Mihai A. TanaseUniversity of Alcalá | UAH · Department of Geology, Geography and Environment
Mihai A. Tanase
PhD Spatial Planning and Environment
About
91
Publications
40,065
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Introduction
I am interested in the use of remote sensing for vegetation characterization. My current research is focused on SAR, InSAR and PolSAR data for fire severity estimation, vegetation recovery monitoring and the retrieval of bio-geophysical parameters of forests and agricultural crops.
Additional affiliations
January 2017 - June 2019
National Institute for Research and Development in Forestry
Position
- Project Manager
Description
- EO-ROFORMON aims to prototype a novel national forest monitoring and forecasting system based on the integration of active (radar) and passive (optical) Earth-Observation (EO) sensors calibrated with in situ data.
November 2015 - present
University of Alcala
Position
- Research Associate
Description
- Fire_CCI Option 3 lead investigator: burned area mapping for the Amazon basin from Sentinel-1 data.
January 2015 - December 2019
Publications
Publications (91)
Systematic Sentinel-1 acquisitions provide an unprecedented stream of SAR data which allows to describe forest temporal dynamics in detail, a powerful tool for phenological studies and forest type classification. Several studies have explored the temporal variation of backscatter intensity in this context, but none considered that scattering direct...
No aplica, dado que se trata de una aportación para la sección "NOTAS Y RESÚMENES DE TRABAJOS DE INVESTIGACIÓN"
Live fuel moisture content (LFMC) influences many fire-related aspects, including flammability, ignition, and combustion. In addition, fire spread models are highly sensitive to LFMC values. Despite its importance, LFMC estimation is still elusive due to its dependence on plant species traits, local conditions, and weather patterns. Although LFMC m...
NASAs Global Ecosystem Dynamics Investigation (GEDI) is collecting space-borne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDIs footprint-level (~25 m) AGBD (GEDI04_A) product, including a descript...
This study tested the ability of Sentinel-1 C-band to separate forest from other common land use classes (i.e., urban, low vegetation and water) at two different sites. The first site is characterized by temperate forests and rough terrain while the second by tropical forest and near-flat terrain. We trained a support vector machine classifier usin...
The structure and functioning of temperate forests are shifting due to changes in climate. Foreseeing the trajectory of such changes is critical to implementing adequate management practices and defining long-term strategies. This study investigated future shifts in temperate forest species composition and abundance expected to occur due to climate...
While products generated at global levels provide easy access to information on forest growing stock volume (GSV), their use at regional to national levels is limited by temporal frequency, spatial resolution, or unknown local errors that may be overcome through locally calibrated products. This study assessed the need, and utility, of developing l...
In this paper, we present an in-depth analysis of the use of convolutional neural networks (CNN), a deep learning method widely applied in remote sensing-based studies in recent years, for burned area (BA) mapping combining radar and optical datasets acquired by Sentinel-1 and Sentinel-2 on-board sensors, respectively. Combining active and passive...
Dead wood, including dead standing trees (DST) and coarse woody debris (CWD), is a critical component of forest ecosystems that provides habitat and refugia for fauna, flora, and microbial communities and plays a key role in carbon and nutrient cycling. However, few studies have modelled the long-term dynamics of dead wood, limiting our ability to...
Wildfires have increased in size and frequency in recent decades in many biomes, but have they also become more severe? This question remains under-examined despite fire severity being a critical aspect of fire regimes that indicates fire impacts on ecosystem attributes and associated post-fire recovery. We conducted a retrospective analysis of wil...
Wildfires worldwide are becoming more frequent but are they also becoming more severe? Here we used remotely sensed burn-severity data from wildfires in Victoria, southeastern Australia to address that question. We selected 162 wildfires of more than 1000 ha that occurred over the past 30 years across a wide range of forest types. Spectral indices...
Spaceborne remote sensing can track ecosystems changes thanks to continuous and systematic coverage at short revisit intervals. Active remote sensing from synthetic aperture radar (SAR) sensors allows day and night imaging as they are not affected by cloud cover and solar illumination and can capture unique information about its targets. However, S...
Research Highlights: The present study case investigates the differences occurring when tree’s biophysical parameters are extracted through single and multiple scans. Scan sessions covered mountainous and hill regions of the Carpathian forests. Background and Objectives: We focused on analyzing stems, as a function of diameter at breast height (DBH...
The International Scientific Conference „Forest Science for a Sustainable Forestry and Human Wellbeing in a Changing World” - INCDS „Marin Drăcea” 85 Years of Activity, Centenary of The Great Union in 1918” is an open scientific event dedicated to the anniversary of 85 years of activity in forestry research of the National Institute for Research an...
