scholarly journals Regional environmental controllers influence continental scale soil carbon stocks and future carbon dynamics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Daniel Ruiz Potma Gonçalves ◽  
Umakant Mishra ◽  
Skye Wills ◽  
Sagar Gautam
Keyword(s):  
Environmental Factors ◽  
Land Cover ◽  
Environmental Conditions ◽  
Climate Feedback ◽  
Soil Types ◽  
Climatic Data ◽  
Earth System ◽  
Land Cover Types ◽  
Continental Scale ◽  
Soc Stocks

AbstractUnderstanding the influence of environmental factors on soil organic carbon (SOC) is critical for quantifying and reducing the uncertainty in carbon climate feedback projections under changing environmental conditions. We explored the effect of climatic variables, land cover types, topographic attributes, soil types and bedrock geology on SOC stocks of top 1 m depth across conterminous United States (US) ecoregions. Using 4559 soil profile observations and high-resolution data of environmental factors, we identified dominant environmental controllers of SOC stocks in 21 US ecoregions using geographically weighted regression. We used projected climatic data of SSP126 and SSP585 scenarios from GFDL-ESM 4 Earth System Model of Coupled Model Intercomparison Project phase 6 to predict SOC stock changes across continental US between 2030 and 2100. Both baseline and predicted changes in SOC stocks were compared with SOC stocks represented in GFDL-ESM4 projections. Among 56 environmental predictors, we found 12 as dominant controllers across all ecoregions. The adjusted geospatial model with the 12 environmental controllers showed an R2 of 0.48 in testing dataset. Higher precipitation and lower temperatures were associated with higher levels of SOC stocks in majority of ecoregions. Changes in land cover types (vegetation properties) was important in drier ecosystem as North American deserts, whereas soil types and topography were more important in American prairies. Wetlands of the Everglades was highly sensitive to projected temperature changes. The SOC stocks did not change under SSP126 until 2100, however SOC stocks decreased up to 21% under SSP585. Our results, based on environmental controllers of SOC stocks, help to predict impacts of changing environmental conditions on SOC stocks more reliably and may reduce uncertainties found in both, geospatial and Earth System Models. In addition, the description of different environmental controllers for US ecoregions can help to describe the scope and importance of global and local models.

scholarly journals Improving the Radiance Assimilation Performance in Estimating Snow Water Storage across Snow and Land-Cover Types in North America

2017 ◽  
Vol 18 (3) ◽  
pp. 651-668 ◽  
Author(s):  
Yonghwan Kwon ◽  
Zong-Liang Yang ◽  
Timothy J. Hoar ◽  
Ally M. Toure
Keyword(s):  
North America ◽  
Radiative Transfer ◽  
Land Cover ◽  
Snow Depth ◽  
Microwave Emission ◽  
Emission Model ◽  
Land Cover Types ◽  
Continental Scale ◽  
Community Land Model ◽  
Radiance Assimilation

Abstract Continental-scale snow radiance assimilation (RA) experiments are conducted in order to improve snow estimates across snow and land-cover types in North America. In the experiments, the ensemble adjustment Kalman filter is applied and the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature TB observations are assimilated into an RA system composed of the Community Land Model, version 4 (CLM4); radiative transfer models (RTMs); and the Data Assimilation Research Testbed (DART). The performance of two snowpack RTMs, the Dense Media Radiative Transfer–Multi-Layers model (DMRT-ML), and the Microwave Emission Model of Layered Snowpacks (MEMLS) in improving snow depth estimates through RA is compared. Continental-scale snow estimates are enhanced through RA by using AMSR-E TB at the 18.7- and 23.8-GHz channels [3% (DMRT-ML) and 2% (MEMLS) improvements compared to the cases using the 18.7- and 36.5-GHz channels] and by considering the vegetation single-scattering albedo ω [2.5% (DMRT-ML) and 4.8% (MEMLS) improvements compared to the cases neglecting ω]. The contribution of TB of the vegetation canopy to TB at the top of the atmosphere is better represented by considering ω in the RA system, and improvements in the resulting snow depth are evident for the forest land-cover type (about 5%–11%) and the taiga and alpine snow classes (about 5%–11% and 4%–8%, respectively), especially in the MEMLS case. Compared to the open-loop run (0.171-m snow depth RMSE), about 7% (DMRT-ML) and 10% (MEMLS) overall improvements of the RA performance are achieved.

scholarly journals Accuracy Assessment of the FROM-GLC30 Land Cover Dataset Based on Watershed Sampling Units: A Continental-Scale Study

2020 ◽  
Vol 12 (20) ◽  
pp. 8435
Author(s):  
Zitian Guo ◽  
Chunmei Wang ◽  
Xin Liu ◽  
Guowei Pang ◽  
Mengyang Zhu ◽  
...  
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Large Scale ◽  
Reference Data ◽  
Accuracy Assessment ◽  
Visual Interpretation ◽  
Land Cover Types ◽  
Practical Applications ◽  
Land Type ◽  
Continental Scale

