scholarly journals In Situ Hyperspectral Remote Sensing for Monitoring of Alpine Trampled and Recultivated Species

2019 ◽  
Vol 11 (11) ◽  
pp. 1296 ◽  
Author(s):  
Marlena Kycko ◽  
Bogdan Zagajewski ◽  
Samantha Lavender ◽  
Anca Dabija
Keyword(s):  
Remote Sensing ◽  
Critical Role ◽  
Fluorescence Analysis ◽  
High Mountain ◽  
Monitoring Methods ◽  
Mountain Areas ◽  
Fluorescence Measurements ◽  
Mountain Grasslands ◽  
Tatra National Park

Vegetation, through its condition, reflects the properties of the environment. Heterogeneous alpine ecosystems play a critical role in global monitoring systems, but due to low accessibility, cloudy conditions, and short vegetation periods, standard monitoring methods cannot be applied comprehensively. Hyperspectral tools offer a variety of methods based on narrow-band data, but before extrapolation to an airborne or satellite scale, they must be verified using plant biometrical variables. This study aims to assess the condition of alpine sward dominant species (Agrostis rupestris, Festuca picta, and Luzula alpino-pilosa) of the UNESCO Man&Biosphere Tatra National Park (TPN) where the high mountain grasslands are strongly influenced by tourists. Data were analyzed for trampled, reference, and recultivated polygons. The field-obtained hyperspectral properties were verified using ground measured photosynthetically active radiation, chlorophyll content, fluorescence, and evapotranspiration. Statistically significant changes in terms of cellular structures, chlorophyll, and water content in the canopy were detected. Lower values for the remote sensing indices were observed for trampled plants (about 10–15%). Species in recultivated areas were characterized by a similar, or sometimes improved, spectral properties than the reference polygons; confirmed by fluorescence measurements (Fv/Fm). Overall, the fluorescence analysis and remote sensing tools confirmed the suitability of such methods for monitoring species in remote mountain areas, and the general condition of these grasslands was determined as good.

Analysis of remote sensing and in situ datasets to estimate spatial precipitation in high mountain areas: case study Cordillera Blanca, Peru

2021 ◽  
Author(s):  
Edwin Loarte ◽  
Katy Medina ◽  
Eduardo Villavicencio ◽  
Hairo León ◽  
Waldo Lavado ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Regression Model ◽  
Coefficient Of Determination ◽  
High Mountain ◽  
Precipitation Data ◽  
Wet Season ◽  
Mountain Areas ◽  
Spatial Gradients ◽  
Mountain Environments

<p>The Santa River basin has a climatology that is characterized by strong spatial gradients in precipitation. The influence of topography becomes increasingly important when smaller time scales are considered and convective and orographic processes have a more profound influence. This makes its estimation complex and of relevance for research on precipitation estimation in high mountain environments.</p><p>This study focused on estimating precipitation for the Santa basin located north of the capital of Peru, assessing spatial patterns and temporal variation. Precipitation products were used at a daily temporal resolution obtained from remote sensing datasets, including CHIRPS, PERSIANN-CCS, GPM and PISCO, altitude and vegetation products as NDVI-BOKU and GDEM. Also ground-based precipitation data from weather stations were collected from 35 meteorological stations (2012 -2019).</p><p>The in situ precipitation data was reviewed, cleaned and quality-checked for processing. The following operations were applied to the raster data: Gaussian filter, resampling at 1km, temporal homogenization (monthly) by accumulating the precipitation products until obtaining the monthly values, and averaging. Afterwards, a linear regression model was built based in which various of the remote sensing datasets served as predictions. The model was validated using the mean square error and the coefficient of determination.</p><p>The developed regression model provides a better estimate of the precipitation than the individual precipitation dataset. Overall, the resulting model performs relatively low in the dry season (May-September) but improves considerably in the wet season (October-April), with correlations that go up to 0.95. The outcomes of this research can be used to improve the estimation of precipitation patterns in high mountain regions with complex orography.</p>

scholarly journals Changes in vegetation cover on Stara planina: Towards sustainable management of ski resorts in sensitive areas

