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Urban surface temperature is a very important variable in the observation and understanding of energy exchange. A comprehensive understanding of the urban thermal environment is of great significance towards the adaptability of urban areas to climate hazards. The heterogeneity of urban space increases the complexity of the urban surface temperature observations and the analyses of the energy exchange. To understand how the urban geometry affects the distribution of surface temperature, we used airborne thermal infrared remotely sensed images at very high spatial resolution (original spatial resolution is 0.2 m × 0.2 m after registration). We did this study in Hong Kong to analyze the effects of various geometric parameters on different facet surface temperatures (roof, road, wall and vegetation) in daytime and nighttime and in different seasons. Results show that the urban geometry has greater impacts on the road temperature than on building temperature, and the impact of the geometric parameters on road surface temperature changes with the time of the day and the season. The building height is a more effective driver of heat dissipation in daytime than nighttime for roof facets. A lower building density improves ground heat dissipation, while a higher building density improves heat dissipation by roof facets. Furthermore, the vegetation only limitedly affects the surface temperatures of facets that are lower than vegetation, but to an extent useful to mitigate urban temperature, which might be a feature relevant in urban design. This research can provide insights useful to city planners and policy makers to better understand the urban thermal environment and help design more livable and healthy cities in the near future.
Jinxin Yang; Qian Shi; Massimo Menenti; Man Sing Wong; Zhifeng Wu; Qunshan Zhao; Sawaid Abbas; Yong Xu. Observing the impact of urban morphology and building geometry on thermal environment by high spatial resolution thermal images. Urban Climate 2021, 39, 100937 .
AMA StyleJinxin Yang, Qian Shi, Massimo Menenti, Man Sing Wong, Zhifeng Wu, Qunshan Zhao, Sawaid Abbas, Yong Xu. Observing the impact of urban morphology and building geometry on thermal environment by high spatial resolution thermal images. Urban Climate. 2021; 39 ():100937.
Chicago/Turabian StyleJinxin Yang; Qian Shi; Massimo Menenti; Man Sing Wong; Zhifeng Wu; Qunshan Zhao; Sawaid Abbas; Yong Xu. 2021. "Observing the impact of urban morphology and building geometry on thermal environment by high spatial resolution thermal images." Urban Climate 39, no. : 100937.
Land surface temperature (LST) in urban agglomerations plays an important role for policymakers in urban planning. The Pearl River Delta (PRD) is one of the regions with the highest urban densities in the world. This study aims to explore the spatial patterns and the dominant drivers of LST in the PRD. MODIS LST (MYD11A2) data from 2005 and 2015 were used in this study. First, spatial analysis methods were applied in order to determine the spatial patterns of LST and to identity the hotspot areas (HSAs). Second, the hotspot ratio index (HRI), as a metric of thermal heterogeneity, was developed in order to identify the features of thermal environment across the nine cities in the PRD. Finally, the geo-detector (GD) metric was employed to explore the dominant drivers of LST, which included elevation, land use/land cover (LUCC), the normalized difference vegetation index (NDVI), impervious surface distribution density (ISDD), gross domestic product (GDP), population density (POP), and nighttime light index (NLI). The GD metric has the advantages of detecting the dominant drivers without assuming linear relationships and measuring the combined effects of the drivers. The results of Moran’s Index showed that the daytime and nighttime LST were close to the cluster pattern. Therefore, this process led to the identification of HSAs. The HSAs were concentrated in the central PRD and were distributed around the Pearl River estuary. The results of the HRI indicated that the spatial distribution of the HSAs was highly heterogeneous among the cities for both daytime and nighttime. The highest HRI values were recorded in the cities of Dongguan and Shenzhen during the daytime. The HRI values in the cities of Zhaoqing, Jiangmen, and Huizhou were relatively lower in both daytime and nighttime. The dominant drivers of LST varied from city to city. The influence of land cover and socio-economic factors on daytime LST was higher in the highly urbanized cities than in the cities with low urbanization rates. For the cities of Zhaoqing, Huizhou, and Jiangmen, elevation was the dominant driver of daytime LST during the study period, and for the other cities in the PRD, the main driver changed from land cover in 2005 to NLI in 2015. This study is expected to provide useful guidance for planning of the thermal environment in urban agglomerations.
Wenxiu Liu; Qingyan Meng; Mona Allam; Linlin Zhang; Die Hu; Massimo Menenti. Driving Factors of Land Surface Temperature in Urban Agglomerations: A Case Study in the Pearl River Delta, China. Remote Sensing 2021, 13, 2858 .
AMA StyleWenxiu Liu, Qingyan Meng, Mona Allam, Linlin Zhang, Die Hu, Massimo Menenti. Driving Factors of Land Surface Temperature in Urban Agglomerations: A Case Study in the Pearl River Delta, China. Remote Sensing. 2021; 13 (15):2858.
Chicago/Turabian StyleWenxiu Liu; Qingyan Meng; Mona Allam; Linlin Zhang; Die Hu; Massimo Menenti. 2021. "Driving Factors of Land Surface Temperature in Urban Agglomerations: A Case Study in the Pearl River Delta, China." Remote Sensing 13, no. 15: 2858.
The deployment of Sentinel-1 (S1) satellite constellation carrying a C-band Synthetic Aperture Radar (SAR) enables regular and timely monitoring of floods from their onset until returning to non-flooded (NF) conditions. The major constraint on using SAR for near-real-time (NRT) flood mapping has been the inability to rapidly process the obtained imagery into reliable flood maps. This study evaluates the efficacy of S1 time series for quantifying and characterising inundations extents in vegetated environments. A novel algorithm based on statistical time series modelling of flooded (F) and a NF pixel is proposed for NRT flood monitoring. For each new available S1 image, the probability of temporarily flooded conditions is tested against that of NF conditions by means of likelihood ratio tests. The likelihoods for the two conditions are derived from early acquisitions in the time series. The algorithm calibration consists of adjusting two likelihood ratio thresholds to match the reference flooded area extent during a single flood season. The proposed algorithm is applied to the Caprivi region and the resulting maps were compared to cloud-free Landsat-8 (LS8) derived maps captured during two flood events. A good spatial agreement, (85-87%), between LS8 and S1 flood maps was observed during flood peak in both 2017 and 2018 seasons. Significant discrepancies were noted during the flood expansion and recession phases, mainly due to different sensitivities of the data sources to emerging vegetation. Overall, the analysis shows that S1 can stand as an effective standalone or gap-filling alternative to optical imagery during a flood event.
Tsitsi Bangira; Lorenzo Iannini; Massimo Menenti; Adriaan van Niekerk; Zoltan Vekerdy. Flood Extent Mapping in the Caprivi Floodplain Using Sentinel-1 Time Series. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021, 14, 5667 -5683.
