Land Surface Changes Research Articles

Loess Plateau evapotranspiration intensified by land surface radiative forcing associated with ecological restoration

Evapotranspiration (ET) is a key variable coupled with water and energy availability and vegetation coverage. Since the year around 2000, several ecological restoration programs have been enacted within the Loess Plateau, China. The restoration programs have promoted vegetation greening and air cleaning, which has changed land surface albedo and solar radiation and consequently altered the land surface radiative forcing. Evidence has showed that ET is impacted by climate change and land use/cover change, but little is known about the effect of the radiative forcing on ET. This study reports the contribution of the surface radiative forcing during the growing season associated with ecological restoration to changes in potential ET (PET) and actual ET (AET) in the Loess Plateau. A differential attribution method based on the Penman-Monteith equation is proposed to isolate the contribution of radiative forcing. Accurate estimates of PET and AET are obtained from a sophisticated land surface hydrological model driven by long-term dynamic albedo, solar radiation, vegetation index, and meteorological forcings. We find that during 2003-2018, the surface albedo significantly decreased with increased solar radiation, which increased radiative forcing by 3.68 W m−2. These changes in radiative forcing increased PET and AET by 1.02 mm yr−1 and 0.12 mm yr−1, respectively. Despite spatial variabilities in radiative forcing, PET and AET intensified in approximately 50% (3.03 × 105 km2) and 60% (3.63 × 105 km2) of the area of the Loess Plateau, respectively. However, the PET and AET intensified by radiative forcing accounted for 8% and 5% of the total change in PET and AET, respectively. Although the average contribution of radiative forcing to the Loess Plateau is relatively small, the accumulated impact is non-negligible; it may mediate hydrological cycle and result in substantial water resource stress, particularly in areas implementing intensive ecological restoration.

Identifying Spatial and Temporal Characteristics of Land Surface Albedo Using GF-1 WFV Data

Land surface albedo (LSA) is an important parameter that affects surface–air interactions and controls the surface radiation energy budget. The spatial and temporal variation characteristics of LSA reflect land surface changes and further influence the local climate. Ganzhou District, which belongs to the middle of the Hexi Corridor, is a typical irrigated agricultural and desert area in Northwest China. The study of the interaction of LSA and the land surface is of great significance for understanding the land surface energy budget and for ground measurements. In this study, high spatial and temporal resolution GF-1 wide field view (WFV) data were used to explore the spatial and temporal variation characteristics of LSA in Ganzhou District. First, the surface albedo of Ganzhou District was estimated by the GF-1 WFV. Then, the estimated results were verified by the surface measured data, and the temporal and spatial variation characteristics of surface albedo from 2014 to 2018 were analyzed. The interaction between albedo and precipitation or temperature was analyzed based on precipitation and temperature data. The results show that the estimation of surface albedo based on GF-1 WFV data was of high accuracy, which can meet the accuracy requirements of spatial and temporal variation characteristic analysis of albedo. There are obvious geographic differences in the spatial distribution of surface albedo in Ganzhou, with the overall distribution characteristics being high in the north and low in the middle. The interannual variation in annual average surface albedo in Ganzhou shows a trend of slow fluctuations and gradual increases. The variation in annual albedo is characterized by “double peaks and a single valley”, with the peaks occurring from December to February at the end and beginning of the year, and the valley occurring from June to August. Surface albedo was negatively correlated with precipitation and temperature in most areas of Ganzhou.

Perlindungan Hukum Terhadap Tanah Hak Milik Masyarakat Pasca Bencana Alam Erupsi Gunung Sinabung

Indonesia is located in a natural disaster prone location where various types of natural disasters, including earthquakes and tsunamis, volcanoes, floods, landslides, droughts, forest and land fires, and other natural disasters still occur very frequently. Post natural disaster events also have a systemic impact on land issues, especially for areas that are most severely affected by natural disasters, where one of the impacts is the loss of land boundaries caused by changes in land surface due to natural disasters, mainly caused by the earthquake and tsunami. The problems raised in this study, namely how the rule of law against community land rights after the Mt. Sinabung eruption natural disaster, the position and status of community property rights after the Mt. Sinabung eruption natural disasters and legal protection of community land ownership after the eruption. Mount Sinabung. To find answers to these problems, this research uses descriptive analytical normative legal research, where this normative legal research uses secondary data as primary data and also uses primary data as complementary data using data collection techniques carried out by means of literature study, as well as Qualitative data analysis. The rule of law for community property rights after the natural disaster of the Mt. Sinabung eruption is broadly regulated in Article 27 of Law Number 5 of 1960 Concerning Basic Agrarian Regulations which states that one of the causes of the abolition of ownership rights is because the land was destroyed, however, this provision does not automatically mean that the community's community-owned land can be abolished. There are a number of activities that must be carried out until the community's community-owned land is removed. The position and status of community property rights after the natural disaster of the Mt. Sinabung eruption, which basically remains the property of victims of natural disasters and victims of disasters do not lose their property rights before the disaster belongs to disaster victims. The state cannot directly control the ex-disaster land even though the land owner has died. Land ownership should still be returned to the community, especially for areas that are still inhabited by indigenous peoples. Legal protection of community land rights after the occurrence of natural disaster of the Mt. Sinabung eruption is through legal protection of individual ownership holders and protection through land consolidation and relocation activities

