scholarly journals Long and Short-Term Coastal Changes Assessment Using Earth Observation Data and GIS Analysis: The Case of Sperchios River Delta

2022 ◽  
Vol 11 (1) ◽  
pp. 61
Author(s):  
Emmanouil Psomiadis

The present study provides information about the evolution of the Sperchios River deltaic area over the last 6500 years. Coastal changes, due to natural phenomena and anthropogenic activities, were analyzed utilizing a variety of geospatial data such as historic records, topographic maps, aerial photos, and satellite images, covering a period from 4500 BC to 2020. A qualitative approach for the period, from 4500 BC to 1852, and a quantitative analysis, from 1852 to the present day, were employed. Considering their scale and overall quality, the data were processed and georeferenced in detail based on the very high-resolution orthophoto datasets of the area. Then, the multitemporal shorelines were delineated in a geographical information system platform. Two different methods were utilized for the estimation of the shoreline changes and trends, namely the coastal change area method and the cross-section analysis, by implementing the digital shoreline analysis system with two statistical approaches, the end point rate and the linear regression rate. Significant river flow and coastline changes were observed with the overall increase in the delta area throughout the study period reaching 135 km2 (mean annual growth of 0.02 km2/yr) and the higher accretion rates to be detected during the periods 1805–1852, 1908–1945 and 1960–1986, especially at the central and north part of the gulf. During the last three decades, the coastline has remained relatively stable with a decreasing tendency, which, along with the expected sea-level rise due to climate change, can infer significant threats for the coastal zone in the near future.

2021 ◽  
Author(s):  
George Alexandrakis ◽  
Federico Nomi ◽  
Claudia Speciale ◽  
Sandro De Vita ◽  
Mauro Antonio Di Vito

<p>Geological and environmental conditions that influence local topography also affect indirectly the location of human settlement dynamics. Understanding those relationships plays an important role in archaeological research related to the evolution of settlement dynamics. In the lower Tyrrhenian Islands, an important parameter is also the volcanic landscape evolution. This work aims to study the patterns of Neolithic, Cooper and Bronze Age settlements, based on known archaeological sites at the Low Tyrrhenian Islands, and to generate hypotheses about the relations of settlement patterns with the volcanic landscape. To that end, a Web-GIS database was created, which was fed with topographic, geological, geomorphological data and Earth Observation data. Geomorphological analysis, derived from digital elevation models, and earth observation products such as the SENTINEL missions, can provide useful estimations into the processes shaping landscapes and insight into the location and evolution of settlements. The analysis includes a series of different data correlation, from geomorphologic to socioeconomic, integrated by an indicator analysis. A series of thematic maps were developed to interpret why areas were selected to host settlements. Through the use of the database that was developed during the project, a set of indexes have been applied. Those included exposure and vulnerability indices for the inland and coastal areas, but also location and defensibility indices for the archaeological sites. Moreover, baseline maps for future risk estimations through a Multi-Criteria Decision Analysis System (MCDA), have been produced. The Volcanic Islands of the lower Tyrrhenian coast have a volcanic origin and were influenced, and partly still are, by explosive and effusive eruptions of various energy and types, by more or less intense deformational events, often connected with the dynamics of the volcano, and quiescent periods of varying duration. The areas under investigation present different characteristics in their geomorphological but also their societal evolution. Geomorphological data further analyzed in a ternary diagram that indicated the relative influence of each of the parameters in each area. From the diagram, it can be seen that the locations of human activities are strongly affected by past and recent volcanic activity.</p><p>Acknowledgement: This work is part of the Brains2Islands “INDAGINE MULTIDISCIPLINARE NEI CONTESTI INSULARI BASSO TIRRENICI” project Funded by FONDAZIONE CON IL SUD project number 2015-0296</p>


2019 ◽  
Vol 3 ◽  
pp. 919
Author(s):  
Khairul Umami ◽  
Syawaludin A. Harahap ◽  
Mega Laksmini Syamsudin ◽  
Sunarto Sunarto