AMA StyleTsitsi Bangira, Lorenzo Iannini, Massimo Menenti, Adriaan van Niekerk, Zoltan Vekerdy. Flood Extent Mapping in the Caprivi Floodplain Using Sentinel-1 Time Series. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2021; 14 (99):5667-5683.
Chicago/Turabian StyleTsitsi Bangira; Lorenzo Iannini; Massimo Menenti; Adriaan van Niekerk; Zoltan Vekerdy. 2021. "Flood Extent Mapping in the Caprivi Floodplain Using Sentinel-1 Time Series." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14, no. 99: 5667-5683.
Glacier albedo determines the net shortwave radiation absorbed at the glacier surface and plays a crucial role in glacier energy and mass balance. Remote sensing techniques are efficient means to retrieve glacier surface albedo over large and inaccessible areas and to study its variability. However, corrections of anisotropic reflectance of glacier surface have been established for specific shortwave bands only, such as Landsat 5 Thematic Mapper (L5/TM) band 2 and band 4, which is a major limitation of current retrievals of glacier broadband albedo. In this study, we calibrated and evaluated four anisotropy correction models for glacier snow and ice, applicable to visible, near-infrared and shortwave-infrared wavelengths using airborne datasets of Bidirectional Reflectance Distribution Function (BRDF). We then tested the ability of the best-performing anisotropy correction model, referred to from here on as the ‘updated model’, to retrieve albedo from L5/TM, Landsat 8 Operational Land Imager (L8/OLI) and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery, and evaluated these results with field measurements collected on eight glaciers around the world. Our results show that the updated model: (1) can accurately estimate anisotropic factors of reflectance for snow and ice surfaces; (2) generally performs better than prior approaches for L8/OLI albedo retrieval but is not appropriate for L5/TM; (3) generally retrieves MODIS albedo better than the MODIS standard albedo product (MCD43A3) in both absolute values and glacier albedo temporal evolution, i.e., exhibiting both fewer gaps and better agreement with field observations. As the updated model enables anisotropy correction of a maximum of 10 multispectral bands and is implemented in Google Earth Engine (GEE), it is promising for observing and analyzing glacier albedo at large spatial scales.
Shaoting Ren; Evan Miles; Li Jia; Massimo Menenti; Marin Kneib; Pascal Buri; Michael McCarthy; Thomas Shaw; Wei Yang; Francesca Pellicciotti. Anisotropy Parameterization Development and Evaluation for Glacier Surface Albedo Retrieval from Satellite Observations. Remote Sensing 2021, 13, 1714 .
AMA StyleShaoting Ren, Evan Miles, Li Jia, Massimo Menenti, Marin Kneib, Pascal Buri, Michael McCarthy, Thomas Shaw, Wei Yang, Francesca Pellicciotti. Anisotropy Parameterization Development and Evaluation for Glacier Surface Albedo Retrieval from Satellite Observations. Remote Sensing. 2021; 13 (9):1714.
Chicago/Turabian StyleShaoting Ren; Evan Miles; Li Jia; Massimo Menenti; Marin Kneib; Pascal Buri; Michael McCarthy; Thomas Shaw; Wei Yang; Francesca Pellicciotti. 2021. "Anisotropy Parameterization Development and Evaluation for Glacier Surface Albedo Retrieval from Satellite Observations." Remote Sensing 13, no. 9: 1714.
The occurrence of natural vegetation at a given time is determined by interplay of multiple drivers. The effects of several drivers, e.g., geomorphology, topography, climate variability, accessibility, demographic indicators, and changes in human activities on the occurrence of natural vegetation in the severe drought periods and, prior to the year 2000, have been analyzed in West Africa. A binary logistic regression (BLR) model was developed to better understand whether the variability in these drivers over the past years was statistically significant in explaining the occurrence of natural vegetation in the year 2000. Our results showed that multiple drivers explained the occurrence of natural vegetation in West Africa at p < 0.05. The dominant drivers, however, were site-specific. Overall, human influence indicators were the dominant drivers in explaining the occurrence of natural vegetation in the selected hotspots. Human appropriation of net primary productivity (HANPP), which is an indicator of human socio-economic activities, explained the decreased likelihood of natural vegetation occurrence at all the study sites. However, the impacts of the remaining significant drivers on natural vegetation were either positive (increased the probability of occurrence) or negative (decreased the probability of occurrence), depending on the unique environmental and socio-economic conditions of the areas under consideration. The study highlights the significant role human activities play in altering the normal functioning of the ecosystem by means of a statistical model. The research contributes to a better understanding of the relationships and the interactions between multiple drivers and the response of natural vegetation in West Africa. The results are likely to be useful for planning climate change adaptation and sustainable development programs in West Africa.
Beatrice Asenso Barnieh; Li Jia; Massimo Menenti; Min Jiang; Jie Zhou; YeLong Zeng; Ali Bennour. Modeling the Underlying Drivers of Natural Vegetation Occurrence in West Africa with Binary Logistic Regression Method. Sustainability 2021, 13, 4673 .
AMA StyleBeatrice Asenso Barnieh, Li Jia, Massimo Menenti, Min Jiang, Jie Zhou, YeLong Zeng, Ali Bennour. Modeling the Underlying Drivers of Natural Vegetation Occurrence in West Africa with Binary Logistic Regression Method. Sustainability. 2021; 13 (9):4673.
Chicago/Turabian StyleBeatrice Asenso Barnieh; Li Jia; Massimo Menenti; Min Jiang; Jie Zhou; YeLong Zeng; Ali Bennour. 2021. "Modeling the Underlying Drivers of Natural Vegetation Occurrence in West Africa with Binary Logistic Regression Method." Sustainability 13, no. 9: 4673.