Water dynamics over a Western Patagonian watershed: Land surface changes and human factors

Warming trends in Patagonia and severe droughts in recent decades are still poorly understood in terms of their hydrological effects. The effects of climate change on water dynamics in addition to human water management could generate a future water scarcity scenario in one of the regions with the most abundant water resources of Chile. The aim of this work is to focus on assessing the impacts of warming trends on water dynamics in the Patagonian Simpson River watershed during the last two decades. We estimated anomalies in the main components of water balance such as precipitation (P), snow cover (SC), evapotranspiration (ET) and streamflows (Q) as well as surface variables and meteorological forcing (i.e. air temperature - Ta, solar radiation - RS, land surface temperature - LST). The processed data were obtained from remote sensing, reanalysis and in-situ data. We implemented a trend analysis for each variable in the period 2000-2019 at monthly, seasonal and annual scale. Results showed a warming trend in Ta and LST of about 1.2 °C and 2.1 °C, respectively, concentrated mainly in the autumn and winter seasons. Although P showed non-significant trends, Q diminished significantly at rates of more than 9.1 m3/s/decade, representing 36% of its historical mean. However, the decreases in Q are seen only in the maximum (spring) and minimum (summer) seasonal flows. These decreases are explained by significant increases in ET, led by a positive feedback of its drivers (LST, Ta and RS), which is directly linked to the impact of warming and an associated vegetation greenness in the watershed, as well as a decrease in SC during winter that feeds the Simpson River during spring and summer. The decrease in Q is reinforced by the intensification of water withdrawals in recent decades, as shown by an accelerated increase in water rights for agricultural and drinking uses. In a context of water scarcity and increasing and extreme droughts, this work contributes to further understanding water dynamics in western Patagonia, providing support for policy and decision-making when defining sustainable productive practices at watershed scale.

Impacts of Saline-Alkali Land Improvement on Regional Climate: Process, Mechanisms, and Implications

Studying land use change and its associated climate effects is important to understand the role of human activities in the regulation of climate systems. By coupling remote sensing measurements with a high-resolution regional climate model, this study evaluated the land surface changes and corresponding climate impact caused by planting rice on saline-alkali land in western Jilin (China). Our results showed that paddy field expansion became the dominant land use change in western Jilin from 2015 to 2019, 25% of which was converted from saline-alkali land; this percentage is expected to increase in the near future. We found that saline-alkali land reclamation to paddy fields significantly increased the leaf area index (LAI), particularly in July and August, whereas it decreased albedo, mainly in May and June. Our simulation results showed that planting rice on saline-alkali land can help decrease the air temperature and increase the relative humidity. The temperature and humidity effects showed different magnitudes during the growing season and were most significant in July and August, followed by September and June. The nonradiative process, rather than the radiative process, played a dominant role in regulating the regional climate in this case, and the biophysical competition between evapotranspiration (ET) and albedo determined the temperature and relative humidity response differences during the growing season.

Combining Optical and Radar Satellite Imagery to Investigate the Surface Properties and Evolution of the Lordsburg Playa, New Mexico, USA

Driven by erodible soil, hydrological stresses, land use/land cover (LULC) changes, and meteorological parameters, windblown dust events initiated from Lordsburg Playa, New Mexico, United States, threaten public safety and health through low visibility and exposure to dust emissions. Combining optical and radar satellite imagery products can provide invaluable benefits in characterizing surface properties of desert playas—a potent landform for wind erosion. The optical images provide a long-term data record, while radar images can observe land surface irrespective of clouds, darkness, and precipitation. As a home for optical and radar imagery, powerful algorithms, cloud computing infrastructure, and application programming interface applications, Google Earth Engine (GEE) is an invaluable resource facilitating acquisition, processing, and analysis. In this study, the fractional abundance of soil, vegetation, and water endmembers were determined from pixel mixtures using the linear spectral unmixing model in GEE for Lordsburg Playa. For this approach, Landsat 5 and 8 images at 30 m spatial resolution and Sentinel-2 images at 10–20 m spatial resolution were used. Employing the Interferometric Synthetic Aperture Radar (InSAR) techniques, the playa’s land surface changes and possible sinks for sediment loading from the surrounding catchment area were identified. In this data recipe, a pair of Sentinel-1 images bracketing a monsoon day with high rainfall and a pair of images representing spring (dry, windy) and monsoon seasons were used. The combination of optical and radar images significantly improved the effort to identify long-term changes in the playa and locations within the playa susceptible to hydrological stresses and LULC changes. The linear spectral unmixing algorithm addressed the limitation of Landsat and Sentinel-2 images related to their moderate spatial resolutions. The application of GEE facilitated the study by minimizing the time required for acquisition, processing, and analysis of images, and storage required for the big satellite data.