Aim
Forest carbon storage is the result of a multitude of interactions among biotic and abiotic factors. Our aim was to use an integrative approach to elucidate mechanistic relationships of carbon storage with biotic and abiotic factors in the natural forests of temperate Australia, a region that has been overlooked in global analyses of carbon‐bio...
This study provides a comparative analysis of two Sentinel-1 and one Sentinel-2 burned area (BA) detection and mapping algorithms over 10 test sites (100 × 100 km) in tropical and sub-tropical Africa. Depending on the site, the burned area was mapped at different time points during the 2015–2016 fire seasons. The algorithms relied on diverse burned...
Burned area algorithms from radar images are often based on temporal differences between pre- and post-fire backscatter values. However, such differences may occur long past the fire event, an effect known as temporal decorrelation. Improvements in radar-based burned areas monitoring depend on a better understanding of the temporal decorrelation ef...
Machine learning and spectral index (SI) thresholding approaches have been tested for fire-severity mapping from local to regional scales in a range of forest types worldwide. While index thresholding can be easily implemented, its operational utility over large areas is limited as the optimum index may vary with forest type and fire regimes. In co...
Fire has a vast influence on the climatic balance, and the Global Climate Observing System (GCOS) considers it an Essential Climate Variable (ECV). Remote sensing data is a powerful source of information for burned area detection and thus for estimating greenhouse gases (GHGs) emissions from fires. Currently, most burned area products are based on...
Pine plantations, very common in the Mediterranean basin, are recurrently affected by forest pests due to intrinsic characteristics (high density, low spatial heterogeneity) and external factors (consistent trend towards a warmer and drier climate). INSTAR is an Agent-Based Model aiming to simulate the population dynamics of the Thaumetopoea pityoc...
This paper presents a burned area mapping algorithm based on change detection of Sentinel-1 backscatter data guided by thermal anomalies. The algorithm self-adapts to the local scattering conditions and it is robust to variations of input data availability. The algorithm applies the Reed-Xiaoli detector (RXD) to distinguish anomalous changes of the...
Forest stands are often parameterized by vegetation indices such as the Leaf Area Index (LAI). However, other indices (i.e. stand denseness, espacement, canopy density, canopy cover, foliage cover, crown porosity, gap fraction) may better characterize forest structure. Terrestrial and airborne active sensor data has been used to describe canopy str...
p>Dehesas are high value agroecosystems that benefit from the effect tree cover has on pastures. Such effect occurs when tree cover is incomplete and homogeneous. Tree cover may be characterized from field data or through visual interpretation of remote sensing data, both time-consuming tasks. An alternative is the extraction of tree cover from aer...
Natural and anthropogenic disturbances pose a significant threat to forest condition. Continuous, reliable and accurate forest monitoring systems are needed to provide early warning of potential declines in forest condition. To address that need, state-of-the-art simulations models were used to evaluate the utility of C-, L- and P-band synthetic ap...
Fire has a diverse range of impacts on Earth's physical and social systems. Accurate and up to date information on areas affected by fire is critical to better understand drivers of fire activity, as well as its relevance for biogeochemical cycles, climate, air quality, and to aid fire management. Mapping burned areas was traditionally done from fi...
Prescribed burning is a technique commonly applied to reduce fire risk. Fire is introduced under specific environmental conditions, with explicit duration, intensity and rate of spread. Such conditions deviate from those encountered during the fire season. As a result, prescribed burns mostly affect surface fuels and understory vegetation, an outco...
Forest ecosystems serve a host of services and societal benefits, including carbon storage, habitat for fauna, recreation, and provision of wood or non-wood products. In a context of complex demands on forest resources, identifying priorities for biodiversity and carbon budgets require accurate tools with sufficient temporal frequency. Moreover, un...
This study aims to present a comparison analysis of two data collection methods that can be used in order to obtain reference ground truth data for forestry-a conventional method that uses specific equipment such as Field Map system, caliper and vertex inclinometer and a modern method based on terrestrial laser scanning (TLS) technology. The resear...
The purpose of ISCRAM Asia Pacific 2018 is to exchange research into and experiences of information systems use in emergency management, particularly focused around applications of information systems in the context of the four priorities of the Sendai Framework (2015-2030) for disaster risk reduction, namely: 1. understanding disaster risk; 2. str...
Spectral indices derived from optical remote sensing data have been widely used for fire 14-severity classification in forests from local to global scales. However, comparative analyses of 15 multiple indices across diverse forest types are few. This represents an information gap for fire 16 management agencies in areas like temperate southeastern...
