scholarly journals The utility of Sentinel-2 Vegetation Indices (VIs) and Sentinel-1 Synthetic Aperture Radar (SAR) for invasive alien species detection and mapping

2019 ◽  
Vol 35 ◽  
pp. 41-61 ◽  
Author(s):  
Perushan Rajah ◽  
John Odindi ◽  
Onisimo Mutanga ◽  
Zolo Kiala
Keyword(s):  
Remote Sensing ◽  
Alien Species ◽  
Invasive Alien Species ◽  
Vegetation Indices ◽  
Cost Effective ◽  
Synthetic Aperture ◽  
Land Use Land Cover ◽  
Alien Plant ◽  
New Generation ◽  
Sentinel 2

The threat of invasive alien plant species is progressively becoming a serious global concern. Alien plant invasions adversely affect both ecological services and socio-economic systems. Hence, accurate detection and mapping of invasive alien species is valuable in mitigating adverse ecological and socio-economic effects. Recent advances in active and passive remote sensing technology have created new and cost-effective opportunities for the application of remote sensing to invasive species mapping. In this study, new generation Sentinel-2 (S2) optical imagery was compared to S2 derived Vegetation Indices (VIs) and S2 VIs fused with Sentinel-1 (S1) Synthetic Aperture Radar (SAR) imagery for detecting and mapping the American Bramble (Rubuscuneifolius). Fusion of S2 VIs and S1SAR imagery was conducted at pixel level and multi-class Support Vector Machine (SVM) image classification was used to determine the dominant land use land cover classes. Results indicated that S2 derived VIs were the most accurate (80%) in detecting and mapping Bramble, while fused S2 VIs and S1SAR were the least accurate (54%). Findings from this study suggest that the application of S2 VIs is more suitable for Bramble detection and mapping than the fused S2 VIs and S1SAR. The superior performance of S2 VIs highlights the value of the new generation S2 VIs for invasive alien species detection and mapping. Furthermore, this study recommends the use of freely available new generation satellite imagery for cost effective and timeous mapping of Bramble from surrounding native vegetation and other land use land cover types.

scholarly journals Aliens in the Aegean – a sea under siege (ALAS)

2020 ◽  
Vol 6 ◽  
Author(s):  
Stelios Katsanevakis ◽  
Konstantinos Tsirintanis ◽  
Maria Sini ◽  
Vasilis Gerovasileiou ◽  
Nikoletta Koukourouvli
Keyword(s):  
Remote Sensing ◽  
Invasive Species ◽  
High Resolution ◽  
Alien Species ◽  
Invasive Alien Species ◽  
Aegean Sea ◽  
Ecological Impacts ◽  
Cumulative Impacts ◽  
Cumulative Impact ◽  
Marine Habitats

ALAS aims to fill knowledge gaps on the impacts of marine alien species in the Aegean Sea, and support marine managers and policy makers in prioritizing mitigation actions. The project will focus on under-studied alien-native interactions, priority and vulnerable habitats (such as shallow forests of canopy algae and underwater caves), and apply a multitude of approaches. It will apply a standardized, quantitative method for mapping Cumulative IMpacts of invasive Alien species on marine ecosystems (CIMPAL), according to which cumulative impact scores are estimated on the basis of the distributions of invasive species and ecosystems, and both the reported magnitude of ecological impacts and the strength of such evidence. Towards that direction, ALAS will improve our knowledge base and compile the needed information to estimate CIMPAL by (1) conducting a series of field experiments and surveys to investigate the impacts of selected invasive alien species on marine habitats, (2) producing high-resolution habitat maps in the coastal zone, refining the results of previous research efforts through fieldwork, remote sensing and satellite imaging, (3) producing species distribution models for all invasive species, based on extensive underwater surveys for the collection of new data and integrating all existing information. ALAS will incorporate skills and analyses in novel ways and provide high-resolution results at a large scale; couple classic and novel tools and follow a trans-disciplinary approach, combining knowledge from the fields of invasion biology, conservation biology, biogeography, fisheries science, marine ecology, remote sensing, statistical modelling; conduct for the first time in the Aegean Sea a comprehensive, high-resolution analysis of cumulative impacts of invasive alien species; and report results in formats appropriate for decision-makers and society, thus transferring research-based knowledge to inform and influence policy decisions.

