scholarly journals Secondary Ecological Succession of Mangrove in the 2004 Tsunami Created Wetlands of South Andaman, India

2020 ◽  
Author(s):  
V. Shiva Shankar ◽  
Neelam Purti ◽  
Ravi Pratap Singh ◽  
Faiyaz A. Khudsar
Keyword(s):  
Storm Surges ◽  
Ecological Succession ◽  
Created Wetlands ◽  
Landsat 8 ◽  
Acanthus Ilicifolius ◽  
Landsat 7 ◽  
South Andaman ◽  
Landsat Satellite ◽  
Gis Software ◽  
2004 Tsunami

Andaman and Nicobar Islands (ANI’s) being situated in the Tropical zone is the cradle of multi-disasters viz., cyclones, floods, droughts, land degradation, runoff, soil erosion, shallow landslides, epidemics, earthquakes, volcanism, tsunami and storm surges. Mangroves are one of the first visible reciprocators above land and sea surface to cyclonic storms, storm surges, and tsunamis among the coastal wetlands. The Indian Ocean 2004 tsunami was denoted as one of the most catastrophic ever recorded in humankind’s recent history. A mega-earthquake of Magnitude (9.3) near Indonesia ruptured the Andaman-Sunda plate triggered this tsunami. Physical fury, subsidence, upliftment, and prolonged water logging resulted in the massive loss of mangrove vegetation. A decade and half years after the 2004 tsunami, a study was initiated to assess the secondary ecological succession of mangrove in Tsunami Created Wetlands (TCWs) of south Andaman using Landsat satellite data products. Since natural ecological succession is a rather slow process and demands isotope techniques to establish a sequence of events succession. However, secondary ecological succession occurs in a short frame of time after any catastrophic event like a tsunami exemplifying nature’s resilience. Band-5 (before tsunami, 2003) and Band-6 (after tsunami, 2018) of Landsat 7 and Landsat-8 satellite respectively were harnessed to delineate mangrove patches and TCWs in the focus area using ArcMap 10.5, Geographic Information Systems (GIS) software. From the study, it was understood that Fimbrisstylis littoralis is the pioneering key-stone plant followed by Acrostichum aureum and Acanthus ilicifolius facilitating Avicennia spp/Rhizopara spp for ecological succession in the TCWs.

scholarly journals Studying Land Use and Land Cover Spatial Patterns Distribution in Crete, Greece with Means of Satellite Remote Sensing

Proceedings ◽  
2020 ◽  
Vol 30 (1) ◽  
pp. 66
Author(s):  
Dimitrios D. Alexakis ◽  
Christos Polykretis
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Spatial Patterns ◽  
Landscape Metrics ◽  
Unsupervised Classification ◽  
Landsat 8 ◽  
Important Indicator ◽  
Rural Environments ◽  
Landsat 7 ◽  
Landsat Satellite

Multi-temporal Land use and Land cover (LULC) monitoring is a crucial parameter for assessing an area’s landscape ecology regime. LULC changes can be effectively used to describe dynamics of both urban or rural environments and vegetation patterns as an important indicator of ecological environments. In this context, spatial land use properties can be quantified by using a set of landscape metrics. Landscape metrics capture inherent spatial structure of the environment and are used to enhance interpretation of spatial pattern of the landscape. This study aims to monitor diachronically the LULC regime of the island of Crete, Greece with the use of Landsat satellite imageries (Landsat 5, Landsat-7 and Landsat-8) in terms of soil erosion. For this reason, radiometric and atmospheric corrections are applied to all satellite products and unsupervised classification algorithms are used to develop detail LULC maps of the island. The LULC classes are developed by generalizing basic CORINE classes. Following, various landscape metrics are applied to estimate the temporal changes in LULC patterns of the island. The results denote that the diachronic research of spatial patterns evolution can effectively assist to the investigation of the structure, function and landscape pattern changes.

scholarly journals Spatial Temporal Analysis of Coral Reefs in Belitung Tourism Destination Islands

2018 ◽  
Vol 73 ◽  
pp. 03024
Author(s):  
Pavita Raudina Sari ◽  
Ratna Saraswati ◽  
Adi Wibowo
Keyword(s):  
Coral Reefs ◽  
Image Data ◽  
Temporal Analysis ◽  
Landsat 8 ◽  
Tourism Destination ◽  
Natural Factor ◽  
Tourist Attractions ◽  
Natural Factors ◽  
Landsat 7 ◽  
Landsat Satellite

