Journal articles on the topic 'Quaestio de aqua et terra'
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1
Mikkel, Annika. "Latin Accentual Clausula as Exemplified in 14th-Century Prose Texts by Dante and Boccaccio." Studia Metrica et Poetica 9, no. 1 (September 1, 2022): 66–88. http://dx.doi.org/10.12697/smp.2022.9.1.04.
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This paper studies 14th-century Latin prose rhythm as exemplified by Dante and Boccaccio. The texts observed in this analysis are samples from De Monarchia, De vulgari eloquentia, Quaestio de aqua et terra and Epistole by Dante and De mulieribus claris and De casibus virorum illustrium by Boccaccio. In ancient rhetoric, rhythmical units were used at the ends of sentences and clauses in prose texts. These units were called clausulae, and the rhythm of classical prose was based on the quantity of syllables. Medieval Latin prose rhythm, however, was based on word stress and was called cursus. The aim of this paper is to study what kinds of cursus occur in the given text samples and their frequency. The research method used in this paper is comparative-statistical analysis. The distribution of cursus in these samples is also analysed by chapters and different types of cursus are distinguished.
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Duda, David P., Sarah T. Bedka, Patrick Minnis, Douglas Spangenberg, Konstantin Khlopenkov, Thad Chee, and William L. Smith Jr. "Northern Hemisphere contrail properties derived from Terra and Aqua MODIS data for 2006 and 2012." Atmospheric Chemistry and Physics 19, no. 8 (April 18, 2019): 5313–30. http://dx.doi.org/10.5194/acp-19-5313-2019.
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Abstract. Linear contrail coverage, optical property, and radiative forcing data over the Northern Hemisphere (NH) are derived from a year (2012) of Terra and Aqua Moderate-resolution Imaging Spectroradiometer (MODIS) imagery and compared with previously published 2006 results (Duda et al., 2013; Bedka et al., 2013; Spangenberg et al., 2013) using a consistent retrieval methodology. Differences in the observed Terra-minus-Aqua screened contrail coverage and patterns in the 2012 annual-mean air traffic estimated with respect to satellite overpass time suggest that most contrails detected by the contrail detection algorithm (CDA) form approximately 2 h before overpass time. The 2012 screened NH contrail coverage (Mask B) shows a relative 3 % increase compared to 2006 data for Terra and increases by almost 7 % for Aqua, although the differences are not expected to be statistically significant. A new post-processing algorithm added to the contrail mask processing estimated that the total contrail cirrus coverage visible in the MODIS imagery may be 3 to 4 times larger than the linear contrail coverage detected by the CDA. This estimate is similar in magnitude to the spreading factor estimated by Minnis et al. (2013). Contrail property retrievals of the 2012 data indicate that both contrail optical depth and contrail effective diameter decreased approximately 10 % between 2006 and 2012. The decreases may be attributed to better background cloudiness characterization, changes in the waypoint screening, or changes in contrail temperature. The total mean contrail radiative forcings (TCRFs) for all 2012 Terra observations were −6.3, 14.3, and 8.0 mW m−2 for the shortwave (SWCRF), longwave (LWCRF), and net forcings, respectively. These values are approximately 20 % less than the corresponding 2006 Terra estimates. The decline in TCRF results from the decrease in normalized CRF, partially offset by the 3 % increase in overall contrail coverage in 2012. The TCRFs for 2012 Aqua are similar, −6.4, 15.5, and 9.0 mW m−2 for shortwave, longwave, and net radiative forcing. The strong correlation between the relative changes in both total SWCRF and LWCRF between 2006 and 2012 and the corresponding relative changes in screened contrail coverage over each air traffic region suggests that regional changes in TCRF from year to year are dominated by year-to-year changes in contrail coverage over each area.
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Saadi, Sameh, Gilles Boulet, Malik Bahir, Aurore Brut, Émilie Delogu, Pascal Fanise, Bernard Mougenot, Vincent Simonneaux, and Zohra Lili Chabaane. "Assessment of actual evapotranspiration over a semiarid heterogeneous land surface by means of coupled low-resolution remote sensing data with an energy balance model: comparison to extra-large aperture scintillometer measurements." Hydrology and Earth System Sciences 22, no. 4 (April 9, 2018): 2187–209. http://dx.doi.org/10.5194/hess-22-2187-2018.
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Abstract. In semiarid areas, agricultural production is restricted by water availability; hence, efficient agricultural water management is a major issue. The design of tools providing regional estimates of evapotranspiration (ET), one of the most relevant water balance fluxes, may help the sustainable management of water resources. Remote sensing provides periodic data about actual vegetation temporal dynamics (through the normalized difference vegetation index, NDVI) and water availability under water stress (through the surface temperature Tsurf), which are crucial factors controlling ET. In this study, spatially distributed estimates of ET (or its energy equivalent, the latent heat flux LE) in the Kairouan plain (central Tunisia) were computed by applying the Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) model fed by low-resolution remote sensing data (Terra and Aqua MODIS). The work's goal was to assess the operational use of the SPARSE model and the accuracy of the modeled (i) sensible heat flux (H) and (ii) daily ET over a heterogeneous semiarid landscape with complex land cover (i.e., trees, winter cereals, summer vegetables). SPARSE was run to compute instantaneous estimates of H and LE fluxes at the satellite overpass times. The good correspondence (R2 = 0.60 and 0.63 and RMSE = 57.89 and 53.85 W m−2 for Terra and Aqua, respectively) between instantaneous H estimates and large aperture scintillometer (XLAS) H measurements along a path length of 4 km over the study area showed that the SPARSE model presents satisfactory accuracy. Results showed that, despite the fairly large scatter, the instantaneous LE can be suitably estimated at large scales (RMSE = 47.20 and 43.20 W m−2 for Terra and Aqua, respectively, and R2 = 0.55 for both satellites). Additionally, water stress was investigated by comparing modeled (SPARSE) and observed (XLAS) water stress values; we found that most points were located within a 0.2 confidence interval, thus the general tendencies are well reproduced. Even though extrapolation of instantaneous latent heat flux values to daily totals was less obvious, daily ET estimates are deemed acceptable.
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Brito, Agni Cristina de Carvalho, Nara Luisa Reis de Andrade, Larissa Santos Fambri, Camila Bermond Ruezzene, and Renata Gonçalves Aguiar. "Aplicação do produto de evapotranspiração do MODIS para uma área de pastagem na Amazônia ocidental." Ciência e Natura 40 (March 22, 2018): 162. http://dx.doi.org/10.5902/2179460x30738.
