scholarly journals Spectral properties of Antarctic and Alpine vegetation monitored by multispectral camera: Case studies from James Ross Island and Jeseníky Mts.

2020 ◽  
Vol 10 (2) ◽  
pp. 297-312
Author(s):  
Peter Váczi ◽  
Miloš Barták ◽  
Michaela Bednaříková ◽  
Filip Hrbáček ◽  
Josef Hájek
Keyword(s):  
Vegetation Cover ◽  
Remote Sensing Data ◽  
Field Research ◽  
Alpine Tundra ◽  
Vegetation Types ◽  
Nostoc Commune ◽  
James Ross Island ◽  
Bryum Pseudotriquetrum ◽  
Reflectance Indices ◽  
Multispectral Camera

In this study, we investigated the utility of spectral remote sensing data gathered by a multispectral camera for estimating of vegetation cover in Antarctic vegetation oasis and Arcto-Alpine tundra. The surveys exploiting unmanned aerial vehicles (UAV) and multispectral camera were done in an Antarctic vegetation oasis located at the Northern shore of James Ross Island (Antarctica), and arcto-alpine tundra located in the Jeseníky Mts. (NE Czech Republic, 1 420 m a.s.l.). For the two locations, false colour images of spectral indices (VARI, NGRDI, GLI, RGVI, ExG, NDVI, PRI) were taken and analysis of vegetation types and components of vegetation cover done. Additionally, field research was performed by handheld instruments measuring NDVI, PRI and of selected vegetation components: Bryum pseudotriquetrum, Nostoc commune colonies (Antarctica), lichens grown on flat stones and boulders (the Jeseníky Mts.). The results show UAV photo surveys and imaging of spectral reflectance indices can be used to monitor vegetation types forming Antarctic vegetation oases and arcto-alpine tundra.

The effect of upper cortex absence on spectral reflectance indices in Antarctic lichens during thallus dehydration

2018 ◽  
Vol 8 (1) ◽  
pp. 107-118 ◽  
Author(s):  
Alla Orekhova ◽  
Michaela Marečková ◽  
Jana Hazdrová ◽  
Miloš Barták
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Spectral Characteristics ◽  
Hydration Status ◽  
Nostoc Commune ◽  
Response Curves ◽  
Relative Water ◽  
James Ross Island ◽  
Species Specific ◽  
Reflectance Indices

In maritime Antarctica, lichens and mosses represent dominant autotrophs forming community structure of vegetation oases. In our study, we selected 4 most common lichen species (Xanthoria elegans, Rhizoplaca melanophthalma, Leptogium puberulum, Physconia muscigena) and monospecific colony of Nostoc commune typical for James Ross Island (Antarctica) for detailed physiological experiments. We investigated their spectral characteristics in response to hydration status of their thalli. In samples desiccating from fully wet (RWC, relative water content of 100%) to dry state (RWC = 0), photochemical reflectance index (PRI), and normalized difference vegetation index (NDVI) were evaluated for control thalli and those with removed upper cortex. In this way, the effect of presence/absence of the upper cortex on PRI, NDVI was studied. PRI showed either no change or species-specific an increase/decrease with dehydration. Removal of the upper cortex caused both PRI decrease (N. commune, P. muscigena) and increase (R. melanophthalma, L. puberulum). Removal of the upper cortex led to increase in NDVI in all species, typically within the RWC range of 20-100%. Species-specific differences of hydration-response curves of PRI and NDVI are discussed as well as the role of the absence of the upper cortex in the evaluation of spectral characteristics in desiccating lichens.

scholarly journals LANDSAT-BASED WOODY VEGETATION COVER MONITORING IN SOUTHERN AFRICAN SAVANNAHS

2016 ◽  
Vol XLI-B7 ◽  
pp. 563-567
Author(s):  
E. Symeonakis ◽  
K. Petroulaki ◽  
T. Higginbottom
Keyword(s):  
Vegetation Cover ◽  
Urban Areas ◽  
Agricultural Land ◽  
Remote Sensing Data ◽  
Earth Observation ◽  
Mitigation Measures ◽  
Management Tool ◽  
Woody Vegetation ◽  
Steady Increase ◽  
Vegetation Types