Lidar (light detection and ranging, also LIDAR, LiDAR, and LADAR) advanced rapidly after the invention of the laser in 1960 (Maiman, 1960; Woodbury et al., 1961; Smullin and Fiocco, 1962; Schotland, 1966; Cooney, 1968; Melfi et al., 1969). A variety of lidar technologies have been developed to provide atmospheric and surface properties during the last 60 years (Fiocco and Smullin, 1963; Weitkamp, 2005; Kashani et al., 2015) to support advancements in digital models of terrain, cryospheric discovery, terrestrial ecology, hydrology, atmospheric science, and oceanography. The successful lidar operations of NASA’s Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO, Winker et al., 2010) and Ice, Cloud, and land Elevation Satellite (ICESat, Markus et al., 2017) and ESA’s Aeolus wind satellite (Kanitz et al., 2020) highlight a new era of lidar developments and applications. Measurement concepts and technology are evolving simultaneously in different directions. Doppler lidars with different measurement capabilities are widely adopted by the wind energy industry (Krishnamurthy et al., 2012; Bos et al., 2016). Miniaturization and photon-counting instruments are opening completely new areas in science and applications with cheaper ground–based instruments and ultra-light, affordable drones. 3D surface mapping by imaging lidar is required across a broad – spectrum of applications, from construction projects (Pu and Vosselman, 2009) to understand land – atmosphere interactions (Colin et al., 2010; Faivre et al., 2017). The higher performance achievable by a time-correlated single-photon counting implemented in a multiple beams system has been documented (see e.g. Chen et al., 2018). A growing range of terrestrial, unmanned aerial vehicle (UAV or ‘drone’) (González-Jorge et al., 2017) and airborne scanning systems is attracting a wide community of professionals to deploy such systems to support large engineering projects and to monitor in great detail infrastructures of all sorts, from bridges to buildings and urban canyons (Wang et al., 2013; Roca et al., 2016). The role of lidar will be increasingly important in the future. Although there are many potentials for new lidar technology advancements, lidar activities are gradually shifting from technology developments to applications. Thus, discussions here mainly focus on the opportunities and challenges for advancing lidar applications in the future. To support operational lidar applications, transferring research lidars into turnkey systems and reduce their costs are necessary steps. During the last 20 years, advances in industrial lasers improved lidar system reliability and lowered system development and operational cost. Recent wind energy developments accelerated the low cost and turnkey Doppler lidar developments. Now micropulse type lidars are available for routine aerosol and water vapor measurements (Welton et al., 2001). Compact Raman lidars were demonstrated for airborne and ground-based operations (Wu et al., 2016; Lange et al., 2019). However, we still need to overcome many issues. First, atmospheric lidar system designs have to consider providing quantitative and automatic or semi-automatic lidar data processing. Second, enhancing system stability has to be one of the high priorities. Micropulse lidar (MPL) is one of the successful lidar designs to support aerosol and cloud observations, and the DOE/ARM program operated MPLs for the last 20 years. However, temporal variations of MPL system performance, especially in near range alignment, makes it difficult to use long-term MPL data to provide consistent long-term aerosol products. Third, it is critical to consider improving near-surface (within 500 m) measurements for ground-based lidar system design. Due to incomplete overlapping between the transmitting and receiving optical system, near-surface measurements of aerosol, water vapor, and temperature are often unavailable or with large uncertainties. However, these near-surface measurements are critical for many applications. Future lidar systems with ceilometer’s robustness and increased capabilities will enhance our atmospheric monitoring capabilities (Engelmann et al., 2016; Wu et al., 2016; Stillwell et al., 2020). The spatial variability of atmospheric properties and processes limits the values of single lidar measurements. Many existing lidar research networks, such as the European Aerosol Research Lidar Network (EARLINET, Pappalardo et al., 2014), the Asian Dust Network (AD-Net, Sugimoto et al., 2016), the National Aeronautics and Space Administration Micropulse lidar network (MPLNET, Welton et al., 2001), and the Network for the Detection of Atmospheric Composition Change (NDACC, De Mazière et al., 2018), were developed in the past with different success. For future operation supports, network lidar operations are critically needed (Bösenberg and Hoff, 2007; National Research Council, 2009; Wulfmeyer et al., 2015). Different-scale networks are needed to meet various application needs. Regional lidar networks can monitor urban air quality and cover the data gaps for weather models (Langford et al., 2018). A global lidar network is necessary to study stratospheric and mesospheric variations (Chu and Yu, 2017; De Mazière et al., 2018). Robust and cost-effective lidar systems are essential to support long-term operational lidar networks in the future. Global ceilometer (a simple elastic lidar) network is the most successful lidar network to support operation so far. Current efforts in using ceilometer vertical profiles to characterize the Planetary Boundary Layer (PBL) structure will further empower the ceilometer network (Hicks et al., 2019). Lidar technologies for temperature, water vapor, and wind measurements, which are regarded as a high priority to fill observation gaps (especially within PBL) to improve weather and air...
Zhien Wang; Massimo Menenti. Challenges and Opportunities in Lidar Remote Sensing. Frontiers in Remote Sensing 2021, 2, 1 .
AMA StyleZhien Wang, Massimo Menenti. Challenges and Opportunities in Lidar Remote Sensing. Frontiers in Remote Sensing. 2021; 2 ():1.
Chicago/Turabian StyleZhien Wang; Massimo Menenti. 2021. "Challenges and Opportunities in Lidar Remote Sensing." Frontiers in Remote Sensing 2, no. : 1.
A distributed hydrological energy-water-balance model (FEST-EWB) is calibrated over the Heihe Basin, a mainly desertic basin in China, employing remotely-sensed Land Surface Temperature (LST) (MODIS, 1-km resolution) as calibration variable. This approach overcomes the problem of model parameters characterization, which are usually difficult to define especially over large basins, allowing a pixel-by-pixel calibration, preserving the spatial heterogeneity. Hence, the spatial distribution of the modelled LST, but also of soil moisture (SM) and evapotranspiration (ET) is improved. The accuracy of the calibration process is documented through common statistical indexes. The modelled ET is compared locally against two eddy covariance stations in the agricultural area, while distributively against the ET estimates of the ETMonitor model and some global re-analysis products (ERA-Interim, GLDAS2, GLEAM and MERRA-2). Calibration and validation performed in this study prove that a considerable model accuracy is attainable even in extremely arid environments. An average LST bias of 2.6 °C is obtained over the basin. A good adaptation of FEST-EWB is also obtained against eddy-covariance stations ET with a little bias around −1 mm/d. On the other hand, the reanalysis products display a much worse performance, with higher absolute biases (around −3.5 mm/d), although with high variability among the models.
Nicola Paciolla; Chiara Corbari; Guangcheng Hu; Chaolei Zheng; Massimo Menenti; Li Jia; Marco Mancini. Evapotranspiration estimates from an energy-water-balance model calibrated on satellite land surface temperature over the Heihe basin. Journal of Arid Environments 2021, 188, 104466 .
AMA StyleNicola Paciolla, Chiara Corbari, Guangcheng Hu, Chaolei Zheng, Massimo Menenti, Li Jia, Marco Mancini. Evapotranspiration estimates from an energy-water-balance model calibrated on satellite land surface temperature over the Heihe basin. Journal of Arid Environments. 2021; 188 ():104466.
Chicago/Turabian StyleNicola Paciolla; Chiara Corbari; Guangcheng Hu; Chaolei Zheng; Massimo Menenti; Li Jia; Marco Mancini. 2021. "Evapotranspiration estimates from an energy-water-balance model calibrated on satellite land surface temperature over the Heihe basin." Journal of Arid Environments 188, no. : 104466.