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The processes of land use and occupation generate interventions in the natural ecosystems making them susceptible to reactions, such as changes in the processes that govern water cycling, emphasizing the importance of monitoring the evapotranspiration behavior. In this sense, the objective of this study was to verify the applicability of the evaporation product originated by the MODIS sensor to a pasture area, from 2003 to 2010, at Fazenda Nossa Senhora in the municipality of Ouro Preto do Oeste - Rondônia. Were used evapotranspiration data from the MODIS (Terra / Aqua) sensor, estimated by MOD16 algorithm, and micrometeorological tower located in the pasture area, generated by eddy covariance system. It was verified that for ET Eddy x ET MOD16 (Quality control – QC 0/8) data set, ET MOD16 (QC 0/8) data showed evapotranspiration values above those of ET Eddy and with a greater amplitude. A linear correlation between the study datasets was not identified, however, seasonal variations are captured by product, showing good approximation with ET Eddy data, especially in the transition periods.
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Nabat, P., S. Somot, M. Mallet, I. Chiapello, J. J. Morcrette, F. Solmon, S. Szopa, and F. Dulac. "A 4-D climatology (1979–2009) of the monthly aerosol optical depth distribution over the Mediterranean region from a comparative evaluation and blending of remote sensing and model products." Atmospheric Measurement Techniques Discussions 5, no. 6 (November 28, 2012): 8469–538. http://dx.doi.org/10.5194/amtd-5-8469-2012.
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Abstract. Since the 1980s several spaceborne sensors have been used to retrieve the aerosol optical depth (AOD) over the Mediterranean region. In parallel, AOD climatologies coming from different numerical model simulations are now also available, permitting to distinguish the contribution of several aerosol types to the total AOD. In this work, we perform a comparative analysis of this unique multi-year database in terms of total AOD and of its apportionment by the five main aerosol types (soil dust, sea-salt, sulfate, black and organic carbon). We use 8 different satellite-derived monthly AOD products: NOAA/AVHRR, SeaWiFS, TERRA/MISR, TERRA/MODIS, AQUA/MODIS, ENVISAT/MERIS, PARASOL/POLDER and MSG/SEVIRI, as well as 3 more historical data sets: NIMBUS7/CZCS, NIMBUS7/TOMS and METEOSAT/MVIRI. Monthly model datasets include the aerosol climatology from Tegen et al. (1997), the climate-chemistry models LMDz-OR-INCA and RegCM-4, and the reanalyses GEMS and MACC. Ground-based Level-2 AERONET AOD observations from 47 stations around the basin are used here to evaluate the model and satellite data. The sensor MODIS (on AQUA and TERRA) has the best average AOD scores over this region, showing a relevant spatio-temporal variability and highlighting high dust loads over Northern Africa and the sea (spring and summer), and sulfate aerosols over continental Europe (summer). The comparison also shows limitations of certain data sets (especially MERIS and SeaWiFS standard products). Models reproduce the main patterns of the AOD variability over the basin. The MACC reanalysis is the closest to AERONET data but appears to underestimate dust over Northern Africa, where RegCM-4 is found closer to MODIS thanks to its interactive scheme for dust emissions. The vertical dimension is also investigated using the CALIOP instrument. This study confirms differences between dust aerosols which can be lifted up to 5000 m, and other continental and marine aerosols which are confined in the boundary layer. From this compilation, we propose a 4-D blended product from model and satellite data, consisting in monthly time series of 3-D aerosol distribution at a 50 km horizontal resolution over the Euro-Mediterranean marine and continental region for the 2003–2009 period. The product is based on the total AOD from AQUA/MODIS, apportioned into sulfates, black and organic carbon from the MACC reanalysis, and into dust and sea-salt aerosols from RegCM-4 simulations, which are distributed vertically based on CALIOP climatology. We extend the 2003–2009 reconstruction to the past up to 1979 using the 2003–2009 average and applying the decreasing trend in sulfate aerosols from the LMDz-OR-INCA model, based on the recent emission reconstruction proposed by Lamarque et al. (2010). Finally optical properties of the different aerosol types in this region are proposed from the literature so that this reconstruction can be included in regional climate models for aerosol radiative forcing and aerosol-climate studies.
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Guzinski, R., M. C. Anderson, W. P. Kustas, H. Nieto, and I. Sandholt. "Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day–night MODIS observations." Hydrology and Earth System Sciences 17, no. 7 (July 16, 2013): 2809–25. http://dx.doi.org/10.5194/hess-17-2809-2013.
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Abstract. The Dual Temperature Difference (DTD) model, introduced by Norman et al. (2000), uses a two source energy balance modelling scheme driven by remotely sensed observations of diurnal changes in land surface temperature (LST) to estimate surface energy fluxes. By using a time-differential temperature measurement as input, the approach reduces model sensitivity to errors in absolute temperature retrieval. The original formulation of the DTD required an early morning LST observation (approximately 1 h after sunrise) when surface fluxes are minimal, limiting application to data provided by geostationary satellites at sub-hourly temporal resolution. The DTD model has been applied primarily during the active growth phase of agricultural crops and rangeland vegetation grasses, and has not been rigorously evaluated during senescence or in forested ecosystems. In this paper we present modifications to the DTD model that enable applications using thermal observations from polar orbiting satellites, such as Terra and Aqua, with day and night overpass times over the area of interest. This allows the application of the DTD model in high latitude regions where large viewing angles preclude the use of geostationary satellites, and also exploits the higher spatial resolution provided by polar orbiting satellites. A method for estimating nocturnal surface fluxes and a scheme for estimating the fraction of green vegetation are developed and evaluated. Modification for green vegetation fraction leads to significantly improved estimation of the heat fluxes from the vegetation canopy during senescence and in forests. When the modified DTD model is run with LST measurements acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellites, generally satisfactory agreement with field measurements is obtained for a number of ecosystems in Denmark and the United States. Finally, regional maps of energy fluxes are produced for the Danish Hydrological ObsErvatory (HOBE) in western Denmark, indicating realistic patterns based on land use.
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Guzinski, R., M. C. Anderson, W. P. Kustas, H. Nieto, and I. Sandholt. "Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day-night MODIS observations." Hydrology and Earth System Sciences Discussions 10, no. 2 (February 11, 2013): 1897–941. http://dx.doi.org/10.5194/hessd-10-1897-2013.
