A Study on the Shoreline Changes and LAND-use/ Land-cover along the South Gujarat Coastline

Monitoring built-up area expansion led by industrial transformation in Delhi using geospatial techniques

Historically, industrialization has been a catalyst for built-up expansion generated by economic growth that transforms a landscape. In India, there is a paucity of exploration into how the economic shift transforms the cityscape. Therefore, the objective of current research work was to monitor built-up growth induced by industrialization using Landsat datasets and registered industry data. The k-means clustering technique was applied for assessing land use/land cover, Shannon entropy for sprawl, and Pearson for correlation between industrial growth and built-up expansion. The results manifest exponential trend in industrialization with 102-year registered industry record along with increase in built-up density from 0.30 in 1989 to 0.69 by 2019 and in the entire Delhi; it rose from 0.16 to 0.39. Furthermore, Shannon entropy confirmed the sprawl and the strong positive correlation was found among built-up of industrial areas and built-up of Delhi and registered industries. The striking chorological change in industrial as well as city's landscape was observed co-occurring with the dynamics of economic reforms. The outcome of current research could be utilized for the sustainable planning of industrial landscape in Delhi and cities with alike geographical conditions.

Assessment of mangrove cover dynamics and its health status in the Gulf of Khambhat, Western India, using high-resolution multi-temporal satellite data and Google Earth Engine

Anthropogenic activity is a major driving factor of greenhouse gas emission, leading to climate change worldwide. So, the best natural approach to lowering the carbon from the atmosphere is mangroves which have more potential to sequestrate carbon. But mangroves are under threat due to land use land cover change. This research has been carried out on the mangroves of Gulf of Khambhat, Gujarat, India, where anthropic activity is affecting the mangrove forest cover with spatiotemporal heterogeneity. In the present study, multi-temporal high-resolution satellite data AVNIR-2 (Advanced Visible and Near Infrared Radiometer type-2) and LISS-4 (Linear Imaging Self-Scanning Sensors-4) were used for the demarcation of various land use/land cover class (LULC), and change analysis and assessment of mangroves health for the years 2009, 2014, and 2019. The impact of saltpan/aquaculture on mangroves growth and its health status has been calculated by various MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data products such as gross primary productivity (GPP), enhanced vegetation index (EVI), and leaf area index (LAI) in Google Earth Engine (GEE), and field-based method was also considered. This study suggests that there is a marginal increase (17.11 km²) in mangrove cover during the assessment period 2009-2019; on other side, 65.42 km² was degraded also. However, increase in saltpan/aquaculture is imposing an adverse effect on mangroves' basal area, plant density, and productivity. Change analysis also suggests a reduction in healthy mangrove area (from 25.20 to 2.84 km²), which will have an impact on ecosystem services.

Shoreline Erosion Assessment Modelling for Sohar Region: Measurements, Analysis, and Scenario

The extended coastlines of Oman have been forced to change in the last few decades because of urbanization development or by natural disasters. Recently, Oman has suffered from a couple of tornados and cyclones, e.g. Cyclone Gonu on June 1, 2007, making the changes even much more dynamic. In order to protect the coastal regions infrastructure, an accurate estimation of shoreline erosion is required. This research paper presents an assessment of shoreline erosion magnitudes using field measurements coupled with Multiple Linear Regressions Models (MLR) to predict future changes. Inverse Distance Weighing and Kriging interpolation methods have been applied in order to visualize shoreline variations from gathered data prospective. The field measurements for the shoreline were taken at 19 different points, the space between the points in a range of 500–700 m approximately. The first field measurements were taken on 19^th 20^th 21^st of June, 2016 while the second field measurements were taken on 14^th 15^th 16^th of November 2016. Pearson correlation shows a strong relationship between the first and the second field trips with an average of 0.83. This significant relationship ensures the applicability of MLRs to project future changes on the shorelines. The results of the MLRs showed severe negative volumetric shoreline erosion with an average of 5.2 m/year with some exceptions at the catchment outlets.

Characteristics of Coastline Changes on Southeast Asia Islands from 2000 to 2015

The future of islands has been the subject of international concern, scientific debate and media interest in the last decade. As a result of global warming and sea level rise, increasingly more research and speculations about the morphology and positions of island coastlines have been produced. However, some assumptions are not well documented due to the lack of large-scale research and data support. This paper contributes to filling this gap by extracting and assessing coastline changes on Southeast Asian islands overall during 2000–2015 based on Landsat remote sensing images. The results are as follows: ① the coastline, defined by the mean high water line (MHWL), of Southeast Asia remained relatively stable but showed considerable variability in space, especially in estuaries, bays and straits. ② A total of 9035 islands were extracted, among which approximately 10% of islands witnessed locational changes in coastlines, resulting in net reductions of nearly 86 km2 in area and 50,000 km in centroid displacement. Additionally, the coastline length increased by 532 km from 2000 (148,508 km) to 2015 (149,040 km). Natural coastlines decreased by 2503 km, while artificial coastlines increased by 3035 km. Among the total coastlines, 11% changed: 5% exhibited deposition, while 6% experienced retreat. ③ The temporal and spatial changes in coastlines were the result of interactions between natural processes and human activities. Climatic and environmental changes had wide impacts, while human activities caused more dramatic local changes. In addition, the sizes, shapes and landforms of the islands played significant roles in coastline changes. ④ Coastal erosion and expansion often coexisted in dynamic equilibrium under the influence of coastal hydrodynamics, such as cyclical tides and near-shore sediment transport. Our findings reveal spatial–temporal variations in island coastlines in Southeast Asia from 2000–2015 and provide critical information for the current study of islands. This work has great significance for the study of global climate change impacts and the integrated management of island coastal zones.

Monitoring Coastline Dynamics of Alakol Lake in Kazakhstan Using Remote Sensing Data

Alakol Lake is one of the largest hydrologically closed lake located in Balkash-Alakol River Basin in southeast Kazakhstan. Having a coastline approximately at 490 km, Alakol Lake has faced multiple threats due to both natural and anthropogenic factors as a result of tectonic movements, geology, wind-wave conditions, growing tourism activities, fishing, and transport, etc. The present study aims to investigate the historical trends in coastline changes along Alakol Lake in Kazakhstan and estimate its change rate by using remote sensing data in particular scale-space images Landsat-5 TM, 7 ETM+, 8 OLI, and Sentinel-2A. Based on Landsat and Sentinel data, the modified normalized difference water index was calculated to demonstrate the coastline changes along Alakol Lake between 1990 and 2018. Moreover, the monitoring and analysis of coastline dynamics is based on the main morphometric characteristics of Alakol Lake including water surface area, coastline length, geomorphology of the coast, etc. Our results reveal that there is a continuous coastline retreat, depending on the coast types. For example, in the case of the denudation coasts, a land inundation was from 120 to 270 m between 1990 and 2018. In the case of the accumulative coast (mainly northeast, north, and northwest coasts) a land inundation was from 200 to 900 m. A vast area of agricultural land around Alakol Lake become flooded and lost. This study demonstrates the importance of monitoring coastline dynamics because it provides essential information for understanding the coastal response to contemporary nature and anthropogenic impacts.