Monitoring glacier flow is vital to understand the response of mountain glaciers to environmental forcing in the context of global climate change. Seasonal and interannual variability of surface velocity in the temperate glaciers of the Parlung Zangbo Basin (PZB) has attracted significant attention. Detailed patterns in glacier surface velocity and its seasonal variability in the PZB are still uncertain, however. We utilized Landsat-8 (L8) OLI data to investigate in detail the variability of glacier velocity in the PZB by applying the normalized image cross-correlation method. On the basis of satellite images acquired from 2013 to 2020, we present a map of time-averaged glacier surface velocity and examined four typical glaciers (Yanong, Parlung No.4, Xueyougu, and Azha) in the PZB. Next, we explored the driving factors of surface velocity and of its variability. The results show that the glacier centerline velocity increased slightly in 2017–2020. The analysis of meteorological data at two weather stations on the outskirts of the glacier area provided some indications of increased precipitation during winter-spring. Such increase likely had an impact on ice mass accumulation in the up-stream portion of the glacier. The accumulated ice mass could have caused seasonal velocity changes in response to mass imbalance during 2017–2020. Besides, there was a clear winter-spring speedup of 40% in the upper glacier region, while a summer speedup occurred at the glacier tongue. The seasonal and interannual velocity variability was captured by the transverse velocity profiles in the four selected glaciers. The observed spatial pattern and seasonal variability in glacier surface velocity suggests that the winter-spring snow might be a driver of glacier flow in the central and upper portions of glaciers. Furthermore, the variations in glacier surface velocity are likely related to topographic setting and basal slip caused by the percolation of rainfall. The findings on glacier velocity suggest that the transfer of winter-spring accumulated ice triggered by mass conservation seems to be the main driver of changes in glacier velocity. The reasons that influence the seasonal surface velocity change need further investigation.
Jing Zhang; Li Jia; Massimo Menenti; Shaoting Ren. Interannual and Seasonal Variability of Glacier Surface Velocity in the Parlung Zangbo Basin, Tibetan Plateau. Remote Sensing 2020, 13, 80 .
AMA StyleJing Zhang, Li Jia, Massimo Menenti, Shaoting Ren. Interannual and Seasonal Variability of Glacier Surface Velocity in the Parlung Zangbo Basin, Tibetan Plateau. Remote Sensing. 2020; 13 (1):80.
Chicago/Turabian StyleJing Zhang; Li Jia; Massimo Menenti; Shaoting Ren. 2020. "Interannual and Seasonal Variability of Glacier Surface Velocity in the Parlung Zangbo Basin, Tibetan Plateau." Remote Sensing 13, no. 1: 80.
The Surface Urban Heat Island Intensity (SUHII) when using nadir‐viewing radiometric and complete surface temperature (Tr and Tc ) was evaluated. The urban areas of the Kowloon peninsula and Hong Kong Island were selected, and four daytime Landsat TM images and two nighttime ASTER images were collected to retrieve Tr and then model Tc based on a semi‐empirical model. SUHIIs were estimated using both the retrieved Tr and modelled Tc. High spatial resolution (HR) airborne thermal images (0.2 m) observed at 12:10 noon on Oct 24 2017 were used to retrieve Tc directly. Results based on HR data and satellite data were consistent and indicated that the geometry of the built‐up space had a larger impact on SUHII when using Tc (SUHIIc) than Tr (SUHIIr). During daytime SUHIIc decreased while SUHIIr showed a very slight increase with building density. Both SUHIIc and SUHIIr decreased with higher building height but the rate of decrease of SUHIIc was higher than SUHIIr. Both SUHIIc and SUHIIr decreased with increasing building height variance and increased with increasing sky view factor (SVF). The rate of decrease with building height variance for SUHIIc was larger than SUHIIr. The rate of increase of SUHIIc with SVF was higher than SUHIIr. During nighttime, geometry effects on SUHIIc and SUHIIr were different from daytime. Both SUHIIc and SUHIIr increased with building density, while the rate of increase of SUHIIc with building density, as well as with building height, was much higher than SUHIIr. Both SUHIIc and SUHIIr decreased with SVF, but the rate of decrease of SUHIIc was higher than SUHIIr. Both SUHIIc and SUHIIr initially increased with building height variance and then remained approximately constant. We also evaluated the UHI intensity: SUHIIc was much closer to UHII than SUHIIr. Overall, building geometry had larger impact on SUHIIc than on SUHIIr, i.e. SUHIIc is more representative of urban climate than SUHIIr. This article is protected by copyright. All rights reserved.
Jinxin Yang; Massimo Menenti; Zhifeng Wu; Man Sing Wong; Sawaid Abbas; Yong Xu; Qian Shi. Assessing the impact of urban geometry on surface urban heat island using complete and nadir temperatures. International Journal of Climatology 2020, 41, 1 .
AMA StyleJinxin Yang, Massimo Menenti, Zhifeng Wu, Man Sing Wong, Sawaid Abbas, Yong Xu, Qian Shi. Assessing the impact of urban geometry on surface urban heat island using complete and nadir temperatures. International Journal of Climatology. 2020; 41 (S1):1.
Chicago/Turabian StyleJinxin Yang; Massimo Menenti; Zhifeng Wu; Man Sing Wong; Sawaid Abbas; Yong Xu; Qian Shi. 2020. "Assessing the impact of urban geometry on surface urban heat island using complete and nadir temperatures." International Journal of Climatology 41, no. S1: 1.
Post-classification change detection was applied to examine the nature of Land Use Land Cover (LULC) transitions in West Africa in three time intervals (1975–2000, 2000–2013, and 1975–2013). Detailed analyses at hotspots coupled with comparison of LULC transitions in the humid and arid regions were undertaken. Climate and anthropic drivers of environmental change were disentangled by the LULC transitions analyses. The results indicated that human-managed LULC types have replaced the natural LULC types. The total vegetation cover declined by −1.6%. Massive net gains in croplands (107.8%) and settlements (140%) at the expense of natural vegetation were detected in the entire period (1975–2013). Settlements expanded in parallel with cropland, which suggests the effort to increase food production to support the increasing population. Expansion of artificial water bodies were detected in the humid regions during the period of 1975–2000. Nonetheless, shrinking of water bodies due to encroachment by wetlands and other vegetation was observed in the arid regions, coupled with net loss in the whole of West Africa. The results indicate deforestation and degradation of natural vegetation and water resources in West Africa. Underlying anthropic drivers and a combination of anthropic and climate drivers were detected. LULC transitions in West Africa are location specific and have both positive and negative implications on the environment. The transitions indicate how processes at the local level, driven by human activities, lead to changes at the continental level and may contribute to global environmental change.
Beatrice Asenso Barnieh; Li Jia; Massimo Menenti; Jie Zhou; YeLong Zeng. Mapping Land Use Land Cover Transitions at Different Spatiotemporal Scales in West Africa. Sustainability 2020, 12, 8565 .
AMA StyleBeatrice Asenso Barnieh, Li Jia, Massimo Menenti, Jie Zhou, YeLong Zeng. Mapping Land Use Land Cover Transitions at Different Spatiotemporal Scales in West Africa. Sustainability. 2020; 12 (20):8565.
Chicago/Turabian StyleBeatrice Asenso Barnieh; Li Jia; Massimo Menenti; Jie Zhou; YeLong Zeng. 2020. "Mapping Land Use Land Cover Transitions at Different Spatiotemporal Scales in West Africa." Sustainability 12, no. 20: 8565.
