scholarly journals Analysis of the Temporal Changes of Inland Ramsar Sites in Turkey Using Google Earth Engine

2021 ◽  
Vol 10 (8) ◽  
pp. 521
Author(s):  
Adalet Dervisoglu
Keyword(s):  
Surface Area ◽  
Water Surface ◽  
Google Earth ◽  
Ramsar Convention ◽  
Computing Platform ◽  
Surface Areas ◽  
Inland Wetlands ◽  
Area Reduction ◽  
Management Plans ◽  
Landsat Satellite

Ramsar Convention (RC) is the first of modern intergovernmental agreement on the conscious use and conservation of natural resources. It provides a platform for contracting parties working together to develop the best available data, advice, and policy recommendations to increase awareness of the benefits of wetlands in nature and society. Turkey became a party of the RC in 1994, and in the years 1994 to 2013, 14 wetlands that reached the Ramsar criteria were recognized as Ramsar sites (RS). With this study, all inland RS in Turkey from 1985 to 2020 were examined, and changes in the water surface areas were evaluated on the GEE cloud computing platform using Landsat satellite images and the NDWI index. The closest meteorological station data to each RS were evaluated and associated with the surface area changes. The reasons for the changes in these areas, besides the meteorological effects, have been scrutinized using management plans and publications. As a result, inland wetlands decreased at different rates from 1985 to 2020, with a total loss of 31.38% and 21571.0 ha for the spring months. Since the designation dates of RS, the total amount of water surface area reduction was 27.35 %, constituting 17,758.90 ha.

scholarly journals Investigation of Long and Short-Term Water Surface Area Changes in Coastal Ramsar Sites in Turkey with Google Earth Engine

2022 ◽  
Vol 11 (1) ◽  
pp. 46
Author(s):  
Adalet Dervisoglu
Keyword(s):  
Surface Area ◽  
Water Surface ◽  
Google Earth ◽  
Short Term ◽  
Annual Average ◽  
Surface Areas ◽  
Inland Wetlands ◽  
Increasing Trend ◽  
Average Surface Area ◽  
Term Analysis

Deltas and lagoons, which contain many flora and fauna, have rich coastal ecological and biological environments, and are wetlands of vital importance for humans. In this study, the current problems in all coastal Ramsar sites in Turkey are summarized, and changes in water surface areas are investigated using Landsat and Sentinel 1/2 satellite images on the Google Earth Engine (GEE) cloud computing platform. Landsat TM and OLI images were used in the long-term analysis, and time series were created by taking annual and July to September averages between 1985 and 2020. In the short-term analysis, monthly averages were determined using Sentinel 2 images between 2016 and 2020. Sentinel-1 Synthetic Aperture Radar (SAR) images were used in the months when optical data were not suitable for use in monthly analysis. The Normalized Difference Water Index (NDWI) was used to extract water surface areas from the optical images. Afterwards, a thresholding process was used for both optical and radar images to determine the changes. The changes were analyzed together with the meteorological data and the information obtained from the management plans and related studies in the literature. Changes in the water surface areas of all coastal Ramsar sites in Turkey were determined from 1985 to 2020 at different rates. There was a decreasing trend in the Goksu and Kızılırmak Deltas, which also have inland wetlands. The decreasing rates from 1985 to 2020 were −24.52% and −2.86%, for annual average water surfaces for the Goksu and Kızılırmak Deltas, respectively, and −21.64% and −6.34% for the dry season averages, respectively. However, Akyatan Lagoon, which also has inland wetlands, showed an increasing trend. Observing the annual average surface area from 1985 to 2020, an increase of 438 ha was seen, corresponding to 7.65%. Every year, there was an increasing trend in the Gediz Delta and Yumurtalık Lagoons, that do not have inland wetlands. The increasing rates from 1985 to 2020 were 46.01% and 17.31% for the annual average surface area, for the Gediz Delta and Yumurtalık Lagoons, respectively, and 38.34% and 21.04% for the dry season average, respectively. The obtained results reveal the importance of using remote sensing methods in formulating strategies for the sustainable management of wetlands.

scholarly journals Recent Changes of Glacial Lakes in the High Mountain Asia and Its Potential Controlling Factors Analysis

2021 ◽  
Vol 13 (18) ◽  
pp. 3757
Author(s):  
Meimei Zhang ◽  
Fang Chen ◽  
Hang Zhao ◽  
Jinxiao Wang ◽  
Ning Wang
Keyword(s):  
Google Earth ◽  
Controlling Factors ◽  
Rapid Expansion ◽  
Expansion Rate ◽  
Glacial Lake ◽  
High Mountain ◽  
Glacial Lakes ◽  
Computing Platform ◽  
Glacier Ice ◽  
Landsat Satellite

The current glacial lake datasets in the High Mountain Asia (HMA) region still need to be improved because their boundary divisions in the land–water transition zone are not precisely delineate, and also some very small glacial lakes have been lost due to their mixed reflectance with backgrounds. In addition, most studies have only focused on the changes in the area of a glacial lake as a whole, but do not involve the actual changes of per pixel on its boundary and the potential controlling factors. In this research, we produced more accurate and complete maps of glacial lake extent in the HMA in 2008, 2012, and 2016 with consistent time intervals using Landsat satellite images and the Google Earth Engine (GEE) cloud computing platform, and further studied the formation, distribution, and dynamics of the glacial lakes. In total, 17,016 and 21,249 glacial lakes were detected in 2008 and 2016, respectively, covering an area of 1420.15 ± 232.76 km2 and 1577.38 ± 288.82 km2; the lakes were mainly located at altitudes between 4400 m and 5600 m. The annual areal expansion rate was approximately 1.38% from 2008 to 2016. To explore the cause of the rapid expansion of individual glacial lakes, we investigated their long-term expansion rates by measuring changes in shoreline positions. The results show that glacial lakes are expanding rapidly in areas close to glaciers and had a high expansion rate of larger than 20 m/yr from 2008 to 2016. Glacial lakes in the Himalayas showed the highest expansion rate of more than 2 m/yr, followed by the Karakoram Mountains (1.61 m/yr) and the Tianshan Mountains (1.52 m/yr). The accelerating rate of glacier ice and snow melting caused by global warming is the primary contributor to glacial lake growth. These results may provide information that will help in the understanding of detailed lake dynamics and the mechanism, and also facilitate the scientific recognition of the potential hazards associated with glacial lakes in this region.