Assessment of the State of the Territories of Closed Waste Disposal Facilities by Vegetation Indices

2021 ◽  
Vol 25 (9) ◽  
pp. 30-37
Author(s):  
N.N. Sliusar ◽  
A.P. Belousova ◽  
G.M. Batrakova ◽  
R.D. Garifzyanov ◽  
M. Huber-Humer ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Waste Disposal ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Cost Effective ◽  
Google Earth ◽  
The State ◽  
Landsat 8 ◽  
The Earth

The possibilities of using remote sensing of the Earth data to assess the formation of phytocenoses at reclaimed dumps and landfills are presented. The objects of study are landfills and dumps in the Perm Territory, which differed from each other in the types and timing of reclamation work. The state of the vegetation cover on the reclaimed and self-overgrowing objects was compared with the reference plots with naturally formed herbage of zonal meadow vegetation. The process of reclamation of the territory of closed landfills was assessed by the presence and homogeneity of the vegetation layer and by the values of the vegetation index NDVI. To identify the dynamics of changes in the vegetation cover, we used multi-temporal satellite images from the open resources of Google Earth and images in the visible and infrared ranges of the Landsat-5/TM and Landsat-8/OLI satellites. It is shown that the data of remote sensing of the Earth, in particular the analysis of vegetation indices, can be used to assess the dynamics of overgrowing of territories of reclaimed waste disposal facilities, as well as an additional and cost-effective method for monitoring the restoration of previously disturbed territories.

scholarly journals Status and impacts of invasive alien plant species in Parsa National Park, central Nepal

2020 ◽  
Vol 30 (1) ◽  
pp. 21-31 ◽  
Author(s):  
R. Chaudhary ◽  
B. B. Shrestha ◽  
H. Thapa ◽  
M. Siwakoti
Keyword(s):  
Alien Species ◽  
Plant Species ◽  
National Parks ◽  
National Park ◽  
Invasive Alien Species ◽  
Plant Invasions ◽  
Tree Regeneration ◽  
Alien Plant Species ◽  
Alien Plant ◽  
Invasive Alien Plant

Extent of plant invasions has been expected to be low in protected areas such as national parks due to low anthropogenic activities and high wilderness. However, recent researches across the world have revealed that plant invasions can be severe in the national parks with negative impacts on the protected species and ecosystems. Unfortunately, the status of plant invasions in the national parks of Nepal is mostly unknown. In this study, we sampled at seven locations inside the Parsa National Park (PNP) to document diversity and abundance of invasive alien plant species (IAPS) and their impacts on tree regeneration. Altogether, 130 quadrats of 10 m × 10 m were sampled. We recorded 14 IAPS in the PNP. Three of the IAPS (Chromolana odorata, Lantana camara and Mikania micrantha) were among the 100 of the world’s worst invasive alien species. C. odorata was found to be the most frequent IAPS with the highest cover. The frequency and cover of the IAPS were higher at the sites close to the settlements than at the sites away from the settlements. The species richness of the IAPS was also higher at the sites closer to the settlements than away. The sapling density of the tree species was found to have declined with the increasing cover of the IAPS suggesting that the IAPS had negatively affected tree regeneration. Our data revealed that the PNP has already witnessed massive plant invasions with widespread occurrence of three of the world’s worst invasive species. Therefore, it is high time to integrate management of invasive alien species in the management plan of the park.

scholarly journals Früherkennung von Buchdruckerbefall dank Fern erkundung: Was ist schon möglich?

2020 ◽  
Vol 171 (1) ◽  
pp. 36-43 ◽  
Author(s):  
Luzia Götz ◽  
Achilleas Psomas ◽  
Harald Bugmann
Keyword(s):  
Remote Sensing ◽  
Early Detection ◽  
Bark Beetle ◽  
Vegetation Indices ◽  
Remote Sensing Data ◽  
Cost Effective ◽  
Hyperspectral Data ◽  
Time Saving ◽  
Federal Institute ◽  
Institute Of Technology