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Abstract. The Dual Temperature Difference (DTD) model, introduced by Norman et al. (2000), uses a two source energy balance modelling scheme driven by remotely sensed observations of diurnal changes in land surface temperature (LST) to estimate surface energy fluxes. By using a time differential temperature measurement as input, the approach reduces model sensitivity to errors in absolute temperature retrieval. The original formulation of the DTD required an early morning LST observation (approximately 1 h after sunrise) when surface fluxes are minimal, limiting application to data provided by geostationary satellites at sub-hourly temporal resolution. The DTD model has been applied primarily during the active growth phase of agricultural crops and rangeland vegetation grasses, and has not been rigorously evaluated during senescence or in forested ecosystems. In this paper we present modifications to the DTD model that enable applications using thermal observation from polar orbiting satellites, such as Terra and Aqua, with day and night overpass times over the area of interest. This allows the application of the DTD model in high latitude regions where large viewing angles preclude the use of geostationary satellites, and also exploits the higher spatial resolution provided by polar orbiting satellites. A method for estimating nocturnal surface fluxes and a scheme for estimating the fraction of green vegetation are developed and evaluated. Modification for green vegetation fraction leads to significantly improved estimation of the heat fluxes from the vegetation canopy during senescence and in forests. Land-cover based modifications to the Priestley–Taylor scheme, used to estimate transpiration fluxes, are explored based on prior findings for conifer forests. When the modified DTD model is run with LST measurements acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellites, generally satisfactory agreement with field measurements is obtained for a number of ecosystems in Denmark and the United States. Finally, regional maps of energy fluxes are produced for the Danish Hydrological ObsErvatory (HOBE) in western Denmark, indicating realistic patterns based on land use.
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Khaldi, Rohaifa, Domingo Alcaraz-Segura, Emilio Guirado, Yassir Benhammou, Abdellatif El Afia, Francisco Herrera, and Siham Tabik. "TimeSpec4LULC: a global multispectral time series database for training LULC mapping models with machine learning." Earth System Science Data 14, no. 3 (March 30, 2022): 1377–411. http://dx.doi.org/10.5194/essd-14-1377-2022.
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Abstract. Land use and land cover (LULC) mapping are of paramount importance to monitor and understand the structure and dynamics of the Earth system. One of the most promising ways to create accurate global LULC maps is by building good quality state-of-the-art machine learning models. Building such models requires large and global datasets of annotated time series of satellite images, which are not available yet. This paper presents TimeSpec4LULC (https://doi.org/10.5281/zenodo.5913554; Khaldi et al., 2022), a smart open-source global dataset of multispectral time series for 29 LULC classes ready to train machine learning models. TimeSpec4LULC was built based on the seven spectral bands of the MODIS sensors at 500 m resolution, from 2000 to 2021, and was annotated using spatial–temporal agreement across the 15 global LULC products available in Google Earth Engine (GEE). The 22-year monthly time series of the seven bands were created globally by (1) applying different spatial–temporal quality assessment filters on MODIS Terra and Aqua satellites; (2) aggregating their original 8 d temporal granularity into monthly composites; (3) merging Terra + Aqua data into a combined time series; and (4) extracting, at the pixel level, 6 076 531 time series of size 262 for the seven bands along with a set of metadata: geographic coordinates, country and departmental divisions, spatial–temporal consistency across LULC products, temporal data availability, and the global human modification index. A balanced subset of the original dataset was also provided by selecting 1000 evenly distributed samples from each class such that they are representative of the entire globe. To assess the annotation quality of the dataset, a sample of pixels, evenly distributed around the world from each LULC class, was selected and validated by experts using very high resolution images from both Google Earth and Bing Maps imagery. This smartly, pre-processed, and annotated dataset is targeted towards scientific users interested in developing various machine learning models, including deep learning networks, to perform global LULC mapping.
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Nabat, P., S. Somot, M. Mallet, I. Chiapello, J. J. Morcrette, F. Solmon, S. Szopa, et al. "A 4-D climatology (1979–2009) of the monthly tropospheric aerosol optical depth distribution over the Mediterranean region from a comparative evaluation and blending of remote sensing and model products." Atmospheric Measurement Techniques 6, no. 5 (May 17, 2013): 1287–314. http://dx.doi.org/10.5194/amt-6-1287-2013.
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Abstract. Since the 1980s several spaceborne sensors have been used to retrieve the aerosol optical depth (AOD) over the Mediterranean region. In parallel, AOD climatologies coming from different numerical model simulations are now also available, permitting to distinguish the contribution of several aerosol types to the total AOD. In this work, we perform a comparative analysis of this unique multi-year database in terms of total AOD and of its apportionment by the five main aerosol types (soil dust, sea-salt, sulfate, black and organic carbon). We use 9 different satellite-derived monthly AOD products: NOAA/AVHRR, SeaWiFS (2 products), TERRA/MISR, TERRA/MODIS, AQUA/MODIS, ENVISAT/MERIS, PARASOL/POLDER and MSG/SEVIRI, as well as 3 more historical datasets: NIMBUS7/CZCS, TOMS (onboard NIMBUS7 and Earth-Probe) and METEOSAT/MVIRI. Monthly model datasets include the aerosol climatology from Tegen et al. (1997), the climate-chemistry models LMDz-OR-INCA and RegCM-4, the multi-model mean coming from the ACCMIP exercise, and the reanalyses GEMS and MACC. Ground-based Level-2 AERONET AOD observations from 47 stations around the basin are used here to evaluate the model and satellite data. The sensor MODIS (on AQUA and TERRA) has the best average AOD scores over this region, showing a relevant spatio-temporal variability and highlighting high dust loads over Northern Africa and the sea (spring and summer), and sulfate aerosols over continental Europe (summer). The comparison also shows limitations of certain datasets (especially MERIS and SeaWiFS standard products). Models reproduce the main patterns of the AOD variability over the basin. The MACC reanalysis is the closest to AERONET data, but appears to underestimate dust over Northern Africa, where RegCM-4 is found closer to MODIS thanks to its interactive scheme for dust emissions. The vertical dimension is also investigated using the CALIOP instrument. This study confirms differences of vertical distribution between dust aerosols showing a large vertical spread, and other continental and marine aerosols which are confined in the boundary layer. From this compilation, we propose a 4-D blended product from model and satellite data, consisting in monthly time series of 3-D aerosol distribution at a 50 km horizontal resolution over the Euro-Mediterranean marine and continental region for the 2003–2009 period. The product is based on the total AOD from AQUA/MODIS, apportioned into sulfates, black and organic carbon from the MACC reanalysis, and into dust and sea-salt aerosols from RegCM-4 simulations, which are distributed vertically based on CALIOP climatology. We extend the 2003–2009 reconstruction to the past up to 1979 using the 2003–2009 average and applying the decreasing trend in sulfate aerosols from LMDz-OR-INCA, whose AOD trends over Europe and the Mediterranean are median among the ACCMIP models. Finally optical properties of the different aerosol types in this region are proposed from Mie calculations so that this reconstruction can be included in regional climate models for aerosol radiative forcing and aerosol-climate studies.
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Sun, Z., M. Gebremichael, and H. A. R. de Bruin. "Mapping daily evapotranspiration and dryness index in the East African highlands using MODIS and SEVIRI data." Hydrology and Earth System Sciences Discussions 7, no. 4 (August 26, 2010): 6285–303. http://dx.doi.org/10.5194/hessd-7-6285-2010.
