Search results for "Remote Sensing"

Mapping daily evapotranspiration at field to continental scales using geostationary and polar orbiting satellite imagery

2011

Abstract. Thermal infrared (TIR) remote sensing of land-surface temperature (LST) provides valuable information about the sub-surface moisture status required for estimating evapotranspiration (ET) and detecting the onset and severity of drought. While empirical indices measuring anomalies in LST and vegetation amount (e.g., as quantified by the Normalized Difference Vegetation Index; NDVI) have demonstrated utility in monitoring ET and drought conditions over large areas, they may provide ambiguous results when other factors (e.g., air temperature, advection) are affecting plant functioning. A more physically based interpretation of LST and NDVI and their relationship to sub-surface moistu…

Shoreline Extraction and Change Detection using 1:5000 Scale Orthophoto Maps: A Case Study of Latvia-Riga

2015

Coastal management requires rapid, up-to-date, and
 correct information. Thus, the determination of coastal movements and its
 directions has primary importance for coastal managers. For monitoring the
 change of shorelines, remote sensing data, very high resolution aerial images
 and orthophoto maps are utilized for detections of change on shorelines. It is
 possible to monitor coastal changes by extracting the coastline from orthophoto
 maps. Along the Baltic Sea and Riga Gulf, Latvian coastline length is 496 km.
 It is rich of coastal resources and natural biodiversity.  Around 120 km of coastline are affected by
 significant coastal chang…

High-resolution orthophoto map and digital surface models of the largest Argentine Islands (the Antarctic) from unmanned aerial vehicle photogrammetry

2020

This study presents the first high-resolution orthophoto maps and digital surface models (DSMs) of the largest Argentine Islands, West Antarctica. Aerial surveys with small unmanned aerial vehicle (UAV) were performed in Austral summer, 2018, taking 10,041 aerial photographs. Accuracy requirements were ensured using ground control points (GCPs). A resolution of 3.4 and 6.8 cm/px of orthomosaics and DSMs is reached on average, and the RMS reprojection error is 0.22 m on average. We report the morphometric parameters of surveyed islands and discuss issues related to accuracy and the usage of UAVs in polar conditions. This study demonstrates that small and low cost UAVs can be successfully use…

OBTAINING POSITIONS OF ASTEROIDS FROM DIGITIZED PROCESSING OF PHOTOGRAPHIC OBSERVATIONS IN BALDONE OBSERVATORY (CODE 069)

2016

Digital processing of photographic plates of star fields allows to determine with high accuracy the coordinates and stellar magnitudes for all registered objects on these plates. The processing results can be used for a broad search for images of small bodies of the Solar system and determination of their coordinates. From the observations of earlier epoch, we can extract information about the locations of these bodies well before discovering them. Modern approach to processing early photographic observations with new technologies can be an effective instrument for rediscovery of asteroids and correction their orbits. We analyzed the results of digital processing of observations of clusters…

Bathymetry time series using high spatial resolution satellite images

2020

The use of the new generation of remote sensors, such as echo sounders and Global Navigation Satellite System (GNSS) receivers with differential correction installed in a drone, allows the acquisition of high-precision data in areas of shallow water, as in the case of the channel of the Encañizadas in the Mar Menor lagoon. This high precision information is the first step to develop the methodology to monitor the bathymetry of the Mar Menor channels. The use of high spatial resolution satellite images is the solution for monitoring many hydrological changes and it is the basis of the three-dimensional (3D) numerical models used to study transport over time, environmental variability, and wa…

A Self-Contained and Automated Method for Flood Hazard Maps Prediction in Urban Areas

2020

Water depths and velocities predicted inside urban areas during severe storms are traditionally the final result of a chain of hydrologic and hydraulic models. The use of a single model embedding all the components of the rainfall&ndash

Mediterranean Maritime Pollution: The Role Of Remote Sensing To Monitor And Mitigate

2010

Challenges in the use of Near Infrared Spectroscopy for improving wood quality: A review

2018

Aims of study: Forestry-related companies require quality monitoring methods capable to pass a large number of samples. This review paper is dealing with the utilization of near infrared (NIR) technique for wood analysis.Area of study: We have a global point of view for NIR applications and characterization of different kind of wood species is considered.Material and methods: NIR spectroscopy is a fast, non-destructive technique, applicable to any biological material, demanding little or no sample preparation. NIR spectroscopy and multivariate analysis serve well in laboratories where the conditions are controlled. The main challenges to NIR spectroscopy technique in field conditions are mo…

Localization of Multi-Class On-Road and Aerial Targets Using mmWave FMCW Radar

2021

mmWave radars play a vital role in autonomous systems, such as unmanned aerial vehicles (UAVs), unmanned surface vehicles (USVs), ground station control and monitoring systems. The challenging task when using mmWave radars is to estimate the accurate angle of arrival (AoA) of the targets, due to the limited number of receivers. In this paper, we present a novel AoA estimation technique, using mmWave FMCW radars operating in the frequency range 77–81 GHz by utilizing the mechanical rotation. Rotating the radar also increases the field of view in both azimuth and elevation. The proposed method estimates the AoA of the targets, using only a single transmitter and receiver. The measurements are…

Noise Reduction and Gap Filling of fAPAR Time Series Using an Adapted Local Regression Filter

2014

Time series of remotely sensed data are an important source of information for understanding land cover dynamics. In particular, the fraction of absorbed photosynthetic active radiation (fAPAR) is a key variable in the assessment of vegetation primary production over time. However, the fAPAR series derived from polar orbit satellites are not continuous and consistent in space and time. Filtering methods are thus required to fill in gaps and produce high-quality time series. This study proposes an adapted (iteratively reweighted) local regression filter (LOESS) and performs a benchmarking intercomparison with four popular and generally applicable smoothing methods: Double Logistic (DLOG), sm…