2015 ◽  
Vol 95 (2) ◽  
pp. 25-40 ◽  
Author(s):  
Ivan Potic ◽  
Marko Joksimovic ◽  
Rajko Golic
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Sustainable Management ◽  
Sustainable Forest Management ◽  
High Mountain ◽  
Landsat 8 ◽  
Mountain Areas ◽  
Ski Resorts ◽  
Landsat 7 ◽  
Multispectral Analysis

Tourism is an indicator and the consequence of the development of many countries. Among the priority areas of the tourism strategy are high mountain areas with complex ecosystems. Mountain tourism in Serbia, as well as continental country is one of the leading forms of tourism through various projects stimulated by the state. In the last ten years, build up and expand the ski slopes of Stara planina in eastern Serbia, leading to various, mostly negative changes in the environment. This paper analyzes the changes in the forest areas of the site Babin Zub in years 2000 and 2013, using satellite imagery (Landsat 7 and Landsat 8) and remote sensing software. We used unsupervised multispectral analysis resolution 30 m and obtained data on forest areas. The aim is to draw attention to the change of vegetation cover and degradation of forest areas. Following to the experiences of the world's ski resorts, the paper presents the opportunities and examples of restoration of ski runs, and sustainable forest management in the studied highland area.

scholarly journals Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity—Part I: Soil Characteristics

2019 ◽  
Vol 11 (20) ◽  
pp. 2356 ◽  
Author(s):  
Angela Lausch ◽  
Jussi Baade ◽  
Lutz Bannehr ◽  
Erik Borg ◽  
Jan Bumberger ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Cost Effective ◽  
Global Scale ◽  
Soil Characteristics ◽  
Monitoring Methods ◽  
In Situ Techniques ◽  
The Face ◽  
Remote Sensing Techniques

In the face of rapid global change it is imperative to preserve geodiversity for the overall conservation of biodiversity. Geodiversity is important for understanding complex biogeochemical and physical processes and is directly and indirectly linked to biodiversity on all scales of ecosystem organization. Despite the great importance of geodiversity, there is a lack of suitable monitoring methods. Compared to conventional in-situ techniques, remote sensing (RS) techniques provide a pathway towards cost-effective, increasingly more available, comprehensive, and repeatable, as well as standardized monitoring of continuous geodiversity on the local to global scale. This paper gives an overview of the state-of-the-art approaches for monitoring soil characteristics and soil moisture with unmanned aerial vehicles (UAV) and air- and spaceborne remote sensing techniques. Initially, the definitions for geodiversity along with its five essential characteristics are provided, with an explanation for the latter. Then, the approaches of spectral traits (ST) and spectral trait variations (STV) to record geodiversity using RS are defined. LiDAR (light detection and ranging), thermal and microwave sensors, multispectral, and hyperspectral RS technologies to monitor soil characteristics and soil moisture are also presented. Furthermore, the paper discusses current and future satellite-borne sensors and missions as well as existing data products. Due to the prospects and limitations of the characteristics of different RS sensors, only specific geotraits and geodiversity characteristics can be recorded. The paper provides an overview of those geotraits.

scholarly journals Remote Sensing Calculation of the Influence of Wildfire on Erosion in High Mountain Areas

Agronomy ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1459
Author(s):  
Yolanda Sánchez Sánchez ◽  
Antonio Martínez Graña ◽  
Fernando Santos- Francés
Keyword(s):  
Remote Sensing ◽  
Fire Severity ◽  
High Mountain ◽  
Mountain Areas ◽  
High Severity ◽  
Natural Reserve ◽  
Remote Sensing Techniques ◽  
Normalized Burn Ratio ◽  
The Moment ◽  
Very High

Soil erosion is one of the most important environmental problems of the moment, especially in areas affected by wildfires. In this paper, we study pre-fire and post-fire erosion using remote sensing techniques with Sentinel-2 satellite images and LiDAR. The Normalized Burn Ratio is used to determine the areas affected by the fire that occurred on 18 August 2016 in the Natural Reserve of Garganta de los Infiernos (Cáceres). To calculate the erosion, the multi-criteria analysis is carried out from the RUSLE. Once all calculations were performed, there was a considerable increase in sediment production from 16 June 2016 (pre-fire) with an erosion of 31 T/ha·year to 16 June 2017 of 74 T/ha·year for areas of moderate fire severity, and an increase from 11 T/ha·year in 2016 to 70 T/ha·year for areas with a very high severity. From the NDVI, it was possible to verify that this also affected the recovery of post-fire vegetation, decreasing the NDVI index 0.36 in areas of moderate severity and 0.53 in areas of very high severity.

