Development of Automatic Techniques for Refugee Camps Monitoring using Very High Spatial Resolution (VHSR) Satellite Imagery

2006 ◽  
Author(s):  
G. Laneve ◽  
G. Santilli ◽  
I. Lingenfelder
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
High Spatial Resolution ◽  
Refugee Camps ◽  
Very High Spatial Resolution ◽  
Very High

Forest inventory stand height estimates from very high spatial resolution satellite imagery calibrated with lidar plots

2013 ◽  
Vol 34 (12) ◽  
pp. 4406-4424 ◽  
Author(s):  
Brice Mora ◽  
Michael A. Wulder ◽  
Geordie W. Hobart ◽  
Joanne C. White ◽  
Christopher W. Bater ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
Forest Inventory ◽  
High Spatial Resolution ◽  
Height Estimates ◽  
Very High Spatial Resolution ◽  
Stand Height ◽  
Very High

scholarly journals Investigation of Informal Settlement Indicators in a Densely Populated Area Using Very High Spatial Resolution Satellite Imagery

2021 ◽  
Vol 13 (9) ◽  
pp. 4735
Author(s):  
Naledzani Mudau ◽  
Paidamwoyo Mhangara
Keyword(s):  
Order Statistics ◽  
Spatial Resolution ◽  
Satellite Imagery ◽  
High Spatial Resolution ◽  
Informal Settlement ◽  
Informal Settlements ◽  
Spectral Indices ◽  
First Order ◽  
Very High Spatial Resolution ◽  
Very High

Automation of informal settlements detection using satellite imagery remains a challenging task in urban remote sensing. This is due to the fact that informal settlements vary in shape, size and spatial arrangement from one region to the other in some cases within a city. This paper investigated the methodology to detect informal settlements in a densely populated township by assessing informal settlement indicators observed from very high spatial resolution satellite imagery. We assessed twelve informal settlement indicators to determine the most effective indicators to distinguish between informal and informal classes. These indicators included the spectral indices first and second-order statistical measurements. In addition to the commonly used informal settlement indicators, we assessed the effectiveness of built-up area and iron cover. The GLCM textural measures performed poorly in separating informal and formal settlements compared to first-order statistics measurement and spectral indices. The built-up area index, coastal blue index and the first-order statistics mean measurements produced higher separability distance of informal and formal settlements. The iron index performed better in separating the two settlement types than the commonly used GLCM measure and NDVI. The proposed ruleset that uses the three features with the highest separability distance achieved producer and user accuracies of informal settlements of 95% and 82%, respectively. The results of this study will contribute towards developing methodologies to automatically detect informal settlements.

scholarly journals An Object-Based Approach for Mapping Tundra Ice-Wedge Polygon Troughs from Very High Spatial Resolution Optical Satellite Imagery

2021 ◽  
Vol 13 (4) ◽  
pp. 558
Author(s):  
Chandi Witharana ◽  
Md Abul Ehsan Bhuiyan ◽  
Anna K. Liljedahl ◽  
Mikhail Kanevskiy ◽  
Torre Jorgenson ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
High Spatial Resolution ◽  
Fine Scale ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Tussock Tundra ◽  
Very High Spatial Resolution ◽  
Ice Wedge ◽  
Very High

Very high spatial resolution commercial satellite imagery can inform observation, mapping, and documentation of micro-topographic transitions across large tundra regions. The bridging of fine-scale field studies with pan-Arctic system assessments has until now been constrained by a lack of overlap in spatial resolution and geographical coverage. This likely introduced biases in climate impacts on, and feedback from the Arctic region to the global climate system. The central objective of this exploratory study is to develop an object-based image analysis workflow to automatically extract ice-wedge polygon troughs from very high spatial resolution commercial satellite imagery. We employed a systematic experiment to understand the degree of interoperability of knowledge-based workflows across distinct tundra vegetation units—sedge tundra and tussock tundra—focusing on the same semantic class. In our multi-scale trough modelling workflow, we coupled mathematical morphological filtering with a segmentation process to enhance the quality of image object candidates and classification accuracies. Employment of the master ruleset on sedge tundra reported classification accuracies of correctness of 0.99, completeness of 0.87, and F1 score of 0.92. When the master ruleset was applied to tussock tundra without any adaptations, classification accuracies remained promising while reporting correctness of 0.87, completeness of 0.77, and an F1 score of 0.81. Overall, results suggest that the object-based image analysis-based trough modelling workflow exhibits substantial interoperability across the terrain while producing promising classification accuracies. From an Arctic earth science perspective, the mapped troughs combined with the ArcticDEM can allow hydrological assessments of lateral connectivity of the rapidly changing Arctic tundra landscape, and repeated mapping can allow us to track fine-scale changes across large regions and that has potentially major implications on larger riverine systems.

Kernel-based reclassification algorithm applied on very high spatial resolution satellite imagery of complex ecosystems

2004 ◽  
Author(s):  
Iphigenia Keramitsoglou ◽  
Charalambos Kontoes ◽  
Panagiotis Elias ◽  
Nicolaos Sifakis ◽  
Eleni Fitoka ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
High Spatial Resolution ◽  
Very High Spatial Resolution ◽  
Very High
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