0000000000204661
AUTHOR
J. C. Jiménez
LST retrieval algorithm adapted to the Amazon evergreen forests using MODIS data
Abstract Amazonian tropical forests play a significant role in global water, carbon and energy cycles. Considering the importance of this biome and climate change projections, the monitoring of vegetation status of these rainforests becomes of significant importance. In this context vegetation temperature is presented as a key variable linked with plant physiology. In particular some studies showed the relationship between this variable and the CO2 absorption capacity and biomass loss of these tropical forests proving the potential use of vegetation temperature in the monitoring of the vegetation status. Nevertheless, the use of thermal remote sensing data over tropical forests still has so…
The role of ENSO flavours and TNA on recent droughts over Amazon forests and the Northeast Brazil region
Amazon tropical forests and the semiarid Northeast Brazil (NEB) region have registered very severe droughts during the last two decades, with a frequency that may have exceeded natural climate variability. Severe droughts impact the physiological response of Amazon forests, decreasing the availability to absorb atmospheric CO2, as well as biodiversity and increasing risk of fires. Droughts on this region also affect population by isolating them due to anomalous low river levels. Impacts of droughts over NEB region are related to water and energy security and subsistence agriculture. Most drought episodes over Amazonia and NEB are associated with El Nino (EN) events, anomalous warming over t…
Comparison of MODIS and Landsat-8 retrievals of Chlorophyll-a and water temperature over Lake Titicaca
Chlorophyll-a concentration ([Chl-a]) and Lake Surface Temperature (LST) were retrieved in Lake Titicaca (Peru-Bolivia) using MODIS and Landsat-8 images. The lake was chosen as a case-study for evaluating the feasibility of Landsat-8 images for [Chl-a] and LST monitoring in oligotrophic and mesotrophic water bodies. The big size of the lake and its spatial and temporal variability, allowed the comparison of MODIS and Landsat-8 products for a wide range of [Chl-a] and LST. The atmospheric correction of the images was facilitated by the very high altitude of the lake. MODIS images were processed with standard ocean color algorithms whereas for Landsat-8, specific algorithms were tested and va…
Sentinel 2 and 3 for Temperature Monitoring Over the Amazon
In this work we present results of an early assessment of the performance of the Land Surface Temperature (LST) product retrieved from the Sea and Land Surface Temperature Radiometer (SLSTR) on board the Sentinel-3 satellite (S3/SLSTR) over the Amazon basin. Results are validated from comparison of S3/SLSTR retrievals against in situ measurements of surface temperature collected over one instrumented site in the Peruvian Amazon. The validation exercise was performed on the standard S3/SLSTR Level-2 LST product as well as on a dedicated LST split-window algorithm with an explicit dependence on surface emissivity. Surface emissivity maps obtained from the high spatial resolution of S2/MSI are…
Droughts Over Amazonia in 2005, 2010, and 2015: A Cloud Cover Perspective
Amazon forests experienced recent severe droughts in an anomalous short period induced by different mechanisms and had different length periods and spatial patterns. Droughts of 2005 and 2010 were attributed to anomalous Sea Surface Temperature (SST) over the Tropical North Atlantic (TNA) during the dry season, but the 2010 drought was more severe and remained for a longer period because it was also induced in late 2009 by a moderate to strong El Niño (EN). Drought in 2015 led to unprecedented warming and extreme soil moisture deficits over some regions, and it was attributed to a very strong EN. Several studies analyzed these drought events regarding different climatic factors such as anom…
Warming trends in Patagonian subantartic forest
Abstract The forests in the Aysen region (ca. 43–49 °S, Chile) have a high degree of wilderness and cover more than 4.8 million hectares, making it one of the largest areas of subantarctic forest in the Southern Hemisphere. The impact of global warming on this region is poorly documented. The main objective of this work was to analyze the normalized difference vegetation index (NDVI), land surface temperature (LST) and precipitation over Aysen forests in the context of ongoing global warming. We used average monthly images of LST and NDVI derived from the MODIS sensor covering the period 2001–2016 and precipitation from gridded datasets. The Aysen region was divided into three nested spatia…
MODIS probabilistic cloud masking over the Amazonian evergreen tropical forests: a comparison of machine learning-based methods
Amazonian tropical forests play a significant role in global water, carbon and energy cycles. Satellite remote sensing is presented as a feasible means in order to monitor these forests. In particu...
