ASSESSMENT OF SURFACE WATER DYNAMICS USING MULTIPLE WATER INDICES AROUND ADAMA WOREDA, ETHIOPIA

Rapid change of Adama wereda during the last three decades has posed a serious threat to the existence of ecological systems, specifically water bodies which play a crucial part in supporting life. Role of Satellite images in Remote Sensing could be more important in investigation, monitoring dynamically and planning of natural surface water resources. Landsat-5(TM) & Landsat 8 (OLI) has high spatial, temporal and multispectral resolution and therefore provides consistent and perfect data to detect changes in surface changes of water bodies. In this paper, a study was conducted to detect the changes in water body extent during the period of 1984, 2000 and 2017 using various water indices such as namely Water Ratio Index (WRI), Normalized Difference Water Index (NDWI), Modified Normalized Difference Water Index (MNDWI), supervised classification and wetness component of K-T transformation and the results are Presented. NDWI has been adopted for this study as compared with other indices through ground survey. The results showed an intense decreasing trend in the lakes of chelekleka, kiroftu, lake 1 and lake 3 of surface area in the period 1984–2017, especially between 2000 and 2017 when the lake lost about 1.309 km2 (one third) of its surface area compared to the year 2000, which is equivalent to 76%, 18%, 0.03% and 96%. Interestingly koka lake has shown very erratic changes in its area coverage by losing almost 3.5 km2 between 1984 and 2000 and then climbing back up by 14.8 km2 in 2017. Percentage of increment was observed that 10.6% as compared with previous year

Historical Morphodynamics Assessment in Bridge Areas using Remote Sensing and GIS Techniques

Currently the Ministry of Construction is responsible for planning and construction of bridges across the country but remote sensing and satellite data are not widely used in the Ministry’s routine process. Although the inspection and monitoring are carried out by the conventional methods, the remote sensing and GIS techniques are available as an alternative way with time and cost saving. From this study, the channel migration in the locations of Ayeyarwady bridges will be analyzed and mapped by identifying temporal changes of channels. Google Earth Engine is used as the primary application in this study and surface water extraction from historical Landsat satellite imagery is done by GEE. River centerline processing and erosion-deposition area identifications are carried out by GIS technique. Study period of each bridge is between 1987 and 2017. Bo Myat Tun Bridge and Ayeyarwady Bridge (Pakokku) are toped in the list with highest migration and erosion-deposition rate according to the study. The goal of this study is to assist the bridge inspections and channel monitoring works by means of remote sensing and GIS techniques which are currently undertaking by Ministry of Construction with conventional techniques

Concept for long-term geo-monitoring of the post-mining environment using the example of the Prosper-Haniel mine

The operation of a mining facility provides a wealth of data, starting from mining licenses, documentation of extracted deposits, tunnel reinforcement methods, to documentation regarding the termination of mining operations, which impacts the natural environment at the local, regional, and supra-regional levels. The results of projects conducted by the Research Center of Post-Mining at the Technical University of Georg Agricola in Bochum present the possibilities of integrating environmental geo-monitoring methods to understand the processes occurring both during and after mining operations. Among the research methods used, spatiotemporal multispectral analyses of satellite imagery and images from drone flights stand out, and these will be presented in this paper. Additionally, in-situ measurements using soil sensors, weather stations, the application of mobile GIS, and three-dimensional modelling of geological structures should be noted. A key aspect of mining process research is the implementation and integration of all available geospatial data, allowing the consideration of post-mining processes as a cycle of interconnected, independent values that, through data analysis and validation, enable a comprehensive understanding

A NOVEL METHOD FOR WATER AND WATER CANAL EXTRACTION FROM LANDSAT-8 OLI IMAGERY

Constituents of hydrologic network, River and water canals play a key role in Agriculture for cultivation, Industrial activities and urban planning. Remote sensing images can be effectively used for water canal extraction, which significantly improves the accuracy and reduces the cost involved in mapping using conventional means. Using remote sensing data, the water Index (WI), Normalized Difference Water Index (NDWI) and Modified NDWI (MNDWI) are used in extracting the water bodies. These techniques are aimed at water body detection and need to be complemented with additional information for the extraction of complete water canal networks. The proposed index MNDWI-2 is able to find the water bodies and water canals as well from the Landsat-8 OLI imagery and is based on the SWIR2 band. In this paper, we use Level-1 precision terrain corrected OLI imagery at 30 meter spatial resolution. The proposed MNDWI-2 index is derived using SWIR2 (B7) band and Green (B3) band. The usage of SWIR2 band over SWIR1 results in very low reflectance values for water features, detection of shallow water and delineation of water features with rest of the features in the image. The computed MNDWI-2 index values are threshold by making the values greater than zero as 1 and less than zero as zero. The binarised values of 1 represent the water bodies and 0 represent the non-water body. This normalized index detects the water bodies and canals as well as vegetation which appears in the form of noise. The vegetation from the MNDWI-2 image is removed by using the NDVI index, which is calculated using the Top of Atmosphere (TOA) corrected images. The paper presents the results of water canal extraction in comparison with the major available indexes. The proposed index can be used for water and water canal extraction from L8 OLI imagery, and can be extended for other high resolution sensors

