The debris cover surface of Ponkar glacier: a laboratory for learning

2020 ◽  
Author(s):  
Adina E. Racoviteanu ◽  
Neil F. Glasser ◽  
Smriti Basnett ◽  
Rakesh Kayastha ◽  
Stephan Harrison
Keyword(s):  
Remote Sensing ◽  
Scientific Knowledge ◽  
Interdisciplinary Approach ◽  
Surface Features ◽  
Ice Melt ◽  
Supraglacial Lakes ◽  
High Asia ◽  
Glacier Ice ◽  
Building Activities ◽  
Remote Sensing Methods

<p>Understanding the evolution of debris-covered glaciers, including their evolution over time, the distribution of surface features such as exposed ice walls and supraglacial lakes, and their contributions to glacier ice melt and to glacier-related hazards such as Glacier Lake Outburst Flood (GLOF) events requires an interdisciplinary approach, with a combination of remote sensing methods and collaborative fieldwork.</p><p>Since 2017, the IGCP 672 /UNESCO project led has been focussing on the transfer of scientific knowledge on monitoring debris-covered glaciers to local partner institutions in high Asia through trainings, workshops and field collaborations. Our long-term goal is to disseminate methodologies developed under this project to local institutions in high Asia and to embed scientific knowledge into local communities. Here we report on recent capacity building activities held within the context of this new project involved local participants from universities in Nepal and Sikkim. The training included remote sensing/GIS modules, temperature measurements, sediment logging and drone surveys of the ablation zone, which will allow us to better quantify the surface features and their evolution.</p><p> </p>

GIS-Based Virtual Testbeds and Their Application to Forestry and City Simulation

2010 ◽  
Author(s):  
Ju¨rgen Roßmann ◽  
Michael Schluse ◽  
Martin Hoppen ◽  
Ralf Waspe
Keyword(s):  
Remote Sensing ◽  
Interdisciplinary Approach ◽  
Remote Sensing Data ◽  
Natural Environments ◽  
Data Sets ◽  
New Approach ◽  
New Class ◽  
Time Simulation ◽  
New Ideas ◽  
Remote Sensing Methods

In this paper we present a new interdisciplinary approach to geographic information systems. The integration of object-oriented data modeling, 3D real-time simulation, virtual reality techniques and remote sensing methods with new semantic world modeling techniques and well known geo information system (GIS) functionalities provides the basis for a new class of “Virtual Testbeds”. These testbeds build on a new approach which combines state-of-the-art GIS functionalities to deal with complex and large geographical data sets with the intuitive operability and the advanced simulation capabilities of latest robotic and automation simulation components. Besides the simulation algorithms, the testbeds take advantage of advanced modeling capabilities to (semi) automatic ally generate models of “natural” environments in e.g. forests or cities. Based on remote sensing data, not only geometric shapes are derived, but also an object’s “function” or “semantics”. The new ideas have already been applied to various applications of which the most successful will also be described in this paper.

Application of Remote Sensing in Agriculture

2014 ◽  
Vol 13 (1) ◽  
Author(s):  
Jan Piekarczyk
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Crop Production ◽  
Satellite Images ◽  
Crop Yields ◽  
Spatial Scales ◽  
Strong Relationship ◽  
Physical Parameters ◽  
Agricultural Crop ◽  
Remote Sensing Methods

AbstractWith increasing intensity of agricultural crop production increases the need to obtain information about environmental conditions in which this production takes place. Remote sensing methods, including satellite images, airborne photographs and ground-based spectral measurements can greatly simplify the monitoring of crop development and decision-making to optimize inputs on agricultural production and reduce its harmful effects on the environment. One of the earliest uses of remote sensing in agriculture is crop identification and their acreage estimation. Satellite data acquired for this purpose are necessary to ensure food security and the proper functioning of agricultural markets at national and global scales. Due to strong relationship between plant bio-physical parameters and the amount of electromagnetic radiation reflected (in certain ranges of the spectrum) from plants and then registered by sensors it is possible to predict crop yields. Other applications of remote sensing are intensively developed in the framework of so-called precision agriculture, in small spatial scales including individual fields. Data from ground-based measurements as well as from airborne or satellite images are used to develop yield and soil maps which can be used to determine the doses of irrigation and fertilization and to take decisions on the use of pesticides.

Application of remote sensing methods for assessment of anthropogenic transformation of rangelands

2000 ◽  
pp. 16-25
Author(s):  
E. I. Rachkovskaya ◽  
S. S. Temirbekov ◽  
R. E. Sadvokasov
Keyword(s):  
Remote Sensing ◽  
New Technology ◽  
Field Studies ◽  
Digital Data ◽  
Aerial Images ◽  
Expert Assessment ◽  
Automated Classification ◽  
Anthropogenic Transformation ◽  
Initial Processing ◽  
Remote Sensing Methods

Capabilities of the remote sensing methods for making maps of actual and potential vegetation, and assessment of the extent of anthropogenic transformation of rangelands are presented in the paper. Study area is a large intermountain depression, which is under intensive agricultural use. Color photographs have been made by Aircraft camera Wild Heerburg RC-30 and multispectral scanner Daedalus (AMS) digital aerial data (6 bands, 3.5m resolution) have been used for analysis of distribution and assessment of the state of vegetation. Digital data were processed using specialized program ENVI 3.0. Main stages of the development of cartographic models have been described: initial processing of the aerial images and their visualization, preliminary pre-field interpretation (classification) of the images on the basis of unsupervised automated classification, field studies (geobotanical records and GPS measurements at the sites chosen at previous stage). Post-field stage had the following sub-stages: final geometric correction of the digital images, elaboration of the classification system for the main mapping subdivisions, final supervised automated classification on the basis of expert assessment. By systematizing clusters of the obtained classified image the cartographic models of the study area have been made. Application of the new technology of remote sensing allowed making qualitative and quantitative assessment of modern state of rangelands.

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