One of the world’s most spectacular ecosystems in this world is the coral reef. In Indonesia, Bangka Belitung is one province which has beautiful coral reefs and has become one of the tourist attractions. However, there might be a loss of the coral reefs area that can be caused by natural factors and human activities. This study aims to analyze the distribution and the changing of coral reefs that occurred in the islands of tourist destination in Belitung Regency from 2005 to 2018 and to analyze its factors. Landsat satellite imageries used in this study are Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI/TIRS. The distribution of coral reefs will be determined by image data processing. Then, overlay methods are used to analyze the changes and its factors. Based on the analysis, in the year of 2005-2018, there are 3.93 km2 areas of coral reefs that have decreased. On the top of that, there are 1.34 km2 or about 34.04% of coral reefs areas have decreased that caused by non-natural factors. It can be concluded that the decreased of the coral reefs occurred in Belitung tourism destination islands, are still dominated by natural factors rather than a non-natural factor.

scholarly journals Monitoring LST-NDVI Relationship Using Premonsoon Landsat Datasets

2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Subhanil Guha ◽  
Himanshu Govil ◽  
Prabhat Diwan
Keyword(s):  
Correlation Coefficient ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Urban Landscape ◽  
Landsat 8 ◽  
Landsat 7 ◽  
Systematic Planning ◽  
Landsat Satellite ◽  
The City

The present study monitors the interrelationship of land surface temperature (LST) with normalized difference vegetation index (NDVI) in Raipur City of India using premonsoon Landsat satellite sensor for the season of 2002, 2006, 2010, 2014, and 2018. The results describe that the mean LST of Raipur City is gradually increased with time. The value of mean NDVI is higher in the area below mean LST compared to the area above mean LST. The value of mean NDVI is also higher in Landsat 8 data than Landsat 5 and Landsat 7 data. A strong negative LST-NDVI correlation is observed throughout the period. The correlation coefficient is higher in the area above mean LST and lower in the area below mean LST. The value of the correlation coefficient is decreased with time. The mixed urban landscape of the city is closely related to the changes of LST-NDVI relationship. These results provide systematic planning of the urban environment.

scholarly journals DYNAMICS OF GREEN SPACES IN ST. PETERSBURG ACCORDING TO REMOTE SENSING DATA

2021 ◽  
Vol 2 (6) ◽  
pp. 38-41
Author(s):  
D.K. Alexeev ◽  
◽  
A.V. Babin ◽  
V.Yu. Sargaeva
Keyword(s):  
Spatial Distribution ◽  
Quantitative Assessment ◽  
Satellite Images ◽  
Vegetation Index ◽  
Remote Sensing Data ◽  
Green Spaces ◽  
Landsat 8 ◽  
Landsat 7 ◽  
Landsat Satellite ◽  
The City

. Urban development is formulated as one of seventeen sustainable development goals for the near future. Among the whole range of environmental problems of a modern city, the issues of urban greening occupy a special place. In the course of the work, the analysis of the spatial distribution and assessment of the dynamics of green spaces on the territory of the city of St. Petersburg and its administrative-territorial units (inner-city districts) was carried out according to the data of multispectral satellite images Landsat 7 and Landsat 8 for the period 2002–2018. The normalized vegetation index (NDVI) was used for quantitative assessment. Maps of the spatial distribution of NDVI for the specified period were built. A decrease in the indicators of the provision of green spaces for the specified period for various districts of the city has been established. The obtained maps of the city’s vegetation cover, based on Landsat satellite images, provide a visual representation of the spatial distribution of landscaping indicators with the possibility of their quantitative assessment, and provide planning of landscaping facilities. The data obtained as a result of the work can supplement existing knowledge when carrying out work on process research and monitoring, as well as when making practical decisions

scholarly journals Radiometric Cross Calibration of Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+)

2014 ◽  
Vol 6 (12) ◽  
pp. 12619-12638 ◽  
Author(s):  
Nischal Mishra ◽  
Md Haque ◽  
Larry Leigh ◽  
David Aaron ◽  
Dennis Helder ◽  
...  
Keyword(s):  
Thematic Mapper ◽  
Landsat 8 ◽  
Landsat 7 ◽  
Cross Calibration

scholarly journals Performance comparisons of particle swarm optimization, echo state neural network and genetic algorithm for vegetation segmentation