scholarly journals An Open-Source Web Platform to Share Multisource, Multisensor Geospatial Data and Measurements of Ground Deformation in Mountain Areas

2019 ◽  
Vol 9 (1) ◽  
pp. 4
Author(s):  
Martina Cignetti ◽  
Diego Guenzi ◽  
Francesca Ardizzone ◽  
Paolo Allasia ◽  
Daniele Giordan
Keyword(s):  
Open Source ◽  
Spatial Data ◽  
Ground Deformation ◽  
Regional Scale ◽  
Heterogeneous Data ◽  
Geospatial Data ◽  
High Mountain ◽  
Mountain Areas ◽  
Data Infrastructure

Nowadays, the increasing demand to collect, manage and share archives of data supporting geo-hydrological processes investigations requires the development of spatial data infrastructure able to store geospatial data and ground deformation measurements, also considering multisource and heterogeneous data. We exploited the GeoNetwork open-source software to simultaneously organize in-situ measurements and radar sensor observations, collected in the framework of the HAMMER project study areas, all located in high mountain regions distributed in the Alpines, Apennines, Pyrenees and Andes mountain chains, mainly focusing on active landslides. Taking advantage of this free and internationally recognized platform based on standard protocols, we present a valuable instrument to manage data and metadata, both in-situ surface measurements, typically acquired at local scale for short periods (e.g., during emergency), and satellite observations, usually exploited for regional scale analysis of surface displacement. Using a dedicated web-interface, all the results derived by instrumental acquisitions and by processing of remote sensing images can be queried, analyzed and downloaded from both expert users and stakeholders. This leads to a useful instrument able to share various information within the scientific community, including the opportunity of reprocessing the raw data for other purposes and in other contexts.

scholarly journals Reversed Surface-Mass-Balance Gradients on Himalayan Debris-Covered Glaciers Inferred from Remote Sensing

2020 ◽  
Vol 12 (10) ◽  
pp. 1563 ◽  
Author(s):  
Rosie R. Bisset ◽  
Amaury Dehecq ◽  
Daniel N. Goldberg ◽  
Matthias Huss ◽  
Robert G. Bingham ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Mass Balance ◽  
Critical Role ◽  
Regional Scale ◽  
High Mountain ◽  
Surface Mass Balance ◽  
Equilibrium Line Altitude ◽  
Ice Dynamics ◽  
Surface Mass ◽  
Debris Coverage

Meltwater from the glaciers in High Mountain Asia plays a critical role in water availability and food security in central and southern Asia. However, observations of glacier ablation and accumulation rates are limited in spatial and temporal scale due to the challenges that are associated with fieldwork at the remote, high-altitude settings of these glaciers. Here, using a remote-sensing-based mass-continuity approach, we compute regional-scale surface mass balance of glaciers in five key regions across High Mountain Asia. After accounting for the role of ice flow, we find distinctively different altitudinal surface-mass-balance gradients between heavily debris-covered and relatively debris-free areas. In the region surrounding Mount Everest, where debris coverage is the most extensive, our results show a reversed mean surface-mass-balance gradient of −0.21 ± 0.18 m w.e. a−1 (100 m)−1 on the low-elevation portions of glaciers, switching to a positive mean gradient of 1.21 ± 0.41 m w.e. a−1 (100 m)−1 above an average elevation of 5520 ± 50 m. Meanwhile, in West Nepal, where the debris coverage is minimal, we find a continuously positive mean gradient of 1.18 ± 0.40 m w.e. a−1 (100 m)−1. Equilibrium line altitude estimates, which are derived from our surface-mass-balance gradients, display a strong regional gradient, increasing from northwest (4490 ± 140 m) to southeast (5690 ± 130 m). Overall, our findings emphasise the importance of separating signals of surface mass balance and ice dynamics, in order to constrain better their contribution towards the ice thinning that is being observed across High Mountain Asia.