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Abstract. Routine information on regional evapotranspiration (ET) and dryness index is essential for agricultural water management, drought monitoring, and studies of water cycle and climate. However, this information is not currently available for the East Africa highlands. The main purpose of this study is to develop (1) a new methodology that produces spatially gridded daily ET estimates on a (near) real-time basis exclusively from satellite data, and (2) a new dryness index that depends only on satellite data and weather forecast data. The methodology that calculates daily actual ET involves combining data from two sensors (MODIS and SEVIRI) onboard two kinds of platforms (Terra/Aqua – polar orbit satellite and MSG – geostationary orbit satellite). The methodology is applied to the East African highlands, and results are compared to eddy covariance measurements at one site. Results show that the methodology produces ET estimates that have high skills in reproducing the daily fluctuation in ET but tends to underestimate ET on the average. It is concluded that the synergistic use of the polar-orbiting MODIS data and the geostationary-orbiting SEVIRI data has potential to produce reliable daily ET, but further research is needed to improve the accuracy of the results. This study also proposes an operational new dryness index that can be calculated from the satellite-based actual daily ET estimates and reference daily ET estimates based on SEVIRI data and weather forecast air temperature. Comparison of this index against ground measurements of actual daily ET at one site indicates that the new dryness index is operational for drought monitoring.
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Zhao, Bing, Kebiao Mao, Yulin Cai, Jiancheng Shi, Zhaoliang Li, Zhihao Qin, Xiangjin Meng, Xinyi Shen, and Zhonghua Guo. "A combined Terra and Aqua MODIS land surface temperature and meteorological station data product for China from 2003 to 2017." Earth System Science Data 12, no. 4 (October 27, 2020): 2555–77. http://dx.doi.org/10.5194/essd-12-2555-2020.
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Abstract. Land surface temperature (LST) is a key variable for high temperature and drought monitoring and climate and ecological environment research. Due to the sparse distribution of ground observation stations, thermal infrared remote sensing technology has become an important means of quickly obtaining ground temperature over large areas. However, there are many missing and low-quality values in satellite-based LST data because clouds cover more than 60 % of the global surface every day. This article presents a unique LST dataset with a monthly temporal resolution for China from 2003 to 2017 that makes full use of the advantages of MODIS data and meteorological station data to overcome the defects of cloud influence via a reconstruction model. We specifically describe the reconstruction model, which uses a combination of MODIS daily data, monthly data and meteorological station data to reconstruct the LST in areas with cloud coverage and for grid cells with elevated LST error, and the data performance is then further improved by establishing a regression analysis model. The validation indicates that the new LST dataset is highly consistent with in situ observations. For the six natural subregions with different climatic conditions in China, verification using ground observation data shows that the root mean square error (RMSE) ranges from 1.24 to 1.58 ∘C, the mean absolute error (MAE) varies from 1.23 to 1.37 ∘C and the Pearson coefficient (R2) ranges from 0.93 to 0.99. The new dataset adequately captures the spatiotemporal variations in LST at annual, seasonal and monthly scales. From 2003 to 2017, the overall annual mean LST in China showed a weak increase. Moreover, the positive trend was remarkably unevenly distributed across China. The most significant warming occurred in the central and western areas of the Inner Mongolia Plateau in the Northwest Region, and the average annual temperature change is greater than 0.1 K (R>0.71, P<0.05), and a strong negative trend was observed in some parts of the Northeast Region and South China Region. Seasonally, there was significant warming in western China in winter, which was most pronounced in December. The reconstructed dataset exhibits significant improvements and can be used for the spatiotemporal evaluation of LST in high-temperature and drought-monitoring studies. The data are available through Zenodo at https://doi.org/10.5281/zenodo.3528024 (Zhao et al., 2019).
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Allies, Aubin, Jérôme Demarty, Albert Olioso, Ibrahim Bouzou Moussa, Hassane Bil-Assanou Issoufou, Cécile Velluet, Malik Bahir, et al. "Evapotranspiration Estimation in the Sahel Using a New Ensemble-Contextual Method." Remote Sensing 12, no. 3 (January 24, 2020): 380. http://dx.doi.org/10.3390/rs12030380.
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In many tropical areas, evapotranspiration is the most important but least known component of the water cycle. An innovative method, named E3S (for EVASPA S-SEBI Sahel), was developed to provide spatially-distributed estimates of daily actual evapotranspiration (ETd) from remote sensing data in the Sahel. This new method combines the strengths of a contextual approach that is used to estimate the evaporative fraction (EF) from surface temperature vs. albedo scatterograms and of an ensemble approach that derives ETd estimates from a weighted average of evapotranspiration estimated from several EF methods. In this work, the two combined approaches were derived from the simplified surface energy balance index (S-SEBI) model and the EVapotranspiration Assessment from SPAce (EVASPA) tool. Main innovative aspects concern (i) ensemble predictions of ETd through the implementation of a dynamic weighting scheme of several evapotranspiration estimations, (ii) epistemic uncertainty of the estimation of ETd from the analysis of the variability of evapotranspiration estimates, and (iii) a new cloud filtering method that significantly improves the detection of cloud edges that negatively affect EF determination. E3S was applied to MODIS/TERRA and AQUA datasets acquired during the 2005–2008 period over the mesoscale AMMA-CATCH (Analyse Multidisciplinaire de la Mousson Africaine—Couplage de l’Atmosphère Tropicale et du Cycle Hydrologique) observatory in South-West Niger. E3S estimates of instantaneous and daily available energy, evaporative fraction, and evapotranspiration were evaluated at a local scale based on two field-monitored plots representing the two main ecosystem types in the area—a millet crop and a fallow savannah bush. In addition to these ground-based observations, the local scale evaluation was performed against continuous simulations by a locally-calibrated soil-vegetation-atmosphere transfer model for the two plots. The RMSE (root mean square error) from this comparison for E3S’s ETd estimates from combined AQUA/TERRA sources was 0.5 mm·day−1, and the determination coefficient was 0.90. E3S significantly improved representation of the evapotranspiration seasonality, compared with a classical implementation of S-SEBI or with the original EVASPA’s non-weighted ensemble scheme. At the mesoscale, ETd estimates were obtained with an average epistemic uncertainty of 0.4 mm·day−1. Comparisons with the reference 0.25°-resolution GLEAM (global land evaporation Amsterdam model) product showed good agreement. These results suggested that E3S could be used to produce reliable continuous regional estimations at a kilometric resolution, consistent with land and water management requirements in the Sahel. Moreover, all these innovations could be easily transposed to other contextual approaches.
