Using satellite image fusion to evaluate the impact of land use changes on ecosystem services and their economic values

Shuangao, W., Padmanaban, R., Mbanze, A. A., Silva, J. M. N., Shamsudeen, M., Cabral, P., & Campos, F. S. (2021). Using satellite image fusion to evaluate the impact of land use changes on ecosystem services and their economic values. Remote Sensing, 13(5), 1-21. [851]. https://doi.org/10.3390/rs13050851Accelerated land use change is a current challenge for environmental management world-wide. Given the urgent need to incorporate economic and ecological goals in landscape planning, cost-effective conservation strategies are required. In this study, we validated the benefit of fusing imagery from multiple sensors to assess the impact of landscape changes on ecosystem services (ES) and their economic values in the Long County, Shaanxi Province, China. We applied several landscape metrics to assess the local spatial configuration over 15 years (2004–2019) from fused image-ries. Using Landsat-7 Enhanced Thematic Mapper Plus (ETM+), Landsat-8 Operational Land Im-ager (OLI) and Indian Remote Sensing Satellite System Linear Imaging Self Scanning Sensor 3 (IRS LISS 3) imageries fused for 2004, 2009, 2014 and 2019, we reclassified land use/land cover (LULC) changes, through the rotation forest (RF) machine-learning algorithm. We proposed an equivalent monetary metric for estimating the ES values, which also could be used in the whole China. Results showed that agriculture farmland and unused land decreased their spatial distribution over time, with an observed increase on woodland, grassland, water bodies and built-up area. Our findings suggested that the patterns of landscape uniformity and connectivity improved, while the distribution of landscape types stabilized, while the landscape diversity had a slight improvement. The overall ES values increased (4.34%) under a benefit transfer approach, mainly concerning woodland and grassland. A sensitivity analysis showed the selected economic value (EV) was relevant and suitable for the study area associated with our ES for LULC changes. We suggested that changes in landscape patterns affected the ESV trends, while the increases on some LULC classes slightly improved the landscape diversity. Using an interdisciplinary approach, we recommend that local au-thorities and environmental practitioners should balance the economic benefits and ecological gains in different landscapes to achieve a sustainable development from local to regional scales.publishersversionpublishe

Landscape Impacts on Ecosystem Service Values Using the Image Fusion Approach

Wang, S., Padmanaban, R., Shamsudeen, M., Campos, F. S., & Cabral, P. (2022). Landscape Impacts on Ecosystem Service Values Using the Image Fusion Approach. Land, 11(8), 1-18. [1186]. https://doi.org/10.3390/land11081186 --- FUNDING: This study was supported by the Research on Capitalization of Natural Resources and Corresponding Market Construction in China (grant number 15ZDB162); and partially through the FCT (Fundação para a Ciência e a Tecnologia) under the projects PTDC/CTA-AMB/28438/2017—ASEBIO and UIDB/04152/2020—Centro de Investigação em Gestão de Informação (MagIC). This research was also funded by the Forest Research Centre, a research unit funded by Fundação para a Ciência e a Tecnologia I.P. (FCT), Portugal (UIDB/00239/2020).The landscape is a complex mosaic of physical and biological patches with infrastructures, cultivable lands, protected ecosystems, water bodies, and many other landforms. Varying land-use changes are vulnerable to the world and need the mitigation and management of landforms to achieve sustainable development, which without proper oversight, may lead to habitat destruction, degradation, and fragmentation. In this study, we quantify the land-use and land-cover (LULC) changes using downscaled satellite imagery and assess their effects on ecosystem services (ES) and economic values in Ningxia Province, China. Various landscape metrics are derived to study the pattern and spatial configuration over 15 years (2005–2020), in which the landscapes are evolving. The impact of LULC change in various ES is analyzed using ecosystem service values (ESV) and validated with a sensitivity index. Finally, the level of urban sprawl (US) due to overpopulation is established using Renyi’s entropy. Using Landsat 8′s Operational Land Imager (OLI) datasets, we downscaled the MODIS data of 2005, 2010, 2015, and 2020 to prepare the LULC map through a rotation forest algorithm. Results demonstrate that water bodies, woodlands, and built-up landscapes increased in their spatial distribution over time and that there was a decrease in farmlands. Results further suggest that the connectivity and uniformity of the landscape pattern improved in the later period due to several plans formulated by the government with a slight improvement in landscape diversity. Overall ESV get improved, while LULC classes such as farmland and water bodies have decreased and increased ESV, respectively, and a sensitivity analysis is used to test the reliability of ESV on LULC classes. The level of US is 0.91 in terms of Renyi’s entropy, which reveals the presence of a dispersion of settlements in urban fringes. The simulated US for 2025 shows urbanization is more severe over a prolonged time and finally the impacts of the US in ESV are analyzed. Using an interdisciplinary approach, several recommendations are formulated to maintain the ESV despite rapid LULC changes and to achieve sustainable development globally.publishersversionpublishe