Pantai merupakan daerah yang sangat dinamis untuk berubah seiring bertambahnya waktu. Salah satu perubahan yang terjadi di daerah pantai yaitu perubahan pada garis pantai. Tujuan penelitian ini yaitu untuk mengetahui tingkat perubahan garis pantai di pesisir Kecamatan Sayung, Kabupaten Demak dari hasil overlay citra satelit Landsat. Penelitian ini diharapkan dapat berguna sebagai rujukan penelitian selanjutnya, serta sebagai informasi untuk instansi-instansi terkait dan pemerintah agar dapat memperhatikan kondisi keseimbangan fisik pantai di Pesisir Sayung. Penelitian ini menggunakan data yang bersumber dari citra Landsat 7 dan 8 dalam kurun waktu 10 tahun dari tahun 2006 sampai 2016. Metode yang digunakan yaitu metode deskriptif dengan menjelaskan masalah yang terjadi pada lokasi penelitian dengan pendekatan pemodelan dan sistematis. Metode analisis perubahan garis pantai dilakukan dalam program Digital Shoreline Analysis System (DSAS) dengan pendekatan statistik End Point Rate (EPR) dan Net Shorline Movement (NSM). Hasil penelitian menunjukkan bahwa perubahan garis pantai di pesisir Sayung didominasi dengan kejadian abrasi yang sangat tinggi dengan luasan abrasi bernilai 116,48 hektar. Abrasi maksimum terjadi di Desa Timbulsloko, Abrasi minimum terjadi di Desa Sriwulan, Akresi maksimum terjadi di Desa Sriwulan, dan Akresi minimum terjadi di Desa Bedono.


GIS Business ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 12-14
Author(s):  
Eicher, A

Our goal is to establish the earth observation data in the business world Unser Ziel ist es, die Erdbeobachtungsdaten in der Geschäftswelt zu etablieren


Author(s):  
Tais Grippa ◽  
Stefanos Georganos ◽  
Sabine Vanhuysse ◽  
Moritz Lennert ◽  
Nicholus Mboga ◽  
...  

2020 ◽  
Vol 13 (1) ◽  
pp. 5
Author(s):  
William Straka ◽  
Shobha Kondragunta ◽  
Zigang Wei ◽  
Hai Zhang ◽  
Steven D. Miller ◽  
...  

The COVID-19 pandemic has infected almost 73 million people and is responsible for over 1.63 million fatalities worldwide since early December 2019, when it was first reported in Wuhan, China. In the early stages of the pandemic, social distancing measures, such as lockdown restrictions, were applied in a non-uniform way across the world to reduce the spread of the virus. While such restrictions contributed to flattening the curve in places like Italy, Germany, and South Korea, it plunged the economy in the United States to a level of recession not seen since WWII, while also improving air quality due to the reduced mobility. Using daily Earth observation data (Day/Night Band (DNB) from the National Oceanic and Atmospheric Administration Suomi-NPP and NO2 measurements from the TROPOspheric Monitoring Instrument TROPOMI) along with monthly averaged cell phone derived mobility data, we examined the economic and environmental impacts of lockdowns in Los Angeles, California; Chicago, Illinois; Washington DC from February to April 2020—encompassing the most profound shutdown measures taken in the U.S. The preliminary analysis revealed that the reduction in mobility involved two major observable impacts: (i) improved air quality (a reduction in NO2 and PM2.5 concentration), but (ii) reduced economic activity (a decrease in energy consumption as measured by the radiance from the DNB data) that impacted on gross domestic product, poverty levels, and the unemployment rate. With the continuing rise of COVID-19 cases and declining economic conditions, such knowledge can be combined with unemployment and demographic data to develop policies and strategies for the safe reopening of the economy while preserving our environment and protecting vulnerable populations susceptible to COVID-19 infection.


2021 ◽  
Vol 13 (7) ◽  
pp. 1310
Author(s):  
Gabriele Bitelli ◽  
Emanuele Mandanici

The exponential growth in the volume of Earth observation data and the increasing quality and availability of high-resolution imagery are increasingly making more applications possible in urban environments [...]


