Stimulating the Impact of Hydrocarbon Micro-Seepage on Vegetation in Ugwueme, from 1996 to 2030, Based on the Leaf Area Index and Markov Chain Model

The Leaf Area Index (LAI) is an important algorithm for studying the health status of vegetation. In this study, the impact of hydrocarbon micro-seepage on vegetation in Ugwueme was investigated using the LAI image classification approach. Landsat TM 1996, ETM+ 2006, and OLI 2016 satellite images that were acquired from the United States Geological Survey (USGS) portal were used to classify various LAI maps as low, moderate, and high classes. The spatial–temporal analysis revealed that the low, moderate, and high LAI density classification changed, respectively, from 41.24 km2 (50.43%), 33.98 km2 (41.54%), and 6.56 km2 (8.02%) in 1996 to 23.70 km2 (28.98%), 29.48 km2 (36.04%), and 28.60 km2 (34.97%) in 2006, and to 38.23 km2 (46.74%), 27.54 km2 (33.68%), and 16.01 km2 (19.58%) in 2016. The stimulation analysis shows that by 2030 (the 14-year planning period), the low, moderate, and high LAI density classifications will be 8.86 km2 (10.82%), 24.28 km2 (29.70%), and 48.63 km2 (59.46%), respectively. The study shows that LAI is an important algorithm that can be effectively used to study the health status of vegetation in an ecosystem

Spatial-Temporal Mapping and Delineating of Agulu Lake Using Remote Sensing and Geographic Information Science for Sustainable Development

Water is a crucial component of ecosystems and a critical resource that cannot be replaced for social progress or human life. In this study, Agulu Lake, an inland water body located in Anambra, southeast Nigeria, was mapped, classified, and delineated with remotely sensed data so as to monitor the spatial-temporal changes that occurred in the lake’s surface water every 15 years, in 1985, 2000, and 2015, in order to achieve sustainable development by 2030. The Sustainable Development Goals (SDGs) of the United Nations emphasize the need to manage the marine environment. Some of the goals of the SDGs have some connection to open surface water, but goal 6a and indicator 6.6.1 are significant to this study. The study adopted Landsat 5 TM (1985), ETM+ (2000), Landsat 8 OLI (2015), ArcGIS 10.5 software, and the maximum likelihood classifier to create various classification maps. The Google Earth image (2015) was also used to show the general overview of Agulu Lake and its environs. The findings demonstrate that during the study period, the land surface class grew while the water surface class (Agulu Lake) shrank

Land use Change Detection of Khana Local Government Area of Rivers State Using Remote Sensing and GIS

This research involved the integration of remote sensing techniques with a Geographic Information System (GIS) framework to get information on the area under study using PC-based image processing and analysis.  Landsat satellite imageries of Khana area was used and a Supervised Classification System (SCS) was adopted using ArcGIS 10.1 software.  Selected bands (7,5 and 3) were processed, training sites were selected to represent land-use classes and image classification was carried out.  A time change mapping and analysis was undertaken for the years 1987, 2000, and 2018.  The area in square kilometers of each land-use type in each year was calculated and thereafter, the change was determined by subtracting the area of the same land-use type in 1987 from 2018.  It was revealed that there was a high percentage of spatial expansion and reduction of some land-use types in the study area between these periods.  There was a steady decline of about 77% in the forested areas from 1987 all through 2000 to 2018 (-228km2).  Cultivated land reduced by 38.46% due to man’s anthropogenic activities (-80km2) and this greatly affected food security in the study area. Water bodies also decreased all through that period in the study area (-2km2).  The study area has been greatly affected by the extent of man’s activities, which have violently shoved away and altered the hydrological pattern as well as creating micro reliefs and changing the traditional land use pattern of forestry and farmland

Designing the future

The Netherlands has a tradition in public spatial planning and design. In the past 20 years, we have seen an increasing role for the market in this field, and more recently, growing attention for sustainability. Sustainability has become an economic factor. Not only at the building level, but also on the level of large-scale area development projects. More and more local governments have high ambitions for sustainable development. Increasingly, during project development, buildings are developed on a sustainable basis. Most of the time, the focus in this approach is on energy. However, sustainability also comprises social aspects. Energy measures have a direct relation to an economic factor such as investment costs, and payback time can be calculated. The economic aspects of social sustainability are more complex. Therefore, for all sustainability development projects, especially in large-scale projects planned over a longer period, it is necessary to make presumptions, which are less reliable as the planning period is extended. For future larger-scale developments, experience in the Netherlands points to two design approaches: ‘backcasting’, or using a growth model (or a combination of these two). The power of design is the ability to imagine possible scenarios for the future. The layer approach helps to integrate sustainability into public spatial planning. And more specifically, Urban Design Management (UDM) supports an integrative and collaborative approach also on the operational level of a project in which public and market partners work together. This article outlines how design, based on these approaches, can contribute to sustainable development based on the ‘new playing field’, where spatial problems should be solved in networks. Dutch projects in Almere (Benoordenhout) and Rijswijk are used to illustrate this approach.Real Estate and HousingArchitectur

Establishment of sustainable health science for future generations: from a hundred years ago to a hundred years in the future

Recently, we have investigated the relationship between environment and health from a scientific perspective and developed a new academic field, “Sustainable Health Science” that will contribute to creating a healthy environment for future generations. There are three key points in Sustainable Heath Science. The first key point is “focusing on future generations”—society should improve the environment and prevent possible adverse health effects on future generations (Environmental Preventive Medicine). The second key point is the “precautious principle”. The third key point is “transdisciplinary science”, which means that not only medical science but also other scientific fields, such as architectural and engineering science, should be involved. Here, we introduce our recent challenging project “Chemiless Town Project”, in which a model town is under construction with fewer chemicals. In the project, a trial of an education program and a health-examination system of chemical exposure is going to be conducted. In the future, we are aiming to establish health examination of exposure to chemicals of women of reproductive age so that the risk of adverse health effects to future generations will decrease and they can enjoy a better quality of life. We hope that society will accept the importance of forming a sustainable society for future generations not only with regard to chemicals but also to the whole surrounding environment. As the proverb of American native people tells us, we should live considering the effects on seven generations in the future