2017 ◽  
Vol 7 (1.1) ◽  
pp. 184
Author(s):  
Rincy Merlin Mathew ◽  
S. Purushothaman ◽  
P. Rajeswari
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Soft Computing ◽  
Particle Swarm ◽  
Band 3 ◽  
Landsat 8 ◽  
Swarm Optimization ◽  
Landsat 7 ◽  
Performance Comparisons

This article presents the implementation of vegetation segmentation by using soft computing methods: particle swarm optimization (PSO), echostate neural network(ESNN) and genetic algorithm (GA). Multispectral image with the required band from Landsat 8 (5, 4, 3) and Landsat 7 (4, 3, 2) are used. In this paper, images from ERDAS format acquired by Landsat 7 ‘Paris.lan’ (band 4, band 3, Band 2) and image acquired from Landsat 8 (band5, band 4, band 3) are used. The soft computing algorithms are used to segment the plane-1(Near infra-red spectra) and plane 2(RED spectra). The monochrome of the two segmented images is compared to present performance comparisons of the implemented algorithms.

scholarly journals Land Cover Change Investigation in the Southern Syrian Coastal Basins During the Past 30-Years Using Landsat Remote Sensing Data

2018 ◽  
Vol 11 (1-2) ◽  
pp. 45-51 ◽  
Author(s):  
Muhannad Hammad ◽  
László Mucsi ◽  
Boudewijn van Leeuwen
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Remote Sensing Data ◽  
Landsat 8 ◽  
Landsat 7 ◽  
Coastal Basins ◽  
Major Increase ◽  
Temporal And Spatial ◽  
Land Cover Maps ◽  
Conflict Period

Abstract Land cover change and deforestation are important global ecosystem hazards. As for Syria, the current conflict and the subsequent absence of the forest preservation are main reasons for land cover change. This study aims to investigate the temporal and spatial aspects and trends of the land cover alterations in the southern Syrian coastal basins. In this study, land cover maps were made from surface reflectance images of Landsat-5(TM), Landsat-7(ETM+) and Landsat-8(OLI) during May (period of maximum vegetation cover) in 1987, 2002 and 2017. The images were classified into four different thematic classes using the maximum likelihood supervised classification method. The classification results were validated using 160 validation points in 2017, where overall accuracy was 83.75%. Spatial analysis was applied to investigate the land cover change during the period of 30 years for each basin and the whole study area. The results show 262.40 km2 reduction of forest and natural vegetation area during (1987-2017) period, and 72.5% of this reduction occurred during (2002-2017) period due to over-cutting of forest trees as a source of heating by local people, especially during the conflict period. This reduction was particularly high in the Alabrash and Hseen basins with 76.13 and 79.49 km2 respectively, and was accompanied by major increase of agriculture lands area which is attributed to dam construction in these basins which allowed people to cultivate rural lands for subsistence or to enhance their economic situation. The results of this study must draw the relevant authorities’ attention to preserve the remaining forest area.

scholarly journals Assessment of shoreline positional uncertainty using remote sensing and GIS techniques: A case study from the east coast of India

2021 ◽  
Vol 71 (3) ◽  
pp. 249-263
Author(s):  
Kongeswaran Thangaraj ◽  
Sivakumar Karthikeyan
Keyword(s):  
Linear Regression ◽  
Coastal Zone ◽  
East Coast ◽  
Coastal Zone Management ◽  
Storm Surges ◽  
Shoreline Change ◽  
Coastal Protection ◽  
East Coast Of India ◽  
Zone Management ◽  
2004 Tsunami

The focus of this research was to assess the shoreline changes by comparing the satellite data from 1980 to 2020. The study area falls in the region between Kodiakarai and Nagapattinam of the east coast of India, which has frequently been distressed by storm surges and cyclones in the Bay of Bengal. The Digital Shoreline Analysis System (DSAS) detects and measures the erosional and accretional shoreline positions through the statistics of the Shoreline Change Envelope, Net Shoreline Movement, End Point Rate, Linear Regression Rate, and Weighted Linear Regression. The results show that the shoreline from Kodiakkarai to Nagapattinam suffered severe erosion of 17.7% in total with an average annual erosion rate of 3.4 m/year from 1980 to 2020 and the rate of erosion ranged between 0.1 m/year to 19.8 m/year. About 90.5% of the total shoreline was faced high erosion during the period between 2000 and 2010. The maximum erosion was about 1061 m from 2000 to 2010, the maximum accretion was found to be 1002 m in transects at Kodiakkarai during 2010 to 2020. After the effect of 2004 tsunami, the corresponding changes in littoral currents caused the drastic erosion and accretion in this shoreline. The DSAS prediction model shows that 19.3% of the current shoreline will erode in 2030. The maximum predicted erosion is 406 m at Kodiakkarai and the maximum predicted accretion is 148 m at Nagapattinam region. The coastal zone from Kodiakkarai to Nagapattinam needs special attention to prevent the erosion and it is recommended to build suitable coastal protection structures along the coast for sustainable development and to execute the coastal zone management for this region.