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Jing, Yinghong, Xinghua Li, and Huanfeng Shen. "STAR NDSI collection: a cloud-free MODIS NDSI dataset (2001–2020) for China." Earth System Science Data 14, no. 7 (July 11, 2022): 3137–56. http://dx.doi.org/10.5194/essd-14-3137-2022.
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Abstract. Snow dynamics are crucial in ecosystems, affecting radiation balance, hydrological cycles, biodiversity, and human activities. Snow areas with notably diverse characteristics are extensively distributed in China, mainly including Northern Xinjiang (NX), Northeast China (NC), and the Qinghai–Tibet Plateau (QTP). Spatiotemporal continuous snow monitoring is indispensable for ecosystem maintenance. Nevertheless, the formidable challenge of cloud obscuration severely impedes data collection. In the past decades, abundant binary snow cover area (SCA) maps have been retrieved from moderate resolution imaging spectroradiometer (MODIS) datasets. However, the integrated normalized difference snow index (NDSI) maps containing additional details on snow cover extent are still extremely scarce. In this study, a recent 20-year stretch seamless Terra–Aqua MODIS NDSI collection in China is generated using a Spatio-Temporal Adaptive fusion method with erroR correction (STAR), which comprehensively considers spatial and temporal contextual information. Evaluation tests confirm that the cloud-free STAR NDSI collection is superior to the two baseline datasets. The omission error decreased by 10 % in NX compared to the snow cover extent product, and the average correlation coefficient increased by 0.11 compared to the global cloud-gap-filled MODIS NDSI product. Consequently, this collection can serve as a basic dataset for hydrological and climatic modeling to explore various critical environmental issues in China. This collection is available from https://doi.org/10.5281/zenodo.5644386 (Jing et al., 2021).
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French, Andrew, Douglas Hunsaker, Lahouari Bounoua, Arnon Karnieli, William Luckett, and Robert Strand. "Remote Sensing of Evapotranspiration over the Central Arizona Irrigation and Drainage District, USA." Agronomy 8, no. 12 (November 26, 2018): 278. http://dx.doi.org/10.3390/agronomy8120278.
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Knowledge of baseline water use for irrigated crops in the U.S. Southwest is important for understanding how much water is consumed under normal farm management and to help manage scarce resources. Remote sensing of evapotranspiration (ET) is an effective way to gain that knowledge: multispectral data can provide synoptic and time-repetitive estimates of crop-specific water use, and could be especially useful for this arid region because of dominantly clear skies and minimal precipitation. Although multiple remote sensing ET approaches have been developed and tested, there is not consensus on which of them should be preferred because there are still few intercomparison studies within this environment. To help build the experience needed to gain consensus, a remote sensing study using three ET models was conducted over the Central Arizona Irrigation and Drainage District (CAIDD). Aggregated ET was assessed for 137 wheat plots (winter/spring crop), 183 cotton plots (summer crop), and 225 alfalfa plots (year-round). The employed models were the Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), the Two Source Energy Balance (TSEB), and Vegetation Index ET for the US Southwest (VISW). Remote sensing data were principally Landsat 5, supplemented by Landsat 7, MODIS Terra, MODIS Aqua, and ASTER. Using district-wide model averages, seasonal use (excluding surface evaporation) was 742 mm for wheat, 983 mm for cotton, and 1427 mm for alfalfa. All three models produced similar daily ET for wheat, with 6–8 mm/day mid-season. Model estimates diverged for cotton and alfalfa sites. Considering ET over cotton, TSEB estimates were 9.5 mm/day, METRIC 6 mm/day, and VISW 8 mm/day. For alfalfa, the ET values from TSEB were 8.0 mm/day, METRIC 5 mm/day, and VISW 6 mm/day. Lack of local validation information unfortunately made it impossible to rank model performance. However, by averaging results from all of them, ET model outliers could be identified. They ranged from −10% to +18%, values that represent expected ET modeling discrepancies. Relative to the model average, standardized ET-estimators—potential ET (ET ∘ ), FAO-56 ET, and USDA-SW gravimetric-ET— showed still greater deviations, up to 35% of annual crop water use for summer and year-round crops, suggesting that remote sensing of actual ET could lead to significantly improved estimates of crop water use. Results from this study highlight the need for conducting multi-model experiments during summer-months over sites with independent ground validation.
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Mbatha, Nkanyiso, and Sifiso Xulu. "Time Series Analysis of MODIS-Derived NDVI for the Hluhluwe-Imfolozi Park, South Africa: Impact of Recent Intense Drought." Climate 6, no. 4 (November 30, 2018): 95. http://dx.doi.org/10.3390/cli6040095.
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The variability of temperature and precipitation influenced by El Niño-Southern Oscillation (ENSO) is potentially one of key factors contributing to vegetation product in southern Africa. Thus, understanding large-scale ocean–atmospheric phenomena like the ENSO and Indian Ocean Dipole/Dipole Mode Index (DMI) is important. In this study, 16 years (2002–2017) of Moderate Resolution Imaging Spectroradiometer (MODIS) Terra/Aqua 16-day normalized difference vegetation index (NDVI), extracted and processed using JavaScript code editor in the Google Earth Engine (GEE) platform was used to analyze the vegetation response pattern of the oldest proclaimed nature reserve in Africa, the Hluhluwe-iMfolozi Park (HiP) to climatic variability. The MODIS enhanced vegetation index (EVI), burned area index (BAI), and normalized difference infrared index (NDII) were also analyzed. The study used the Modern Retrospective Analysis for the Research Application (MERRA) model monthly mean soil temperature and precipitations. The Global Land Data Assimilation System (GLDAS) evapotranspiration (ET) data were used to investigate the HiP vegetation water stress. The region in the southern part of the HiP which has land cover dominated by savanna experienced the most impact of the strong El Niño. Both the HiP NDVI inter-annual Mann–Kendal trend test and sequential Mann–Kendall (SQ-MK) test indicated a significant downward trend during the El Niño years of 2003 and 2014–2015. The SQ-MK significant trend turning point which was thought to be associated with the 2014–2015 El Niño periods begun in November 2012. The wavelet coherence and coherence phase indicated a positive teleconnection/correlation between soil temperatures, precipitation, soil moisture (NDII), and ET. This was explained by a dominant in-phase relationship between the NDVI and climatic parameters especially at a period band of 8–16 months.
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Mueller, Marlin M., Clémence Dubois, Thomas Jagdhuber, Florian M. Hellwig, Carsten Pathe, Christiane Schmullius, and Susan Steele-Dunne. "Sentinel-1 Backscatter Time Series for Characterization of Evapotranspiration Dynamics over Temperate Coniferous Forests." Remote Sensing 14, no. 24 (December 16, 2022): 6384. http://dx.doi.org/10.3390/rs14246384.