Application of Satellite Imagery and Water Indices to the Hydrography of the Cetina River Basin (Middle Adriatic)

The paper gives a brief description of the remote sensing method used for the identification and extraction of water surfaces. Landsat 8 and Sentinel 2 satellite imagery was used to separate land from bodies of water in the complex karst area surrounding the Croatian Cetina River, flowing into the Adriatic Sea. Water indexing methods are presented in detail. The most frequently used water indices were selected: NDWI, MNDWI, AWEI_nsh, AWEI_sh, WRI and LSWI, and their results compared. The combination of satellite imagery and calculated water indices is concluded to be very useful for the identification and mapping of the area and banks of lakes, riverine zones, river mouths and the coastline in the coastal zone. Landsat 8 satellite imagery is slightly inferior to Sentinel 2 due to lower image resolution. The best results were obtained with the NDWI water index and the worst with LSWI

Vergleich von Algorithmen zur Kartierung der Küstenlinie mittels Satellitenmethoden

U radu su prikazane metode određivanja obalne crte, a detaljnije je prikazana metoda korištenja algoritama daljinske detekcije. Analizirani su rezultati najčešće korištenih algoritama vodenih indeksa: NDWI, MNDWI, AWEI_nsh, AWEI_sh i WRI, koji se koriste za potrebe određivanja obalne crte ili općenito vodenih površina. Algoritmi su primijenjeni na Landsat 8 i Sentinel 2 satelitskim scenama, a kao testno područje je odabrana srednja Dalmacija. Nakon izračuna vodenih indeksa, na područjima je provedena nenadzirana klasifikacija, zatim reklasifikacija i na kraju je prikazana ocjena točnosti klasifikacije pojedinog indeksa. Rezultati su u krupnijem mjerilu prikazani na dva područja: ušće rijeke Jadro u Solinu i ušće rijeke Cetine u Omišu. Analiza rezultata je pokazala da najbolje rezultate daje NDWI, a najlošije AWEI_nsh vodeni indeks.The paper presents the methods of coastline determination and describes the method using remote sensing algorithms in more detail. It further analyses the results of the most widely used algorithms of the water indices NDWI, MNDWI, AWEI_nsh, AWEI_sh and WRI, which are used for determining coastlines and water surfaces in general. The algorithms were applied to the Landsat 8 and Sentinel 2 satellite imagery, with central Dalmatia selected as the test area. After the calculation of water indices, unsupervised classification and reclassification were conducted in these areas and, finally, the evaluation of the classification accuracy for each individual index was presented. The results were shown at larger scale for two areas – the Jadro river mouth in Solin and the Cetina river mouth in Omiš. The result analysis revealed that the best results were obtained using the NDWI water index and the poorest results using the AWEI_nsh water index.Im Beitrag werden die Methoden zur Bestimmung der Küstenlinie und insbesondere die Anwendung von Algorithmen zur Fernerkundung dargestellt. Die Ergebnisse von am meisten genutzten Algorithmen zur Berechnung der für die Bestimmung von Küstenlinien oder allgemein von offenen Gewässern genutzten Wasserindices, d.h. NDWI, MNDWI, AWEI_nsh, AWEI_sh und WRI, werden analysiert. Die Algorithmen wurden auf die Landsat 8 und Sentinel 2 Satellitenszenen von in Mitteldalmatien befindlichen Testgebieten angewendet. Nach der Berechnung der Wasserindices wurden für die Testgebiete erstens unüberwachte Klassifizierung und zweitens Reklassifizierung durchgeführt, und schließlich wurde die Richtigkeit der Klassifikation einzelner Indices beurteilt. Die Ergebnisse werden für zwei Gebiete – die Mündung des Flusses Jadro in der Stadt Solin und die Mündung des Flusses Cetina in Omiš – in größerem Maßstab gezeigt. Die Analyse der Ergebnisse zeigte, dass die besten Ergebnisse mit NDWI und die schlechtesten mit AWEI_nsh erzielt wurden

Uso de sensores remotos para el control de cambios durante las inundaciones en la cuenca media del Río Salado, provincia de Buenos Aires, Argentina

Fil: Pommarés, Nicole Nadín. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Estudios Integrales de la Dinámica Exógena; ArgentinaFil: Salinas de Salmuni, Nélida Graciela. Comisión Nacional de Actividades Espaciales; ArgentinaFil: Fucks, Enrique. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentin

Toward a trans-regional vulnerability assessment for Alps. A methodological approach to land cover changes over alpine landscapes, supporting urban adaptation

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