Contributions of different land cover types in Otindag Sandy Land and Bashang area of Hebei Province to the material source of sand stormy weather in Beijing

2003 ◽  
Vol 48 (17) ◽  
pp. 1853-1856 ◽  
Author(s):  
Hongyan Liu ◽  
Yuhong Tian ◽  
Deng Ding
Keyword(s):  
Land Cover ◽  
Hebei Province ◽  
Sandy Land ◽  
Material Source ◽  
Land Cover Types ◽  
Stormy Weather ◽  
Otindag Sandy Land

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 Exploring the Use of PlanetScope Data for Particulate Matter Air Quality Research

2021 ◽  
Vol 13 (15) ◽  
pp. 2981
Author(s):  
Jeanné le Roux ◽  
Sundar Christopher ◽  
Manil Maskey
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Land Cover ◽  
Spectral Response ◽  
Fine Particulate Matter ◽  
Daily Basis ◽  
Land Cover Types ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference ◽  
Geolocation Accuracy

Planet, a commercial company, has achieved a key milestone by launching a large fleet of small satellites (smallsats) that provide high spatial resolution imagery of the entire Earth’s surface on a daily basis with its PlanetScope sensors. Given the potential utility of these data, this study explores the use for fine particulate matter (PM2.5) air quality applications. However, before these data can be utilized for air quality applications, key features of the data, including geolocation accuracy, calibration quality, and consistency in spectral signatures, need to be addressed. In this study, selected Dove-Classic PlanetScope data is screened for geolocation consistency. The spectral response of the Dove-Classic PlanetScope data is then compared to Moderate Resolution Imaging Spectroradiometer (MODIS) data over different land cover types, and under varying PM2.5 and mid visible aerosol optical depth (AOD) conditions. The data selected for this study was found to fall within Planet’s reported geolocation accuracy of 10 m (between 3–4 pixels). In a comparison of top of atmosphere (TOA) reflectance over a sample of different land cover types, the difference in reflectance between PlanetScope and MODIS ranged from near-zero (0.0014) to 0.117, with a mean difference in reflectance of 0.046 ± 0.031 across all bands. The reflectance values from PlanetScope were higher than MODIS 78% of the time, although no significant relationship was found between surface PM2.5 or AOD and TOA reflectance for the cases that were studied. The results indicate that commercial satellite data have the potential to address Earth-environmental issues.

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.

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