scholarly journals Experts’ Perception of the Key Drivers of Land-Use/Land-Cover Changes in Serbia from 1990 to 2012

2021 ◽  
Vol 13 (14) ◽  
pp. 7771
Author(s):  
Tijana Dabović ◽  
Bojana Pjanović ◽  
Oliver Tošković ◽  
Dejan Djordjević ◽  
Bogdan Lukić

Negative trends in land use and land cover changes (LULCCs) are embodied in environmental, economic and social problems, keeping entire societies away from sustainable development goals (SDGs). This recognition incites a need for securing comprehensive and transdiciplinary knowledge on the complex interplay between LULCCs and their drivers. It should inform land use policy makers and produce adequate sustainable social responses. However, fragmentation in both academic and governmental arenas is an important impediment to the needed application of sustainability to land use policy. With this regard, the study offers a transdisciplinary, bottom-up and reproducible framework for understanding key drivers of LULCCs at the national/regional level where sustainable land use policies should be defined. Its main component is the repeated measure ANOVA of the expert survey data. The analysis allows aggregation of experts’ different disciplinary, professional and experiential perceptions and produces comparable results. It is tested in Serbia in three sub-periods during post-socialism. Main results confirm that LULCCs and drivers are complexly intertwined and need to be analysed within a comprehensive and transdisciplinary framework. Furthermore, the study should enable the transdisciplinary discussion, learning and knowledge coproduction that are required to inform land use policy makers about the needed trans-sectoral coproduction of policy responses towards SDGs.

2020 ◽  
Vol 12 (4) ◽  
pp. 1570 ◽  
Author(s):  
Mads Christensen ◽  
Jamal Jokar Arsanjani

The United Nations 2030 Agenda for Sustainable Development and the Sustainable Development Goals (SDG’s) presents a roadmap and a concerted platform of action towards achieving sustainable and inclusive development, leaving no one behind, while preventing environmental degradation and loss of natural resources. However, population growth, increased urbanisation, deforestation, and rapid economic development has decidedly modified the surface of the earth, resulting in dramatic land cover changes, which continue to cause significant degradation of environmental attributes. In order to reshape policies and management frameworks conforming to the objectives of the SDG’s, it is paramount to understand the driving mechanisms of land use changes and determine future patterns of change. This study aims to assess and quantify future land cover changes in Virunga National Park in the Democratic Republic of the Congo by simulating a future landscape for the SDG target year of 2030 in order to provide evidence to support data-driven decision-making processes conforming to the requirements of the SDG’s. The study follows six sequential steps: (a) creation of three land cover maps from 2010, 2015 and 2019 derived from satellite images; (b) land change analysis by cross-tabulation of land cover maps; (c) submodel creation and identification of explanatory variables and dataset creation for each variable; (d) calculation of transition potentials of major transitions within the case study area using machine learning algorithms; (e) change quantification and prediction using Markov chain analysis; and (f) prediction of a 2030 land cover. The model was successfully able to simulate future land cover and land use changes and the dynamics conclude that agricultural expansion and urban development is expected to significantly reduce Virunga’s forest and open land areas in the next 11 years. Accessibility in terms of landscape topography and proximity to existing human activities are concluded to be primary drivers of these changes. Drawing on these conclusions, the discussion provides recommendations and reflections on how the predicted future land cover changes can be used to support and underpin policy frameworks towards achieving the SDG’s and the 2030 Agenda for Sustainable Development.


2021 ◽  
Vol 14 (14) ◽  
Author(s):  
Syed Atif Bokhari ◽  
Zafeer Saqib ◽  
Amjad Ali ◽  
Arif Mahmud ◽  
Nadia Akhtar ◽  
...  

2021 ◽  
Vol 10 (5) ◽  
pp. 272
Author(s):  
Auwalu Faisal Koko ◽  
Wu Yue ◽  
Ghali Abdullahi Abubakar ◽  
Akram Ahmed Noman Alabsi ◽  
Roknisadeh Hamed

Rapid urbanization in cities and urban centers has recently contributed to notable land use/land cover (LULC) changes, affecting both the climate and environment. Therefore, this study seeks to analyze changes in LULC and its spatiotemporal influence on the surface urban heat islands (UHI) in Abuja metropolis, Nigeria. To achieve this, we employed Multi-temporal Landsat data to monitor the study area’s LULC pattern and land surface temperature (LST) over the last 29 years. The study then analyzed the relationship between LULC, LST, and other vital spectral indices comprising NDVI and NDBI using correlation analysis. The results revealed a significant urban expansion with the transformation of 358.3 sq. km of natural surface into built-up areas. It further showed a considerable increase in the mean LST of Abuja metropolis from 30.65 °C in 1990 to 32.69 °C in 2019, with a notable increase of 2.53 °C between 2009 and 2019. The results also indicated an inverse relationship between LST and NDVI and a positive connection between LST and NDBI. This implies that urban expansion and vegetation decrease influences the development of surface UHI through increased LST. Therefore, the study’s findings will significantly help urban-planners and decision-makers implement sustainable land-use strategies and management for the city.


Author(s):  
Edivaldo Afonso de Oliveira Serrão ◽  
Madson Tavares Silva ◽  
Thomás Rocha Ferreira ◽  
Lorena Conceição Paiva de Ataide ◽  
Cleber Assis dos Santos ◽  
...  

2020 ◽  
Vol 18 ◽  
pp. 100314 ◽  
Author(s):  
Abdulla - Al Kafy ◽  
Md. Shahinoor Rahman ◽  
Abdullah-Al- Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Muhaiminul Islam

Sign in / Sign up

Export Citation Format

Share Document