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  • 1
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    SEVA: Scalable explorative change detection for big Sentinel-2 data (2020)
    GFZ German Research Centre for Geosciences
    Details
    Publication Date: 2021-08-03
    Description: Abstract
    Description: SEVA is a scalable exploration tool that supports users to conduct change detection based on optical Sentinel-2 satellite observations. It supports the following essential steps of change detection: a) exploration and selection of optical satellite images to recognize proper data for the current application scenario, b) automated extraction of changes from the optical satellite images, c) analysis of errors and d) assessment and interpretation of the extracted changes.
    Description: TechnicalInfo
    Description: License: GNU General Public License, Version 3, 29 June 2007 Copyright © 2020 Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany SEVA is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. SEVA is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.
    Keywords: remote sensing ; satellite data ; visualilsation ; change detection ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION ; EARTH SCIENCE SERVICES 〉 DATA ANALYSIS AND VISUALIZATION 〉 GEOGRAPHIC INFORMATION SYSTEMS 〉 WEB-BASED GEOGRAPHIC INFORMATION SYSTEMS
    Type: Software , Software
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    DATA GFZ
  • 2
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    Dataset on effects of conservation with wildlife and agriculture on plant lignin and n-alkanes components in soils (2022)
    TRR228 Database (TRR228DB)
    Details
    Publication Date: 2022-03-09
    Description: Abstract
    Description: 1.Nature conservation is fostered through the expansion of protected areas. This is particularly evident in Sub-Saharan Africa (SSA), where conservation is intended to simultaneously promote the recovery of megafauna like elephants. Rising numbers of megaherbivores induce woody biomass losses but restore soil organic carbon (SOC). We hypothesized that increases of SOC under conservation with wildlife in SSA go directly along with increases in the preservation of plant residues in soil organic matter (SOM), traceable by plant biomarkers such as lignin and n-alkane. In contrast, intensification with agriculture leads to a reduction of them. To test this, we sampled topsoil (0-10 cm) and corresponding plant samples along different intensities of conservation and intensification in the Zambezi Region of Namibia, comprising a) conservation sites with low, medium and high elephant densities and b) adjacent intensification sites with rangeland and cropland. We found that lignin and n-alkane patterns of the above-ground vegetation were preserved in the soil. Confirming our hypothesis, increasing SOC contents with rising elephant densities went along with increasing accumulation of lignin-derived phenols. Under conservation, lignin concentrations were influenced by the input of woody debris into the soil, traced by carbon isotopes, clay, and total woody biomass. This could not be proved for n-alkanes. Under intensification, lignin derived phenols were lower than under conservation, but again, there was no clear pattern for n-alkanes. We showed that conservation with wildlife leads to an increase of SOC, which was accompanied by an accumulation of lignin-derived phenols in the soil organic matter. Increased input of woody debris, clay content and total biomass were important parameters for this lignin accumulation. In contrast, intensification with agriculture leads to a loss of lignin. Contrary, n- alkanes were not sensitive to detect effects of conservation or intensification. We conclude that increasing incorporation of woody residues into soil is a key mechanism controlling SOC accrual and to offset losses of aboveground biomass on SOC in sites under conservation with wildlife. The dataset contains raw data of lignin and n-alkanes and related soil properties. A third sheet contains a legend with information on abbreviations.
    Keywords: Ecology ; Environment ; Conservation ; Intensification ; Soil Organic Carbon ; Carbon Storage Dynamics ; Carbon Sequestration ; Biomarker ; Lignin ; n-Alkanes
    Type: Dataset , Microsoft excel file
    Format: MS Excel
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    DATA GFZ
  • 3
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    Historical road network of Kenya (1950s – 1980s) extracted from topographic maps (Version 1.0) (2024)
    TRR228 Database (TRR228DB)
    Details
    Publication Date: 2024-04-26
    Description: Abstract
    Description: This dataset includes a shapefile representing the digitized historical road network of Kenya. It contains over 56,000 km of historical roads extracted from 449 historical topographic maps of 1:50,000 scale and 71 maps of 1:100,000 scale covering the time period from the 1950s to the 1980s. The topographic maps were obtained from various sources in Kenya and the UK. Most of maps were collected in Kenya provided by the Survey of Kenya and several local county governments’ survey and urban planning departments. Additionally, some maps were obtained from archives in Great Britain, namely the Bodleian Library of the University of Oxford and the Cambridge University Library. All the acquired maps were originally created and published by the Directorate of Overseas Surveys (DOS), the War Office, General Staff, Geographical Section and the Survey of Kenya. The road data was extracted from these maps using deep learning techniques, including a Python script and ArcGIS Pro “Multi-Task Road Extractor” tool.
    Keywords: Infrastructure ; Imagery/Base Maps/Earth Cover ; Road Network ; Roads ; Geodata ; Historical Data ; Vector Data ; GIS ; Africa ; African History ; Historical Maps ; Infrastructure ; Road ; Geographic information system ; Data ; road network ; road ; data ; infrastructure development
    Type: Dataset , Shapefile
    Format: ESRI Shapefile
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    DATA GFZ
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