Mapping woody cover over large areas can only be effectively achieved using remote sensing data and techniques. The longest continuously operating Earth-observation program, the Landsat series, is now freely-available as an atmospherically corrected, cloud masked surface reflectance product. The availability and length of the Landsat archive is thus an unparalleled Earth-observation resource, particularly for long-term change detection and monitoring. Here, we map and monitor woody vegetation cover in the Northwest Province of South Africa, an area of more than 100,000&thinsp;km<sup>2</sup> covered by 11 Landsat scenes. We employ a multi-temporal approach with dry-season data from 7 epochs between 1990 to 2015. We use 0.5&thinsp;m-pixel colour aerial photography to collect >&thinsp;15,000 point samples for training and validating Random Forest classifications of (i) woody vegetation cover, (ii) other vegetation types (including grasses and agricultural land), and (iii) non-vegetated areas (i.e. urban areas and bare land). Overall accuracies for all years are around 80&thinsp;% and overall kappa between 0.45 and 0.66. Woody vegetation covers a quarter of the Province and is the most accurately mapped class (balanced accuracies between 0.74-0.84 for the 7 epochs). There is a steady increase in woody vegetation cover over the 25-year-long period of study in the expense of the other vegetation types. We identify potential woody vegetation encroachment 'hot-spots' where mitigation measures might be required and thus provide a management tool for the prioritisation of such measures in degraded and food-insecure areas.

scholarly journals LANDSAT-BASED WOODY VEGETATION COVER MONITORING IN SOUTHERN AFRICAN SAVANNAHS

2016 ◽  
Vol XLI-B7 ◽  
pp. 563-567 ◽  
Author(s):  
E. Symeonakis ◽  
K. Petroulaki ◽  
T. Higginbottom
Keyword(s):  
Vegetation Cover ◽  
Urban Areas ◽  
Agricultural Land ◽  
Remote Sensing Data ◽  
Earth Observation ◽  
Mitigation Measures ◽  
Management Tool ◽  
Woody Vegetation ◽  
Steady Increase ◽  
Vegetation Types

Mapping woody cover over large areas can only be effectively achieved using remote sensing data and techniques. The longest continuously operating Earth-observation program, the Landsat series, is now freely-available as an atmospherically corrected, cloud masked surface reflectance product. The availability and length of the Landsat archive is thus an unparalleled Earth-observation resource, particularly for long-term change detection and monitoring. Here, we map and monitor woody vegetation cover in the Northwest Province of South Africa, an area of more than 100,000&thinsp;km&lt;sup&gt;2&lt;/sup&gt; covered by 11 Landsat scenes. We employ a multi-temporal approach with dry-season data from 7 epochs between 1990 to 2015. We use 0.5&thinsp;m-pixel colour aerial photography to collect &gt;&thinsp;15,000 point samples for training and validating Random Forest classifications of (i) woody vegetation cover, (ii) other vegetation types (including grasses and agricultural land), and (iii) non-vegetated areas (i.e. urban areas and bare land). Overall accuracies for all years are around 80&thinsp;% and overall kappa between 0.45 and 0.66. Woody vegetation covers a quarter of the Province and is the most accurately mapped class (balanced accuracies between 0.74-0.84 for the 7 epochs). There is a steady increase in woody vegetation cover over the 25-year-long period of study in the expense of the other vegetation types. We identify potential woody vegetation encroachment 'hot-spots' where mitigation measures might be required and thus provide a management tool for the prioritisation of such measures in degraded and food-insecure areas.

STUDYING OF TERSKO-SULAKSKAYA LOWLAND VEGETATION UNDER THE RESULTS OF GROUND-BASED RESEARCH AND AUTOMATED INTERPRETATION

1970 ◽  
pp. 29-32
Author(s):  
M. I. Dzhalalova ◽  
A. B. Biarslanov ◽  
D. B. Asgerova
Keyword(s):  
Plant Communities ◽  
Satellite Imagery ◽  
Vegetation Cover ◽  
Anthropogenic Impacts ◽  
Species Abundance ◽  
Remote Sensing Data ◽  
Indigenous Communities ◽  
The State ◽  
Anthropogenic Factors ◽  
Internet Resource

The state of plant communities in areas located in the Tersko-Sulak lowland was studied by assessing phytocenotic indicators: the structure of vegetation cover, projective cover, species diversity, species abundance and elevated production, as well as automated decoding methods. There are almost no virgin soils and natural phytocenoses here; all of them have been transformed into agrocenoses (irrigated arable lands and hayfields, rice-trees and pastures). The long-term impact on pasture ecosystems of natural and anthropogenic factors leads to significant changes in the indigenous communities of this region. Phytocenoses are formed mainly by dry-steppe types of cereals with the participation of feather grass, forbs and ephemera, a semi-desert haloxerophytic shrub - Taurida wormwood. At the base of the grass stand is common coastal wormwood and Taurida wormwood - species resistant to anthropogenic influences. Anthropogenic impacts have led to a decrease in the number of species of feed-rich grain crops and a decrease in the overall productivity of pastures. Plant communities in all areas are littered with ruderal species. The seasonal dynamics of the land cover of the sites was estimated by the methods of automatic decoding of satellite images of the Landsat8 OLI series satellite for 2015, dated by the periods: spring - May 20, summer - July 23, autumn - October 20. Satellite imagery data obtained by Landsat satellite with a resolution in the multispectral image of 30 m per pixel, and in the panchromatic image - 10 m per pixel, which correspond to the requirements for satellite imagery to assess the dynamics of soil and vegetation cover. Lower resolution data, for example, NDVI MODIS, does not provide a reliable reflection of the state of soil and vegetation cover under arid conditions. In this regard, remote sensing data obtained from the Internet resource https://earthexplorer.usgs.gov/ was used.