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Forests’ ecosystems are an essential part of the global carbon cycle with vast carbon storage potential. These systems are currently under external pressures showing increasing change due to climate change. A better understanding of the biophysical properties of forests is, therefore, of paramount importance for research and monitoring purposes. While there are many biophysical properties, the focus of this study is on the in-depth analysis of the connection between the C-band Copernicus Sentinel-1 SAR backscatter and evapotranspiration (ET) estimates based on in situ meteorological data and the FAO-based Penman–Monteith equation as well as the well-established global terrestrial ET product from the Terra and Aqua MODIS sensors. The analysis was performed in the Free State of Thuringia, central Germany, over coniferous forests within an area of 2452 km2, considering a 5-year time series (June 2016–July 2021) of 6- to 12-day Sentinel-1 backscatter acquisitions/observations, daily in situ meteorological measurements of four weather stations as well as an 8-day composite of ET products of the MODIS sensors. Correlation analyses of the three datasets were implemented independently for each of the microwave sensor’s acquisition parameters, ascending and descending overpass direction and co- or cross-polarization, investigating different time series seasonality filters. The Sentinel-1 backscatter and both ET time series datasets show a similar multiannual seasonally fluctuating behavior with increasing values in the spring, peaks in the summer, decreases in the autumn and troughs in the winter months. The backscatter difference between summer and winter reaches over 1.5 dB, while the evapotranspiration difference reaches 8 mm/day for the in situ measurements and 300 kg/m2/8-day for the MODIS product. The best correlation between the Sentinel-1 backscatter and both ET products is achieved in the ascending overpass direction, with datasets acquired in the late afternoon, and reaches an R2-value of over 0.8. The correlation for the descending overpass direction reaches values of up to 0.6. These results suggest that the SAR backscatter signal of coniferous forests is sensitive to the biophysical property evapotranspiration under some scenarios.
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Corbett, J., and W. Su. "Accounting for the effects of sastrugi in the CERES clear-sky Antarctic shortwave angular distribution models." Atmospheric Measurement Techniques 8, no. 8 (August 10, 2015): 3163–75. http://dx.doi.org/10.5194/amt-8-3163-2015.
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Abstract. The Cloud and the Earth's Radiant Energy System (CERES) instruments on NASA's Terra, Aqua and Soumi NPP satellites are used to provide a long-term measurement of Earth's energy budget. To accomplish this, the radiances measured by the instruments must be inverted to fluxes by the use of a scene-type-dependent angular distribution model (ADM). For permanent snow scenes over Antarctica, shortwave (SW) ADMs are created by compositing radiance measurements over the full viewing zenith and azimuth range. However, the presence of small-scale wind blown roughness features called sastrugi cause the BRDF (bidirectional reflectance distribution function) of the snow to vary significantly based upon the solar azimuth angle and location. This can result in monthly regional biases between −12 and 7.5 Wm−2 in the inverted TOA (top-of-atmosphere) SW flux. The bias is assessed by comparing the CERES shortwave fluxes derived from nadir observations with those from all viewing zenith angles, as the sastrugi affect fluxes inverted from the oblique viewing angles more than for the nadir viewing angles. In this paper we further describe the clear-sky Antarctic ADMs from Su et al. (2015). These ADMs account for the sastrugi effect by using measurements from the Multi-Angle Imaging Spectro-Radiometer (MISR) instrument to derive statistical relationships between radiance from different viewing angles. We show here that these ADMs reduce the bias and artifacts in the CERES SW flux caused by sastrugi, both locally and Antarctic-wide. The regional monthly biases from sastrugi are reduced to between −5 and 7 Wm−2, and the monthly-mean biases over Antarctica are reduced by up to 0.64 Wm−2, a decrease of 74 %. These improved ADMs are used as part of the Edition 4 CERES SSF (Single Scanner Footprint) data.
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Tortini, Riccardo, Nina Noujdina, Samantha Yeo, Martina Ricko, Charon M. Birkett, Ankush Khandelwal, Vipin Kumar, Miriam E. Marlier, and Dennis P. Lettenmaier. "Satellite-based remote sensing data set of global surface water storage change from 1992 to 2018." Earth System Science Data 12, no. 2 (May 19, 2020): 1141–51. http://dx.doi.org/10.5194/essd-12-1141-2020.
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Abstract. The recent availability of freely and openly available satellite remote sensing products has enabled the implementation of global surface water monitoring at a level not previously possible. Here we present a global set of satellite-derived time series of surface water storage variations for lakes and reservoirs for a period that covers the satellite altimetry era. Our goals are to promote the use of satellite-derived products for the study of large inland water bodies and to set the stage for the expected availability of products from the Surface Water and Ocean Topography (SWOT) mission, which will vastly expand the spatial coverage of such products, expected from 2021 on. Our general strategy is to estimate global surface water storage changes (ΔV) in large lakes and reservoirs using a combination of paired water surface elevation (WSE) and water surface area (WSA) extent products. Specifically, we use data produced by multiple satellite altimetry missions (TOPEX/Poseidon, Jason-1, Jason-2, Jason-3, and Envisat) from 1992 on, with surface extent estimated from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) from 2000 on. We leverage relationships between elevation and surface area (i.e., hypsometry) to produce estimates of ΔV even during periods when either of the variables was not available. This approach is successful provided that there are strong relationships between the two variables during an overlapping period. Our target is to produce time series of ΔV as well as of WSE and WSA for a set of 347 lakes and reservoirs globally for the 1992–2018 period. The data sets presented and their respective algorithm theoretical basis documents are publicly available and distributed via the Physical Oceanography Distributed Active Archive Center (PO DAAC; https://podaac.jpl.nasa.gov/, last access: 13 May 2020) of NASA's Jet Propulsion Laboratory. Specifically, the WSE data set is available at https://doi.org/10.5067/UCLRS-GREV2 (Birkett et al., 2019), the WSA data set is available at https://doi.org/10.5067/UCLRS-AREV2 (Khandelwal and Kumar, 2019), and the ΔV data set is available at https://doi.org/10.5067/UCLRS-STOV2 (Tortini et al., 2019). The records we describe represent the most complete global surface water time series available from the launch of TOPEX/Poseidon in 1992 (beginning of the satellite altimetry era) to the near present. The production of long-term, consistent, and calibrated records of surface water cycle variables such as in the data set presented here is of fundamental importance to baseline future SWOT products.
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Ewald, F., L. Bugliaro, H. Mannstein, and B. Mayer. "An improved cirrus detection algorithm MeCiDA2 for SEVIRI and its validation with MODIS." Atmospheric Measurement Techniques Discussions 5, no. 4 (August 1, 2012): 5271–311. http://dx.doi.org/10.5194/amtd-5-5271-2012.
