Advances on Land Cover/Land Use Ontologies for Innovative Production/Utilization of Land Information

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land – Observation and Monitoring".

Deadline for manuscript submissions: 25 July 2024 | Viewed by 5514

Special Issue Editors


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Guest Editor
Food and Agriculture Organization of the United Nations, 00100 Rome, Italy
Interests: ISO standards for land cover and land use; ontologies; remote sensing; GIS; agriculture; land cover classification; land use classification; natural resource survey; land cover mapping; ecological/environmental monitoring

E-Mail Website
Guest Editor
Food and Agriculture Organization of the United Nations, 00100 Rome, Italy
Interests: ISO standards for land cover and land use; forestry; environment; natural resources management and conservation; climate change mitigation and adaptation; sustainable land management; conservation agriculture; safe access to fuel and energy; landscape restoration; biodiversity conservation; data management and analysis; information system; remote sensing; GIS; classification system; field inventory; planning; coordination of field interventions; research; education and knowledge sharing
School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
Interests: remote sensing; coastal management; geomorphology; environmental management; climate change adaptation; sustainable development; natural resource management; geographic information system; participatory rural appraisal; ecosystem services valuation

E-Mail Website
Co-Guest Editor
GeoData Institute, University of Southampton, Southampton SO17 1BJ, UK
Interests: natural resource management; agricultural monit. & agric. statistics; geo-spatial data and agric. area frames; spatial data infrastructures; geo-spatial data standards; data governance; project formulation; project management; capacity development; food security; climate change; agroecology; AEZ/NAEZ; in emerging and developing country context

E-Mail Website
Co-Guest Editor
Institute of Water and Flood Management (IWFM), Bangladesh University of Engineering and Technology (BUET), Dhaka 1205, Bangladesh
Interests: fate of trace metals and persistent organics in soil and water systems; impact of climate change on environment and ecology; impact of interventions on environmental quality and ecology; flow and sedimentation processes in coastal environment

E-Mail Website
Co-Guest Editor
1. Remote Sensing, GIS and Climatic Research Lab (RSGCRL), National Center of GIS and Space Applications, Islamabad 44000, Pakistan
2. Department of Space Science, University of the Punjab, Lahore 54590, Pakistan
Interests: geospatial economic alternatives; satellite based indices; land use planning and management; climate change; water resources assessment; GIS; satellite remote sensing; multi criteria analysis; land cover dynamics; municipal waste hazard assessment; atmospheric pollution; rainwater harvesting; bio/thermal indicators; urban heat island effect

E-Mail Website
Co-Guest Editor
Centre for Remote Sensing and Geographic Information Services (CERGIS), Accra P.O. Box LG 59, Ghana
Interests: biodiversity; ecology; forestry and land cover

Special Issue Information

Dear Colleagues,

The “Land” is where human beings stand, act and grow. The term land encompasses all physical elements bestowed by nature; therefore, it supports all aspects of our life.

Land cover and land use are the fundamental information required  in the monitoring and planning of natural resources, agriculture production, forest management, emergency responses, green cities development, climate change, and achieving and monitoring of the Sustainable Development Goals (SDGs), in addition to many other initiatives and goals at the local to global levels.

The advancement in remote sensing (RS), geographical information system (GIS) and machine learning techniques provides more and more remarkable and crucial information in understanding the complex dynamics of the environment. Despite those innovations, however, there is a lot of effort still to be made in the “formalization of the meaning” of that information, how they are conceptualized and shared. The compatibility of land products become increasingly crucial as the amount of available information rises, but inconsistencies still exist affecting their comparability and efficient functional use.

During the past decade, new innovative methods and tools to characterize and functionally define/classify land cover (and land use) information have emerged. Those efforts can potentially redefine many aspects of how the user community generates and utilizes land information. Therefore, reviewing and understanding the potentialities of those advances, as well as their impacts in the generation/utilization of “Land” information, is critical.

