Impact of land use and land cover change on land surface temperature in Iskandar Malaysia using remote sensing technique

Iskandar Malaysia is one of the impressive development projects ever undertaken in Malaysia that has been experiencing rapid rate of land use change since 2006. Land use change is due to the urban expansion and reduction in natural green areas resulted from enhanced economic growth. The three objectives of this study are (i) to estimate the land use and land cover changes (LULC) in Iskandar Malaysia from 1989 to 2014, (ii) to investigate the effect of LULC changes on land surface temperature (LST) change in the study area and (iii) to predict the LST by 2025. Remote sensing data namely Landsat (Landsat 5, 7 and 8) and Moderate Resolution Imaging Spectroradiometer (MODIS) of Terra product (MOD11A1) were used to classify various LULC and to calculate the LST in Iskandar Malaysia. There are two digital classification techniques used to classify and test the different LULC in this study area. Maximum Likelihood Classification (MLC) technique provided higher accuracies compared to the Support Vector Machine (SVM) technique. Consequently, the classified satellite images using the MLC technique were used to monitor changes in LULC in Iskandar Malaysia. LST was extracted using mono window. The mean LST using Geographic Information System (GIS) analysis according to LULC shows that water areas recorded the highest night time LST value, while forest recorded the lowest day time LST value. Urban areas are the warmest land use during the day and the second warmest land use during the night time. Moreover, the weighted average used to predict the mean LST of entire Iskandar Malaysia, it was found that if green space increases LST value would decrease by 0.5○C. To predict the effect of LULC changes on mean LST of each LULC types linear curve fitting model was used. According to the results, the mean night LST from 2000 to 2025 will increase in Iskandar Malaysia as urban (20.89°C to 22.39°C±0.45), mangrove (20.88°C to 22.59°C±0.50), forest (20.39°C to 21.04°C±0.18), oil palm (20.39°C to 21.25±0.25), rubber (20.34°C to 22.36°C ± 0.57), and water (21.61 °C to 23.31°C ± 0.51). The results show increment in day time at urban (29.26°C to 32.78°C±1.07), mangrove (26.23°C to 28.82 °C±0.89), forest (25.76°C to 27.54°C±0.49), oil palm (27.02°C to 29.54±0.70), rubber (26.49°C to 27.24°C ±0.29), and water (26.10 °C to 28.77 °C ± 0.8) respectively. Moreover, the relationship between LST and several impervious and vegetation indexes show that there is a strong relationship between impervious indexes and LST, and an inverse relationship between vegetation indexes and LST. Finally, this study concluded that replacing green natural area with improvise surface can increase the land surface temperature and have negative effect on urban thermal comfort

Resilience in Soils and Land Use

Currently, studies on land use in territorial planning are of interest, the purpose of which was previously to analyze the aptitude of each type of land for a specific use, based on its ability to assume impacts and the potential that the land may have had. The analysis of erosive risks constitutes a parameter to take into account in said management.The scientific community, given the enormous social interest in monitoring and controlling the environment, is developing methodologies that allow such control that is more efficient. One of the environmental factors to consider is the soil, which constitutes the support for life and is one of the basic natural elements, which is evident in the European Soil Charter, of the Council of Europe, which says, in its first point: “The soil is one of the most precious goods of Humanity. It allows the life of plants, animals and man on the surface of the Earth”. This European charter also highlights the scarcity and fragility of the edaphic resource, indicating that it must be protected through a greater effort in scientific research and interdisciplinary collaboration to ensure the rational use and conservation of soil

Remote Sensing for Land Administration 2.0

The reprint “Land Administration 2.0” is an extension of the previous reprint “Remote Sensing for Land Administration”, another Special Issue in Remote Sensing. This reprint unpacks the responsible use and integration of emerging remote sensing techniques into the domain of land administration, including land registration, cadastre, land use planning, land valuation, land taxation, and land development. The title was chosen as “Land Administration 2.0” in reference to both this Special Issue being the second volume on the topic “Land Administration” and the next-generation requirements of land administration including demands for 3D, indoor, underground, real-time, high-accuracy, lower-cost, and interoperable land data and information

Trend assessment of changing climate patterns over the major agro-climatic zones of Sindh and Punjab

