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Data
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Geomatic Data for Land Degradation Surveillance
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Geomatic Data for Land Degradation Surveillance

A special issue of Data (ISSN 2306-5729).

Deadline for manuscript submissions: closed (30 September 2017) | Viewed by 16878

Special Issue Editor

Dr. Gabriel Del Barrio

E-Mail Website
Guest Editor
Estacion Experimental de Zonas Aridas (CSIC), Carr. Sacramento sn, 04120 La Cañada de San Urbano, Almeria, Spain
Interests: desertification and land degradation; ecological connectivity; spatial ecology

Special Issue Information

Dear Colleagues,

Land degradation is a foremost threat to sustainable development in a world increasingly submitted to human management. This has sparked a variety of current, scientific approaches to the problem, ranging from expert-driven observational and empirical assessment at the local scale, to fully deployed geomatic systems operating at regional scales. Many of them seek to meet the indicator and metric requirements of international initiatives, such as those of the Strategic Objectives of the United Nations Convention to Combat Desertification, or Goal 15.3 of the Sustainable Development Goals. All of them converge on the need for reliable and harmonized input data in order to feed their respective methods, which is particularly important in developing countries where data availability may be a critical factor to join the above-mentioned initiatives. This Special Issue of Data focuses on such a need, and presents a collection of articles dealing with elements needed to seek, process, and visualize relevant data sources for land degradation surveillance.

Dr. Gabriel del Barrio
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Data is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Earth Observation platforms and time-series products to assess vegetation biomass and productivity
  • A comparison of NDVI and fAPAR time-series to estimate Net Primary Productivity
  • Surface soil moisture time-series for the regional assessment of vegetation performance
  • Global and regional climate archives
  • Drought analysis by SPI and SPEI archived time-series
  • Land use/land cover data products
  • A tool for querying and visualising large raster archives: The EDAL library

Published Papers (2 papers)

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2175 KiB  
Data Descriptor
A 2001–2015 Archive of Fractional Cover of Photosynthetic and Non-Photosynthetic Vegetation for Beijing and Tianjin Sandstorm Source Region
by Xiaosong Li, Zengyuan Li, Cuicui Ji, Hongyan Wang, Bin Sun, Bo Wu and Zhihai Gao
Data 2017, 2(3), 27; https://doi.org/10.3390/data2030027 - 25 Aug 2017
Cited by 3 | Viewed by 3741
Abstract
Fractional covers of photosynthetic and non-photosynthetic vegetation are key indicators for land degradation surveillance in the dryland of China. However, there are no available, well validated, and multispectral-based products. Aiming for this, we selected the Beijing and Tianjin Sandstorm Source Region as the [...] Read more.
Fractional covers of photosynthetic and non-photosynthetic vegetation are key indicators for land degradation surveillance in the dryland of China. However, there are no available, well validated, and multispectral-based products. Aiming for this, we selected the Beijing and Tianjin Sandstorm Source Region as the study area, and utilized the linear spectral mixture model for generating the fractional cover of PV, NPV, and bare soil, with endmember spectra retrieved from the field measured endmember spectral library, based on the MODIS NBAR data from 2001 to 2015. The unmixing results were validated through comparison with the field samples. The results show the method adopted could acquire rational and accurate estimation of fractional cover of photosynthetic vegetation (R2 = 0.6297, RMSE = 0.2443) and non-photosynthetic vegetation (R2 = 0.3747, RMSE = 0.2568). The dataset could provide key data support for the users in land degradation surveillance fields. Full article
(This article belongs to the Special Issue Geomatic Data for Land Degradation Surveillance)
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2205 KiB  
Data Descriptor
A High Resolution Dataset of Drought Indices for Spain
by Sergio M. Vicente-Serrano, Miquel Tomas-Burguera, Santiago Beguería, Fergus Reig, Borja Latorre, Marina Peña-Gallardo, M. Yolanda Luna, Ana Morata and José C. González-Hidalgo
Data 2017, 2(3), 22; https://doi.org/10.3390/data2030022 - 28 Jun 2017
Cited by 126 | Viewed by 12780
Abstract
Drought indices are essential metrics for quantifying drought severity and identifying possible changes in the frequency and duration of drought hazards. In this study, we developed a new high spatial resolution dataset of drought indices covering all of Spain. The dataset includes seven [...] Read more.
Drought indices are essential metrics for quantifying drought severity and identifying possible changes in the frequency and duration of drought hazards. In this study, we developed a new high spatial resolution dataset of drought indices covering all of Spain. The dataset includes seven drought indices, spans the period 1961–2014, and has a spatial resolution of 1.1 km and a weekly temporal resolution. A web portal has been created to enable download and visualization of the data. The data can be downloaded as single gridded points for each drought index, but the entire drought index dataset can also be downloaded in netCDF4 format. The dataset will be updated for complete years as the raw meteorological data become available. Full article
(This article belongs to the Special Issue Geomatic Data for Land Degradation Surveillance)
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