Modelling urban sprawl detection using remotely sensed data: a case of Сhennai, Tamilnadu

Urban sprawl propelled by rapid population growth leads to the shrinkage of productive agricultural lands and pristine forests in the suburban areas and, in turn, substantially alters ecosystem services. Hence, the quantification of urban sprawl is crucial for effective urban planning, and environmental and ecosystem management. Like many megacities in fast growing developing countries, Chennai, the capital of Tamilnadu and one of the business hubs in India, has experienced extensive urban sprawl triggered by the doubling of total population over the past three decades. We employed the Random Forest (RF) classification on Landsat imageries from 1991, 2003, and 2016, and computed spatial metrics to quantify the extent of urban sprawl within a 10km suburban buffer of Chennai. The rate of urban sprawl was quantified using Renyi’s entropy, and the urban extent was predicted for 2027 using land-use and land-cover change modeling. A 70.35% increase in urban areas was observed for the suburban periphery of Chennai between 1991 and 2016. The Renyi’s entropy value for year 2016 was ≥ 0.9, exhibiting a two-fold rate of urban sprawl. The spatial metrics values indicate that the existing urban areas of Chennai became denser and the suburban agricultural, forests and barren lands were transformed into fragmented urban settlements. The forecasted urban growth for 2027 predicts a conversion of 13670.33ha (16.57 % of the total landscape) of existing forests and agricultural lands into urban areas with an associated increase in the entropy value of 1.7. Our findings are relevant for urban planning and environmental management in Chennai and provide quantitative measures for addressing the social-ecological consequences of urban sprawl and the protection of ecosystem services

Recent Progress in ZnO-Based Nanostructures for Photocatalytic Antimicrobial in Water Treatment: A Review

Advances in nanotechnology have led to the development of antimicrobial technology of nanomaterials. In recent years, photocatalytic antibacterial disinfection methods with ZnO-based nanomaterials have attracted extensive attention in the scientific community. In addition, recently widely and speedily spread viral microorganisms, such as COVID-19 and monkeypox virus, have aroused global concerns. Traditional methods of water purification and disinfection are inhibited due to the increased resistance of bacteria and viruses. Exploring new and effective antimicrobial materials and methods has important practical application value. This review is a comprehensive overview of recent progress in the following: (i) preparation methods of ZnO-based nanomaterials and comparison between methods; (ii) types of nanomaterials for photocatalytic antibacterials in water treatment; (iii) methods for studying the antimicrobial activities and (iv) mechanisms of ZnO-based antibacterials. Subsequently, the use of different doping strategies to enhance the photocatalytic antibacterial properties of ZnO-based nanomaterials is also emphatically discussed. Finally, future research and practical applications of ZnO-based nanomaterials for antibacterial activity are proposed

Modelling Urban Sprawl Using Remotely Sensed Data: A Case Study of Chennai City, Tamilnadu

Urban sprawl (US), propelled by rapid population growth leads to the shrinkage of productive agricultural lands and pristine forests in the suburban areas and, in turn, adversely affects the provision of ecosystem services. The quantification of US is thus crucial for effective urban planning and environmental management. Like many megacities in fast growing developing countries, Chennai, the capital of Tamilnadu and one of the business hubs in India, has experienced extensive US triggered by the doubling of total population over the past three decades. However, the extent and level of US has not yet been quantified and a prediction for future extent of US is lacking. We employed the Random Forest (RF) classification on Landsat imageries from 1991, 2003, and 2016, and computed six landscape metrics to delineate the extent of urban areas within a 10 km suburban buffer of Chennai. The level of US was then quantified using Renyi’s entropy. A land change model was subsequently used to project land cover for 2027. A 70.35% expansion in urban areas was observed mainly towards the suburban periphery of Chennai between 1991 and 2016. The Renyi’s entropy value for year 2016 was 0.9, exhibiting a two-fold level of US when compared to 1991. The spatial metrics values indicate that the existing urban areas became denser and the suburban agricultural, forests and particularly barren lands were transformed into fragmented urban settlements. The forecasted land cover for 2027 indicates a conversion of 13,670.33 ha (16.57% of the total landscape) of existing forests and agricultural lands into urban areas with an associated increase in the entropy value to 1.7, indicating a tremendous level of US. Our study provides useful metrics for urban planning authorities to address the social-ecological consequences of US and to protect ecosystem services