Early detection of bark beetle infestations by remote sensing: what is feasible today? Infestation by the Norway spruce (Picea abies) bark beetle (Ips typographus) in uniform forest stands of the high montane and subalpine stage is a major challenge for management. It is impossible to identify in time all susceptible or already infested spruces in the often steep terrain solely by terrestrial observations and to prevent the proliferation of the beetle. A time-saving, cost-effective and effective method for finding these spruces is necessary and remote sensing techniques appear promising. Therefore, we investigated the potential of hyperspectral remote sensing data for the early detection of stressed or infested spruces using a case study in the experimental forest of the Swiss Federal Institute of Technology Zurich (ETHZ) in Sedrun. The approach that we developed is based on a combination of field surveys, hyperspectral data, vegetation indices calculated from these and their classification into the three classes “dead”, “stressed” and “healthy” using Random Forests, a machine-learning approach. We demonstrate that stressed spruces can be identified with this approach, but it is not yet ready for operational use. In particular, a slope-specific calibration of the method is necessary, which makes practical application impossible.

scholarly journals INTEGRATION OF HUMAN PARTICIPATORY SENSING AND ARCHIVES OF REMOTE SENSING OBSERVATIONS FOR FIELD LEVEL CROP PHENOLOGY ESTIMATION

2018 ◽  
Vol XLII-4 ◽  
pp. 547-550
Author(s):  
S. A. Sawant ◽  
J. D. Mohite ◽  
S. Pappula
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Vegetation Indices ◽  
Crop Growth ◽  
Growth Stages ◽  
Growth Monitoring ◽  
Specific Information ◽  
Crop Phenology ◽  
Field Level ◽  
Sentinel 2

<p><strong>Abstract.</strong> The rise in global population has increased food and water demand thereby causing excessive pressure on existing resources. In developing countries with fragmented land holdings there exists constant pressure on available water and land resources. Obtaining field scale crop specific information is challenging task. Advent of open freely available multi-temporal remote sensing observations with improved radiometric resolution the possibilities for near real / real time applications has increased. In this study and an attempt has been made to establish operational model for field level crop growth monitoring using integrated approach of crowd sourcing and time series of remote sensing observations. The time series of Sentinel 2 (A and B) satellite has been used to estimate crop growth related components such as vegetation indices and crop growth stage and crop phenology. In initial stage high valued cereal crop Wheat has been selected. The field level information (i.e. 108 Wheat fields) collected using mobile based agro-advisory platform mKRISHI&amp;reg; has been used to extract time series of Sentinel 2 observations (44 scenes for year 2016 and 2018). The moving average has been used for filling gaps in the time series of vegetation indices. The BFAST and GreenBrown package in R were used for detecting breaks in vegetation index time series and estimating crop growth stages. Analysis shows that the estimated crop phenology parameters were in better agreement with the field observations. In future more crops from different agro-climatic conditions will be considered for providing field level crop management advisory.</p>

Estimating natural grassland biomass by vegetation indices using Sentinel 2 remote sensing data

2019 ◽  
Vol 41 (8) ◽  
pp. 2861-2876 ◽  
Author(s):  
Marildo Guerini Filho ◽  
Tatiana Mora Kuplich ◽  
Fernando L. F. De Quadros
Keyword(s):  
Remote Sensing ◽  
Vegetation Indices ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Natural Grassland ◽  
Sentinel 2

scholarly journals Upscaling Northern Peatland CO2 Fluxes Using Satellite Remote Sensing Data

2021 ◽  
Vol 13 (4) ◽  
pp. 818
Author(s):  
Sofia Junttila ◽  
Julia Kelly ◽  
Natascha Kljun ◽  
Mika Aurela ◽  
Leif Klemedtsson ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Surface ◽  
Ecosystem Respiration ◽  
Gross Primary Production ◽  
Vegetation Indices ◽  
Sensor Data ◽  
Spatial And Temporal Variation ◽  
Model Parameters ◽  
Co2 Fluxes ◽  
Sentinel 2

