Integrative Geophysical Studies at the Novaya Kurya-1 Cemetery in the Kulunda Steppe

2022 ◽  
Vol 49 (4) ◽  
pp. 69-79
Author(s):  
O. A. Pozdnyakova ◽  
E. V. Balkov ◽  
P. G. Dyadkov ◽  
Z. V. Marchenko ◽  
A. E. Grishin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Aerial Photography ◽  
Western Siberia ◽  
Magnetic Survey ◽  
Large Area ◽  
Aeromagnetic Survey ◽  
Digital Elevation ◽  
Structural Details ◽  
Kulunda Steppe ◽  
Remote Sensing Methods

We outline the results of prospection studies at the Novaya Kurya-1 cemetery in the south of Western Siberia, using remote sensing methods such as aerial photography, ground-based magnetometry, high-precision aeromagnetic survey, electromagnetic profi ling, and electrotomography. Original techniques were used to construct relative relief maps, and an inversion of data from ground-based magnetic survey at various altitudes was carried out. The fi rst technique reduces the effect of natural relief, and highlights anthropogenic altitudinal anomalies, making the analysis of digital elevation models more effi cient. The second technique is helpful for assessing the thickness and depth of anomalous magnetic bodies or horizons, not only providing planigraphic information but enabling us to evaluate two- and threedimensional geometric properties of the detected objects. As a result of the analyses, at least 14 kurgans were identifi ed at the cemetery, six of which lack salient outward features. Structural details suggest that most of them date to the Early Scythian time (800–400 BC). On the basis of the interpretation of the results of highly effi cient prospection analyses using the UAV platform, offering the possibility of surveying a large area (about 25 ha), the boundaries of the site were determined. Several features were detected. To identify these, further studies are needed.

scholarly journals A new glacier inventory on southern Baffin Island, Canada, from ASTER data: II. Data analysis, glacier change and applications

2009 ◽  
Vol 50 (53) ◽  
pp. 22-31 ◽  
Author(s):  
Frank Paul ◽  
Felix Svoboda
Keyword(s):  
Strong Dependence ◽  
Baffin Island ◽  
Automated Classification ◽  
Inventory Data ◽  
Large Area ◽  
Glacier Inventory ◽  
Ice Caps ◽  
Digital Elevation ◽  
Elevation Model ◽  
Remote Sensing Methods

AbstractDespite its large area covered by glaciers and ice caps, detailed glacier inventory data are not yet available for most parts of Baffin Island, Canada. Automated classification of satellite data could help to overcome the data gaps. Along-track stereo sensors allow the derivation of a digital elevation model (DEM) and glacier outlines from the same point in time, and are particularly useful for this task. While part I of this study describes the remote-sensing methods, in part II we present an analysis of the derived glacier inventory data for 662 glaciers and an application to glacier volume and volume-change calculations. Among other things, the analysis reveals a mean glacier elevation of 990 m, with a weak dependence on aspect and a close agreement of the arithmetic mean with the statistical mean elevation as derived from the DEM. A strong scatter of mean slope is observed for glaciers <1 km2, and the derived glacier thickness differs by a factor of two for glaciers of the same size. For the period from about 1920 to 2000 the relative area change is –12.5% (264 glaciers), with a strong dependence on glacier size. Mean mass loss as derived from volume changes is about –0.15 mw.e. a–1.

scholarly journals OPERATIONAL APPLICATION OF THE LANDSAT TIMESERIES TO ADDRESS LARGE AREA LANDCOVER UNDERSTANDING

2015 ◽  
Vol XL-3/W3 ◽  
pp. 571-575 ◽  
Author(s):  
P. Scarth ◽  
J. Armston ◽  
N. Flood ◽  
R. Denham ◽  
L. Collett ◽  
...  
Keyword(s):  
Remote Sensing ◽  
State Government ◽  
Governance Structure ◽  
Large Area ◽  
Operational Application ◽  
Eastern Australia ◽  
Recent Developments ◽  
National Programs ◽  
The University ◽  
Remote Sensing Methods

State Government agencies in northern and eastern Australia and the University of Queensland, Brisbane, have been collaborating through the Joint Remote Sensing Research Program (JRSRP). This has resulted in a significant acceleration in the development and successful operational application of remote sensing methods for the JRSRP members and the various state and national programs and policies which they support. The JRSRP provides an open and collaborative mechanism and governance structure to successfully bring together a unique combination of expertise in image processing, field data collection, and data integration approaches to deliver accurate, repeatable and robust methods for mapping and monitoring Australia’s unique ecosystems. Remote sensing provides spatially- and temporally-comprehensive information about land cover features at a range of scales and often for minimal cost compared to traditional mapping and monitoring approaches. This makes remote sensing a very useful operational mapping and monitoring tool for land managers, particularly in the vast rangelands of Australia. This paper outlines recent developments in remote sensing and modelling products that are being used operationally by JRSRP members to address large area landcover understanding.

Remote sensing methods in medium spatial resolution satellite data land cover classification of large areas

2002 ◽  
Vol 26 (2) ◽  
pp. 173-205 ◽  
Author(s):  
S. E. Franklin ◽  
M. A. Wulder
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Data Acquisition ◽  
Spatial Resolution ◽  
Accuracy Assessment ◽  
Land Cover Classification ◽  
Forest Monitoring ◽  
Large Area ◽  
Ancillary Data ◽  
Remote Sensing Methods

Numerous large-area, multiple image-based, multiple sensor land cover mapping programs exist or have been proposed, often within the context of national forest monitoring, mapping and modelling initiatives, worldwide. Common methodological steps have been identified that include data acquisition and preprocessing, map legend development, classification approach, stratification, incorporation of ancillary data and accuracy assessment. In general, procedures used in any large-area land cover classification must be robust and repeatable; because of data acquisition parameters, it is likely that compilation of the maps based on the classification will occur with original image acquisitions of different seasonality and perhaps acquired in different years and by different sensors. This situation poses some new challenges beyond those encountered in large-area single image classifications. The objective of this paper is to review and assess general medium spatial resolution satellite remote sensing land cover classification approaches with the goal of identifying the outstanding issues that must be overcome in order to implement a large-area, land cover classification protocol.

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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