Automated Shoreline Detection Using Natural Colour Composite on SPOT 5 Satellite Imagery

2017 ◽  
Vol 23 (5) ◽  
pp. 4601-4604
Author(s):  
Siti Zaleha Ismail ◽  
Mohd Asyraf Zulkifley ◽  
Aini Hussain ◽  
Mohd Marzuki Mustafa ◽  
Anuar Mikdad Muad
Keyword(s):  
Satellite Imagery ◽  
Colour Composite ◽  
Spot 5

scholarly journals Evaluating high resolution SPOT 5 satellite imagery for crop identification

2011 ◽  
Vol 75 (2) ◽  
pp. 347-354 ◽  
Author(s):  
Chenghai Yang ◽  
James H. Everitt ◽  
Dale Murden
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Spot 5

scholarly journals Towards an automated monitoring of human settlements in South Africa using high resolution SPOT satellite imagery

2015 ◽  
Vol XL-7/W3 ◽  
pp. 1389-1394 ◽  
Author(s):  
T. Kemper ◽  
N. Mudau ◽  
P. Mangara ◽  
M. Pesaresi
Keyword(s):  
South Africa ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Informal Settlement ◽  
Informal Settlements ◽  
Image Features ◽  
Sub Saharan Africa ◽  
Image Feature ◽  
Data Set ◽  
Spot 5

Urban areas in sub-Saharan Africa are growing at an unprecedented pace. Much of this growth is taking place in informal settlements. In South Africa more than 10% of the population live in urban informal settlements. South Africa has established a National Informal Settlement Development Programme (NUSP) to respond to these challenges. This programme is designed to support the National Department of Human Settlement (NDHS) in its implementation of the Upgrading Informal Settlements Programme (UISP) with the objective of eventually upgrading all informal settlements in the country. Currently, the NDHS does not have access to an updated national dataset captured at the same scale using source data that can be used to understand the status of informal settlements in the country. <br><br> This pilot study is developing a fully automated workflow for the wall-to-wall processing of SPOT-5 satellite imagery of South Africa. The workflow includes an automatic image information extraction based on multiscale textural and morphological image features extraction. The advanced image feature compression and optimization together with innovative learning and classification techniques allow a processing of the SPOT-5 images using the Landsat-based National Land Cover (NLC) of South Africa from the year 2000 as low-resolution thematic reference layers as. The workflow was tested on 42 SPOT scenes based on a stratified sampling. The derived building information was validated against a visually interpreted building point data set and produced an accuracy of 97 per cent. Given this positive result, is planned to process the most recent wall-to-wall coverage as well as the archived imagery available since 2007 in the near future.

scholarly journals VOLUMETRIC FOREST CHANGE DETECTION THROUGH VHR SATELLITE IMAGERY

2016 ◽  
Vol XLI-B8 ◽  
pp. 1213-1220
Author(s):  
Devrim Akca ◽  
Efstratios Stylianidis ◽  
Konstantinos Smagas ◽  
Martin Hofer ◽  
Daniela Poli ◽  
...  
Keyword(s):  
High Resolution ◽  
Change Detection ◽  
Satellite Imagery ◽  
Optical Sensors ◽  
Optical Data ◽  
Surface Matching ◽  
Surface Model ◽  
3D Surface ◽  
Optical Imagery ◽  
Spot 5

Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2D/3D information extraction. This includes: image radiometric pre-processing, image and ground point measurement, improvement of geometric sensor orientation, quasiepipolar image generation for stereo measurements, digital surface model (DSM) extraction by using a precise and robust image matching approach specially designed for VHR satellite imagery, generation of orthoimages, and 3D measurements in single images using mono-plotting and in stereo images as well as triplets. FORSAT supports most of the VHR optically imagery commonly used for civil applications: IKONOS, OrbView – 3, SPOT – 5 HRS, SPOT – 5 HRG, QuickBird, GeoEye-1, WorldView-1/2, Pléiades 1A/1B, SPOT 6/7, and sensors of similar type to be expected in the future. The second unit of FORSAT is dedicated to 3D surface comparison for change detection. It allows users to import digital elevation models (DEMs), align them using an advanced 3D surface matching approach and calculate the 3D differences and volume changes between epochs. To this end our 3D surface matching method LS3D is being used. FORSAT is a single source and flexible forest information solution with a very competitive price/quality ratio, allowing expert and non-expert remote sensing users to monitor forests in three and four dimensions from VHR optical imagery for many forest information needs. The capacity and benefits of FORSAT have been tested in six case studies located in Austria, Cyprus, Spain, Switzerland and Turkey, using optical data from different sensors and with the purpose to monitor forest with different geometric characteristics. The validation run on Cyprus dataset is reported and commented.