New methodical approaches to mapping of geosystems (by the example of Baikalian Siberia’s geosystems)

2018 ◽  
Vol 937 (7) ◽  
pp. 23-34 ◽  
Author(s):  
I.N. Vladimirov
Keyword(s):  
Global Climate ◽  
Remote Sensing Data ◽  
Field Research ◽  
Scientific Basis ◽  
Nature Management ◽  
Climate Data ◽  
Structural Dynamic ◽  
Digital Elevation ◽  
North Asia ◽  
Elevation Model

The article considers a new approach to landscape mapping based on the synthesis of remote sensing data of high and medium spatial resolution, a digital elevation model, maps of various thematic contents, a set of global climate data, and materials of field research. The map of the Baikalian’s Siberia geosystems is based on the principles of the multistage regional-typological and structural-dynamic classification of geosystems proposed by Academician V.B. Sochava. The structure of the geosystems of the Baikalian Siberia is characterized by great complexity, both in the set of natural complexes and in the degree of their contrast. The regional classification range covers the geosystems inherent in different subcontinents of Asia and reflects their interpenetration, being a unique landscape-situational example of Siberian nature within North Asia. The map of the geosystems of the Baikalian Siberia reflects the main structural and dynamic diversity of geosystems in the region in the systems of their geographic and genetic spatial structures. These landscape cartographic studies fit into a single system of geographic forecasting and create a new fundamental scientific basis for developing recommendations for optimizing nature management in the Baikal region within the framework of implementing state environmental policy.

scholarly journals Rapid Evaluation and Validation Method of Above Ground Forest Biomass Estimation Using Optical Remote Sensing in Tundi Reserved Forest Area, India

2021 ◽  
Vol 10 (1) ◽  
pp. 29
Author(s):  
Praveen Kumar ◽  
Akhouri P. Krishna ◽  
Thorkild M. Rasmussen ◽  
Mahendra K. Pal
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Remote Sensing Data ◽  
Test Site ◽  
Forest Area ◽  
Relational Model ◽  
Biomass Estimation ◽  
Optical Remote Sensing ◽  
Ground Sample ◽  
Sensing Data

Optical remote sensing data are freely available on a global scale. However, the satellite image processing and analysis for quick, accurate, and precise forest above ground biomass (AGB) evaluation are still challenging and difficult. This paper is aimed to develop a novel method for precise, accurate, and quick evaluation of the forest AGB from optical remote sensing data. Typically, the ground forest AGB was calculated using an empirical model from ground data for biophysical parameters such as tree density, height, and diameter at breast height (DBH) collected from the field at different elevation strata. The ground fraction of vegetation cover (FVC) in each ground sample location was calculated. Then, the fraction of vegetation cover (FVC) from optical remote sensing imagery was calculated. In the first stage of method implementation, the relation model between the ground FVC and ground forest AGB was developed. In the second stage, the relational model was established between image FVC and ground FVC. Finally, both models were fused to derive the relational model between image FVC and forest AGB. The validation of the developed method was demonstrated utilizing Sentinel-2 imagery as test data and the Tundi reserved forest area located in the Dhanbad district of Jharkhand state in eastern India was used as the test site. The result from the developed model was ground validated and also compared with the result from a previously developed crown projected area (CPA)-based forest AGB estimation approach. The results from the developed approach demonstrated superior capabilities in precision compared to the CPA-based method. The average forest AGB estimation of the test site obtained by this approach revealed 463 tons per hectare, which matches the previous estimate from this test site.

scholarly journals Consideration of NDVI thematic changes in density analysis and floristic composition of Wadi Yalamlam, Saudi Arabia

2018 ◽  
Vol 7 (4) ◽  
pp. 297-306 ◽  
Author(s):  
Amal Y. Aldhebiani ◽  
Mohamed Elhag ◽  
Ahmad K. Hegazy ◽  
Hanaa K. Galal ◽  
Norah S. Mufareh
Keyword(s):  
Saudi Arabia ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing Data ◽  
Floristic Composition ◽  
Water Source ◽  
Shannon Index ◽  
Landsat 8 ◽  
Main Stream

