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The Detection and Application of Remote Sensing

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainability in Geographic Science".

Deadline for manuscript submissions: closed (13 October 2023) | Viewed by 4012

Special Issue Editors


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Guest Editor
1. Department of Geosciences, Environment and Land Planning, Faculty of Sciences, University of Porto, 4169007 Porto, Portugal
2. Institute of Earth Sciences (ICT)-Porto Pole, University of Porto, 4169007 Porto, Portugal
Interests: remote sensing; image processing; environmental applications; geologic applications; GIS
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Geosciences, Environmental and Land Planning and Institute of Earth Sciences, Faculty of Sciences, University of Porto, 4169-007 Porto, Portugal
Interests: remote sensing; machine learning algorithms; geological exploration; mineral deposits; Li mineralizations; geochemistry
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Salesian Polytechnic University, Quito, Ecuador
Interests: remote sensing; machine learning; google earth engine; cloud computing; gis cloud

Special Issue Information

Dear Colleagues,

The Earth and its ecosystems face, especially in the last years, severe environmental damages and are constantly exposed to risks. This is mainly caused by imbalances associated with unsustainable development related to population increase, fast urbanization, high rates of industrialization and the increase of extreme weather events. Remote sensing data and techniques are powerful tools for monitoring the Earth's ecosystems, integrating different types of data (optical, SAR, aerial photographs, UAV) that can be used for effective decision-making at different temporal and spatial scales. Over the past years, powered by new freely available Earth observation sensors/programs, remote sensing data and techniques were applied in several thematics regarding sustainable development. The combination of geographic information systems (GIS) and the recent advances in machine learning (ML) algorithms makes remote sensing data, even more of an essential tool for sustainable development.

This SI aims to cover contributions related to remote sensing data/technology (sensors, techniques, approaches) that are used to support sustainable development, with a special focus on environmental applications, geological applications, climate change, natural disasters, and risks monitoring, but not limited to these topics. This SI also accepts review papers.

We look forward to receiving your contributions,

Dr. Ana Cláudia Teodoro
Dr. Joana Cardoso-Fernandes
Dr. Cesar I. Alvarez-Mendoza
Guest Editors

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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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

  • environmental applications
  • geological applications
  • climate change
  • natural disasters
  • risks

Published Papers (2 papers)

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Research

25 pages, 15443 KiB  
Article
Spatio-Temporal Distribution and Trends of Major Agricultural Crops in Romania Using Interactive Geographic Information System Mapping
by Ionuț-Adrian Drăguleasa, Amalia Niță, Mirela Mazilu and Gheorghe Curcan
Sustainability 2023, 15(20), 14793; https://doi.org/10.3390/su152014793 - 12 Oct 2023
Cited by 2 | Viewed by 1507
Abstract
This research study presents the spatio-temporal distribution of the main agricultural crops in Romania using a modern digitalisation technique, namely interactive GIS mapping. Interactive GIS mapping includes various features specific to the development of sustainable Romanian agriculture, including the arable area of Romania, [...] Read more.
This research study presents the spatio-temporal distribution of the main agricultural crops in Romania using a modern digitalisation technique, namely interactive GIS mapping. Interactive GIS mapping includes various features specific to the development of sustainable Romanian agriculture, including the arable area of Romania, information on the area (hectares) cultivated with corn, wheat, sunflower, and rape during the 1990–2018 period, the degree of mechanisation, the number of tractors, and information regarding the landforms, a natural factor in relation to cultivated surfaces. Agricultural land should be properly used based on its ability to meet the demands of consumers of traditional Romanian products with an ecological label, but also the needs of the local population, and, at the same time, to ensure the sustainability of the natural environment through the practice of ecological agriculture. The purpose of this research is to provide an overview of the current state of the main agricultural crops in Romania. From a theoretical but also practical point of view, this research presents, for the first time, a retrospective analysis of each county in Romania in terms of the geospatial distribution of major agricultural crops using interactive GIS mapping. Geospatial data were processed in ArcGIS Geographic Information System 10.7.2. The results of this study show that the most extensive cereal areas at the county level in Romania are corn and wheat. The largest areas cultivated with corn and wheat in 2018 were recorded in the Western Plain, the Romanian Plain, and the Moldavian Plateau. For wheat, increases were also recorded in the Dobrogea Plateau. The intensification of labour productivity and the promotion of the sustainability of the natural environment in Romania is presented through the main indicator (the number of tractors) of the degree of mechanisation of agriculture. The higher values of this indicator are in the counties of Bihor, Timiș, and Maramureș. Limitations in Romania’s agricultural data present substantial challenges to the sector’s development and sustainability. Addressing these challenges is essential for informed decision making, policy formulation, and effective resource allocation. Full article
(This article belongs to the Special Issue The Detection and Application of Remote Sensing)
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24 pages, 3999 KiB  
Article
Spatio-Temporal Description of the NDVI (MODIS) of the Ecuadorian Tussock Grasses and Its Link with the Hydrometeorological Variables and Global Climatic Indices
by Jhon Villarreal-Veloz, Xavier Zapata-Ríos, Karla Uvidia-Zambrano and Carla Borja-Escobar
Sustainability 2023, 15(15), 11562; https://doi.org/10.3390/su151511562 - 26 Jul 2023
Viewed by 1202
Abstract
This study examined the changes in tussock grass greenness over 18 years (2001–2018) using NDVI data from 10 key areas of the Páramo ecosystem in the Ecuadorian Andes. In addition, the study investigated the influence of hydrometeorological variables (precipitation, soil temperature, and water [...] Read more.
This study examined the changes in tussock grass greenness over 18 years (2001–2018) using NDVI data from 10 key areas of the Páramo ecosystem in the Ecuadorian Andes. In addition, the study investigated the influence of hydrometeorological variables (precipitation, soil temperature, and water availability) and climatic indices (AAO, MEI, MJO, NAO, PDO, El Niño 1 + 2, 3, 3.4, and 4) on greenness dynamics. The spatial and temporal variations of NDVI were studied, applying several analysis and indicators, such as: the standard deviation, z-score anomalies, Sen slope, Mann–Kendall test, and time integrated-NDVI (TI-NDVI). Linear and multilinear correlations were used to evaluate the influence of hydrometeorological variables and climatic indices on the greenness of tussock. The findings of the study show that Páramo, located in the Inter-Andean valley above 2° S, is the most productive, followed by those located in the Royal Range (eastern cordillera). The anomalies and trends of NDVI on the Royal Range tended to be greening over time. NDVI showed a moderate multilinear correlation with precipitation and soil temperature, and a strong response to water availability. Finally, NDVI was weakly linearly related to the climatic indices, the most representative being the MJO, and slightly related to ENSO events. Understanding the regional and global-scale variables that control tussock grasses’ phenology will help to determine how present and future climate changes will impact this ecosystem. Full article
(This article belongs to the Special Issue The Detection and Application of Remote Sensing)
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