Specific spectral bands for different land cover contexts to improve the efficiency of remote sensing archaeological prospection: The Arpi case study

2009 ◽  
Vol 10 ◽  
pp. e41-e48 ◽  
Author(s):  
Cristiana Bassani ◽  
Rosa Maria Cavalli ◽  
Roberto Goffredo ◽  
Angelo Palombo ◽  
Simone Pascucci ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Archaeological Prospection ◽  
Spectral Bands

scholarly journals Applications of Satellite Remote Sensing for Archaeological Survey: A Case Study from the Sinis Archaeological Project, Sardinia

2020 ◽  
Vol 8 (2) ◽  
pp. 192-205
Author(s):  
Daniel Plekhov ◽  
Linda R. Gosner ◽  
Alexander J. Smith ◽  
Jessica Nowlin
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Daily Basis ◽  
Archaeological Survey ◽  
Short Term ◽  
Spectral Bands ◽  
Archaeological Project

ABSTRACTSatellite imagery has long been recognized as well suited for the regional and ecological questions of many archaeological surveys. One underexplored aspect of such data is their temporal resolution. It is now possible for areas to be imaged on an almost daily basis, and this resolution offers new opportunities for studying landscapes through remote sensing in parallel with ground-based survey. This article explores the applications of these data for visibility assessment and land-cover change detection in the context of the Sinis Archaeological Project, a regional archaeological survey of west-central Sardinia. We employ imagery provided by Planet, which has a spatial resolution of 3 m, in four spectral bands, and is collected daily. Using Normalized Difference Vegetation Index (NDVI) values calculated for each survey unit, we find that there is a relationship between NDVI values and field-reported visibility in general, though the strength of this correlation differs according to land-cover classes. We also find the data to be effective at tracking short-term changes in field conditions that allow us to differentiate fields of similar land cover and visibility. We consider limitations and potentials of these data and encourage further experimentation and development.

scholarly journals Applications of Satellite Remote Sensing for Archaeological Survey: A Case Study from the Sinis Archaeological Project, Sardinia

2020 ◽  
Author(s):  
Daniel Plekhov ◽  
Linda R. Gosner ◽  
Alexander J. Smith ◽  
Jessica Nowlin
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Daily Basis ◽  
Archaeological Survey ◽  
Short Term ◽  
Spectral Bands ◽  
Archaeological Project

Satellite imagery has long been recognized as well suited for the regional and ecological questions of many archaeological surveys. One underexplored aspect of such data is their temporal resolution. It is now possible for areas to be imaged on an almost daily basis, and this resolution offers new opportunities for studying landscapes through remote sensing in parallel with ground-based survey. This article explores the applications of these data for visibility assessment and land-cover change detection in the context of the Sinis Archaeological Project, a regional archaeological survey of west-central Sardinia. We employ imagery provided by Planet, which has a spatial resolution of 3 m, in four spectral bands, and is collected daily. Using Normalized Difference Vegetation Index (NDVI) values calculated for each survey unit, we find that there is a relationship between NDVI values and field-reported visibility in general, though the strength of this correlation differs according to land-cover classes. We also find the data to be effective at tracking short-term changes in field conditions that allow us to differentiate fields of similar land cover and visibility. We consider limitations and potentials of these data and encourage further experimentation and development.

Integration of Satellite Remote Sensing Techniques and Landscape Metrics to Characterize Land Cover Change and Dynamics

2013 ◽  
pp. 228-244
Author(s):  
Carmelo Riccardo Fichera ◽  
Giuseppe Modica ◽  
Maurizio Pollino
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Landscape Metrics ◽  
Landsat Images ◽  
Aerial Photos ◽  
Multi Temporal ◽  
Urban Rural ◽  
Remote Sensing Techniques

