scholarly journals Identifying and mapping very small (<0.5 km2) mountain glaciers on coarse to high-resolution imagery

2019 ◽  
Vol 65 (254) ◽  
pp. 873-888 ◽  
Author(s):  
J. R. Leigh ◽  
C. R. Stokes ◽  
R. J. Carr ◽  
I. S. Evans ◽  
L. M. Andreassen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Minimum Size ◽  
Minimum Threshold ◽  
Mountain Glaciers ◽  
Seasonal Snow ◽  
High Resolution Imagery ◽  
Size Threshold ◽  
Seasonal Snow Cover ◽  
Consistent Approach

AbstractSmall mountain glaciers are an important part of the cryosphere and tend to respond rapidly to climate warming. Historically, mapping very small glaciers (generally considered to be <0.5 km2) using satellite imagery has often been subjective due to the difficulty in differentiating them from perennial snowpatches. For this reason, most scientists implement minimum size-thresholds (typically 0.01–0.05 km2). Here, we compare the ability of different remote-sensing approaches to identify and map very small glaciers on imagery of varying spatial resolutions (30–0.25 m) and investigate how operator subjectivity influences the results. Based on this analysis, we support the use of a minimum size-threshold of 0.01 km2 for imagery with coarse to medium spatial resolution (30–10 m). However, when mapping on high-resolution imagery (<1 m) with minimal seasonal snow cover, glaciers <0.05 km2 and even <0.01 km2 are readily identifiable and using a minimum threshold may be inappropriate. For these cases, we develop a set of criteria to enable the identification of very small glaciers and classify them as certain, probable or possible. This should facilitate a more consistent approach to identifying and mapping very small glaciers on high-resolution imagery, helping to produce more comprehensive and accurate glacier inventories.

Identifying and mapping very small mountain glaciers on coarse to high-resolution imagery

2020 ◽  
Author(s):  
Joshua Leigh ◽  
Chris Stokes ◽  
Rachel Carr ◽  
Ian Evans ◽  
Liss Andreassen ◽  
...  
Keyword(s):  
High Resolution ◽  
Surface Structures ◽  
Minimum Size ◽  
Minimum Threshold ◽  
Mountain Glaciers ◽  
Seasonal Snow ◽  
Ice Surface ◽  
High Resolution Imagery ◽  
Glacial Landforms ◽  
Seasonal Snow Cover

&lt;p&gt;Small mountain glaciers are an important part of the cryosphere and tend to respond rapidly to climate warming. Historically, mapping very small glaciers (generally considered to be &lt;0.5 km&lt;sup&gt;2&lt;/sup&gt;) using satellite imagery has often been subjective due to the difficulty in differentiating them from perennial snowpatches. For this reason, most scientists implement minimum size-thresholds (typically 0.01&amp;#8211;0.05 km&lt;sup&gt;2&lt;/sup&gt;). However, when mapping on high-resolution imagery (&lt;1 m) with minimal seasonal snow cover, glaciers &lt;0.05 km&lt;sup&gt;2 &lt;/sup&gt;and even &lt;0.01 km&lt;sup&gt;2 &lt;/sup&gt;are readily identifiable and using a minimum threshold may be inappropriate. For these cases, we have developed a set of criteria to enable the identification of very small glaciers and classify them as &lt;em&gt;certain&lt;/em&gt;, &lt;em&gt;probable&lt;/em&gt;, or &lt;em&gt;possible&lt;/em&gt;. Our identification criteria are based on detailed ice surface structures (e.g. evidence of flow banding and crevasses) and diagnostic glacial landforms (e.g. moraines). Implementation of this scoring system should facilitate a more consistent and objective approach to identifying and mapping very small glaciers on high-resolution imagery, helping to produce more comprehensive and accurate glacier inventories.&lt;/p&gt;

scholarly journals Multi-Scene Building Height Estimation Method Based on Shadow in High Resolution Imagery

2021 ◽  
Vol 13 (15) ◽  
pp. 2862
Author(s):  
Yakun Xie ◽  
Dejun Feng ◽  
Sifan Xiong ◽  
Jun Zhu ◽  
Yangge Liu
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Estimation Method ◽  
Absolute Error ◽  
Large Error ◽  
Estimation Methods ◽  
Height Estimation ◽  
Building Height ◽  
Remote Sensing Imagery ◽  
High Resolution Imagery

Accurately building height estimation from remote sensing imagery is an important and challenging task. However, the existing shadow-based building height estimation methods have large errors due to the complex environment in remote sensing imagery. In this paper, we propose a multi-scene building height estimation method based on shadow in high resolution imagery. First, the shadow of building is classified and described by analyzing the features of building shadow in remote sensing imagery. Second, a variety of shadow-based building height estimation models is established in different scenes. In addition, a method of shadow regularization extraction is proposed, which can solve the problem of mutual adhesion shadows in dense building areas effectively. Finally, we propose a method for shadow length calculation combines with the fish net and the pauta criterion, which means that the large error caused by the complex shape of building shadow can be avoided. Multi-scene areas are selected for experimental analysis to prove the validity of our method. The experiment results show that the accuracy rate is as high as 96% within 2 m of absolute error of our method. In addition, we compared our proposed approach with the existing methods, and the results show that the absolute error of our method are reduced by 1.24 m-3.76 m, which can achieve high-precision estimation of building height.