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Abstract. The influence of cirrus clouds on the radiation budget of the Earth depends on their optical properties and their global coverage. The monitoring of cirrus coverage with instruments aboard geostationary satellites enables the investigation of cirrus clouds at the global scale as well as the identification of their diurnal variation. For instance, the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard the Meteosat Second Generation (MSG) satellites provides data with high temporal resolution of 15 min and a spatial resolution of 3 km × 3 km at the sub-satellite point. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the sun-synchronous platforms Terra and Aqua delivers at least one observation per day with a high spatial resolutions ranging from 250 m × 250 m to 1 km × 1 km. Since the infrared channels of the SEVIRI instrument are suitable for an observation which is independent from day-light, Krebs et al. (2007) developed a cirrus detection algorithm for SEVIRI (called MeCiDA), based solely on its thermal channels. Since MeCiDA was optimised for the area of Europe only, we present an improved version of the algorithm which allows application to the full Meteosat disc. Required changes include the consideration of the viewing angle dependency and of the sensitivity of the 9.7 μm channel to the ozone column. To this end, a correction is implemented that minimises the influence of the variability of the stratospheric ozone. The validation of the proposed improvements is carried out by using MeCiDA applied to MODIS data to address viewing angle-dependent cirrus detection and by additionally comparing it to the Cloud Optical Properties MOD06 cirrus product. The new MeCiDA version detects less cirrus than the original one for latitudes larger than 40° but almost the same amount elsewhere. MeCiDA's version for MODIS is more sensitive than that for SEVIRI with cirrus occurrences higher by 10%, and the new MeCiDA provides almost the same cirrus coverage (±0.1) as given by the Cloud Phase Optical Properties from MODIS for latitudes smaller than 50°. Finally, the influence of sub-pixel clouds on the SEVIRI cirrus detection has been examined: more than 60% of the undetected SEVIRI cirrus pixels have a cirrus coverage smaller than 0.5.
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Dalagnol, Ricardo, Lênio Soares Galvão, Fabien Hubert Wagner, Yhasmin Mendes de Moura, Nathan Gonçalves, Yujie Wang, Alexei Lyapustin, Yan Yang, Sassan Saatchi, and Luiz Eduardo Oliveira Cruz Aragão. "AnisoVeg: anisotropy and nadir-normalized MODIS multi-angle implementation atmospheric correction (MAIAC) datasets for satellite vegetation studies in South America." Earth System Science Data 15, no. 1 (January 19, 2023): 345–58. http://dx.doi.org/10.5194/essd-15-345-2023.
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Abstract. The AnisoVeg product consists of monthly 1 km composites of anisotropy (ANI) and nadir-normalized (NAD) surface reflectance layers obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor over the entire South American continent. The satellite data were preprocessed using the multi-angle implementation atmospheric correction (MAIAC). The AnisoVeg product spans 22 years of observations (2000 to 2021) and includes the reflectance of MODIS bands 1 to 8 and two vegetation indices (VIs), namely the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). While the NAD layers reduce the data variability added by bidirectional effects on the reflectance and VI time series, the unique ANI layers allow the use of this multi-angular data variability as a source of information for vegetation studies. The AnisoVeg product has been generated using daily MODIS MAIAC data from both Terra and Aqua satellites, normalized for a fixed solar zenith angle (SZA = 45∘), modeled for three sensor view directions (nadir, forward, and backward scattering), and aggregated to monthly composites. The anisotropy was calculated by the subtraction of modeled backward and forward scattering surface reflectance. The release of the ANI data for open usage is novel, and the NAD data are at an advanced processing level. We demonstrate the use of such data for vegetation studies using three types of forests in the eastern Amazon with distinct gradients of vegetation structure and aboveground biomass (AGB). The gradient of AGB was positively associated with ANI, while NAD values were related to different canopy structural characteristics. This was further illustrated by the strong and significant relationship between EVIANI and forest height observations from the Global Ecosystem Dynamics Investigation (GEDI) lidar sensor considering a simple linear model (R2=0.55). Overall, the time series of the AnisoVeg product (NAD and ANI) provide distinct information for various applications aiming at understanding vegetation structure, dynamics, and disturbance patterns. All data, processing codes, and results are made publicly available to enable research and the extension of AnisoVeg products for other regions outside of South America. The code can be found at https://doi.org/10.5281/zenodo.6561351 (Dalagnol and Wagner, 2022), EVIANI and EVINAD can be found as assets in the Google Earth Engine (GEE; described in the data availability section), and the full dataset is available from the open repository https://doi.org/10.5281/zenodo.3878879 (Dalagnol et al., 2022).
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Jia, Aolin, Shunlin Liang, Dongdong Wang, Lei Ma, Zhihao Wang, and Shuo Xu. "Global hourly, 5 km, all-sky land surface temperature data from 2011 to 2021 based on integrating geostationary and polar-orbiting satellite data." Earth System Science Data 15, no. 2 (February 16, 2023): 869–95. http://dx.doi.org/10.5194/essd-15-869-2023.
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Abstract. Land surface temperature (LST) plays a dominant role in the surface energy budget (SEB) and hydrological cycling. Thermal infrared (TIR) remote sensing is the primary method of estimating LST globally. However, cloud cover leaves numerous data gaps in satellite LST products, which seriously restricts their applications. Efforts have been made to produce gap-free LST products from polar-orbiting satellites (e.g., Terra and Aqua); however, satellite data from limited overpasses are not suitable for characterizing the diurnal temperature cycle (DTC), which is directly related to heat waves, plant water stress, and soil moisture. Considering the high temporal variability in LST and the importance of the DTC, we refined the SEB-based cloudy-sky LST recovery method by improving its feasibility and efficiency and produced a global hourly, 5 km, all-sky land surface temperature (GHA-LST) dataset from 2011 to 2021. The GHA-LST product was generated using TIR LST products from geostationary and polar-orbiting satellite data from the Copernicus Global Land Service (CGLS) and the Moderate Resolution Imaging Spectroradiometer (MODIS). Based on ground measurements at the 201 global sites from the Surface Radiation Budget (SURFRAD), Baseline Surface Radiation Network (BSRN), Fluxnet, AmeriFlux, Heihe River basin (HRB), and Tibetan Plateau (TP) networks, the overall root-mean-square error (RMSE) of the hourly GHA-LST product was 3.31 K, with a bias of −0.57 K and R2 of 0.95. Thus, this product was more accurate than the clear-sky CGLS and MODIS MYD21C1 LST samples. The RMSE value of the daily mean LST was 1.76 K. Validation results at individual sites indicate that the GHA-LST dataset has relatively larger RMSEs for high-elevation regions, which can be attributed to high surface heterogeneity and input data uncertainty. Temporal and spatial analyses suggested that GHA-LST has satisfactory spatiotemporal continuity and reasonable variation and matches the reference data well at hourly and daily scales. Furthermore, the regional comparison of GHA-LST with other gap-free hourly datasets (ERA5 and Global Land Data Assimilation System, GLDAS) demonstrated that GHA-LST can provide more spatial texture information. The monthly anomaly analysis suggests that GHA-LST couples well with global surface air temperature datasets and other LST datasets at daily mean and minimum temperature scales, whereas the maximum temperature and diurnal temperature range of LST and air temperature (AT) have different anomalous magnitudes. The GHA-LST dataset is the first global gap-free LST dataset at an hourly, 5 km scale with high accuracy, and it can be used to estimate global evapotranspiration, monitor extreme weather, and advance meteorological forecasting models. GHA-LST is freely available at https://doi.org/10.5281/zenodo.7487284 (Jia et al., 2022b) and http://glass.umd.edu/allsky_LST/GHA-LST (last access: 10 February 2023; Jia et al., 2022c).