scholarly journals Implementation of a Surface Water Extent Model in Cambodia using Cloud-Based Remote Sensing

2020 ◽  
Vol 12 (6) ◽  
pp. 984 ◽  
Author(s):  
Christopher E. Soulard ◽  
Jessica J. Walker ◽  
Roy E. Petrakis
Keyword(s):  
Time Series ◽  
Surface Water ◽  
Open Water ◽  
Google Earth ◽  
Measurement Tool ◽  
Dynamic Surface ◽  
Computing Platform ◽  
Flooding Hazard ◽  
Landsat Satellite ◽  
Over Time

Mapping surface water over time provides the spatially explicit information essential for hydroclimatic research focused on droughts and flooding. Hazard risk assessments and water management planning also rely on accurate, long-term measurements describing hydrologic fluctuations. Stream gages are a common measurement tool used to better understand flow and inundation dynamics, but gage networks are incomplete or non-existent in many parts of the world. In such instances, satellite imagery may provide the only data available to monitor surface water changes over time. Here, we describe an effort to extend the applicability of the USGS Dynamic Surface Water Extent (DSWE) model to non-US regions. We leverage the multi-decadal archive of the Landsat satellite in the Google Earth Engine (GEE) cloud-based computing platform to produce and analyze 372 monthly composite maps and 31 annual maps (January 1988–December 2018) in Cambodia, a flood-prone country in Southeast Asia that lacks a comprehensive stream gage network. DSWE relies on a series of spectral water indices and elevation data to classify water into four categories of water inundation. We compared model outputs to existing surface water maps and independently assessed DSWE accuracy at discrete dates across the time series. Despite considerable cloud obstruction and missing imagery across the monthly time series, the overall accuracy exceeded 85% for all annual tests. The DSWE model consistently mapped open water with high accuracy, and areas classified as “high confidence” water correlate well to other available maps at the country scale. Results in Cambodia suggest that extending DSWE globally using a cloud computing framework may benefit scientists, managers, and planners in a wide array of applications across the globe.

Cell morphology, volume, and surface area determinations from multilevel contouring within HVEM micrographs of serial sections and whole-cell mounts

1987 ◽  
Vol 45 ◽  
pp. 588-589
Author(s):  
M. Marko ◽  
A. Leith ◽  
D. Parsons
Keyword(s):  
Surface Area ◽  
Electron Micrographs ◽  
Cell Morphology ◽  
Individual Variation ◽  
Serial Section ◽  
Stereo Pair ◽  
Complex Structures ◽  
Serial Sections ◽  
Surface Areas ◽  
Computer Based

The use of serial sections and computer-based 3-D reconstruction techniques affords an opportunity not only to visualize the shape and distribution of the structures being studied, but also to determine their volumes and surface areas. Up until now, this has been done using serial ultrathin sections.The serial-section approach differs from the stereo logical methods of Weibel in that it is based on the Information from a set of single, complete cells (or organelles) rather than on a random 2-dimensional sampling of a population of cells. Because of this, it can more easily provide absolute values of volume and surface area, especially for highly-complex structures. It also allows study of individual variation among the cells, and study of structures which occur only infrequently.We have developed a system for 3-D reconstruction of objects from stereo-pair electron micrographs of thick specimens.

scholarly journals Tuning the hierarchical pore structure of graphene oxide through dual thermal activation for high-performance supercapacitor

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jeongpil Kim ◽  
Jeong-Hyun Eum ◽  
Junhyeok Kang ◽  
Ohchan Kwon ◽  
Hansung Kim ◽  
...  
Keyword(s):  
Graphene Oxide ◽  
Pore Structure ◽  
Specific Capacitance ◽  
Surface Area ◽  
Thermal Annealing ◽  
High Performance ◽  
Annealing Process ◽  
Supercapacitor Electrode ◽  
Simple Method ◽  
Surface Areas

AbstractHerein, we introduce a simple method to prepare hierarchical graphene with a tunable pore structure by activating graphene oxide (GO) with a two-step thermal annealing process. First, GO was treated at 600 °C by rapid thermal annealing in air, followed by subsequent thermal annealing in N2. The prepared graphene powder comprised abundant slit nanopores and micropores, showing a large specific surface area of 653.2 m2/g with a microporous surface area of 367.2 m2/g under optimized conditions. The pore structure was easily tunable by controlling the oxidation degree of GO and by the second annealing process. When the graphene powder was used as the supercapacitor electrode, a specific capacitance of 372.1 F/g was achieved at 0.5 A/g in 1 M H2SO4 electrolyte, which is a significantly enhanced value compared to that obtained using activated carbon and commercial reduced GO. The performance of the supercapacitor was highly stable, showing 103.8% retention of specific capacitance after 10,000 cycles at 10 A/g. The influence of pore structure on the supercapacitor performance was systematically investigated by varying the ratio of micro- and external surface areas of graphene.

Sign in / Sign up

Export Citation Format

Share Document