Contrasting Responses of Local Climate to the Perturbation of Atmospheric Boundary Layer Winds Linked to Land‐Atmosphere Interactions

AbstractThe atmospheric boundary layer (ABL) is an interface through which the land surface influences the atmosphere and is crucial to land‐atmosphere (L‐A) interactions. Winds are an important element of the ABL, but their role in L‐A interactions is still partly unclear. Here, we use regional climate model experiments to investigate the impact of ABL winds on intraseasonal climate variabilities in East Asia. Two ensemble experiments were performed: one is a control ensemble, and the other is a perturbed ensemble, in which the ABL winds are shuffled from corresponding ensemble members of the control ensemble to produce a random perturbation of ABL winds. We found that the climates of the ensemble members become less similar in humid southern China, but generally more similar in semiarid northern China/Mongolia (NCM), especially for the mean values of several variables. The weather in southern China strongly responds to ABL winds and becomes less similar after perturbation. In NCM, however, the strong L‐A positive feedbacks, which involve wind field change in response to land surface changes and tend to cause large weather and climate anomalies, are weakened by the ABL wind perturbations. Thus, the inter‐member divergences of related variables, including surface temperature, sensible heat flux, soil moisture, and to some extent precipitation, are smaller and their time series are more similar. Clearly, the different L‐A interactions in these two regions are the main reason for the contrasting responses of local climate to the ABL wind perturbations.

A Time Series Analysis of Forest Cover and Land Surface Temperature Change Over Dudpukuria-Dhopachari Wildlife Sanctuary Using Landsat Imagery

Forest cover change is an important criterion as it affects the environmental balance whereas land surface temperature is a significant parameter within the earth climate system. Spatio-temporal change of forest cover can be detected and land surface temperature can be retrieved by applying remote sensing technology. The present study aimed to capture the impact of forest cover change on land surface temperature in Dudpukuria-Dhopachari Wildlife Sanctuary (DDWS), Bangladesh, using multi-spectral and multi-temporal satellite data. To avoid the biasness in the calculation, leaf flash time was targeted for collecting Landsat images from United States Geological Survey (USGS) Earth Explorer and, based on availability, images were collected purposively which ones had closer time period:1990 (March 5, 1990), 2000 (February 5, 2000), 2010 (February 24, 2010) and 2020 (March 23, 2020). Unsupervised classification was applied over the images Landsat 4–5 Thematic Mapper (TM), 7 Enhanced Thematic Mapper Plus (ETM+), and 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) data for detecting forest cover change. To retrieve the land surface temperature, Mono Window Algorithm (MWA) method was applied over similar images. Maximum forest degradation was observed in 2010 and the change found was 17% as compared to 1990. After 2010, the forest started to flourish. Land surface temperature dramatically changes over the time period. The highest land surface temperature in the forested area was observed in 2020 (32.2°C) and it was changed 7.7°C from that of the 1990 (24.5°C). In every 10 years, almost 2.3°C–3.0°C temperature change was detected. In the first three decades, a reverse relationship was observed between land surface temperature and forest cover; however, in the last decade, land surface temperature was found to increase with the increase of forest cover. Thus, the results of the study revealed that land surface temperature may not be relevant with the local forest cover change directly. It can be estimated from the results that local forest cover change may have limited impact on local temperature rather than global forest cover change, whereas global warming could play a vital role in changing land surface temperature locally as well as globally.

Land-use changes in Northern Ukraine: patterns and dynamics of illegal amber mining during 1986-2016.