Remote sensing based assessment of hazards from glacier lake outbursts: a case study in the Swiss Alps

2002 ◽  
Vol 39 (2) ◽  
pp. 316-330 ◽  
Author(s):  
Christian Huggel ◽  
Andreas Kääb ◽  
Wilfried Haeberli ◽  
Philippe Teysseire ◽  
Frank Paul
Keyword(s):  
Remote Sensing ◽  
Hazard Assessment ◽  
Swiss Alps ◽  
High Mountain ◽  
Mountain Areas ◽  
Runout Distance ◽  
Hazard Potential ◽  
Empirical Relations ◽  
Scale Levels ◽  
Remote Sensing Techniques

Glacier lakes are a common phenomenon in high mountain areas. Outbursts from glacier lakes have repeatedly caused the loss of human lives as well as severe damage to local infrastructure. In several high mountain ranges around the world, a grave uncertainty about the hazard potential of glacier lakes still exists, especially with respect to the effects of accelerating rates of glacier retreat as a consequence of atmospheric warming. Area-wide detection and modeling of glacier lake hazard potentials is, therefore, a major challenge. In this study, an approach integrating three scale levels allows for the progressive focus on critical glacier lakes. Remote sensing methods for application in glacier lake hazard assessment are presented, and include channel indexing, data fusion, and change detection. Each method matches the requirements of a certain scale level. For estimating potential disaster amplitudes, assessments must be made of maximum discharge and runout distance of outbursts floods and debris flows. Existing empirical relations are evaluated and complementary ones as derived from available data are proposed. Tests with observations from a recent outburst event from a moraine-dammed lake in the Swiss Alps show the basic applicability of the proposed techniques and the usefulness of empirical relations for first hazard assessments. In particular, the observed runout distance of the debris flow resulting from the outburst does not exceed the empirically estimated maximum runout distance. A list of decision criteria and related remote sensing techniques are discussed in conclusion. Such a list is an essential tool for evaluating the hazard potential of a lake. A systematic application of remote sensing based methods for glacier lake hazard assessment is recommended.Key words: glacier lake outburst, hazard potential, remote sensing, empirical parameters.

DACAPO-PESO: Remote Sensing and In-situ Observations in Sub-Antarctica (53°S,71°W) to Enhance the Understanding of Aerosol-Moisture-Cloud-Precipitation Interaction

2020 ◽  
Author(s):  
Heike Kalesse ◽  
Patric Seifert ◽  
Martin Radenz ◽  
Johannes Bühl ◽  
Teresa Vogl ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Climate Models ◽  
Cloud Condensation Nuclei ◽  
Microwave Radiometer ◽  
Shortwave Radiation ◽  
High Mountain ◽  
Climate Modelling ◽  
Aerosol Cloud ◽  
In Situ Observations

<p>The southern midlatitudes and Sub-Antarctica are a key region for the Earth’s climate and a source for uncertainties in climate modelling. The low concentration of ice nucleating particles is considered to diminish the efficiency of heterogeneous ice formation. Climate models underestimate the supercooled liquid water content which causes shortwave radiation biases.</p><p>The project DACAPO-PESO (Dynamics, Aerosol, Cloud And Precipitation Observations in the Pristine Environment of the Southern Ocean) which is being conducted in Punta Arenas (53°S, 71°W), Chile from Nov 2018 – March 2020 is endorsed by YOPP (Year of Polar Prediction) and fills an observational gap in the Southern Oceans, for which to date hardly any combined observations of lidar, cloud radar and microwave radiometer are available.</p><p>During that field experiment, LACROS (Leipzig Aerosol and Cloud Remote Observations System) of Leibniz Institute for Tropospheric Research (TROPOS) which comprises numerous remote sensing instruments, including multi-wavelength polarization Raman lidar, cloud radars, microwave radiometer, radiation sensors among others is deployed. From March 2019 onwards, additionally in-situ observations of the INP and cloud condensation nuclei properties were collected by TROPOS on a 623m high mountain 10 km upwind of the LACROS site. Meso-scale numerical modeling will provide support for interpretation of the results.</p><p>The presentation will be dedicated to</p><ol><li>a) provide an overview of the setup of DACAPO-PESO</li> <li>b) show case studies of how instrument synergies are used to characterize aerosol-cloud-interaction processes in the pristine atmosphere over Punta Arenas and</li> <li>c) show a case study of an Atmospheric River event which was also observed in Antarctica.</li> </ol>

scholarly journals Variations of the Snow Water Equivalent in the Ourika Catchment (Morocco) over 2000–2018 Using Downscaled MERRA-2 Data

