PPAs have a high percentage of misuse (47.12 %), with livestock being the largest contributor, occupying 26.65 % of the PPAs, followed by altered vegetation (12.64 %) and palm oil (4.29 %). Therefore, the main objective in Tailândia is to reconcile economic activity with sustainable development. It is important to emphasize the partnerships between the government, research institutions, regulatory agencies, states departments and local communities, else it would be impossible to monitor or control an area as vast as the Amazon.

scholarly journals Assessment of land cover on soil erosion in Lam Phra Phloeng watershed by USLE model

2018 ◽  
Vol 192 ◽  
pp. 02017 ◽  
Author(s):  
Jatuwat Wattanasetpong ◽  
Uma Seeboonruang ◽  
Uba Sirikaew ◽  
Walter Chen
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Soil Loss ◽  
Land Development ◽  
Developed Countries ◽  
Surface Erosion ◽  
Agricultural Field ◽  
Land Cover Data

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.

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