Abstract. Wadi Yalamlam is known as one of the significant wadis in the west of Saudi Arabia. It is a very important water source for the western region of the country. Thus, it supplies the holy places in Mecca and the surrounding areas with drinking water. The floristic composition of Wadi Yalamlam has not been comprehensively studied. For that reason, this work aimed to assess the wadi vegetation cover, life-form presence, chorotype, diversity, and community structure using temporal remote sensing data. Temporal datasets spanning 4 years were acquired from the Landsat 8 sensor in 2013 as an early acquisition and in 2017 as a late acquisition to estimate normalized difference vegetation index (NDVI) changes. The wadi was divided into seven stands. Stands 7, 1, and 3 were the richest with the highest Shannon index values of 2.98, 2.69, and 2.64, respectively. On the other hand, stand 6 has the least plant biodiversity with a Shannon index of 1.8. The study also revealed the presence of 48 different plant species belonging to 24 families. Fabaceae (17 %) and Poaceae (13 %) were the main families that form most of the vegetation in the study area, while many families were represented by only 2 % of the vegetation of the wadi. NDVI analysis showed that the wadi suffers from various types of degradation of the vegetation cover along with the wadi main stream.

Analysis of agronomic drought over North Africa using remote sensing satellite data

2021 ◽  
Author(s):  
Mehrez Zribi ◽  
Simon Nativel ◽  
Michel Le Page
Keyword(s):  
Remote Sensing ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
North Africa ◽  
Vegetation Cover ◽  
Remote Sensing Data ◽  
Study Region ◽  
Semi Arid Region ◽  
Anomaly Index

&lt;p&gt;This paper aims to analyze the agronomic drought in a highly anthropogenic &amp;#160;semi-arid region, North Africa. In the context of the Mediterranean climate, characterized by frequent droughts, North Africa is particularly affected. Indeed, in addition to this climatic aspect, it is one of the areas most affected by water scarcity in the world. Thus, understanding and describing agronomic drought is essential. The proposed study is based on remote sensing data from TERRA-MODIS and ASCAT satellite, describing the dynamics of vegetation cover and soil water content through NDVI and SWI indices. Two indices are analyzed, the Vegetation Anomaly Index (VAI) and the Moisture Anomaly Index (MAI). The dynamics of the VAI is analyzed for different types of regions (agircultural, forest areas). The contribution of vegetation cover is combined with the effect of soil water content through a new drought index combining the VAI and MAI. A discussion of this combination is proposed on different study areas in the study region. It illustrates the complementarity of these two informations in analysis of agronomic drought.&lt;/p&gt;

scholarly journals The Tale of a Disappearing Lagoon: A Habitat Mapping and Ecological Assessment of Fosu Lagoon, Ghana

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Bernard Essel ◽  
Justice Kwame Gyesi ◽  
Richmond Kofi Addo ◽  
Wisdom Galley ◽  
Gideon MacCarthy
Keyword(s):  
Vegetation Cover ◽  
Current Trend ◽  
Ecological Assessment ◽  
Remote Sensing And Gis ◽  
Vegetation Types ◽  
Marsh Vegetation ◽  
Gis Technique ◽  
If Current ◽  
Gradual Disappearance ◽  
Very High

Coastal regions of Ghana are primarily engaged in sea and lagoon fishing. Like many lagoons in Ghana, Fosu lagoon is a major source of livelihood for its surrounding communities. However, the lagoon and its associated marsh vegetation is under serious threat from human-induced interference. Due to this, the lagoon is considered as one of the most polluted lagoons in Ghana. Also, studies reveal that a major conservation challenge is the lack of inventory for the lagoon’s associated vegetation. Hence, the research was to map and assess the lagoon’s habitat and identify threats to the lagoon. In achieving the research objectives, remote sensing and GIS technique were used to effectively map the lagoon and the catchment area. The result indicated that the Fosu lagoon is characterized by a massive decline in lagoon size and the vegetation cover. Thus, the standing water has declined by 50.2 acres from 1970 to 2017 to physical development and weeds. Also, it was evident in the result that the lagoon’s vegetation is now fragmented into six various vegetation types and the weeds in the lagoon make approximately one-third of the lagoon’s vegetation cover. Also, adding to the threat of the lagoon were high levels of plastic waste and metal pollution. Hence, if current trend continues, the possibility of further degradation is very high. The main impact of this research was to provide evidence to the gradual disappearance of the Fosu lagoon.

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