The aim of this Special Issue is to encourage the science and research community to provide their inputs through innovative ideas and proposals in the development of consistent, sustainable and interoperable land cover and land use datasets using integrated approaches and implementing existing standards to support various ongoing local to global land cover and land use initiatives. This subject is highly related to the scope of the journal in the context of ;and system science and social–ecological system research; land/land-use/land-cover change; land management including agriculture, forestry, the built environment and others; land–climate interactions, including climate–biosphere–biodiversity interactions; assessment and evaluation frameworks, indicators, indices, methods, tools and approaches (ecosystem services, multifunctionality and sustainability); and emerging technologies of data processing (deep learning/machine-based learning).

In this Special Issue, we invite papers regarding, but not limited to, the following topics:

  • innovative ways to define/characterize land cover/land use ontologies;
  • multi-disciplinary research that investigates the intrinsic relationship between land cover and land use;
  • use of new standards and new methodologies for the functional integration of earth observation data, field data, remote sensing and other ancillary information;
  • automatic comparison and similarity assessment of existing different land cover ontologies using ISO standard (ISO 19144-2).LCML (Land Cover Meta Language) to assure semantic interoperability and harmonization of data sets from national to global level;
  • role, importance and use cases of land information for Sustainable Development Goals, climate action (SDG 13) and life on land (SDG 15).

Dr. Antonio Di Gregorio
Dr. Matieu Henry
Guest Editors

Chris T. Hill
Prof. John Latham
Prof. Dr. Mohammed Abed Hossain
Dr. Khalid Mahmood
Dr. Foster Mensah
Co-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. Land 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 2600 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

  • land cover
  • land use
  • interoperability
  • standardization
  • geospatial technology
  • semantic ontology
  • harmonization
  • classification
  • earth observation
  • remote sensing
  • sustainable development

Published Papers (3 papers)