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1120 ◽  
Author(s):  
Mohamed Baba ◽  
Simon Gascoin ◽  
Lionel Jarlan ◽  
Vincent Simonneaux ◽  
Lahoucine Hanich
Keyword(s):  
Snow Cover ◽  
River Flow ◽  
Snow Water Equivalent ◽  
Temporal Variations ◽  
In Situ Measurements ◽  
High Mountain ◽  
Snow Cover Area ◽  
Mountain Areas ◽  
Snow Water

The Ourika River is an important tributary of the Tensift River in the water-stressed region of Marrakesh (Morocco). The Ourika river flow is dominated by the snow melt contribution from the High Atlas mountains. Despite its importance in terms of water resources, the snow water equivalent (SWE) is poorly monitored in the Ourika catchment. Here, we used MERRA-2 data to run a distributed energy-balance snowpack model (SnowModel) over 2000–2018. MERRA-2 data were downscaled to 250-m spatial resolution using a digital elevation model. The model outputs were compared to in situ measurements of snow depth, precipitation, river flow and remote sensing observations of the snow cover area from MODIS. The results indicate that the model provides an overall acceptable representation of the snow cover dynamics given the coarse resolution of the MERRA-2 forcing. Then, we used the model output to analyze the spatio-temporal variations of the SWE in the Ourika catchment for the first time. We suggest that MERRA-2 data, which are routinely available with a delay of a few weeks, can provide valuable information to monitor the snow resource in high mountain areas without in situ measurements.

scholarly journals DETAILED AND HIGHLY ACCURATE 3D MODELS OF HIGH MOUNTAIN AREAS BY THE MACS-HIMALAYA AERIAL CAMERA PLATFORM

2015 ◽  
Vol XL-7/W3 ◽  
pp. 1129-1136 ◽  
Author(s):  
J. Brauchle ◽  
D. Hein ◽  
R. Berger
Keyword(s):  
Remote Sensing ◽  
Dynamic Range ◽  
Point Clouds ◽  
High Dynamic Range ◽  
3D Models ◽  
High Mountain ◽  
Mountain Areas ◽  
Pixel Resolution ◽  
Camera System ◽  
Mountainous Regions

Remote sensing in areas with extreme altitude differences is particularly challenging. In high mountain areas specifically, steep slopes result in reduced ground pixel resolution and degraded quality in the DEM. Exceptionally high brightness differences can in part no longer be imaged by the sensors. Nevertheless, detailed information about mountainous regions is highly relevant: time and again glacier lake outburst floods (GLOFs) and debris avalanches claim dozens of victims. Glaciers are sensitive to climate change and must be carefully monitored. <br><br> Very detailed and accurate 3D maps provide a basic tool for the analysis of natural hazards and the monitoring of glacier surfaces in high mountain areas. There is a gap here, because the desired accuracies are often not achieved. <br><br> It is for this reason that the DLR Institute of Optical Sensor Systems has developed a new aerial camera, the MACS-Himalaya. The measuring unit comprises four camera modules with an overall aperture angle of 116° perpendicular to the direction of flight. A High Dynamic Range (HDR) mode was introduced so that within a scene, bright areas such as sun-flooded snow and dark areas such as shaded stone can be imaged. In 2014, a measuring survey was performed on the Nepalese side of the Himalayas. The remote sensing system was carried by a Stemme S10 motor glider. Amongst other targets, the Seti Valley, Kali-Gandaki Valley and the Mt. Everest/Khumbu Region were imaged at heights up to 9,200 m. Products such as dense point clouds, DSMs and true orthomosaics with a ground pixel resolution of up to 15 cm were produced. Special challenges and gaps in the investigation of high mountain areas, approaches for resolution of these problems, the camera system and the state of evaluation are presented with examples.

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