| 1. |
- Abdi, A. M., et al.
(author)
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First assessment of the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems
- 2019
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In: International Journal of Applied Earth Observation and Geoinformation. - : Elsevier BV. - 1569-8432. ; 78, s. 249-260
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Journal article (peer-reviewed)abstract
- The importance of semi-arid ecosystems in the global carbon cycle as sinks for CO 2 emissions has recently been highlighted. Africa is a carbon sink and nearly half its area comprises arid and semi-arid ecosystems. However, there are uncertainties regarding CO 2 fluxes for semi-arid ecosystems in Africa, particularly savannas and dry tropical woodlands. In order to improve on existing remote-sensing based methods for estimating carbon uptake across semi-arid Africa we applied and tested the recently developed plant phenology index (PPI). We developed a PPI-based model estimating gross primary productivity (GPP) that accounts for canopy water stress, and compared it against three other Earth observation-based GPP models: the temperature and greenness (T-G) model, the greenness and radiation (GöR) model and a light use efficiency model (MOD17). The models were evaluated against in situ data from four semi-arid sites in Africa with varying tree canopy cover (3–65%). Evaluation results from the four GPP models showed reasonable agreement with in situ GPP measured from eddy covariance flux towers (EC GPP) based on coefficient of variation (R 2 ), root-mean-square error (RMSE), and Bayesian information criterion (BIC). The GöR model produced R 2 = 0.73, RMSE = 1.45 g C m −2 d −1 , and BIC = 678; the T-G model produced R 2 = 0.68, RMSE = 1.57 g C m −2 d −1 , and BIC = 707; the MOD17 model produced R 2 = 0.49, RMSE = 1.98 g C m −2 d −1 , and BIC = 800. The PPI-based GPP model was able to capture the magnitude of EC GPP better than the other tested models (R 2 = 0.77, RMSE = 1.32 g C m −2 d −1 , and BIC = 631). These results show that a PPI-based GPP model is a promising tool for the estimation of GPP in the semi-arid ecosystems of Africa.
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| 2. |
- Huesca, Margarita, et al.
(author)
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Ecosystem functional assessment based on the "optical type" concept and self-similarity patterns: An application using MODIS-NDVI time series autocorrelation
- 2015
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In: International Journal of Applied Earth Observation and Geoinformation. - : Elsevier BV. - 1569-8432. ; 43, s. 132-148
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Journal article (peer-reviewed)abstract
- Remote sensing (RS) time series are an excellent operative source for information about the land surface across several scales and different levels of landscape heterogeneity. Ustin and Gamon (2010) proposed the new concept of "optical types" (OT), meaning "optically distinguishable functional types", as a way to better understand remote sensing signals related to the actual functional behavior of species that share common physiognomic forms but differ in functionality. Whereas the OT approach seems to be promising and consistent with ecological theory as a way to monitor vegetation derived from RS, it received little implementation. This work presents a method for implementing the OT concept for efficient monitoring of ecosystems based on RS time series. We propose relying on an ecosystem's repetitive pattern in the temporal domain (self-similarity) to assess its dynamics. Based on this approach, our main hypothesis is that distinct dynamics are intrinsic to a specific OT. Self-similarity level in the temporal domain within a broadleaf forest class was quantitatively assessed using the auto-correlation function (ACF), from statistical time series analysis. A vector comparison classification method, spectral angle mapper, and principal component analysis were used to identify general patterns related to forest dynamics. Phenological metrics derived from MOD IS NDVI time series using the TIMESAT software, together with information from the National Forest Map were used to explain the different dynamics found. Results showed significant and highly stable self-similarity patterns in OTs that corresponded to forests under non-moisture-limited environments with an adaptation strategy based on a strong phenological synchrony with climate seasonality. These forests are characterized by dense closed canopy deciduous forests associated with high productivity and low biodiversity in terms of dominant species. Forests in transitional areas were associated with patterns of less temporal stability probably due to mixtures of different adaptation strategies (i.e., deciduous, marcescent and evergreen species) and higher functional diversity related to climate variability at long and short terms. A less distinct seasonality and even a double season appear in the OT of the broadleaf Mediterranean forest characterized by an open canopy dominated by evergreen-sclerophyllous formations. Within this forest, understory and overstory dynamics maximize functional diversity resulting in contrasting traits adapted to summer drought, winter frosts, and high precipitation variability. (C) 2015 Elsevier B.V. All rights reserved.
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| 3. |
- Kelly, Julia, et al.
(author)
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Challenges and Best Practices for Deriving Temperature Data from an Uncalibrated UAV Thermal Infrared Camera
- 2019
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In: Remote Sensing. - : MDPI AG. - 2072-4292. ; 11:5
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Journal article (peer-reviewed)abstract
- Miniaturized thermal infrared (TIR) cameras that measure surface temperature are increasingly available for use with unmanned aerial vehicles (UAVs). However, deriving accurate temperature data from these cameras is non-trivialsince they are highly sensitive to changes in their internal temperature and low-cost models are often not radiometrically calibrated. We present the results of laboratory and field experiments that tested the extent of the temperature-dependency of a non-radiometric FLIR Vue Pro 640. We found that a simple empirical line calibration using at least three ground calibration points was sufficient to convert camera digital numbers to temperature values for images captured during UAV flight. Although the camera performed well under stable laboratory conditions (accuracy +/- 0.5 degrees C), the accuracy declined to +/- 5 degrees C under the changing ambient conditions experienced during UAV flight. The poor performance resulted from the non-linear relationship between camera output and sensor temperature, which was affected by wind and temperature-drift during flight. The camera's automated non-uniformity correction (NUC) could not sufficiently correct for these effects. Prominent vignetting was also visible in images captured under both stable and changing ambient conditions. The inconsistencies in camera output over time and across the sensor will affect camera applications based on relative temperature differences as well as user-generated radiometric calibration. Based on our findings, we present a set of best practices for UAV TIR camera sampling to minimize the impacts of the temperature dependency of these systems.
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| 4. |
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| 5. |
- Porcar-Castell, A., et al.
(author)
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EUROSPEC: at the interface between remote-sensing and ecosystem CO2 flux measurements in Europe
- 2015
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In: Biogeosciences. - : Copernicus GmbH. - 1726-4189. ; 12:20, s. 6103-6124
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Research review (peer-reviewed)abstract
- Resolving the spatial and temporal dynamics of gross primary productivity (GPP) of terrestrial ecosystems across different scales remains a challenge. Remote sensing is regarded as the solution to upscale point observations conducted at the ecosystem level, using the eddy covariance (EC) technique, to the landscape and global levels. In addition to traditional vegetation indices, the photochemical reflectance index (PRI) and the emission of solar-induced chlorophyll fluorescence (SIF), now measurable from space, provide a new range of opportunities to monitor the global carbon cycle using remote sensing. However, the scale mismatch between EC observations and the much coarser satellite-derived data complicates the integration of the two sources of data. The solution is to establish a network of in situ spectral measurements that can act as bridge between EC measurements and remote sensing data. In situ spectral measurements have been already conducted for many years at EC sites, but using variable instrumentation, setups, and measurement standards. In Europe in particular, in situ spectral measurements remain highly heterogeneous. The goal of EUROSPEC Cost Action ES0930 was to promote the development of common measuring protocols and new instruments towards establishing best practices and standardization of in situ spectral measurements. In this review we describe the background and main tradeoffs of in situ spectral measurements, review the main results of EUROSPEC Cost Action, and discuss the future challenges and opportunities of in situ spectral measurements for improved estimation of local and global carbon cycle.
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