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Research

19 pages, 7103 KiB  
Article
Enabling Spatial Data Interoperability through the Use of a Semantic Meta-Model—The Peatland Example from the JRC SEPLA Project
by Pavel Milenov, Aleksandra Sima, Emanuele Lugato, Wim Devos and Philippe Loudjani
Land 2024, 13(4), 473; https://doi.org/10.3390/land13040473 - 07 Apr 2024
Viewed by 568
Abstract
Numerous geographic data on peatland exist but definitions vary, and the correspondent classes are often neither harmonized nor interoperable. This hinders the efforts to employ the available national datasets on peatlands and wetlands for policy monitoring and reporting. The existing meta-languages, such as [...] Read more.
Numerous geographic data on peatland exist but definitions vary, and the correspondent classes are often neither harmonized nor interoperable. This hinders the efforts to employ the available national datasets on peatlands and wetlands for policy monitoring and reporting. The existing meta-languages, such as ISO-Land Cover Meta Language (LCML) and EAGLE, offer the possibility to “deconstruct” the relevant nomenclatures in an object-oriented manner, allowing the comparability and interoperable use of related information. The complex nature of peatlands calls for a dedicated and structured vocabulary of keywords and terms, comprising the biotic substrate and the soil. In the SEPLA project, a semantic meta-model has been developed, combining the hierarchical ontology of the LCML with the matrix structure of the EAGLE model. The necessary elements were provided to describe peatland bio-physical characteristics, while representing the definitions in a concise and user-friendly manner (semantic passports). The proposed semantic meta-model is innovative as it enables the documentation of the spatial distribution of peatland characteristics, considering also their temporal dimension, their intrinsic relation with land use, and the soil. It has been successfully implemented for the translation of the national peatland nomenclature into common land categories relevant for reporting under LULUCF regulation, as part of the EU Climate Law. Full article
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22 pages, 3342 KiB  
Article
Deep Insight on Land Use/Land Cover Geospatial Assessment through Internet-Based Validation Tool in Upper Karkheh River Basin (KRB), South-West Iran
by Sina Mallah, Manouchehr Gorji, Mohammad Reza Balali, Hossein Asadi, Naser Davatgar, Hojjat Varmazyari, Anna Maria Stellacci and Mirko Castellini
Land 2023, 12(5), 979; https://doi.org/10.3390/land12050979 - 28 Apr 2023
Cited by 1 | Viewed by 1464
Abstract
Recently, the demand for high-quality land use/land cover (LULC) information for near-real-time crop type mapping, in particular for multi-relief landscapes, has increased. While the LULC classes are inherently imbalanced, the statistics generally overestimate the majority classes and underestimate the minority ones. Therefore, the [...] Read more.
Recently, the demand for high-quality land use/land cover (LULC) information for near-real-time crop type mapping, in particular for multi-relief landscapes, has increased. While the LULC classes are inherently imbalanced, the statistics generally overestimate the majority classes and underestimate the minority ones. Therefore, the aim of this study was to assess the classes of the 10 m European Satellite Agency (ESA) WorldCover 2020 land use/land cover product with the support of the Google Earth Engine (GEE) in the Honam sub-basin, south-west Iran, using the LACOVAL (validation tool for regional-scale land cover and land cover change) online platform. The effect of imbalanced ground truth has also been explored. Four sampling schemes were employed on a total of 720 collected ground truth points over approximately 14,100 ha. The grassland and cropland totally canopied 94% of the study area, while barren land, shrubland, trees and built-up covered the rest. The results of the validation accuracy showed that the equalized sampling scheme was more realistically successful than the others in terms of roughly the same overall accuracy (91.6%), mean user’s accuracy (91.6%), mean producers’ accuracy (91.9%), mean partial portmanteau (91.9%) and kappa (0.9). The product was statistically improved to 93.5% ± 0.04 by the assembling approach and segmented with the help of supplementary datasets and visual interpretation. The findings confirmed that, in mapping LULC, data of classes should be balanced before accuracy assessment. It is concluded that the product is a reliable dataset for environmental modeling at the regional scale but needs some modifications for barren land and grassland classes in mountainous semi-arid regions of the globe. Full article
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19 pages, 4540 KiB  
Article
Estimating Double Cropping Plantations in the Brazilian Cerrado through PlanetScope Monthly Mosaics
by Edson Eyji Sano, Édson Luis Bolfe, Taya Cristo Parreiras, Giovana Maranhão Bettiol, Luiz Eduardo Vicente, Ieda Del′Arco Sanches and Daniel de Castro Victoria
Land 2023, 12(3), 581; https://doi.org/10.3390/land12030581 - 28 Feb 2023
Cited by 4 | Viewed by 1945
Abstract
Farmers in the Brazilian Cerrado are increasing grain production by cultivating second crops during the same crop growing season. The release of PlanetScope (PS) satellite images represents an innovative opportunity to monitor double cropping production. In this study, we analyzed the potential of [...] Read more.
Farmers in the Brazilian Cerrado are increasing grain production by cultivating second crops during the same crop growing season. The release of PlanetScope (PS) satellite images represents an innovative opportunity to monitor double cropping production. In this study, we analyzed the potential of six PS monthly mosaics from the 2021/2022 crop growing season to discriminate double cropping areas in the municipality of Goiatuba, Goiás State, Brazil. The four multispectral bands of the PS images were converted into normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), green–red normalized difference index (GRNDI), and textural features derived from the gray-level co-occurrence matrix (GLCM). The ten most important combinations of these attributes were used to map double cropping systems and other land use and land cover classes (cultivated pasture, sugarcane, and native vegetation) of the municipality through the Random Forest classifier. Training and validation samples were obtained from field campaigns conducted in October 2021 and April 2022. PS mosaic from February 2022 was the most relevant data. The overall accuracy and Kappa index of the final map were 92.2% and 0.892, respectively, with an accuracy confidence of 81%. This approach can be expanded for mapping and monitoring other agricultural frontiers in the Cerrado biome. Full article
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