scholarly journals The hydrological responses of different land cover types in a re-vegetation catchment area of the Loess Plateau, China

2012 ◽  
Vol 9 (5) ◽  
pp. 5809-5835 ◽  
Author(s):  
S. Wang ◽  
B. J. Fu ◽  
G. Y. Gao ◽  
J. Zhou
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Land Cover ◽  
Water Loss ◽  
The Other ◽  
Land Cover Type ◽  
Land Cover Types ◽  
Cover Type ◽  
Daily Water ◽  
The Impact

Abstract. The impact of re-vegetation on soil moisture dynamics was investigated by comparing five land cover types. Soil moisture and temperature variations under grass (Andropogon), subshrub (Artemisia scoparia), shrub (Spiraea pubescens), tree (Robinia pseudoacacia), and crop (Zea mays) vegetation were monitored in an experiment performed during the growing season of 2011. There were more than 10 soil moisture pulses during the period of data collection, and the surface soil moisture of all of the land cover types showed an increasing trend. Corn cover was associated with consistently higher soil moisture readings than the other surfaces. Grass and subshrubs showed an intermediate moisture level, with that of grass being slightly higher than that of subshrub most of the time. Shrubs and trees were characterized by lower soil moisture readings, with the shrub levels consistently being slightly higher than those of the trees. With the exception of the corn land cover type, the average soil temperature showed the same regime as the average moisture content, but exhibiting a downward trend throughout the observation period. Three typical decreasing periods were chosen to compare the differences in water losses. In periods of both relatively lower and higher water soil moisture contents, subshrubs lost the largest amount of water. The daily water loss associated with corn was most variable. The tree and shrub sites presented an intermediate level, with that of tree being slightly higher compared to shrub; the daily water loss trends of these two land cover types were similar and were more stable than those of the other types. The amount of water loss related to the grass land cover type is determined by the initial moisture content. Soil under subshrubs acquired and retained soil moisture resources more efficiently than the other cover types, representing an adaptive vegetation type in this area.

Effect of Land-Cover Type on the SMAP Active/Passive Soil Moisture Downscaling Algorithm Performance

2015 ◽  
Vol 12 (4) ◽  
pp. 846-850 ◽  
Author(s):  
Xiaoling Wu ◽  
Jeffrey P. Walker ◽  
Christoph Rudiger ◽  
Rocco Panciera
Keyword(s):  
Soil Moisture ◽  
Land Cover ◽  
Land Cover Type ◽  
Algorithm Performance ◽  
Cover Type

scholarly journals High-Resolution SMAP-Derived Root-Zone Soil Moisture Using an Exponential Filter Model Calibrated per Land Cover Type

2021 ◽  
Vol 13 (6) ◽  
pp. 1112
Author(s):  
Vivien-Georgiana Stefan ◽  
Gianfranco Indrio ◽  
Maria-José Escorihuela ◽  
Pere Quintana-Seguí ◽  
Josep Maria Villar
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Land Cover ◽  
Root Zone ◽  
Agricultural Drought ◽  
Intermediate Step ◽  
Land Cover Type ◽  
Simple Method ◽  
Cover Type ◽  
Spatial Coverage

