Recent Advances in Land Systems Mapping and Monitoring under Global Environmental Changes

A special issue of Land (ISSN 2073-445X).

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 5847

Special Issue Editors

Special Issue Information

Dear Colleagues,

Land systems are crucial for human society and activities because they provide multiple ecosystem services for their well-being and health. Nonetheless, increasing anthropogenic land use transformations and population growth, coupled with the increasing and evident effects of climate change are depleting resource availability and threatening protected ecosystems. Understanding land systems dynamics and their changes are important for governing transformative changes of the landscape and for supporting the sustainable use of the resources.

New methods, tools and digital data have widened up the possibility to monitor and understand land systems and their dynamics under different environmental and human-induced changes.

The Special Issue aims at synthesizing current knowledge, highlighting modern and disruptive approaches for monitoring and mapping land systems changes. We are interested in contributions that link the aforementioned cornerstones through either empirical research or conceptual/theoretical works that:

  • analyze, map and characterize land-use/cover changes with new methods;
  • monitor anthropogenic pressures in land systems;
  • propose new ways of using big data, artificial intelligence and new technology for analyzing land systems.

Contributions at the intersection of land use science, landscape sustainability science and environmental governance are especially welcome, but contributions from other related fields at the local, regional and global scale are also highly welcome.

Dr. Giuseppe Pulighe
Dr. Flavio Lupia
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-use change
  • land systems
  • ecosystem services
  • resources
  • climate change
  • mapping
  • big data

Published Papers (3 papers)

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Research

18 pages, 2941 KiB  
Article
Estimation of Above-Ground Forest Biomass in Nepal by the Use of Airborne LiDAR, and Forest Inventory Data
by Yam Bahadur KC, Qijing Liu, Pradip Saud, Damodar Gaire and Hari Adhikari
Land 2024, 13(2), 213; https://doi.org/10.3390/land13020213 - 08 Feb 2024
Viewed by 1733
Abstract
Forests play a significant role in sequestering carbon and regulating the global carbon and energy cycles. Accurately estimating forest biomass is crucial for understanding carbon stock and sequestration, forest degradation, and climate change mitigation. This study was conducted to estimate above-ground biomass (AGB) [...] Read more.
Forests play a significant role in sequestering carbon and regulating the global carbon and energy cycles. Accurately estimating forest biomass is crucial for understanding carbon stock and sequestration, forest degradation, and climate change mitigation. This study was conducted to estimate above-ground biomass (AGB) and compare the accuracy of the AGB estimating models using LiDAR (light detection and ranging) data and forest inventory data in the central Terai region of Nepal. Airborne LiDAR data were collected in 2021 and made available by Nepal Ban Nigam Limited, Government of Nepal. Thirty-two metrics derived from the laser-scanned LiDAR point cloud data were used as predictor variables (independent variables), while the AGB calculated from field data at the plot level served as the response variable (dependent variable). The predictor variables in this study were LiDAR-based height and canopy metrics. Two statistical methods, the stepwise linear regression (LR) and the random forest (RF) models, were used to estimate forest AGB. The output was an accurate map of AGB for each model. The RF method demonstrated better precision compared to the stepwise LR model, as the R2 metric increased from 0.65 to 0.85, while the RMSE values decreased correspondingly from 105.88 to 60.9 ton/ha. The estimated AGB density varies from 0 to 446 ton/ha among the sample plots. This study revealed that the height-based LiDAR metrics, such as height percentile or maximum height, can accurately and precisely predict AGB quantities in tropical forests. Consequently, we confidently assert that substantial potential exists to monitor AGB levels in forests effectively by employing airborne LiDAR technology in combination with field inventory data. Full article
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20 pages, 8866 KiB  
Article
Computational Decision Support for Socio-Technical Awareness of Land-Use Planning under Complexity—A Dam Resilience Planning Case Study
by Andreas Tolk, Jennifer A. Richkus, F. LeRon Shults and Wesley J. Wildman
Land 2023, 12(5), 952; https://doi.org/10.3390/land12050952 - 25 Apr 2023
Viewed by 1000
Abstract
Land-use planning for modern societies requires technical competence as well as social competence. We therefore propose an integrative solution enabling better land-use planning and management through better-informed decision-making. We adapt a method developed for cross-disciplinary team building to identify the stakeholders and their [...] Read more.
Land-use planning for modern societies requires technical competence as well as social competence. We therefore propose an integrative solution enabling better land-use planning and management through better-informed decision-making. We adapt a method developed for cross-disciplinary team building to identify the stakeholders and their various objectives and value systems. We use these results to populate artificial societies embedded into a dynamic data analytics framework as a tool to identify, explore, and visualize the challenges resulting from the different objectives and value systems in land-use planning and management. To prove the feasibility of the proposed solution, we present two use cases from the dam resilience planning domain, show how to apply the process and tools, and present the results. The solution is not limited to such use cases but can be generalized to address challenges in socio-technical systems, such as water resource evaluations or climate change effects. Full article
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26 pages, 6630 KiB  
Article
An Integrated Modelling Approach to Urban Growth and Land Use/Cover Change
by Parviz Azizi, Ali Soltani, Farokh Bagheri, Shahrzad Sharifi and Mehdi Mikaeili
Land 2022, 11(10), 1715; https://doi.org/10.3390/land11101715 - 03 Oct 2022
Cited by 13 | Viewed by 2534
Abstract
Long-term sustainable development in developing countries requires researching and projecting urban physical growth and land use/land cover change (LUCC). This research fills a gap in the literature by exploring the issues of modelling coupled LUCC and urban growth, their causes, and the role [...] Read more.
Long-term sustainable development in developing countries requires researching and projecting urban physical growth and land use/land cover change (LUCC). This research fills a gap in the literature by exploring the issues of modelling coupled LUCC and urban growth, their causes, and the role of policymakers. Tabriz metropolitan area (TMA), located at north-west Iran, was chosen as a case study to design an integrated framework using four well-established methods: cellular automata (CA), Markov chains (MC), logistic regression (LR), and stepwise weight assessment ratio analysis (SWARA). Northern, north-west, and central TMA were affected the worst by urbanisation and the loss of cultivated and grassland between 1990 and 2020. The accessibility of arterial roadways and proximity to major cities influenced these changes. Three scenarios characterise LUCC dynamics: the uncontrolled growth scenario (UGS) and the historical trend growth scenario (HTGS) foresee significant loss of cultivated land and continued urban expansion above the long-term average in 2050, while the environmental protection growth scenario (EPGS) promotes sustainable development and compact urbanisation. The methods used in this research may be used to various contexts to examine the temporal and spatial dynamics of LUCC and urban growth. Full article
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