The agriculture sector, due to its significant dependence on climate patterns and water availability, is highly vulnerable to changing climate patterns. Pakistan is an agrarian economy with 30% of its land area under cultivation and 93% of its water resources being utilized for agricultural production. Therefore, the changing climate patterns may adversely affect the agriculture and water resources of the country. This study was conducted to assess the climate variations over the major agro-climatic zones of Sindh and Punjab, which serve as an important hub for the production of major food and cash crops in Pakistan. For this purpose, the climate data of 21 stations were analyzed using the Mann–Kendall test and Sen's slope estimator method for the period 1990–2022. The results obtained from the analysis revealed that, in Sindh, the mean annual temperature rose by ~0.1 to 1.4°C, with ~0.1 to 1.2°C in cotton-wheat Sindh and 0.8 to 1.4°C in rice-other Sindh during the study period. Similarly, in Punjab, the mean annual temperature increased by ~0.1 to 1.0°C, with 0.6 to 0.9°C in cotton-wheat Punjab and 0.2 to 0.6°C in rainfed Punjab. Seasonally, warming was found to be highest during the spring season. The precipitation analysis showed a rising annual precipitation trend in Sindh (+30 to +60 mm) and Punjab (+100 to 300 mm), while the monsoon precipitation increased by ~50 to 200 mm. For winter precipitation, an upward trend was found in mixed Punjab, while the remaining stations showed a declining pattern. Conclusively, the warming temperatures as found in the analysis may result in increased irrigation requirements, soil moisture desiccation, and wilting of crops, ultimately leading to low crop yield and threatening the livelihoods of local farmers. On the other hand, the increasing precipitation may favor national agriculture in terms of less freshwater withdrawals. However, it may also result in increased rainfall-induced floods inundating the crop fields and causing water logging and soil salinization. The study outcomes comprehensively highlighted the prevailing climate trends over the important agro-climatic zones of Pakistan, which may aid in devising an effective climate change adaptation and mitigation strategy to ensure the state of water and food security in the country

Environmental Management

Environmental Management - Pollution, Habitat, Ecology, and Sustainability includes sixteen chapters that discuss pressing environmental issues in diverse locations around the world. Chapters discuss methods, technologies, analyses, and actions that may enlighten and enable decision-makers and managers in their quests for control of environmental problems. The authors present the facts and the challenges behind the assorted issues and offer new perspectives for contending with natural, social, economic, and political aspects of management

Machine Learning in Sensors and Imaging

Machine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens

Proceedings of Abstracts 10th International Conference on Air Quality Science and Application

This 10th International Conference in Air Quality - Science and Application is being held in the elegant and vibrant city of Milan, Italy. Our local hosts are ARIANET and ARPA Lombardia both of whom play a leading role in assessing and managing air pollution in the area. The meeting builds upon the series that began at the University of Hertfordshire, UK in July 1996. Subsequent meetings have been held at the Technical University of Madrid, Spain (1999), Loutraki, Greece (2001), Charles University, Prague, Czech Republic (2003), Valencia, Spain (2005), Cyprus (2007), Istanbul, Turkey (2009) Athens, Greece (2012) and Garmisch-Partenkirchen, Germany (2014). Over the last two decades controls to limit air pollution have increased but the problem of poor air quality persists in all cities of the world. Consequently, the issue of the quality of air that we breathe remains at the forefront of societal concerns and continues to demand the attention of scientists and policy makers to reduce health impacts and to achieve sustainable development. Although urbanisation is growing in terms of population, transport, energy consumption and utilities, science has shown that impact from air pollution in cities is not restricted to local scales but depends on contributions from regional and global scales including interactions with climate change. Despite improvements in technology, users still demand robust management and assessment tools to formulate effective control policies and strategies for reducing the health impact of air pollution. The topics of papers presented at the conference reflect the diversity of scales, processes and interactions affecting air pollution and its impact on health and the environment. As usual, the conference is stimulating cross-fertilisation of ideas and cooperation between the different air pollution science and user communities. In particular, there is greater involvement of city, regional and global air pollution, climate change, users and health communities at the meeting. This international conference brings together scientists, users and policy makers from across the globe to discuss the latest scientific advances in our understanding of air pollution and its impacts on our health and environment. In addition to the scientific advances, the conference will also seek to highlight applications and developments in management strategies and assessment tools for policy and decision makers. This volume presents a collection of abstracts of papers presented at the Conference. The main themes covered in the Conference include: Air quality and impact on regional to global scales Development/application/evaluation of air quality and related models Environmental and health impact resulting from air pollution Measurement of air pollutants and process studies Source apportionment and emission models/inventories Urban meteorology Special session: Air quality impacts of the increasing use of biomass fuels Special session: Air quality management for policy support and decisions Special session: Air pollution meteorology from local to global scales Special session: Climate change and human health Special Session: Modelling and measuring non-exhaust emissions from traffic Special session: Transport related air pollution - PM and its impact on cities and across EuropeFinal Published versio

Agroforestry Opportunities for Enhancing Resilience to Climate Change in Rainfed Areas,

Not AvailableAgroforestry provides a unique opportunity to achieve the objectives of enhancing the productivity and improving the soil quality. Tree systems can also play an important role towards adapting to the climate variability and important carbon sinks which helps to decrease the pressure on natural forests. Realizing the importance of the agroforestry in meeting the twin objectives of mitigation and adaptation to climate change as well as making rainfed agriculture more climate resilient, the ICAR-CRIDA has taken up the challenge in pursuance of National Agroforestry Policy 2014, in preparing a book on Agroforestry Opportunities for Enhancing Resilience to Climate Change in Rainfed Areas at ICAR-CRIDA to sharpen the skills of all stakeholders at national, state and district level in rainfed areas to increase agricultural productivity in response to climate changeNot Availabl