Mountain glaciers are excellent indicators of climate change and have an important role in the terrestrial water cycle and food security in many parts of the world. Glaciers are the major water source of rivers and lakes in the Nyainqentanglha Mountains (NM) region, where the glacier area has the second largest extent on the Tibetan Plateau. The potential of the high spatial resolution ZiYuan-3 (ZY-3) Three-Line-Array (TLA) stereo images to retrieve glacier mass balance has not been sufficiently explored. In this study, we optimized the procedure to extract a Digital Elevation Model (DEM) from ZY-3 TLA stereo images and estimated the geodetic mass balance of representative glaciers in the two typical areas of the NM using ZY-3 DEMs and the C-band Shuttle Radar Topography Mission (SRTM) DEM in three periods, i.e., 2000–2013, 2013–2017 and 2000–2017. The results provide detailed information towards better understanding of glacier change and specifically show that: (1) with our new stereo procedure, ZY-3 TLA data can significantly increase point cloud density and decrease invalid data on the glacier surface map to generate a high resolution (5 m) glacier mass balance map; (2) the glacier mass balance in both the Western Nyainqentanglha Mountains (WNM) and Eastern Nyainqentanglha Mountains (ENM) was negative in 2000–2017, and experienced faster mass loss in recent years (2013–2017) in the WNM. Overall, the glaciers in the western and eastern NM show different change patterns since they are influenced by different climate regimes; the glacier mass balances in WNM was –0.22 ± 0.23 m w.e. a−1 and –0.43 ± 0.06 m w.e. a−1 in 2000–2013 and 2013–2017, respectively, while in 2000–2017, it was –0.30 ± 0.19 m w.e. a−1 in the WNM and –0.56 ± 0.20 m w.e. a−1 in the ENM; (3) in the WNM, the glaciers experienced mass loss in 2000–2013 and 2013–2017 in the ablation zone, while in the accumulation zone mass increased in 2000–2013 and a large mass loss occurred in 2013–2017; as regards the ENM, the glacier mass balance was negative in 2000–2017 in both zones; (4) glacier mass balance can be affected by the fractional abundance of debris and glacier slope; (5) the glacier mass balances retrieved by ZY-3 and TanDEM-X data agreed well in the ablation zone, while a large difference occurred in the accumulation zone because of the snow/firn penetration of the X-band SAR signal.
Shaoting Ren; Massimo Menenti; Li Jia; Jing Zhang; Jingxiao Zhang; Xin Li. Glacier Mass Balance in the Nyainqentanglha Mountains between 2000 and 2017 Retrieved from ZiYuan-3 Stereo Images and the SRTM DEM. Remote Sensing 2020, 12, 864 .
AMA StyleShaoting Ren, Massimo Menenti, Li Jia, Jing Zhang, Jingxiao Zhang, Xin Li. Glacier Mass Balance in the Nyainqentanglha Mountains between 2000 and 2017 Retrieved from ZiYuan-3 Stereo Images and the SRTM DEM. Remote Sensing. 2020; 12 (5):864.
Chicago/Turabian StyleShaoting Ren; Massimo Menenti; Li Jia; Jing Zhang; Jingxiao Zhang; Xin Li. 2020. "Glacier Mass Balance in the Nyainqentanglha Mountains between 2000 and 2017 Retrieved from ZiYuan-3 Stereo Images and the SRTM DEM." Remote Sensing 12, no. 5: 864.
Observing and understanding changes in Africa is a hotspot in global ecological environmental research since the early 1970s. As possible causes of environmental degradation, frequent droughts and human activities attracted wide attention. Remote sensing of nighttime light provides an effective way to map human activities and assess their intensity. To identify settlements more effectively, this study focused on nighttime light in the northern Equatorial Africa and Sahel settlements to propose a new method, namely, the patches filtering method (PFM) to identify nighttime lights related to settlements from the National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) monthly nighttime light data by separating signal components induced by biomass burning, thereby generating a new annual image in 2016. The results show that PFM is useful for improving the quality of NPP-VIIRS monthly nighttime light data. Settlement lights were effectively separated from biomass burning lights, in addition to capturing the seasonality of biomass burning. We show that the new 2016 nighttime light image can very effectively identify even small settlements, notwithstanding their fragmentation and unstable power supply. We compared the image with earlier NPP-VIIRS annual nighttime light data from the National Oceanic and Atmospheric Administration (NOAA) National Center for Environmental Information (NCEI) for 2016 and the Sentinel-2 prototype Land Cover 20 m 2016 map of Africa released by the European Space Agency (ESA-S2-AFRICA-LC20). We found that the new annual nighttime light data performed best among the three datasets in capturing settlements, with a high recognition rate of 61.8%, and absolute superiority for settlements of 2.5 square kilometers or less. This shows that the method separates biomass burning signals very effectively, while retaining the relatively stable, although dim, lights of small settlements. The new 2016 annual image demonstrates good performance in identifying human settlements in sparsely populated areas toward a better understanding of human activities.
Xiaotian Yuan; Li Jia; Massimo Menenti; Jie Zhou; Qiting Chen. Filtering the NPP-VIIRS Nighttime Light Data for Improved Detection of Settlements in Africa. Remote Sensing 2019, 11, 3002 .
AMA StyleXiaotian Yuan, Li Jia, Massimo Menenti, Jie Zhou, Qiting Chen. Filtering the NPP-VIIRS Nighttime Light Data for Improved Detection of Settlements in Africa. Remote Sensing. 2019; 11 (24):3002.
Chicago/Turabian StyleXiaotian Yuan; Li Jia; Massimo Menenti; Jie Zhou; Qiting Chen. 2019. "Filtering the NPP-VIIRS Nighttime Light Data for Improved Detection of Settlements in Africa." Remote Sensing 11, no. 24: 3002.