Land cover information plays an essential role in the study of global surface change. Multiple land cover datasets have been produced to meet various application needs. The FROM-GLC30 (Finer Resolution Observation and Monitoring of Global Land Cover) dataset is one of the latest land cover products with a resolution of 30 m, which is a relatively high resolution among global public datasets, and the accuracy of this dataset is of great concern in many related researches. The objective of this study was to calculate the accuracy of the FROM-GLC30 2017 dataset at the continental scale and to explore the spatial variation differences of each land type accuracy in different regions. In this study, the visual interpretation land cover results at 20,936 small watershed sampling units based on high-resolution remote sensing images were used as the reference data covering 65 countries in Asia, Europe, and Africa. The reference data were verified by field survey in typical watersheds. Based on that, the accuracy assessment of the FROM-GLC30 2017 dataset was carried out. The results showed (1) the area proportion of different land cover types in the FROM-GLC30 2017 dataset was generally consistent with that of the reference data. (2) The overall accuracy of the FROM-GLC30 2017 dataset was 72.78%, and was highest in West Asia–Northeast Africa, and lowest in South Asia. (3) Among all the seven land cover types, the accuracy of bareland and forest was relatively higher than that of others, and the accuracy of shrubland was the lowest. The accuracy for each land cover type differed among regions. The results of this work can provide useful information for land cover accuracy assessment researches at a large scale and promote the further practical applications of the open-source land cover datasets.

Soil moisture dynamics of different land-cover types in the blacksoil regions of China

2009 ◽  
Vol 17 (2) ◽  
pp. 256-260 ◽  
Author(s):  
Feng WANG ◽  
Shu-Qi WANG ◽  
Xiao-Zeng HAN ◽  
Feng-Xian WANG ◽  
Ke-Qiang ZHANG
Keyword(s):  
Soil Moisture ◽  
Land Cover ◽  
Soil Moisture Dynamics ◽  
Land Cover Types ◽  
Moisture Dynamics

scholarly journals Tree Species Diversity, Composition and Aboveground Biomass Across Dry Forest Land-Cover Types in Coastal Ecuador

2021 ◽  
Vol 14 ◽  
pp. 194008292199541
Author(s):  
Xavier Haro-Carrión ◽  
Bette Loiselle ◽  
Francis E. Putz
Keyword(s):  
Species Diversity ◽  
Land Cover ◽  
Community Composition ◽  
Aboveground Biomass ◽  
Tree Species ◽  
Dry Forest ◽  
Stem Density ◽  
Tree Species Diversity ◽  
Land Cover Types ◽  
Schizolobium Parahyba

Tropical dry forests (TDF) are highly threatened ecosystems that are often fragmented due to land-cover change. Using plot inventories, we analyzed tree species diversity, community composition and aboveground biomass patterns across mature (MF) and secondary forests of about 25 years since cattle ranching ceased (SF), 10–20-year-old plantations (PL), and pastures in a TDF landscape in Ecuador. Tree diversity was highest in MF followed by SF, pastures and PL, but many endemic and endangered species occurred in both MF and SF, which demonstrates the importance of SF for species conservation. Stem density was higher in PL, followed by SF, MF and pastures. Community composition differed between MF and SF due to the presence of different specialist species. Some SF specialists also occurred in pastures, and all species found in pastures were also recorded in SF indicating a resemblance between these two land-cover types even after 25 years of succession. Aboveground biomass was highest in MF, but SF and Tectona grandis PL exhibited similar numbers followed by Schizolobium parahyba PL, Ochroma pyramidale PL and pastures. These findings indicate that although species-poor, some PL equal or surpass SF in aboveground biomass, which highlights the critical importance of incorporating biodiversity, among other ecosystem services, to carbon sequestration initiatives. This research contributes to understanding biodiversity conservation across a mosaic of land-cover types in a TDF landscape.

scholarly journals Cooling Effect of Different Land Cover Types: A Case Study in Xi’an and Xianyang, China

2021 ◽  
Vol 13 (3) ◽  
pp. 1099
Author(s):  
Yuhe Ma ◽  
Mudan Zhao ◽  
Jianbo Li ◽  
Jian Wang ◽  
Lifa Hu
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Cooling Effect ◽  
Heat Island ◽  
Land Cover Types ◽  
Island Effect ◽  
Urban Heat