Root-zone soil moisture (RZSM) plays a key role for most water and energy budgets, as it is particularly relevant in controlling plant transpiration and hydraulic redistribution. RZSM data is needed for a variety of different applications, such as forecasting crop yields, improving flood predictions and monitoring agricultural drought, among others. Remote sensing provides surface soil moisture (SSM) retrievals, whose key advantage is the large spatial coverage on a systematic basis. This study tests a simple method to retrieve RZSM estimates from high-resolution SSM derived from SMAP (Soil Moisture Active Passive). A recursive exponential filter using a time constant τ is calibrated per land cover type, which uses as an intermediate step a long-term ISBA-DIF (Interaction Soil Biosphere Atmosphere—Diffusion scheme) dataset over an area located in Catalonia, NE of Spain. The τ values thus obtained are then used as an input to the same recursive exponential filter, to derive 1 km resolution RZSM estimates from 1 km SMAP SSM, which are obtained from the original data by downscaling to a 1 km resolution, through the DISPATCH (DISaggregation based on a Physical and Theoretical scale CHange) methodology. The results are then validated with scaled in situ observations at different depths, over two different areas, one representative of rainfed crops, and the other of irrigated crops. In general, the estimates agree well with the observations over the rainfed crops, especially at a 10 cm and 25 cm depth. Nash–Sutcliffe (NS) scores ranging between 0.33 and 0.58, and between 0.37 and 0.56 have been found, respectively. Correlation coefficients for these depths are high, between 0.76 and 0.91 (10 cm), and between 0.71 and 0.90 (25 cm). For the irrigated sites, results are poorer (partly due to the extremely high heterogeneity present), with NS scores ranging between −2.57 and 0.16, and correlations ranging between −0.56 and 0.48 at 25 cm. Given the strong correlations and NS scores found in the surface, the sensitivity of the filter to different τ values was investigated. For the rainfed site, it was found, as expected, with increasing τ, increasing NS and correlations with the deeper layers, suggesting a better coupling. Nevertheless, a strong correlation with the surface (5 cm) or shallower depths (10 cm) observed over certain sites indicates a certain lack of skill of the filter to represent processes which occur at lower levels in the SM column. All in all, a calibration accounting for the vegetation was shown to be an adequate methodology in applying the recursive exponential filter to derive the RZSM estimates over large areas. Nevertheless, the relative shallow surface at which the estimates correlate in some cases seem to indicate that an effect of evapotranspiration in the profile is not well captured by the filter.

scholarly journals Comparison of Accuracy of Surface Temperature Images from Unmanned Aerial Vehicle and Satellite for Precise Thermal Environment Monitoring of Urban Parks Using In Situ Data

2021 ◽  
Vol 13 (10) ◽  
pp. 1977
Author(s):  
Dongwoo Kim ◽  
Jaejin Yu ◽  
Jeongho Yoon ◽  
Seongwoo Jeon ◽  
Seungwoo Son
Keyword(s):  
Land Cover ◽  
Unmanned Aerial Vehicle ◽  
Thermal Environment ◽  
Green Spaces ◽  
Urban Park ◽  
Land Cover Type ◽  
Land Cover Types ◽  
Cover Type ◽  
Aerial Vehicle

Rapid urbanization has led to several severe environmental problems, including so-called heat island effects, which can be mitigated by creating more urban green spaces. However, the temperature of various surfaces differs and precise measurement and analyses are required to determine the “coolest” of these. Therefore, we evaluated the accuracy of surface temperature data based on thermal infrared (TIR) cameras mounted on unmanned aerial vehicles (UAVs), which have recently been utilized for the spatial analysis of surface temperatures. Accordingly, we investigated land surface temperatures (LSTs) in green spaces, specifically those of different land cover types in an urban park in Korea. We compared and analyzed LST data generated by a thermal infrared (TIR) camera mounted on an unmanned aerial vehicle (UAV) and LST data from the Landsat 8 satellite for seven specific periods. For comparison and evaluation, we measured in situ LSTs using contact thermometers. The UAV TIR LST showed higher accuracy (R2 0.912, root mean square error (RMSE) 3.502 °C) than Landsat TIR LST accuracy (R2 value lower than 0.3 and RMSE of 7.246 °C) in all periods. The Landsat TIR LST did not show distinct LST characteristics by period and land cover type; however, grassland, the largest land cover type in the study area, showed the highest accuracy. With regard to the accuracy of the UAV TIR LST by season, the accuracy was higher in summer and spring (R2 0.868–0.915, RMSE 2.523–3.499 °C) than in autumn and winter (R2 0.766–0.79, RMSE 3.834–5.398 °C). Some land cover types (concrete bike path, wooden deck) were overestimated, showing relatively high total RMSEs of 4.439 °C and 3.897 °C, respectively, whereas grassland, which has lower LST, was underestimated—showing a total RMSE of 3.316 °C. Our results showed that the UAV TIR LST could be measured with sufficient reliability for each season and land cover type in an urban park with complex land cover types. Accordingly, our results could contribute to decision-making for urban spaces and environmental planning in consideration of the thermal environment.

scholarly journals Relationships between algal biomass and diversity with stream size and adjacent land use

Fine Focus ◽  
2014 ◽  
Vol 1 (1) ◽  
pp. 20-28
Author(s):  
Rachel A. Habegger ◽  
Jordan M. Marshall
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Algal Biomass ◽  
Water Movement ◽  
Forested Wetlands ◽  
Land Cover Type ◽  
Wetland Area ◽  
Land Cover Types ◽  
Cover Type ◽  
Open Development