One of the most relevant applications of Remote Sensing (RS) techniques is related to the analysis and the characterization of Land Cover (LC) and its change, very useful to efficiently undertake land planning and management policies. Here, a case study is described, conducted in the area of Avellino (Southern Italy) by means of RS in combination with GIS and landscape metrics. A multi-temporal dataset of RS imagery has been used: aerial photos (1954, 1974, 1990), Landsat images (MSS 1975, TM 1985 and 1993, ETM+ 2004), and digital orthophotos (1994 and 2006). To characterize the dynamics of changes during a fifty year period (1954-2004), the approach has integrated temporal trend analysis and landscape metrics, focusing on the urban-rural gradient. Aerial photos and satellite images have been classified to obtain maps of LC changes, for fixed intervals: 1954-1985 and 1985-2004. LC pattern and its change are linked to both natural and social processes, whose driving role has been clearly demonstrated in the case analysed. In fact, after the disastrous Irpinia earthquake (1980), the local specific zoning laws and urban plans have significantly addressed landscape changes.

Remote sensing of land-cover change and landscape context of the National Parks: A case study of the Northeast Temperate Network

2009 ◽  
Vol 113 (7) ◽  
pp. 1453-1461 ◽  
Author(s):  
Yeqiao Wang ◽  
Brian R. Mitchell ◽  
Jarunee Nugranad-Marzilli ◽  
Gregory Bonynge ◽  
Yuyu Zhou ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Land Cover Change ◽  
National Parks ◽  
Landscape Context

Monitoring and assessment of seasonal land cover changes using remote sensing: a 30-year (1987–2016) case study of Hamoun Wetland, Iran

2018 ◽  
Vol 190 (6) ◽  
Author(s):  
Rasoul Kharazmi ◽  
Ali Tavili ◽  
Mohammad Reza Rahdari ◽  
Lyudmila Chaban ◽  
Evgeny Panidi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Land Cover Changes

scholarly journals ANALYSIS OF SOIL DEGRADATION AND DESERTIFICATION IN SOUTHERN BALKASH DESERT BASED ON GIS

REPORTS ◽  
2020 ◽  
Vol 2 (330) ◽  
pp. 41-48
Author(s):  
A.G. Gabdykadyr ◽  
G.T. Issanova ◽  
Y.Kh. Kakimzhanov ◽  
Long Ma
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
River Flow ◽  
Remote Sensing Data ◽  
Geological Structure ◽  
Anthropogenic Factors ◽  
Economic Activities ◽  
Spectral Bands ◽  
Indirect Sign ◽  
Tasseled Cap Transformation

Desertification and degradation provide a clear picture of global environmental and socio-economic issues. Most of Kazakhstan is located in a desert region, including the suburbs of South Balkhash. The reason is that desertification of the region has a strong influence on natural and anthropogenic factors. To consider the geomorphological state of the region and the problem of desertification of the territory, it is necessary to determine the importance of the process of relief of geological structure and relief of tectonics. In recent years, the environmental situation in Balkhash has deteriorated sharply not only as a result of river flow regulation, but also as a result of non-commercial economic activities. Therefore, it is very important to assess the situation of desertification and degradation in the Balkhash region. Desert vegetation has been identified, since information in the spectral range is often insufficient to describe the state of plants, plant indices often develop by combining two or more spectral bands. Land cover index is the percentage of vegetation over a given surface area. Remote sensing information was used to detect the entire land cover. Remote sensing with time and space limitations is widely used to classify vegetation cover. In this work, the proportion of vegetation was estimated by NDVI. The proportion of land cover is based on the relationship between NDVI (NDVIS) and NDVI (NDVIV) in the soil. Using the NDVI index, land cover zones were determined based on satellite images of 2006 and Landsat-5 from 2011. TCT (Tasseled Cap Transformation) coefficients are used in the widest range of problems solved using Earth remote sensing data: from recognition of the coastline of water bodies to determination of forest disturbances. Stressful vegetation may be an indirect sign of the presence of salt in soils. Saline soils are usually characterized by poorly planted areas. A normalized differential salinity index (NDSI) was also determined.

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