scholarly journals Estimation and monitoring of aboveground carbon stocks using spatial technology

2015 ◽  
Vol 111 (9/10) ◽  
Author(s):  
Adolph Nyamugama ◽  
Vincent Kakembo
Keyword(s):  
Regression Model ◽  
Satellite Imagery ◽  
Geographical Information Systems ◽  
Vegetation Index ◽  
Anthropogenic Activities ◽  
Temporal Changes ◽  
Geographical Information ◽  
Aboveground Carbon ◽  
Normalised Difference Vegetation Index ◽  
Spot 5

Monitoring temporal changes of aboveground carbon (AGC) stocks distribution in subtropical thicket is key to understanding the role of vegetation in carbon sequestration. The main objectives of this research paper were to model and quantify the temporal changes of AGC stocks between 1972 and 2010 in the Great Fish River Nature Reserve and its environs, Eastern Cape Province, South Africa. We used a method based on the integration of remote sensing and geographical information systems to estimate AGC stocks in a time series framework. A non-linear regression model was developed using Normalised Difference Vegetation Index values generated from SPOT 5 High Resolution Geometric satellite imagery of 2010 as an independent variable and AGC stock estimates from field plots as the dependent variable. The regression model was used to estimate AGC stocks from satellite imagery for 1972 (Landsat TM), 1982 (Landsat 4 TM), 1992 (Landsat 7 ETM), 2002 (Landsat ETM+) and 2010 (SPOT 5) satellite imagery. AGC stocks for the respective years were compared by means of change detection analysis at the subtropical thicket class level. The results showed a decline of AGC stocks in all the classes from 1972 to 2010. Degraded and transformed thicket classes had the highest AGC stock losses. The decline of AGC stocks was attributed to thicket transformation and degradation, which were attributed to anthropogenic activities.

scholarly journals Satellite Imagery Assists in the Assessment of Hail Damage for Salvage Harvest

1990 ◽  
Vol 66 (5) ◽  
pp. 463-468 ◽  
Author(s):  
M. D. Gillis ◽  
D. G. Leckie ◽  
R. D. Pick
Keyword(s):  
Satellite Imagery ◽  
Field Work ◽  
Landsat Thematic Mapper ◽  
Storm Damage ◽  
Severe Thunderstorm ◽  
Hail Damage ◽  
Colour Composite ◽  
Cooperative Project ◽  
Provincial Park ◽  
Area And Volume

On June 8, 1987 a severe thunderstorm caused extensive hail damage to portions of the forest within Algonquin Provincial Park, Ontario. The Algonquin Forestry Authority, charged with the responsibility for harvest operations within the Park, decided to salvage the damaged forest. A map of the damage was required to determine the area and volume to be harvested. A cooperative project between the Algonquin Forestry Authority and the Petawawa National Forestry Institute was established to map the damaged area by combining satellite imagery and existing ground information and to define the cut blocks using the satellite data as a guide for field work. A colour composite transparency of Landsat Thematic Mapper data was acquired and the damaged area mapped in just over two weeks. The satellite imagery in combination with ground work provided a simple, effective, and timely method for assessing hail storm damage for an operational salvage harvest.

Evaluating high resolution SPOT 5 satellite imagery to estimate crop yield

2009 ◽  
Vol 10 (4) ◽  
pp. 292-303 ◽  
Author(s):  
C. Yang ◽  
J. H. Everitt ◽  
J. M. Bradford
Keyword(s):  
High Resolution ◽  
Crop Yield ◽  
Satellite Imagery ◽  
Spot 5
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