scholarly journals Supraglacial debris cover assessment in the Caucasus Mountains, 1986-2000-2014

2017 ◽  
Author(s):  
Levan G. Tielidze ◽  
Roger D. Wheate ◽  
Stanislav S. Kutuzov ◽  
Kate Doyle ◽  
Ivan I. Lavrentiev
Keyword(s):  
Morphological Type ◽  
Ice Age ◽  
Landsat 8 ◽  
Glacier Area ◽  
Greater Caucasus ◽  
Rock Structure ◽  
Debris Cover ◽  
Landsat 7 ◽  
Caucasus Mountains ◽  
Elevation Model

Abstract. Surpaglacial debris cover plays an increasingly important role impacting on glacier ablation, while there have been limited recent studies for the assessment of debris covered glaciers in the Greater Caucasus mountains. We selected 559 glaciers according to the sections and macroslopes in the Greater Caucasus main watershed range and the Elbrus massif to assess supraglacial debris cover (SDC) for the years 1986, 2000 and 2014. Landsat (Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI) and SPOT satellite imagery were analysed to generate glacier outlines using manual and semi-automated methods, along with slope information from a Digital Elevation Model. The study shows there is greater SDC area on the northern than the southern macroslope, and more in the eastern section than the western and central. In 1986-2000-2014, the SDC area increased from 6.4 %-8.2 %-19.4 % on the northern macroslope (apart from the eastern Greater Caucasus section), while on the southern macroslope, SDC increased from 4.0 %-4.9 %-9.2 %. Overall, debris covered glacier numbers increased from 122-143-172 (1986-2000-2014) for 559 selected glaciers. Despite the total glacier area decrease, the SDC glacier area and numbers increased as a function of slope inclination, aspect, glacier morphological type, Little Ice Age (LIA) moraines, rock structure and elevation. The datasets are available for public download at https://doi.pangaea.de/10.1594/PANGAEA.880147.

scholarly journals Komparasi Kemampuan Citra Satelit Landsat Dalam Mengidentifikasi Suhu Permukaan Daratan Di Kota Pekalongan

2020 ◽  
Author(s):  
Trida Ridho Fariz ◽  
Tjaturahono Budi Sanjoto ◽  
Dewi Liesnoor Setyowati
Keyword(s):  
Brightness Temperature ◽  
Landsat 8 ◽  
Landsat 7

Kajian pemetaan suhu permukaan daratan (LST) berbasis citra Landsat sudah sering dilakukan di Indonesia. Tetapi kajian yang membandingkan kemampuan citra satelit Landsat-7 dan Landsat-8 masih jarang dilakukan. Padahal kedua saluran termal pada citra satelit Landsat-7 dan Landsat-8 memiliki kelebihan dan kekurangan masing-masing, sehingga perlu dilakukan kajian untuk membandingkan kemampuan kedua citra satelit tersebut. Penelitian ini bertujuan untuk membandingkan kemampuan band termal antara citra satelit Landsat 7 dengan citra satelit Landsat 8 hanya untuk identifikasi LST, selain itu juga mengetahui perubahannya secara temporal.Data yang digunakan dalam penelitian ini adalah citra satelit Landsat 7 dan Landsat 8. Tahapan analisis data dimulai dengan pengolahan citra satelit untuk suhu perukaan daratan yang terdiri dari kalibrasi radian, koreksi atmosferik, konversi brightness temperature lalu diakhiri dengan konversi suhu permukaan daratan. Setiap peta suhu permukaan daratan dianalisis statistik berupa regresi linier dengan data suhu permukaan daratan hasil pengukuran dilapangan.Hasil penelitian ini menunjukkan bahwa citra satelit Landsat 8 cenderung lebih baik dalam memetakan LST di Kota Pekalongan. Citra satelit Landsat 8 juga digunakan untuk mengidentifikasi perubahan LST di Kota Pekalongan. Kota Pekalongan dalam kurun tahun 2015 sampai 2019 telah terjadi peningkatan suhu sekitar 0,60C. Wilayah yang menngalami perubahan suhu terbsar adalah Kecamatan Pekalongan Selatan.

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