The polarimetric L-band imaging synthetic aperture radar (PLIS) is a high spatial resolution (better than 6 m) airborne synthetic aperture radar system that has been dedicated to scientific research into civilian applications since 2010. The weight of PLIS is ∼38 kg, allowing it to be installed aboard small low-cost aircraft, with two antennas used...
Prescribed burning is a technique applied to control fire risk, and it has been used in the forests of Western Australia since the 1960s. Synthetic Aperture Radar (SAR) data are sensitive to vegetation structural changes and may detect changes in understory vegetation particularly when the upper forest canopy remains largely unaffected, as it is of...
Fire is considered an essential climate variable (ECV) by the Global Climate Observing System (GCOS). Remote sensing is often used to detect the burned areas and subsequently estimate CO2 emissions from wildfires. Most burned area mapping approaches are based on optical images. However, cloud cover independent radar datasets are increasingly employ...
Worldwide, about 2.1 PgC are released every year from biomass burning. Due to its importance for climate modelling, several products were developed to map burned areas (BA) at global levels. Most of these products are based on medium or low-resolution optical sensors which are rather insensitive to small size fires. Moreover, frequent cloud cover a...
Question
Do remote sensing signals represent beta diversity? Does beta diversity agree with community types?.
Location
UNESCO Man and Biosphere Reserve, La Palma, Canary Islands.
Methods
We recorded perennial, vascular plant species abundances in 69 plots (10 m x 10 m) in three pre‐defined community types along an elevational gradient of 2400 m:...
Natural disturbances significantly influence forest ecosystem services and biodiversity. Accurate delineation and early detection of areas affected by wind and insect outbreaks are crucial for guiding management decisions. To this end, past studies relied mostly on passive sensors (e.g., optical), and active sensors (i.e., radar) were rarely used....
Mediterranean pine forests in Spain experience wildland fire events with different frequencies, intensities, and severities. An estimation of the fire severity as accurate as possible is required by forest managers to decide which strategy is most appropriate to mitigate the effect of fire. The aim of this research is to estimate the post-fire seve...
The study of fires has a high environmental interest, because fires can make changes in some ecosystems. Also fires are an important source of aerosols and gases of greenhouse effect. This study develops an automatic detection algorithm for burned areas using time series of Sentinel-1 radar images, which allow the detection of burned areas where th...
Recent estimates show that about 2.1 PgC are released every year due to biomass burning. Because of its importance, numerous approaches have been developed to estimate fire affected area globally with most of them using low to medium resolution optical and thermal wavelengths. However, there is an increasing evidence of burned area underestimation...
The objective of this letter is to extend the alpha approximation method, a method proposed by Balenzano et al., for soil moisture retrieval from multitemporal synthetic aperture radar (SAR) data. The original alpha approach requires an initial estimate of the upper and lower bound soil moisture values to constrain the soil moisture retrieval. This...
Mixed-species eucalypt forests of temperate Australia are assumed tolerant of most fire regimes based on the impressive capacity of the dominant eucalypts to resprout. However, empirical data to test this assumption are rare, limiting capacity to predict forest tolerance to emerging fire regimes including more frequent severe wildfires and extensiv...
The aim of this paper was to estimate soil moisture in agricultural crop fields from fully polarimetric L-band synthetic aperture radar (SAR) data through the polarimetric decomposition of the SAR coherency matrix. A nonnegative-eigenvalue-decomposition scheme, together with an adaptive volume scattering model, is extended to an adaptive model-base...
Fires affect wide areas and their effects can be successfully estimated from a range of remote sensing sensors, with synthetic aperture radars (SAR) being of particular interest due to their sensitivity to forest vertical structure, global availability and independence of cloud cover or solar elevation. Previous studies have demonstrated the sensit...
Monitoring fire effects at landscape level is viable from remote sensing platforms providing repeatable and
consistent measurements. Previous studies have estimated fire severity using optical and synthetic aperture radar (SAR) sensors, but to our knowledge, none have compared their effectiveness. Our study carried out such a comparison by using ch...
This paper evaluates the opportunity provided by global interferometric radar datasets for monitoring deforestation, degradation and forest regrowth in tropical and semi-arid environments. The paper describes an easy to implement method for detecting forest spatial changes and estimating their magnitude. The datasets were acquired within space-born...
A Canopy Height Profile (CHP) procedure presented in Harding et al. (2001) for large footprint LiDAR data was tested in a closed canopy environment as a way of extracting vertical foliage profiles from LiDAR raw-waveform. In this study, an adaptation of this method to small-footprint data has been shown, tested and validated in an Australian sparse...
