scholarly journals A new glacier inventory of Iran

2009 ◽  
Vol 50 (53) ◽  
pp. 93-103 ◽  
Author(s):  
M.S. Moussavi ◽  
M.J. Valadan Zoej ◽  
F. Vaziri ◽  
M.R. Sahebi ◽  
Y. Rezaei
Keyword(s):  
Remote Sensing ◽  
Satellite Imagery ◽  
Maximum Height ◽  
Mountain Range ◽  
Glacier Inventory ◽  
Mountain Glaciers ◽  
Alborz Mountain ◽  
Gis Environment ◽  
Mountain Chain ◽  
Comprehensive Study

AbstractA new glacier inventory of Iran, compiled according to GLIMS guidelines through the use of photogrammetry and remote sensing supported by fieldwork, provides the first comprehensive study of its mountain glaciers. The glaciers are found in five main areas: two in the higher elevations of the Alborz mountain range (Damavand and Takhte–Soleiman regions), two on the Zardkuh and Oshtorankuh mountain chain in the Zagros mountain range and one in the Sabalan Mountains in northwest Iran. Several important glacier attributes, including minimum and maximum height of ice, area and maximum length and width, together with glacier extent, were successfully extracted using aerial and satellite imagery. Thereafter a comprehensive glacier database was established in a GIS environment.

scholarly journals Present extent, features and regional distribution of Italian glaciers

2019 ◽  
pp. 159-175 ◽  
Author(s):  
Guglielmina Adele Diolaiuti ◽  
Roberto Sergio Azzoni ◽  
Carlo D'Agata ◽  
Davide Maragno ◽  
Davide Fugazza ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Regional Scale ◽  
Regional Distribution ◽  
Alpine Region ◽  
Glacier Area ◽  
Glacier Inventory ◽  
Mountain Glaciers ◽  
Multi Temporal ◽  
Comprehensive Study

Remote sensing investigations permit to map and describe at a regional scale and with a multi-temporal approach mountain glaciers. In this work, we present some results from the New Italian Glacier Inventory which we developed by analyzing high-resolution color orthophotos acquired in the timeframe 2005–2011. In particular, in this paper we focused on each Italian Alpine Region, describing in detail glacier extent and features of each mountain group. Although Italian glaciologists were the first to produce glacier inventories (developing a glacier database as early as the beginning of the 20th century), during the last three decades only regional and local glacier lists have been developed. Therefore, a comprehensive study describing the actual whole Italian glaciation has been lacking. The New Italian Glacier Inventory describes 903 glaciers covering altogether an area of 368.10 km2 ± 2%. We found that about 84% of the total number of ice bodies is composed of glaciers smaller than 0.5 km2 covering only 21% of the total area, indicating that the Italian glacier resource is spread into several small ice bodies with only few larger glaciers. A comparison between the total glacier area of the new inventory and the glacier coverage value from the CGI Inventory (1959–1962) suggests a reduction of the glacier extent of about 30%.

scholarly journals LAND COVER / LAND USE MONITORING FOR AGRICULTURE FEATURES CLASSIFICATION

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 61-65
Author(s):  
S. H. Guliyeva
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Satellite Image ◽  
Research Work ◽  
Mountain Range ◽  
Land Use Land Cover ◽  
Stress Monitoring ◽  
Sensing Applications

Abstract. Remote sensing applications are directed to agricultural observation and monitoring. It has been huge of scientific papers are dedicated to the research of the contribution of remote sensing for agriculture studies. There are several global challenges needed to be considered within agriculture activities. It can be embraced by the main agriculture sector facing the obstacles impacting the production and productivity of the sector. These are the following options that can be pointed out: biomass and yield estimation; vegetation vigor and drought stress monitoring; assessment of crop phenological development; crop acreage estimation and cropland mapping; and mapping of disturbances and Land Use/Land Cover changes. In this study has been undertaken the realization of satellite-based Land Use/Land Cover monitoring based on various optical satellite data. It has been used satellite images taken from satellites AZERSKY, RapidEye, Sentinel-2B and further processed for Land Use/Land Cover classification. Following the complex approach of the supervised and unsupervised classification, the methodology has been used for satellite image processing. As the main satellite imagery for monitoring crop condition were AZERSKY taken during the growing season, from May to June of 2019 year. The study area was some part of the Sheki region, which covers the central part of the southern slope of the Greater Caucasus Mountain Range within Azerbaijan Republic. In this research work satellite imagery processing and mapping has been carried out on the basis of software application of ArcGIS Pro 2.5.