Use of Remotely Sensed Imagery in Cyber Warfare and Cyber Counterterrorism

2011 ◽  
pp. 298-305
Author(s):  
Gang Gong ◽  
Mark R. Leipnik
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Remotely Sensed ◽  
Aerial Photographs ◽  
The Internet ◽  
Cyber Warfare ◽  
Future Trends ◽  
Remotely Sensed Imagery ◽  
General Terms ◽  
High Resolution Imagery

Remote sensing refers to the acquisition of information at a distance. More specifically, it has come to mean using aerial photographs or sensors on satellites to gather data about features on the surface of the earth. In this article, remote sensing and related concepts are defined and the methods used in gathering and processing remotely sensed imagery are discussed. The evolution of remote sensing, generic applications and major sources of remotely sensed imagery and programs used in processing and analyzing remotely sensed imagery are presented. Then the application of remote sensing in warfare and counterterrorism is discussed in general terms with a number of specific examples of successes and failures in this particular area. Next, the potential for misuse of the increasing amount of high resolution imagery available over the Internet is discussed along with prudent countermeasures to potential abuses of this data. Finally, future trends with respect to this rapidly evolving technology are included.

scholarly journals POTENSI PEMANFAATAN DRONE UNTUK PENYEDIAAN DATA WILAYAH PESISIR

OSEANA ◽  
2018 ◽  
Vol 43 (1) ◽  
pp. 44-52
Author(s):  
Bayu Prayudha
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Coastal Area ◽  
Service Providers ◽  
Remote Sensing Data ◽  
Unmanned Aircraft ◽  
High Resolution Imagery ◽  
Potential Use ◽  
Vast Area ◽  
Imagery Data

POTENTIAL USE OF DRONE FOR PROVIDING DATA ON COASTAL AREA. The accurate data and information are needed for the decision maker to manage coastal area. However, the data and information of the coastal area are still lack because Indonesia has vast area and some of the locations are difficult to reach. Remote sensing is a technology that can be utilized to answer those needs. Some of the remote sensing data, especially satellite imagery can be freely acquired from various service providers using online media. Nevertheless, high resolution imagery data is still not available freely because it takes high cost and not always available at any time. One of the potential vehicle to acquire high resolution imagery data of coastal area is Unmanned Aircraft Vehicle (UAV) or widely known as drone.

scholarly journals Identification of a Threshold Minimum Area for Reflectance Retrieval from Thermokarst Lakes and Ponds Using Full-Pixel Data from Sentinel-2

2019 ◽  
Vol 11 (6) ◽  
pp. 657 ◽  
Author(s):  
Pedro Freitas ◽  
Gonçalo Vieira ◽  
João Canário ◽  
Diogo Folhas ◽  
Warwick Vincent
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Lake Area ◽  
Small Lakes ◽  
Thermokarst Lakes ◽  
High Resolution Imagery ◽  
Complementary Approach ◽  
Boundary Definition ◽  
Ground Truthing ◽  
Sentinel 2

Thermokarst waterbodies caused by permafrost thawing and degradation are ubiquitous in many subarctic and Arctic regions. They are globally important components of the biogeochemical carbon cycle and have potential feedback effects on climate. These northern waters are mostly small lakes and ponds, and although they may be mapped using very high-resolution satellites or aerial photography, these approaches are generally not suitable for monitoring purposes, due to the cost and limited availability of such images. In this study we evaluated the potential use of widely available high-resolution imagery from Sentinel-2 (S2) for the characterization of the spectral reflectance of thermokarst lakes and ponds. Specifically, we aimed to define the minimum lake area that could be reliably imaged, and to identify challenges and solutions for remote sensing of such waters in the future. The study was conducted in subarctic Canada, in the vicinity of Whapmagoostui-Kuujjuarapik (Nunavik, Québec), an area in the sporadic permafrost zone with numerous thermokarst waterbodies that vary greatly in size. Ground truthing lake reflectance data were collected using an Unmanned Aerial System (UAS) fitted with a multispectral camera that collected images at 13 cm resolution. The results were compared with reflectance from Sentinel-2 images, and the effect of lake area on the reflectance response was assessed. Our results show that Sentinel-2 imagery was suitable for waterbodies larger than 350 m2 once their boundaries were defined, which in the two test sites would allow monitoring from 11% to 30% of the waterbodies and 73% to 85% of the total lake area. Challenges for remote sensing of small lakes include the confounding effects of water reflection (both direct radiation and diffuse), wind and shadow. Given the small threshold area and frequent revisit time, Sentinel-2 provides a valuable approach towards the continuous monitoring of waterbodies, including ponds and small lakes such as those found in thermokarst landscapes. UASs provide a complementary approach for ground truthing and boundary definition.

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