Special Issue "Geo-Informatics in Resource Management"

Special Issue Editor

Dr. Francisco Javier Mesas Carrascosa
E-Mail Website
Guest Editor
Professor at the Department of Graphic Engineering and Geomatic. University of Córdoba, Córdoba, Spain
Interests: UAV; Remote Sensing; Photogrammetry; Precision Agriculture; Cloud Computing; Heritage; GIS
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Natural resources management requires reliable and timely information available at local, regional, national, and global scales. GeoInfomatics, by remote sensing, global navigation satellite systems, geographical information systems, and related technologies provide information for natural resource management, environmental protection, and supporting issues related to sustainable development. Geoinformatics has proven as a powerful technology for studying and monitoring natural resources and in generating modeling for probable scenarios, being an important management and decision-making tool to ensure optimum use of natural resources.

This Special Issue aims to examine to all aspects of geo-informatics related to resource management. We cordially invite original research contributions on topics including but not limited to the following:

  • Satellite, aircraft, and UAV platforms to support natural resource management;
  • GIS-based decision support systems for analysis, management and scenario simulations;
  • Climatic parameters changes;
  • Environmental statistics;
  • Land use change;
  • Big data and machine learning;
  • Location-based services;
  • And more.

Dr. Francisco Javier Mesas Carrascosa
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 papers will be 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. ISPRS International Journal of Geo-Information 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 1000 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

  • spatial data analysis
  • mapping and monitoring
  • integration of technologies and sensors
  • data mining
  • temporal series
  • spatial modeling
  • big data and cloud computing

Published Papers (2 papers)

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Research

Open AccessArticle
Evaluation of the Accuracy of the Field Quadrat Survey of Alpine Grassland Fractional Vegetation Cover Based on the Satellite Remote Sensing Pixel Scale
ISPRS Int. J. Geo-Inf. 2019, 8(11), 497; https://doi.org/10.3390/ijgi8110497 - 03 Nov 2019
Abstract
The fractional vegetation cover (FVC) data measured on the ground is the main source for the calibration and verification of FVC remote sensing inversion, and its accuracy directly affects the accuracy of remote sensing inversion results. However, the existing research on the evaluation [...] Read more.
The fractional vegetation cover (FVC) data measured on the ground is the main source for the calibration and verification of FVC remote sensing inversion, and its accuracy directly affects the accuracy of remote sensing inversion results. However, the existing research on the evaluation of the accuracy of the field quadrat survey of FVC based on the satellite remote sensing pixel scale is inadequate, especially in the alpine grassland of the Qinghai-Tibet Plateau. In this paper, five different alpine grasslands were examined, the accuracy of the FVC obtained by the photography method was analyzed, and the influence of the number of samples on the field survey results was studied. First, the results show that the threshold method could accurately extract the vegetation information in the photos and obtain the FVC with high accuracy and little subjective interference. Second, the number of samples measured on the ground was logarithmically related to the accuracy of the FVC of the sample plot (p < 0.001). When the number of samples was larger, the accuracy of the FVC of the sample plot was higher and closer to the real value, and the stability of data also increased with the increase of the number of samples. Third, the average FVC of the measured quadrats on the ground was able to represent the FVC of the sample plot, but on the basis that there were enough measured quadrats. Finally, the results revealed that the degree of fragmentation reflecting the state of ground vegetation affects the acquisition accuracy of FVC. When the degree of fragmentation of the sample plot is higher, the number of samples needed to achieve the accuracy index is higher. Our results suggest that when obtaining the FVC on the satellite remote sensing pixel scale, the number of samples measured on the ground is an important factor affecting the accuracy, which cannot be ignored. Full article
(This article belongs to the Special Issue Geo-Informatics in Resource Management)
Open AccessArticle
The Efficacy Analysis of Determining the Wooded and Shrubbed Area Based on Archival Aerial Imagery Using Texture Analysis
ISPRS Int. J. Geo-Inf. 2019, 8(10), 450; https://doi.org/10.3390/ijgi8100450 - 12 Oct 2019
Abstract
Open areas, along with their non-forest vegetation, are often threatened by secondary succession, which causes deterioration of biodiversity and the habitat’s conservation status. The knowledge about characteristics and dynamics of the secondary succession process is very important in the context of management and [...] Read more.
Open areas, along with their non-forest vegetation, are often threatened by secondary succession, which causes deterioration of biodiversity and the habitat’s conservation status. The knowledge about characteristics and dynamics of the secondary succession process is very important in the context of management and proper planning of active protection of the Natura 2000 habitats. This paper presents research on the evaluation of the possibility of using selected methods of textural analysis to determine the spatial extent of trees and shrubs based on archival aerial photographs, and consequently on the investigation of the secondary succession process. The research was carried out on imagery from six different dates, from 1971 to 2015. The images differed from each other in spectral resolution (panchromatic, in natural colors, color infrared), in original spatial resolution, as well as in radiometric quality. Two methods of textural analysis were chosen for the analysis: Gray level co-occurrence matrix (GLCM) and granulometric analysis, in a number of variants, depending on the selected parameters of these transformations. The choice of methods has been challenged by their reliability and ease of implementation in practice. The accuracy assessment was carried out using the results of visual photo interpretation of orthophotomaps from particular years as reference data. As a result of the conducted analyses, significant efficacy of the analyzed methods has been proved, with granulometric analysis as the method of generally better suitability and greater stability. The obtained results show the impact of individual image features on the classification efficiency. They also show greater stability and reliability of texture analysis based on granulometric/morphological operations. Full article
(This article belongs to the Special Issue Geo-Informatics in Resource Management)
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