The complete surface temperature (Tc) in urban areas, defined as the mean temperature of the total active surface area, is an important variable in urban micro-climate research, specifically for assessment of the urban surface energy balance. Since most vertically-oriented building facets are not observed by a nadir-viewing remote imaging radiometer, the radiometric surface temperature (Tr) measured at a specific view angle cannot be used with existing heat transfer equations to estimate radiative and convective fluxes in the urban environment. Thus, it is necessary to derive Tc for city neighborhoods. This study develops a simple method to estimate Tc from Tr with the aid of the Temperatures of Urban Facets in 3D (TUF-3D) numerical model, which calculates 3-D sub-facet scale urban surface temperatures for a variety of surface geometries and properties, weather conditions and solar angles. The effects of geometric and meteorological characteristics – e.g., building planar area index (λp), wall facet area index (F), solar irradiance – on the difference between Tc and Tr were evaluated using the TUF-3D model. Results showed the effects of geometric and meteorological characteristics on the difference between Tc and Tr differ between daytime and nighttime. The study then sought to predict the relationship between Tr and Tc, using λp, F, and solar irradiance for daytime and only using λp and F for nighttime. Based on the simulated data from TUF-3D, the resulting relationships achieve a coefficient of determination (r2) of 0.97 and a RMSE of 1.5 K during daytime, with corresponding nighttime values of r2 = 0.98 and RMSE = 0.69 K. The relationships between Tr and Tc are evaluated using high resolution airborne thermal images of daytime urban scenes: r2 = 0.75 and RMSE = 1.09 K on August 6, 2013 at 12:40 pm; and r2 = 0.86 and RMSE = 1.86K on October 24, 2017 at 11:30 am. The new relationships were also applied to estimate Tc from Tr in Hong Kong retrieved from Landsat 5 Thematic Mapper (TM) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER). In the present climatic context, the difference between Tc and Tr can reach 10 K during daytime in summer, and 6 K during daytime in winter, with seasonal variation attributable to the variations in shortwave irradiance. The nighttime difference between Tc and Tr can also reach 2 K in both summer and spring seasons.
Jinxin Yang; Man Sing Wong; Hung Chak Ho; E. Scott Krayenhoff; P.W. Chan; Sawaid Abbas; Massimo Menenti. A semi-empirical method for estimating complete surface temperature from radiometric surface temperature, a study in Hong Kong city. Remote Sensing of Environment 2019, 237, 111540 .
AMA StyleJinxin Yang, Man Sing Wong, Hung Chak Ho, E. Scott Krayenhoff, P.W. Chan, Sawaid Abbas, Massimo Menenti. A semi-empirical method for estimating complete surface temperature from radiometric surface temperature, a study in Hong Kong city. Remote Sensing of Environment. 2019; 237 ():111540.
Chicago/Turabian StyleJinxin Yang; Man Sing Wong; Hung Chak Ho; E. Scott Krayenhoff; P.W. Chan; Sawaid Abbas; Massimo Menenti. 2019. "A semi-empirical method for estimating complete surface temperature from radiometric surface temperature, a study in Hong Kong city." Remote Sensing of Environment 237, no. : 111540.
The daily AMSR-E/NASA (the Advanced Microwave Scanning Radiometer-Earth Observing System/the National Aeronautics and Space Administration) and JAXA (the Japan Aerospace Exploration Agency) soil moisture (SM) products from 2002 to 2011 at 25 km resolution were developed and distributed by the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) and JAXA archives, respectively. This study analyzed and evaluated the temporal changes and accuracy of the AMSR-E/NASA SM product and compared it with the AMSR-E/JAXA SM product. The accuracy of both AMSR-E/NASA and JAXA SM was low, with RMSE (root mean square error) > 0.1 cm3 cm−3 against the in-situ SM measurements, especially the AMSR-E/NASA SM. Compared with the AMSR-E/JAXA SM, the dynamic range of AMSR-E/NASA SM is very narrow in many regions and does not reflect the intra- and inter-annual variability of soil moisture. We evaluated both data products by building a linear relationship between the SM and the Microwave Polarization Difference Index (MPDI) to simplify the AMSR-E/NASA SM retrieval algorithm on the basis of the observed relationship between samples extracted from the MPDI and SM data. We obtained the coefficients of this linear relationship (i.e., A0 and A1) using in-situ measurements of SM and brightness temperature (TB) data simulated with the same radiative transfer model applied to develop the AMSR-E/NASA SM algorithm. Finally, the linear relationships between the SM and MPDI were used to retrieve the SM monthly from AMSR-E TB data, and the estimated SM was validated using the in-situ SM measurements in the Naqu area on the Tibetan Plateau of China. We obtained a steeper slope, i.e., A1 = 8, with the in-situ SM measurements against A1 = 1, when using the NASA SM retrievals. The low A1 value is a measure of the low sensitivity of the NASA SM retrievals to MPDI and its narrow dynamic range. These results were confirmed by analyzing a data set collected in Poland. In the case of the Tibetan Plateau, the higher value A1 = 8 gave more accurate monthly AMSR-E SM retrievals with RMSE = 0.065 cm3 cm−3. The dynamic range of the improved retrievals was more consistent with the in-situ SM measurements than with both the AMSR-E/NASA and JAXA SM products in the Naqu area of the Tibetan Plateau in 2011.
Qiuxia Xie; Massimo Menenti; Li Jia. Improving the AMSR-E/NASA Soil Moisture Data Product Using In-Situ Measurements from the Tibetan Plateau. Remote Sensing 2019, 11, 2748 .
AMA StyleQiuxia Xie, Massimo Menenti, Li Jia. Improving the AMSR-E/NASA Soil Moisture Data Product Using In-Situ Measurements from the Tibetan Plateau. Remote Sensing. 2019; 11 (23):2748.
Chicago/Turabian StyleQiuxia Xie; Massimo Menenti; Li Jia. 2019. "Improving the AMSR-E/NASA Soil Moisture Data Product Using In-Situ Measurements from the Tibetan Plateau." Remote Sensing 11, no. 23: 2748.
Operational forest fire danger rating systems rely on the recent evolution of meteorological variables to estimate dead fuel condition. Further combining the latter with meteorological and environmental variables, they predict fire occurrence and spread. In this study we retrieved live fuel condition from MODIS multispectral measurements in the near infrared and shortwave infrared. Next, we combined these retrievals with an extensive dataset on actual forest fires in Campania (13,595 km2), Italy, to determine how live fuel condition affects the probability distribution functions of fire characteristics. Accordingly, the specific objective of this study was to develop and evaluate a new approach to estimate the probability distribution functions of fire burned area, duration and rate of spread as a function of the Perpendicular Moisture Index (PMI), whose value decreases with decreasing live fuel moisture content (LFMC). To this purpose, available fire data was intersected with MODIS 8-day composited reflectance data so to associate each fire event with the corresponding pre-fire PMI observation. Fires were then grouped in ten decile bins of PMI, and the conditional probability distribution functions of burned area, fire duration and rate of spread were determined in each bin. Distributions of burned area and rate of spread vary across PMI decile bins, while no significant difference was observed for fire duration. Further testing this result with a likelihood ratio test confirmed that PMI is a covariate of burned area and rate of spread, but not of fire duration. We defined an extreme event as a fire whose burned area (respectively rate of spread) exceeds the 95th percentile of the frequency distribution of all observed fire events. The probability distribution functions in the ten decile bins of PMI were combined to obtain a conditional probability distribution function, which was then used to predict the probability of extreme fires, as defined. It was found that the probability of extreme events steadily increases with decreasing PMI. Overall, at the end of the dry season the probability of extreme events is about the double than at the beginning. These results may be used to produce frequently (e.g. daily) updated maps of the probability of extreme events given a PMI map retrieved from e.g. MODIS reflectance data.