Editorial : Tropical Climate Variability and Change: Impacts in the Amazon
Vast amounts of data from satellites and ground-based systems, and improvements on modeling techniques, allows a better understanding of Earth processes and advances on climate science. The tropics play a key role on global climate processes, and the tropical forest is a sensitive biome in the global hydrological and carbon cycles. In particular, the Amazon region includes about one half of the world’s tropical forest, and relatively small change in Amazon forest dynamics have the potential to substantially affect the rate of climate change. This Research Topics focus on recent finding on the impacts of tropical climate variability and change over the Amazon ecosystem using satellite data, …
Intercomparison of remote-sensing based evapotranspiration algorithms over amazonian forests
Abstract Evapotranspiration (ET) is considered a key variable in the understanding of the Amazonian tropical forests and their response to climate change. Remote-Sensing (RS) based evapotranspiration models are presented as a feasible means in order to provide accurate spatially-distributed ET estimates over this region. In this work, the performance of four commonly used ET RS models was evaluated over Amazonia using Moderate Resolution Imaging Spectroradiometer (MODIS) data. RS models included i) Priestley-Taylor Jet Propulsion Laboratory (PT-JPL), ii) Penman-Monteith MODIS operative parametrization (PM-Mu), iii) Surface Energy Balance System (SEBS), and iv) Satellite Application Facility…
Quantifying the spatial extent and intensity of recent extreme drought events in the Amazon rainforest and their impacts on the carbon cycle
Over the last decades, the Amazon rainforest was hit by multiple severe drought events. Here we assess the severity and spatial extent of the extreme drought years 2005, 2010, and 2015/2016 in the Amazon region and their impacts on the carbon cycle. As an indicator of drought stress in the Amazon rainforest, we use the widely applied maximum cumulative water deficit (ΔMCWD). Evaluating an ensemble of ten state-of-the-art precipitation datasets for the Amazon region, we find that the spatial extent of the drought in 2005 ranges from 2.8 to 4.2 (mean = 3.2) million km2 (46–71 % of the Amazon basin, mean = 53 %) where ΔMCWD indicates at le…
A simplified method for estimating the total water vapor content over sea surfaces using NOAA-AVHRR channels 4 and 5
A simplified method for estimating the total amount of atmospheric water vapor, W, over sea surfaces using NOAA-AVHRR Channels 4 and 5 is presented. This study has been carried out using simulated AVHRR data at 11 and 12 /spl mu/m (with MODTRAN 3.5 code and the TIGR database) and AVHRR, PODAAC, and AVISO databases provided by the Louis Pasteur University (Strasbourg-France), NASA-NOAA, and Meteo France, respectively. The method is named linear atmosphere-surface temperature relationship (LASTR). It is based on a linear relationship between the effective atmospheric temperature in AVHRR Channel 4 and sea surface temperature. The LASTR method was compared with the linear split-window relation…
Fire severity estimation in southern of the Buenos Aires province, Argentina, using Sentinel-2 and its comparison with Landsat-8
[EN] Assessment of rural fire severity is fundamental to evaluate fire damages and to analyze recovery processes in a low-cost and efficient way. Burnt areas covering shrubs and grasslands were estimated in more than 30,000 km2 in Argentina from December 2016 to January 2017. The study area presented in this work is located in the South of the Buenos Aires province, and it covers a semiarid area with the presence of xerophilous shrubs and grasslands. This is one of the most abundant ecosystem in Central and Southern Argentina. Field campaigns were carried out over the area affected by the fire in order to georreference the burnt plots and characterized the fire severity in 5 levels. The obj…
Early Diagnosis of Vegetation Health From High-Resolution Hyperspectral and Thermal Imagery: Lessons Learned From Empirical Relationships and Radiative Transfer Modelling
[Purpose of Review] We provide a comprehensive review of the empirical and modelling approaches used to quantify the radiation–vegetation interactions related to vegetation temperature, leaf optical properties linked to pigment absorption and chlorophyll fluorescence emission, and of their capability to monitor vegetation health. Part 1 provides an overview of the main physiological indicators (PIs) applied in remote sensing to detect alterations in plant functioning linked to vegetation diseases and decline processes. Part 2 reviews the recent advances in the development of quantitative methods to assess PI through hyperspectral and thermal images.
Vicarious Calibration of Landsat-8 Thermal Data Collections and its Influence on Split-Window Algorithm Validation
Landsat 8 (L8) satellite was launched on February 11, 2013 with two thermal bands located in the atmospheric window between $10-12\ \mu \mathrm{m}$ . Continuous monitoring of the Thermal Infrared Sensor (TIRS) onboard of L8 was performed over two Spanish test sites – Barrax and Donana – in order to contribute to the quality of TIRS data. In this work, a Vicarious Calibration (VC) of the TIRS bands was performed between years 2013–2016 in order to assess the new Stray Light (SL) data correction. The results of VC show us that band 10 and 11 provide accurate results (bias near to zero, and precision around 0.8 K) which is an improvement – especially for band 11 – in comparison to preprocessed…
Spatio-temporal patterns of thermal anomalies and drought over tropical forests driven by recent extreme climatic anomalies
The recent 2015–2016 El Niño (EN) event was considered as strong as the EN in 1997–1998. Given such magnitude, it was expected to result in extreme warming and moisture anomalies in tropical areas. Here we characterize the spatial patterns of temperature anomalies and drought over tropical forests, including tropical South America (Amazonia), Africa and Asia/Indonesia during the 2015–2016 EN event. These spatial patterns of warming and drought are compared with those observed in previous strong EN events (1982–1983 and 1997–1998) and other moderate to strong EN events (e.g. 2004–2005 and 2009–2010). The link between the spatial patterns of drought and sea surface temperature anomalies in th…