One of the climate problems caused by rapid urbanization is the urban heat island effect, which directly threatens the human survival environment. In general, some land cover types, such as vegetation and water, are generally considered to alleviate the urban heat island effect, because these landscapes can significantly reduce the temperature of the surrounding environment, known as the cold island effect. However, this phenomenon varies over different geographical locations, climates, and other environmental factors. Therefore, how to reasonably configure these land cover types with the cooling effect from the perspective of urban planning is a great challenge, and it is necessary to find the regularity of this effect by designing experiments in more cities. In this study, land cover (LC) classification and land surface temperature (LST) of Xi’an, Xianyang and its surrounding areas were obtained by Landsat-8 images. The land types with cooling effect were identified and their ideal configuration was discussed through grid analysis, distance analysis, landscape index analysis and correlation analysis. The results showed that an obvious cooling effect occurred in both woodland and water at different spatial scales. The cooling distance of woodland is 330 m, much more than that of water (180 m), but the land surface temperature around water decreased more than that around the woodland within the cooling distance. In the specific urban planning cases, woodland can be designed with a complex shape, high tree planting density and large planting areas while water bodies with large patch areas to cool the densely built-up areas. The results of this study have utility for researchers, urban planners and urban designers seeking how to efficiently and reasonably rearrange landscapes with cooling effect and in urban land design, which is of great significance to improve urban heat island problem.

SateLoc: A Virtual Fingerprinting Approach to Outdoor LoRa Localization Using Satellite Images

2021 ◽  
Vol 17 (4) ◽  
pp. 1-28
Author(s):  
Yuxiang Lin ◽  
Wei Dong ◽  
Yi Gao ◽  
Tao Gu
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Satellite Images ◽  
Low Cost ◽  
Tracking Error ◽  
Location Based Services ◽  
Distance Constraint ◽  
Combination Strategy ◽  
Land Cover Types ◽  
High Resolution Satellite Images

With the increasing relevance of the Internet of Things and large-scale location-based services, LoRa localization has been attractive due to its low-cost, low-power, and long-range properties. However, existing localization approaches based on received signal strength indicators are either easily affected by signal fading of different land-cover types or labor intensive. In this work, we propose SateLoc, a LoRa localization system that utilizes satellite images to generate virtual fingerprints. Specifically, SateLoc first uses high-resolution satellite images to identify land-cover types. With the path loss parameters of each land-cover type, SateLoc can automatically generate a virtual fingerprinting map for each gateway. We then propose a novel multi-gateway combination strategy, which is weighted by the environmental interference of each gateway, to produce a joint likelihood distribution for localization and tracking. We implement SateLoc with commercial LoRa devices without any hardware modification, and evaluate its performance in a 227,500-m urban area. Experimental results show that SateLoc achieves a median localization error of 43.5 m, improving more than 50% compared to state-of-the-art model-based approaches. Moreover, SateLoc can achieve a median tracking error of 37.9 m with the distance constraint of adjacent estimated locations. More importantly, compared to fingerprinting-based approaches, SateLoc does not require the labor-intensive fingerprint acquisition process.

scholarly journals An investigation of the effects of environmental and ecologic factors on cutaneous leishmaniasis in the old world: a systematic review study

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Abolfazl Mohammadbeigi ◽  
Salman Khazaei ◽  
Hamidreza Heidari ◽  
Azadeh Asgarian ◽  
Shahram Arsangjang ◽  
...  
Keyword(s):  
Systematic Review ◽  
Environmental Factors ◽  
Land Cover ◽  
Cutaneous Leishmaniasis ◽  
Weather Condition ◽  
Weather Conditions ◽  
Eligibility Criteria ◽  
Screening Process ◽  
Old World ◽  
Review Study

AbstractObjectivesLeishmaniasis is a neglected and widespread parasitic disease that can lead to serious health problems. The current review study aimed to synthesize the relationship between ecologic and environmental factors (e.g., weather conditions, climatology, temperature and topology) and the incidence of cutaneous leishmaniasis (CL) in the Old World.ContentA systematic review was conducted based on English, and Persian articles published from 2015 to 2020 in PubMed/Medline, Science Direct, Web of Science and Google Scholar. Keywords used to search articles were leishmaniasis, environmental factors, weather condition, soil, temperature, land cover, ecologic* and topogr*. All articles were selected and assessed for eligibility according to the titles or abstracts. The quality screening process of articles was carried out by two independent authors. The selected articles were checked according to the inclusion and exclusion criteria.Summary and outlookA total of 827 relevant records in 2015–2020 were searched and after evaluating the articles, 23 articles met the eligibility criteria; finally, 14 full-text articles were included in the systematic review. Two different categories of ecologic/environmental factors (weather conditions, temperature, rainfall/precipitation and humidity) and land characteristics (land cover, slope, elevation and altitude, earthquake and cattle sheds) were the most important factors associated with CL incidence.ConclusionsTemperature and rainfall play an important role in the seasonal cycle of CL as many CL cases occurred in arid and semiarid areas in the Old World. Moreover, given the findings of this study regarding the effect of weather conditions on CL, it can be concluded that designing an early warning system is necessary to predict the incidence of CL based on different weather conditions.

Sign in / Sign up

Export Citation Format

Share Document