Land use adjacent to waterways, such as development or agriculture, alters hydrological patterns leading to increases in runoff and nutrient input. Forests and wetlands, as natural land cover types, reduce water movement and allow infiltration into soil. We measured algal biomass and diversity in order to quantify the influence neighboring land cover types have on streams in Northeastern Indiana. In the study area, cultivated crops were the dominant land cover type, with open development and deciduous forest following. Emergent wetland area had the greatest influence on algal biomass, with increases in wetland area decreasing biomass. However, open development, low intensity development, grassland, shrub, and forested wetlands added to increases in biomass. Conversely, forested wetlands reduced algal richness, while open development and pastures increased richness. Because open development (i.e. dominated by turf grass, lawns, parks, golf courses) was the second most common land cover type and positively influenced both algal biomass and richness, management of those properties will likely have direct impact on nutrient flow into streams. Additionally, adding functional wetlands dominated by emergent herbaceous plants will directly impact future algal biomass.

scholarly journals Soil moisture and evapotranspiration of different land cover types in the Loess Plateau, China

2012 ◽  
Vol 16 (8) ◽  
pp. 2883-2892 ◽  
Author(s):  
S. Wang ◽  
B. J. Fu ◽  
G. Y. Gao ◽  
X. L. Yao ◽  
J. Zhou
Keyword(s):  
Soil Moisture ◽  
Land Cover ◽  
Loess Plateau ◽  
Vegetation Type ◽  
The Other ◽  
Plantation Forest ◽  
The Loess Plateau ◽  
Soil Moisture Dynamics ◽  
Land Cover Types ◽  
Moisture Dynamics

Abstract. We studied the impacts of re-vegetation on soil moisture dynamics and evapotranspiration (ET) of five land cover types in the Loess Plateau in northern China. Soil moisture and temperature variations under grass (Andropogon), subshrub (Artemisia scoparia), shrub (Spiraea pubescens), plantation forest (Robinia pseudoacacia), and crop (Zea mays) vegetation were continuously monitored during the growing season of 2011. There were more than 10 soil moisture pulses during the period of data collection. Surface soil moisture of all of the land cover types showed an increasing trend in the rainy season. Soil moisture under the corn crop was consistently higher than the other surfaces. Grass and subshrubs showed an intermediate moisture level. Grass had slightly higher readings than those of subshrub most of the time. Shrubs and plantation forests were characterized by lower soil moisture readings, with the shrub levels consistently being slightly higher than those of the forests. Despite the greater post-rainfall loss of moisture under subshrub and grass vegetation than forests and shrubs, subshrub and grass sites exhibit a higher soil moisture content due to their greater soil retention capacity in the dry period. The daily ET trends of the forests and shrub sites were similar and were more stable than those of the other types. Soils under subshrubs acquired and retained soil moisture resources more efficiently than the other cover types, with a competitive advantage in the long term, representing an adaptive vegetation type in the study watershed. The interactions between vegetation and soil moisture dynamics contribute to structure and function of the ecosystems studied.

scholarly journals Urban Heat and Urban Cool Islands of Different Land Use Types in Cuiabá, Brazil

2021 ◽  
Author(s):  
Natallia Sanches e Souza ◽  
Marta Cristina de Jesus Albuquerque Nogueira ◽  
Flávia Maria de Moura Santos ◽  
Luciana Sanches
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Urban Heat Islands ◽  
Land Cover Type ◽  
Land Use Land Cover ◽  
Local Climate ◽  
Land Cover Types ◽  
Cover Type ◽  
Urban Heat

Abstract Urban heat islands (UHIs), urban cool islands (UCIs), and their varying effects due to land use/land cover types and the local climate were investigated from 2014 to 2015 in three urban zones located in Cuiabá city, Brazil, during hot-humid, and hot-dry periods. All the urban zones were analysed for land use/land cover type, local climate, and rate of warming and cooling based on the difference in air temperature (ΔT) between the urban zones and the rural zone located outside the urban perimeter. The annual UHI effect in all the urban zones exhibited varying intensities during the day, with the highest daytime intensity recorded after the sunrise. The duration of UHI effect varied with land use/land cover type; a consequence of high built-up density, verticalization, waterproof surface, and other peculiarities of urban areas. In the urban zones with high built-up density, the duration of UHI effect was observed for up to 24 h, while in the urban areas with low built-up density, the maximum duration of UHI effect was 8 h. On an average, during the daytime, the urban zone with approximately 70% of vegetation cover and water bodies recorded a UCI value of approximately –8 °C, whereas the urban zones with approximately 80% waterproof surface and bare land recorded a UCI value close to +2 °C during the hot-dry and hot-humid periods. The results indicate that land use and land cover types directly influence UHI intensity.