Carmine Maffei; Massimo Menenti. Predicting forest fires burned area and rate of spread from pre-fire multispectral satellite measurements. ISPRS Journal of Photogrammetry and Remote Sensing 2019, 158, 263 -278.
AMA StyleCarmine Maffei, Massimo Menenti. Predicting forest fires burned area and rate of spread from pre-fire multispectral satellite measurements. ISPRS Journal of Photogrammetry and Remote Sensing. 2019; 158 ():263-278.
Chicago/Turabian StyleCarmine Maffei; Massimo Menenti. 2019. "Predicting forest fires burned area and rate of spread from pre-fire multispectral satellite measurements." ISPRS Journal of Photogrammetry and Remote Sensing 158, no. : 263-278.
This study on a large irrigation scheme in Morocco addressed a two-fold question: (a) does the local water management authority adapt water releases to atmospheric water demand ET0-P? and (b) does crop actual evapotranspiration respond to inter- and intra-annual variability in water releases? We have evaluated the inter-annual variability of ET0-P during the period 1992–2017 and compared its anomalies (i.e., deviations from average) with anomalies in annual water release. Overall, it appeared that anomalies in water release were consistent with anomalies in ET0-P. The actual evapotranspiration (ETa) was estimated using a time series of multi-spectral satellite image data by applying the Surface Energy Balance (SEBAL) algorithm in a dry, wet, and reference year. We have determined the quartiles of the distribution of the ET0-P time series to identify these three years. The dry year was 2015–2016, the wet year was 2014–2015, and the reference (median of ET0-P) was 2013–2014. Finally, we compared seasonal and annual anomalies in ET0-P, ETa and release, Wd of irrigation water. In the period 1992–2017, the relative anomalies in ET0-P and Wd were similar only in 2000–2001 and 2015–2016. The analysis of anomalies in water inflow and stocks confirmed the response in increased Wd following wet years with higher inflow and replenishment of the reservoir. The response of crop water use to the irrigation water supply was evaluated by comparing anomalies in the ratio of actual to maximum ET, i.e., ETa/ETc with anomalies in Wd. As regards the Sidi Bennour, Faregh, and Gharbia districts, the relative anomalies in ETa/ETc and Wd were consistent, i.e., they had the same sign and comparable magnitude. Overall, the study shows that water delivery Wd responds to inter-annual variability in the pre-irrigation season water inflows into the reservoirs, rather than in ET0-P. On the other hand, actual crop water use, i.e., ETa/ETc, does respond to inter- and intra-annual variability in Wd. This evidence suggests that there is scope for adaptive water management based on a flexible adaptation of water release to inter- and intra-annual variability in water demand.
Fatima-Ezzahra El Ghandour; Silvia Maria Alfieri; Youssef Houali; Adnane Habib; Nadia Akdim; Kamal Labbassi; Massimo Menenti. Detecting the Response of Irrigation Water Management to Climate by Remote Sensing Monitoring of Evapotranspiration. Water 2019, 11, 2045 .
AMA StyleFatima-Ezzahra El Ghandour, Silvia Maria Alfieri, Youssef Houali, Adnane Habib, Nadia Akdim, Kamal Labbassi, Massimo Menenti. Detecting the Response of Irrigation Water Management to Climate by Remote Sensing Monitoring of Evapotranspiration. Water. 2019; 11 (10):2045.
Chicago/Turabian StyleFatima-Ezzahra El Ghandour; Silvia Maria Alfieri; Youssef Houali; Adnane Habib; Nadia Akdim; Kamal Labbassi; Massimo Menenti. 2019. "Detecting the Response of Irrigation Water Management to Climate by Remote Sensing Monitoring of Evapotranspiration." Water 11, no. 10: 2045.
Small reservoirs play an important role in mining, industries, and agriculture, but storage levels or stage changes are very dynamic. Accurate and up-to-date maps of surface water storage and distribution are invaluable for informing decisions relating to water security, flood monitoring, and water resources management. Satellite remote sensing is an effective way of monitoring the dynamics of surface waterbodies over large areas. The European Space Agency (ESA) has recently launched constellations of Sentinel-1 (S1) and Sentinel-2 (S2) satellites carrying C-band synthetic aperture radar (SAR) and a multispectral imaging radiometer, respectively. The constellations improve global coverage of remotely sensed imagery and enable the development of near real-time operational products. This unprecedented data availability leads to an urgent need for the application of fully automatic, feasible, and accurate retrieval methods for mapping and monitoring waterbodies. The mapping of waterbodies can take advantage of the synthesis of SAR and multispectral remote sensing data in order to increase classification accuracy. This study compares automatic thresholding to machine learning, when applied to delineate waterbodies with diverse spectral and spatial characteristics. Automatic thresholding was applied to near-concurrent normalized difference water index (NDWI) (generated from S2 optical imagery) and VH backscatter features (generated from S1 SAR data). Machine learning was applied to a comprehensive set of features derived from S1 and S2 data. During our field surveys, we observed that the waterbodies visited had different sizes and varying levels of turbidity, sedimentation, and eutrophication. Five machine learning algorithms (MLAs), namely decision tree (DT), k-nearest neighbour (k-NN), random forest (RF), and two implementations of the support vector machine (SVM) were considered. Several experiments were carried out to better understand the complexities involved in mapping spectrally and spatially complex waterbodies. It was found that the combination of multispectral indices with SAR data is highly beneficial for classifying complex waterbodies and that the proposed thresholding approach classified waterbodies with an overall classification accuracy of 89.3%. However, the varying concentrations of suspended sediments (turbidity), dissolved particles, and aquatic plants negatively affected the classification accuracies of the proposed method, whereas the MLAs (SVM in particular) were less sensitive to such variations. The main disadvantage of using MLAs for operational waterbody mapping is the requirement for suitable training samples, representing both water and non-water land covers. The dynamic nature of reservoirs (many reservoirs are depleted at least once a year) makes the re-use of training data unfeasible. The study found that aggregating (combining) the thresholding results of two SAR and multispectral features, namely the S1 VH polarisation and the S2 NDWI, respectively, provided better overall accuracies than when thresholding was applied to any of the individual features considered. The accuracies of this dual thresholding technique were comparable to those of machine learning and may thus offer a viable solution for automatic mapping of waterbodies.
Tsitsi Bangira; Silvia Maria Alfieri; Massimo Menenti; Adriaan Van Niekerk. Comparing Thresholding with Machine Learning Classifiers for Mapping Complex Water. Remote Sensing 2019, 11, 1351 .
AMA StyleTsitsi Bangira, Silvia Maria Alfieri, Massimo Menenti, Adriaan Van Niekerk. Comparing Thresholding with Machine Learning Classifiers for Mapping Complex Water. Remote Sensing. 2019; 11 (11):1351.