Estimations for Percentage of Impervious Area by the Use of Satellite Remote Sensing Imagery

1994 ◽  
Vol 29 (1-2) ◽  
pp. 135-144 ◽  
Author(s):  
C. Deguchi ◽  
S. Sugio
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Satellite Imagery ◽  
Satellite Remote Sensing ◽  
Aerial Photographs ◽  
Estimation Errors ◽  
Remote Sensing Imagery ◽  
Impervious Area ◽  
Urbanized Areas

This study aims to evaluate the applicability of satellite imagery in estimating the percentage of impervious area in urbanized areas. Two methods of estimation are proposed and applied to a small urbanized watershed in Japan. The area is considered under two different cases of subdivision; i.e., 14 zones and 17 zones. The satellite imageries of LANDSAT-MSS (Multi-Spectral Scanner) in 1984, MOS-MESSR(Multi-spectral Electronic Self-Scanning Radiometer) in 1988 and SPOT-HRV(High Resolution Visible) in 1988 are classified. The percentage of imperviousness in 17 zones is estimated by using these classification results. These values are compared with the ones obtained from the aerial photographs. The percent imperviousness derived from the imagery agrees well with those derived from aerial photographs. The estimation errors evaluated are less than 10%, the same as those obtained from aerial photographs.

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

Assessment and Bibliometric Review of Scientific Achievements Published in the Archives of Photogrammetry, Cartography and Remote Sensing

2019 ◽  
Vol 31 (1) ◽  
pp. 145-166
Author(s):  
Krzysztof Bakuła ◽  
Zdzisław Kurczyński
Keyword(s):  
Remote Sensing ◽  
Statistical Data ◽  
Spatial Information ◽  
Technological Development ◽  
Scientific Work ◽  
Scientific Institutions ◽  
Bibliometric Review ◽  
History Of ◽  
Gis Environment ◽  
Scientific Achievements

Abstract The Archives of Photogrammetry, Cartography and Remote Sensing is a journal which, in the era of technological development of photogrammetry and remote sensing and changes related to cartography in the field of common digitization of sources and processing of spatial information in GIS environment, has been one of the most popular places for publishing articles in this field in Poland for years. Thirty volumes published throughout 25 years have provided nearly 1000 scientific articles and monographic studies summarizing the scientific work of several hundred authors from dozens of scientific institutions and production companies in Poland. This article is an attempt to summarize the achievements published in the journal in the field of bibliometric evaluation and statistical data of the publications from the time of the existence of this inter-association journal. The text quotes the history of the journal, indicates statistics on the number of articles, their citation with the most popular items, authors, reviewers. This evaluation was compared with other national and foreign journals.

scholarly journals Remote Sensing of Vegetation Recovery in Grasslands after the 1988 Yellowstone Fires in Yellowstone National Park

1990 ◽  
Vol 14 ◽  
pp. 151-153
Author(s):  
Evelyn Merrill ◽  
Cathy Wilson ◽  
Ronald Marrs
Keyword(s):  
Remote Sensing ◽  
Spectral Data ◽  
Satellite Imagery ◽  
Yellowstone National Park ◽  
National Park ◽  
Large Scale ◽  
Vegetation Recovery ◽  
Electromagnetic Spectrum ◽  
Traditional Methods ◽  
Vegetative Biomass

Traditional methods for measurement of vegetative biomass can be time-consuming and labor­intensive, especially across large areas. Yet such estimates are necessary to investigate the effects of large scale disturbances on ecosystem components and processes. One alternative to traditional methods for monitoring rangeland vegetation is to use satellite imagery. Because foliage of plants differentially absorbs and reflects energy within the electromagnetic spectrum, remote sensing of spectral data can be used to quantify the amount of green vegetative biomass present in an area (Tucker and Sellers 1986).

scholarly journals Ground Data Inputs To Image Processing for Estimating Terrain Characteristics for Glacio-Hydrological Analysis

1987 ◽  
Vol 9 ◽  
pp. 45-49 ◽  
Author(s):  
M.J. Clark ◽  
A.M. Gurnell ◽  
P.J. Hancock
Keyword(s):  
Remote Sensing ◽  
Image Processing ◽  
Satellite Imagery ◽  
Geometric Correction ◽  
Data Set ◽  
Glacial Environments ◽  
Methodological Problems ◽  
Terrain Characteristics ◽  
Radiometric Data

Remote-sensing research in glacial and pro-glacial environments raises several methodological problems relating to the handling of ground and satellite radiometric data. An evaluation is undertaken of the use of ground radiometry to elucidate properties of relevant surface types in order to interpret satellite imagery. It identifies the influence that geometric correction and re-sampling have on the radiometric purity of the resulting data set. Methodological problems inherent in deriving catchment terrain characteristics are discussed with reference to currently glacierized and pro-glacial zones of south-western Switzerland.