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 Land Use and Land Cover Change Assessment in the Context of Flood Hazard in Lagos State, Nigeria

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1105
Author(s):  
Dorcas Idowu ◽  
Wendy Zhou
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Flood Hazard ◽  
The State ◽  
Land Cover Type ◽  
Lulc Change ◽  
Cover Type ◽  
Lulc Changes ◽  
Lagos State ◽  
Very High

Incessant flooding is a major hazard in Lagos State, Nigeria, occurring concurrently with increased urbanization and urban expansion rate. Consequently, there is a need for an assessment of Land Use and Land Cover (LULC) changes over time in the context of flood hazard mapping to evaluate the possible causes of flood increment in the State. Four major land cover types (water, wetland, vegetation, and developed) were mapped and analyzed over 35 years in the study area. We introduced a map-matrix-based, post-classification LULC change detection method to estimate multi-year land cover changes between 1986 and 2000, 2000 and 2016, 2016 and 2020, and 1986 and 2020. Seven criteria were identified as potential causative factors responsible for the increasing flood hazards in the study area. Their weights were estimated using a combined (hybrid) Analytical Hierarchy Process (AHP) and Shannon Entropy weighting method. The resulting flood hazard categories were very high, high, moderate, low, and very low hazard levels. Analysis of the LULC change in the context of flood hazard suggests that most changes in LULC result in the conversion of wetland areas into developed areas and unplanned development in very high to moderate flood hazard zones. There was a 69% decrease in wetland and 94% increase in the developed area during the 35 years. While wetland was a primary land cover type in 1986, it became the least land cover type in 2020. These LULC changes could be responsible for the rise in flooding in the State.

scholarly journals A GNSS-IR Method for Retrieving Soil Moisture Content from Integrated Multi-Satellite Data That Accounts for the Impact of Vegetation Moisture Content

2021 ◽  
Vol 13 (13) ◽  
pp. 2442
Author(s):  
Jichao Lv ◽  
Rui Zhang ◽  
Jinsheng Tu ◽  
Mingjie Liao ◽  
Jiatai Pang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Satellite Data ◽  
Vegetation Index ◽  
Soil Moisture Content ◽  
Support Vector ◽  
Observation Data ◽  
Multipath Effect ◽  
Mars Model ◽  
The Impact

There are two problems with using global navigation satellite system-interferometric reflectometry (GNSS-IR) to retrieve the soil moisture content (SMC) from single-satellite data: the difference between the reflection regions, and the difficulty in circumventing the impact of seasonal vegetation growth on reflected microwave signals. This study presents a multivariate adaptive regression spline (MARS) SMC retrieval model based on integrated multi-satellite data on the impact of the vegetation moisture content (VMC). The normalized microwave reflection index (NMRI) calculated with the multipath effect is mapped to the normalized difference vegetation index (NDVI) to estimate and eliminate the impact of VMC. A MARS model for retrieving the SMC from multi-satellite data is established based on the phase shift. To examine its reliability, the MARS model was compared with a multiple linear regression (MLR) model, a backpropagation neural network (BPNN) model, and a support vector regression (SVR) model in terms of the retrieval accuracy with time-series observation data collected at a typical station. The MARS model proposed in this study effectively retrieved the SMC, with a correlation coefficient (R2) of 0.916 and a root-mean-square error (RMSE) of 0.021 cm3/cm3. The elimination of the vegetation impact led to 3.7%, 13.9%, 11.7%, and 16.6% increases in R2 and 31.3%, 79.7%, 49.0%, and 90.5% decreases in the RMSE for the SMC retrieved by the MLR, BPNN, SVR, and MARS model, respectively. The results demonstrated the feasibility of correcting the vegetation changes based on the multipath effect and the reliability of the MARS model in retrieving the SMC.

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