Timely information on spatial variation of live fuel moisture is critical for fire risk assessment and behaviour modelling. Using an airborne synthetic aperture radar (SAR) system the sensitivity of radar data to live fuel (i.e., canopy foliage) moisture was evaluated. Field and airborne measurements were collected over a three-week period in a sem...
This study has tested Canopy Height Profile (CHP) methodology as a way of effective Leaf Area Index (LAIe) and vertical vegetation profile retrieval at a single-tree level. Waveform and discrete airborne LiDAR data from five swaths as well as from the combined data of five swaths were used to extract LAIe of a single live Callitris glaucophylla tre...
Mediterranean pine forests in Spain experience wildland fire events with different frequencies, intensities, and severities which result in diverse socio-ecological consequences. In order to predict fire severity, spectral indices derived from remotely sensed images have been used extensively. Such spectral indices are usually used in combination w...
This letter evaluates the biomass-retrieval error in pine-dominated stands when using high-spatial-resolution airborne measurements from fully polarimetric L-band radar and airborne laser scanning sensors. Information on total above-ground biomass was estimated through allometric relationships from plot-level field measurements. Multiple-linear-reg...
Using the airborne Polarimetric L-band Imaging Synthetic aperture radar (PLIS) the impact of high revisit cycle and full polarimetric acquisitions on biomass retrieval was investigated by means of backscatter-based multi-temporal methods. Parametric and non-parametric models were used to relate reference biomass levels obtained from field plot meas...
The backscatter predicted by three common surface scattering models (the Integral Equation Model (IEM), the Dubois, and the Oh models) was evaluated against fully polarized L-band airborne observations. Before any site-specific calibration, the Oh model was found to be the most accurate among the three, with mean errors between the simulated and th...
The usefulness of L-band radiometer observations for the retrieval of near-surface soil moisture has already been demonstrated in many studies. Unfortunately, the ability to estimate soil moisture from these remotely sensed observations is hampered by the infeasibility to characterize the roughness of the soil surface. Given the difficulty to measu...
This study investigated the effectiveness of frequently used parametric and non-parametric models for biomass retrieval from L-band radar backscatter. Two areas, one in Spain and one in Australia, characterized by different tree species, forest structure and field sampling designs were selected to demonstrate that retrieval error metrics are simila...
High resolution Spaceborne Synthetic Aperture Radar (SAR) is a promising option for global and frequent high resolution monitoring of near-surface soil moisture for hydrological, atmospheric and agricultural applications. The backscatter from natural and agricultural areas is strongly affected by the geometrical roughness of the surface. Several mo...
This study investigates the potentialities offered by active and passive simultaneous acquisitions at L band for monitoring of soil moisture in forested areas. Airborne data, acquired over the moderately dense Gillenbah forest in the framework of SMAPEx-3 project, have been analyzed to derive the sensitivity of emissivity and backscattering coeffic...
This study has compared preliminary estimates of effective leaf area index (LAI) derived from fish-eye lens photographs to those estimated from airborne full-waveform small-footprint LiDAR data for a forest dataset in Australia. The full-waveform data was decomposed and optimized using a trust-region-reflective algorithm to extract denser point clo...
The capability of L band wavelengths to register the soil emission over sparse to moderately dense forests makes attractive the comparative study of the soil moisture content and vegetation biophysical parameter. Soil and vegetation conditions contribute to the microwave measurements through complex interactions, basically resulting from vegetation...
The relationship between X-band Synthetic Aperture Radar (SAR) observations and soil moisture (SM) and surface roughness (SR) is investigated over well-monitored bare agricultural fields, using TerraSAR-X observations at 37.8° (VV and HH polarization) and 42.3° (VV and VH). TerraSAR backscatter increased with increasing SM but exhibited limited sen...
Using an airborne L-band system the impact of increased spatial resolution and a fully polarized sensor on biomass retrieval was investigated. A water cloud type model was used to retrieve biomass from backscatter intensities and polarimetric target decomposition components. The analysis revealed similar biomass estimation errors (around 60%) when...
Fully polarimetric C- and L-band synthetic aperture radar (SAR) data have been investigated to determine the relationship between polarimetric target decomposition components and forest burn severity over two sites located in a Mediterranean environment. The dependence of the polarimetric decomposition metrics on SAR acquisition geometry and enviro...
Polarimetric SARs are designed to measure the full scattering matrix. In practice, however, distortions are introduced on transmit and receive and the measurements may not accurately reflect the true characteristics of the scattering process. The polarimetric data calibration tries to estimate the distortion characteristics on transmit (T) and rece...