Advances in Applied Remote Sensing to Coastal Environments Using Free Satellite Imagery

2014 ◽  
pp. 77-102 ◽  
Author(s):  
Cristina Lira ◽  
Rui Taborda
Keyword(s):  
Remote Sensing ◽  
Satellite Imagery ◽  
Coastal Environments

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.

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. 

Optimal splitting technique for remote sensing satellite imagery data

2001 ◽  
Author(s):  
Debasis Chaudhuri ◽  
A. Mishra ◽  
S. K. Anand ◽  
V. Gohri
Keyword(s):  
Remote Sensing ◽  
Satellite Imagery ◽  
Splitting Technique ◽  
Remote Sensing Satellite ◽  
Imagery Data
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