2021 ◽  
Vol 10 (1) ◽  
pp. 32
Author(s):  
Abhishek V. Potnis ◽  
Surya S. Durbha ◽  
Rajat C. Shinde

Earth Observation data possess tremendous potential in understanding the dynamics of our planet. We propose the Semantics-driven Remote Sensing Scene Understanding (Sem-RSSU) framework for rendering comprehensive grounded spatio-contextual scene descriptions for enhanced situational awareness. To minimize the semantic gap for remote-sensing-scene understanding, the framework puts forward the transformation of scenes by using semantic-web technologies to Remote Sensing Scene Knowledge Graphs (RSS-KGs). The knowledge-graph representation of scenes has been formalized through the development of a Remote Sensing Scene Ontology (RSSO)—a core ontology for an inclusive remote-sensing-scene data product. The RSS-KGs are enriched both spatially and contextually, using a deductive reasoner, by mining for implicit spatio-contextual relationships between land-cover classes in the scenes. The Sem-RSSU, at its core, constitutes novel Ontology-driven Spatio-Contextual Triple Aggregation and realization algorithms to transform KGs to render grounded natural language scene descriptions. Considering the significance of scene understanding for informed decision-making from remote sensing scenes during a flood, we selected it as a test scenario, to demonstrate the utility of this framework. In that regard, a contextual domain knowledge encompassing Flood Scene Ontology (FSO) has been developed. Extensive experimental evaluations show promising results, further validating the efficacy of this framework.


2020 ◽  
Vol 3 (1) ◽  
pp. 78
Author(s):  
Francis Oloo ◽  
Godwin Murithi ◽  
Charlynne Jepkosgei

Urban forests contribute significantly to the ecological integrity of urban areas and the quality of life of urban dwellers through air quality control, energy conservation, improving urban hydrology, and regulation of land surface temperatures (LST). However, urban forests are under threat due to human activities, natural calamities, and bioinvasion continually decimating forest cover. Few studies have used fine-scaled Earth observation data to understand the dynamics of tree cover loss in urban forests and the sustainability of such forests in the face of increasing urban population. The aim of this work was to quantify the spatial and temporal changes in urban forest characteristics and to assess the potential drivers of such changes. We used data on tree cover, normalized difference vegetation index (NDVI), and land cover change to quantify tree cover loss and changes in vegetation health in urban forests within the Nairobi metropolitan area in Kenya. We also used land cover data to visualize the potential link between tree cover loss and changes in land use characteristics. From approximately 6600 hectares (ha) of forest land, 720 ha have been lost between 2000 and 2019, representing about 11% loss in 20 years. In six of the urban forests, the trend of loss was positive, indicating a continuing disturbance of urban forests around Nairobi. Conversely, there was a negative trend in the annual mean NDVI values for each of the forests, indicating a potential deterioration of the vegetation health in the forests. A preliminary, visual inspection of high-resolution imagery in sample areas of tree cover loss showed that the main drivers of loss are the conversion of forest lands to residential areas and farmlands, implementation of big infrastructure projects that pass through the forests, and extraction of timber and other resources to support urban developments. The outcome of this study reveals the value of Earth observation data in monitoring urban forest resources.


Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 110
Author(s):  
Filippo Sarvia ◽  
Elena Xausa ◽  
Samuele De Petris ◽  
Gianluca Cantamessa ◽  
Enrico Borgogno-Mondino

Farmers that intend to access Common Agricultural Policy (CAP) contributions must submit an application to the territorially competent Paying Agencies (PA). Agencies are called to verify consistency of CAP contributions requirements through ground campaigns. Recently, EU regulation (N. 746/2018) proposed an alternative methodology to control CAP applications based on Earth Observation data. Accordingly, this work was aimed at designing and implementing a prototype of service based on Copernicus Sentinel-2 (S2) data for the classification of soybean, corn, wheat, rice, and meadow crops. The approach relies on the classification of S2 NDVI time-series (TS) by “user-friendly” supervised classification algorithms: Minimum Distance (MD) and Random Forest (RF). The study area was located in the Vercelli province (NW Italy), which represents a strategic agricultural area in the Piemonte region. Crop classes separability proved to be a key factor during the classification process. Confusion matrices were generated with respect to ground checks (GCs); they showed a high Overall Accuracy (>80%) for both MD and RF approaches. With respect to MD and RF, a new raster layer was generated (hereinafter called Controls Map layer), mapping four levels of classification occurrences, useful for administrative procedures required by PA. The Control Map layer highlighted that only the eight percent of CAP 2019 applications appeared to be critical in terms of consistency between farmers’ declarations and classification results. Only for these ones, a GC was warmly suggested, while the 12% must be desirable and the 80% was not required. This information alone suggested that the proposed methodology is able to optimize GCs, making possible to focus ground checks on a limited number of fields, thus determining an economic saving for PA and/or a more effective strategy of controls.


Sign in / Sign up

Export Citation Format

Share Document