scholarly journals The Mapping of Land Use Using Object-Based Image Analysis (OBIA) in Klaten Regency

2020 ◽  
Vol 202 ◽  
pp. 06036
Author(s):  
Nurhadi Bashit ◽  
Novia Sari Ristianti ◽  
Yudi Eko Windarto ◽  
Desyta Ulfiana
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Image Analysis ◽  
Satellite Imagery ◽  
Agricultural Land ◽  
Scale Parameter ◽  
Land Use Classification ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Sentinel 2

Klaten Regency is one of the regencies in Central Java Province that has an increasing population every year. This can cause an increase in built-up land for human activities. The built-up land needs to be monitored so that the construction is in accordance with the regional development plan so that it does not cause problems such as the occurrence of critical land. Therefore, it is necessary to monitor land use regularly. One method for monitoring land use is the remote sensing method. The remote sensing method is much more efficient in mapping land use because without having to survey the field. The remote sensing method utilizes satellite imagery data that can be processed for land use classification. This study uses the sentinel 2 satellite image data with the Object-Based Image Analysis (OBIA) algorithm to obtain land use classification. Sentinel 2 satellite imagery is a medium resolution image category with a spatial resolution of 10 meters. The land use classification can be used to see the distribution of built-up land in Klaten Regency without having to conduct a field survey. The results of the study obtained a segmentation scale parameter value of 60 and a merge scale parameter value of 85. The classification results obtained by 5 types of land use with OBIA. Agricultural land use dominates with an area of 50% of the total area.

scholarly journals KLASIFIKASI HABITAT PERAIRAN DANGKAL MENGGUNAKAN LOGIKA FUZZY DAN MAXIMUM LIKELIHOOD PADA CITRA SATELIT MULTISPEKTRAL

2018 ◽  
Vol 10 (3) ◽  
pp. 667-681
Author(s):  
Muhammad Siddiq Sangadji ◽  
Vincentius Paulus Siregar ◽  
Henry Munandar Manik
Keyword(s):  
Remote Sensing ◽  
Fuzzy Logic ◽  
Maximum Likelihood ◽  
Satellite Imagery ◽  
Data Retrieval ◽  
Classification Algorithm ◽  
Benthic Habitat ◽  
Fuzzy Logic Algorithm ◽  
Accuracy Level ◽  
Sentinel 2A

ABSTRAKLogika fuzzy memiliki aplikasi di berbagai bidang, namun memiliki arti khusus untuk penginderaan jarak jauh. Logika fuzzy memungkinkan keanggotaan parsial, bagian yang sangat penting dibidang penginderaan jarak jauh, karena keanggotaan parsial diterjemahkan secara dekat dengan masalah piksel campuran. Penelitian ini bertujuan untuk menerapkan algoritma klasifikasi logika fuzzy untuk memetakan habitat dasar Perairan dangkal pada Citra Satelit SPOT 7 dan Sentinel 2A, menguji tingkat akurasinya dan membandingkan algoritma klasifikasi logika fuzzy dengan maximum likelihood. Pengambilan data lapang berlokasi di gusung Karang Lebar dan Karang Congkak, Kepuluan Seribu pada tanggal 6 Desember sampai dengan 10 Desember 2017. Keseluruhan hasil uji akurasi menunjukan bahwa algoritma logika fuzzy masih memiliki tingkat akurasi yang baik dibandingkan dengan algoritma maximum likelihood. Perbedaan ukuran pixel (resolusi spasial) dari citra satelit juga mempengaruhi hasil akurasi, dimana citra satelit SPOT 7 memiliki tingkat akurasi yang lebih besar dibandingkan dengan Sentinel 2A.ABSTRACTFuzzy logic has applications in various fields, but has special meaning for remote sensing. Fuzzy logic allows partial membership, a very important property in the field of remote sensing, since partial membership is translated closely to the problem of mixed pixels. The aim of this research is to apply fuzzy logic classification algorithm to map benthic habitat in SPOT 7 and Sentinel 2A satellite imagery, test its accuracy level and compare fuzzy logic classification algorithm with maximum likelihood. Field data retrieval located in Karang Lebar and Karang Congkak, Kepulauan Seribu on 6 December until 10 December 2017. The overall accuracy test results show that fuzzy logic algorithm still has a good accuracy level compared to the maximum likelihood algorithm. Differences in pixel size (spatial resolution) of satellite imagery also affect accuracy results, where SPOT 7 satellite imagery has greater accuracy then Sentinel 2A. 

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