Chicago/Turabian StyleTsitsi Bangira; Silvia Maria Alfieri; Massimo Menenti; Adriaan Van Niekerk. 2019. "Comparing Thresholding with Machine Learning Classifiers for Mapping Complex Water." Remote Sensing 11, no. 11: 1351.
Sensible heat exchange has important consequences for urban meteorology and related applications. Directional radiometric surface temperatures of urban canopies observed by remote sensing platforms have the potential to inform estimations of urban sensible heat flux. An imaging radiometer viewing the surface from nadir cannot capture the complete urban surface temperature, which is defined as the mean surface temperature over all urban facets in three dimensions, which includes building wall surface temperatures and requires an estimation of urban sensible heat flux. In this study, a numerical microclimate model, Temperatures of Urban Facets in 3-D (TUF-3D), was used to model sensible heat flux as well as radiometric and complete surface temperatures. Model data were applied to parameterize an effective resistance for the calculation of urban sensible heat flux from the radiometric (nadir view) surface temperature. The results showed that sensible heat flux was overestimated during daytime when the radiometric surface temperature was used without the effective resistance that accounts for the impact of wall surface temperature on heat flux. Parameterization of this additional resistance enabled reasonably accurate estimates of urban sensible heat flux from the radiometric surface temperature.
Jinxin Yang; Massimo Menenti; E. Scott Krayenhoff; Zhifeng Wu; Qian Shi; Xiaoying Ouyang. Parameterization of Urban Sensible Heat Flux from Remotely Sensed Surface Temperature: Effects of Surface Structure. Remote Sensing 2019, 11, 1347 .
AMA StyleJinxin Yang, Massimo Menenti, E. Scott Krayenhoff, Zhifeng Wu, Qian Shi, Xiaoying Ouyang. Parameterization of Urban Sensible Heat Flux from Remotely Sensed Surface Temperature: Effects of Surface Structure. Remote Sensing. 2019; 11 (11):1347.
Chicago/Turabian StyleJinxin Yang; Massimo Menenti; E. Scott Krayenhoff; Zhifeng Wu; Qian Shi; Xiaoying Ouyang. 2019. "Parameterization of Urban Sensible Heat Flux from Remotely Sensed Surface Temperature: Effects of Surface Structure." Remote Sensing 11, no. 11: 1347.
Glaciers in the Tibetan Plateau are an important indicator of climate change. Automatic glacier facies mapping utilizing remote sensing data is challenging due to the spectral similarity of supraglacial debris and the adjacent bedrock. Most of the available glacier datasets do not provide the boundary of clean ice and debris-covered glacier facies, while debris-covered glacier facies play a key role in mass balance research. The aim of this study was to develop an automatic algorithm to distinguish ice cover types based on multi-temporal satellite data, and the algorithm was implemented in a subregion of the Parlung Zangbo basin in the southeastern Tibetan Plateau. The classification method was built upon an automated machine learning approach: Random Forest in combination with the analysis of topographic and textural features based on Landsat-8 imagery and multiple digital elevation model (DEM) data. Very high spatial resolution Gao Fen-1 (GF-1) Panchromatic and Multi-Spectral (PMS) imagery was used to select training samples and validate the classification results. In this study, all of the land cover types were classified with overall good performance using the proposed method. The results indicated that fully debris-covered glaciers accounted for approximately 20.7% of the total glacier area in this region and were mainly distributed at elevations between 4600 m and 4800 m above sea level (a.s.l.). Additionally, an analysis of the results clearly revealed that the proportion of small size glaciers (
Jingxiao Zhang; Li Jia; Massimo Menenti; Guangcheng Hu. Glacier Facies Mapping Using a Machine-Learning Algorithm: The Parlung Zangbo Basin Case Study. Remote Sensing 2019, 11, 452 .
AMA StyleJingxiao Zhang, Li Jia, Massimo Menenti, Guangcheng Hu. Glacier Facies Mapping Using a Machine-Learning Algorithm: The Parlung Zangbo Basin Case Study. Remote Sensing. 2019; 11 (4):452.
Chicago/Turabian StyleJingxiao Zhang; Li Jia; Massimo Menenti; Guangcheng Hu. 2019. "Glacier Facies Mapping Using a Machine-Learning Algorithm: The Parlung Zangbo Basin Case Study." Remote Sensing 11, no. 4: 452.
Thermal InfraRed (TIR) image data at high temporal and spatial resolution are required to monitor the rapid development of crops during the growing season, taking into account the fragmentation of most agricultural landscapes. Moreover, integrating high-resolution satellite TIR data to calibrate hydrological models is a powerful information to efficiently monitor crop water use. Conversely, no single sensor meets these combined requirements in the TIR spectral region. Data fusion approaches offer an alternative to exploit observations from multiple sensors, providing image data to meet the combined requirements on spatial and temporal resolution. A novel spatio-temporal data fusion workflow based on a multi-sensor multi-resolution algorithm was developed and applied to generate TIR synthetic image data at high temporal and spatial resolution. The workflow includes two steps: in the first step, synthetic daily radiance images at Top of Atmosphere (TOA) and 30-m spatial resolution (at the ground) are generated using TIR radiometric data at TOA collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) daily 1-km and Landsat 8/TIRS 16-day 30-m. This procedure is applied to two image pairs on different dates. The workflow yields an estimator to generate TIR TOA radiance data on any given date, provided a MODIS radiance image is available. The next step applies constrained unmixing of the 30 m (now considered as low-resolution) TIR images using the information about sub-pixel land-cover obtained from co-registered images at higher spatial resolution in the VNIR (Visible Near InfraRed) spectrum. In our case study, the L8/TIRS synthetic image data were unmixed to the Sentinel 2/MSI with 10 m × 10 m spatial resolution. Two geographically diverse experiments were carried out using the same procedure: one in The Netherlands to evaluate the procedure and other in Puglia (Italy) to generate a time series of the 10-m × 10-m TIR image data product. The validation experiment, where an actual TIRS image was applied as a reference, gave a RMSE value of 35.3 W/(m2 μm sr), which corresponds to a relative value of 8.5% against the TIRS reference values. The results confirm the feasibility of the proposed methodology, which yields a synthetic thermal band to integrate with the multi-spectral data provided by the S2/MSI at 10 m resolution.
M. Herrero-Huerta; S. Lagüela; S.M. Alfieri; M. Menenti. Generating high-temporal and spatial resolution TIR image data. International Journal of Applied Earth Observation and Geoinformation 2019, 78, 149 -162.
AMA StyleM. Herrero-Huerta, S. Lagüela, S.M. Alfieri, M. Menenti. Generating high-temporal and spatial resolution TIR image data. International Journal of Applied Earth Observation and Geoinformation. 2019; 78 ():149-162.
Chicago/Turabian StyleM. Herrero-Huerta; S. Lagüela; S.M. Alfieri; M. Menenti. 2019. "Generating high-temporal and spatial resolution TIR image data." International Journal of Applied Earth Observation and Geoinformation 78, no. : 149-162.