Peatlands play an important role in the global carbon cycle as they contain a large soil carbon stock. However, current climate change could potentially shift peatlands from being carbon sinks to carbon sources. Remote sensing methods provide an opportunity to monitor carbon dioxide (CO2) exchange in peatland ecosystems at large scales under these changing conditions. In this study, we developed empirical models of the CO2 balance (net ecosystem exchange, NEE), gross primary production (GPP), and ecosystem respiration (ER) that could be used for upscaling CO2 fluxes with remotely sensed data. Two to three years of eddy covariance (EC) data from five peatlands in Sweden and Finland were compared to modelled NEE, GPP and ER based on vegetation indices from 10 m resolution Sentinel-2 MSI and land surface temperature from 1 km resolution MODIS data. To ensure a precise match between the EC data and the Sentinel-2 observations, a footprint model was applied to derive footprint-weighted daily means of the vegetation indices. Average model parameters for all sites were acquired with a leave-one-out-cross-validation procedure. Both the GPP and the ER models gave high agreement with the EC-derived fluxes (R2 = 0.70 and 0.56, NRMSE = 14% and 15%, respectively). The performance of the NEE model was weaker (average R2 = 0.36 and NRMSE = 13%). Our findings demonstrate that using optical and thermal satellite sensor data is a feasible method for upscaling the GPP and ER of northern boreal peatlands, although further studies are needed to investigate the sources of the unexplained spatial and temporal variation of the CO2 fluxes.

scholarly journals Optimization and validation of a cost‐effective protocol for biosurveillance of invasive alien species

2021 ◽  
Vol 11 (5) ◽  
pp. 1999-2014
Author(s):  
Yoamel Milián‐García ◽  
Robert Young ◽  
Mary Madden ◽  
Erin Bullas‐Appleton ◽  
Robert H. Hanner
Keyword(s):  
Alien Species ◽  
Invasive Alien Species ◽  
Cost Effective

scholarly journals Determination of Crop Health Monitoring in MPKV – Rahuri, Using Remote Sensing Approach

2021 ◽  
pp. 11-16
Author(s):  
Ankita P. Kamble ◽  
A. A. Atre ◽  
Payal A. Mahadule ◽  
C. B. Pande ◽  
N. S. Kute ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Health Monitoring ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Plant Stress ◽  
Vegetation Indices ◽  
Remotely Sensed Data ◽  
Pests And Diseases ◽  
Crop Health ◽  
Sentinel 2

Pests and diseases cause major harm during crop development. Also plant stress affects crop quality and quantity. Recent developments in high resolution remotely sensed data has seen a great potential in mapping cropland areas infected by pests and diseases, as well as potential vulnerable areas over expansive areas. Crop health monitoring in this study was carried out using remote sensing techniques. The present study was carried out in MPKV, Rahuri, Ahmednagar District, Maharashtra. Vegetation indices like Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) were used to classify the crops into healthy and dead or unhealthy one. Sentinel-2 image data from October 2019 to January 2020 processed in Arc GIS 10.1 were used for this study. Vegetation is a key component of the ecosystem and plays an important role in stabilizing the global environment. The result showed that the average vegetation cover was decreased in the month of November and healthy vegetation was found more in month of October as compared to December and January. This shows that NDVI and SAVI indices for Sentinel-2 images can be used for crop health monitoring.

scholarly journals SPECTRAL IMAGING AND CLAY DETECTION IN LATGALE LAKES

2019 ◽  
Vol 1 ◽  
pp. 307
Author(s):  
Rasma Tretjakova ◽  
Sergejs Kodors ◽  
Juris Soms
Keyword(s):  
Remote Sensing ◽  
Incomplete Data ◽  
Spectral Imaging ◽  
Cost Effective ◽  
Indirect Methods ◽  
Sediment Samples ◽  
Pilot Experiment ◽  
Pearson Coefficient ◽  
Remote Sensing Methods ◽  
Sentinel 2

The survey of lake sediments is complex, time consuming and costly process with risks to human health. Additionally, manually obtained sediment samples provide incomplete data about a survey region. In turn, remote sensing methods are cost-effective and can provide continuous data about a survey region. Therefore, authors decided to perform a pilot experiment with a remote sensing method in order to detect clay sediments deposited in lakebeds. The evaluated method is the analysis of spectral images of Sentinel-2. Pearson coefficient and C4.5 datamining methods were applied for data analysis. Survey objects are Latgale lakes with and without clay sediments. The pilot experiment showed, that spectral imaging of lake water is not applicable method to detect definitely clay sediments in lakes, however, research results provide ideas about indirect methods, which must be studied in the future.

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