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Podolskaia, Ekaterina, Dmitriy Ershov, and Konstantin Kovganko. "GIS-analysis of ground transport accessibility of fire stations at regional scale." Abstracts of the ICA 1 (July 15, 2019): 1–2. http://dx.doi.org/10.5194/ica-abs-1-301-2019.
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<p><strong>Abstract.</strong> Geospatial approaches are widely used to organize access and to manage the extinguishing of forest fires globally. Term “transport accessibility” is used in a variety of geographical and economic researches. Assessment of transport accessibility is directly related to the feasibility study to locate the fire stations in a particular region. Location analysis of objects relative to other objects, while taking into account various quantitative and qualitative parameters, is a classical problem solved by geoinformation systems.</p><p>Present research work is aimed to be used to improve the situation with forest fires in Russia where one of the main asset of operational regional firefighting in the forests is a fire-and-chemical (fire) station. Traditionally station placement is under the responsibility of Russian region to which stations are administratively subordinate. The location of fire station is determined taking into account the species structure of forests, natural fire danger, road infrastructure and some other factors. Irkutsk region, one of the territories with the constant perennial fire danger in the forests, was chosen as a test area.</p><p>Using this area as a typical example of regional extent, an analysis of fire stations placement then planning the ground movement of fire brigades from a station to the forest fire locations has been carried out. Previously obtained results to create the shortest routes within three-hour accessibility for the fire hazardous seasons 2002&ndash;2017 are used. Russian regulatory documents of the forest industry are applied. Thus, topic of GIS analysis serves as a continuation of the study (http://cepl.rssi.ru/wp-content/uploads/2018/11/Podolskaya-E.S.-et.-al..pdf, in Russian) and various aspects of transportation problem are considered on the example of Irkutsk region.</p><p>We used the following input data: point layer of fire stations, road network (including roads of different classes and forest glades), and archive of forest fires detected using the spectroradiometer MODIS from the Aqua and Terra spacecraft. Additional data were collected from the open regional Internet sources. GIS analysis used ArcGIS ArcMap Desktop extensions such as Network Analyst, Spatial Analyst, and ArcGIS tools like ET GeoWizards (https://www.ian-ko.com/).</p><p>We have developed and have used a <i>forest fire transport model of ground access</i> by trucks for the Irkutsk region with the spatial arrangement of fire stations, two protection zones and road network. Speed of the forest fire trucks is classified into 5 groups, taking into account the official permissions and road class. Also every segment of road has its attributive data of speed “adjusted” by the elevation value of the ETopo2, an open-access model (https://www.ngdc.noaa.gov/mgg/global/etopo2.html). Taking into consideration these relief data allows to decrease the vehicle’s speed in the mountainous conditions.</p><p>Based on the regional specifics and available data for a fire hazardous season, the following set of evaluation parameters was proposed, namely:</p><ul><li>Road network: roads existence, length, density, and configuration;</li><li>Spatial distribution of detected forest fires;</li><li>Territory of fire stations servicing.</li></ul><p>All the listed parameters are interconnected to each other and, in combination, jointly impact the stations ground transport accessibility assessment at the regional level. We have used GIS-analysis methods such as buffering, allocation, and density, as well as geographic and directional distribution. Time frame of analysis is the full fire hazardous season. Undertaken analysis for the forest fires detected within the ground protection zone (archive of 2002&ndash;2017) has shown that the fire stations’ distribution was appropriate. The analysis was based on the assumption that stations had the same weight, geographical and transport location of the stations was reviewed in conjunction to the thematical forestry recommendations. To go further in the GIS analysis some characteristics (work force and technical resources) of the weighted stations could be added.</p><p>Additional factors of influence can be the location of protected areas with their specific access regime, seasonality of road use, forest fire zoning, forestry boundaries, economic criteria, placement of fire stations in the populated area, etc. It is advisable to conduct a fire stations placement analysis as a preparation event before and after the end of the fire-hazardous season to summarize the effectiveness of actions to extinguish forest fires in the region. Practical results of the study can be used as well to prepare the regional forestry development programs and plans.</p>
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Jonathan, Milton, Margareth Simões Penello Meirelles, Jean-Paul Berroir, and Isabelle Herlin. "CONSIDERAÇÕES PARA O MONITORAMENTO DO USO DO SOLO COM DADOS MODIS PARA LONGOS PERÍODOS E EM ESCALA REGIONAL, E SUA APLICAÇÃO NA BACIA DO ALTO TAQUARI, MS/MT." Revista Brasileira de Cartografia 59, no. 1 (November 9, 2009). http://dx.doi.org/10.14393/rbcv59n1-43957.
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Este artigo discute uma metodologia para a classificação sistemática do uso e cobertura do solo em escala regional e para períodos extensos de tempo. O cerne desta metodologia está baseado no trabalho descrito em JONATHAN et al. (2005, 2006) e se fundamenta na análise de dados multitemporais provenientes do sensor MODIS (Moderate Resolution Imaging Spectroradiometer), o qual se encontra a bordo dos satélites Terra e Aqua da NASA e apresenta propriedades de alta freqüência temporal, extensa cobertura, e baixíssimo custo para aquisição de dados. Neste trabalho, realizou-se uma avaliação dos maiores potenciais e possíveis impedimentos da aplicação desta metodologia para o monitoramento plurianual do uso e cobertura do solo, concluindo-se ser de fato viável monitorar grandes regiões por longos períodos de tempo com baixo custo e altos níveis de automação. Neste sentido, tomou-se como área de estudos a Bacia do Alto Taquari, localizada nos estados de Mato Grosso do Sul e Mato Grosso, de forma a se enfatizar a relevância da aplicação desta abordagem para a detecção e quantificação de fenômenos como o desflorestamento e a dinâmica agrícola, que são por sua vez essenciais para o melhor entendimento dos principais processos de degradação relacionados ao ecossistema do Pantanal.