Political instability and economic crises may trigger informal, unsustainable and often illegal land use, leading to land degradation. One of the most recent and striking examples of such a phenomenon within Europe is demonstrated by the Polissia region in Northern Ukraine, famous for its amber deposits. Amid severe political disturbances and subsequent economic recession in Ukraine in 2014 and 2015, amber mining flourished in the region. However, the extent and spatial pattern of degraded land caused by amber mining over the entire region has remained unknown. To fill this gap and track land surface changes, we used multi-source satellite imagery. We found a gradual decrease of the area without vegetation cover, as a proxy for degraded land, from the late Soviet period until 2014 in most of the analysed administrative districts of Polissia. In contrast to this, we identified substantial conversion of forest and agricultural land to bare soil that occurred between 2014 and 2016, which can be attributed to the rush of illegal amber mining in the region. The estimated total area of affected land on the produced Landsat-based map for 2016 was 1066ha, 60% of which occurred in 2014-2016. Land cover classification within a key study area suggests that utilization of very high-resolution images from the WorldView-2 satellite enables more accurate mapping of land degradation and identification of small mining sites. Further monitoring of land-use change caused by amber mining is essential to improving understanding of long-lasting environmental impacts on regional ecosystems and biodiversity.

Evaluating the monetary environmental compensation over a Hydroelectric Power Plant based on opportunity cost simulation, GIS, and remote sensing images

In Brazil, electricity generation comes mainly from Hydroelectric Power Plants (HPP) that accounts for 65% of the national production. The establishment of a given HPP promotes significant land surface changes since vast areas are covered by the water reservoir. To mitigate such impact, a percentual of the produced energy is charged as a monetary environmental compensation (MEC). In this study, a WorldView-2 scene was used to delineate the flooded area. After, based on Landsat-5/TM and Landsat-7/ETM + scenes, we map the major land use and land cover classes before establishing an HPP in the Southern Santa Catarina Plateau (Southern Brazil). Then, based on the resulted land cover map, we address the MEC's effectiveness by simulating in a GIS environment the opportunity costs over the productivity of the agricultural areas lost by the HPP water reservoir. Agricultural statistics databases were consulted to obtain historical values and mean productivity of corn, soybean, and beef cattle. Results show that MEC was efficient for the timeframe of 2006–2018. The opportunity cost reveals a positive benefit value of US$4,738,862.03 (R$6,123,292.25) for the directed affected municipalities. In summary, MEC was more beneficial than maintaining agricultural activities. This research brought a simple methodology of low cost to evaluate a given HPP's effectiveness, from an economic point of view, for the directed affected municipalities. The presented method can be applied to other similar enterprises and other HPPs in Brazil.

Hotter Drought Escalates Tree Cover Declines in Blue Oak Woodlands of California

California has, in recent years, become a hotspot of interannual climatic variability, recording devastating climate-related disturbances with severe effects on tree resources. Understanding the patterns of tree cover change associated with these events is vital for developing strategies to sustain critical habitats of endemic and threatened vegetation communities. We assessed patterns of tree cover change, especially the effects of the 2012–2016 drought within the distribution range of blue oak (Quercus douglasii), an endemic tree species to California with a narrow geographic extent. We utilized multiple, annual land-cover and land-surface change products from the U.S. Geological Survey (USGS) Land Change Monitoring, Assessment and Projection (LCMAP) project along with climate and wildfire datasets to monitor changes in tree cover state and condition and examine their relationships with interannual climate variability between 1985 and 2016. Here, we refer to a change in tree cover class without a land-cover change to another class as “conditional change.” The unusual drought of 2012–2016, accompanied by anomalously high temperatures and vapor pressure deficit, was associated with exceptional spikes in the amount of both fire and non-fire induced tree cover loss and tree cover conditional change, especially in 2015 and 2016. Approximately 1,266 km2 of tree cover loss and 617 km2 of tree cover conditional change were recorded during that drought. Tree cover loss through medium to high severity fires was especially large in exceptionally dry and hot years. Our study demonstrates the usefulness of the LCMAP products for monitoring the effects of climatic extremes and disturbance events on both thematic and conditional land-cover change over a multi-decadal period. Our results signify that blue oak woodlands may be vulnerable to extreme climate events and changing wildfire regimes. Here, we present early evidence that frequent droughts associated with climate warming may continue to affect tree cover in this region, while drought interaction with wildfires and the resulting feedbacks may have substantial influence as well. Consequently, efforts to conserve the blue oak woodlands, and potentially other vegetation communities in the Western United States, may benefit from consideration of climate risks as well as the potential for climate-fire and vegetation feedbacks.

Prediction of long-term inter-seasonal variations of streamflow and sediment load by state-space model in the Loess Plateau of China

Streamflow and sediment load exporting from catchments usually show high inter-variability caused by climate variability and land surface changes. It is challenge to predict monthly or daily streamflow and sediment load using simply statistical methods. The state-space model is an effective tool for quantifying localized variations, and it only needs some easily obtained climate and land surface variables. However, there is no state-space model developed to predict the long-term variations of monthly streamflow, sediment load and suspended sediment concentration. In this study, fourteen main catchments in the Loess Plateau of China were chosen, and these catchments experienced abrupt reductions of annual streamflow (Q), specific sediment yield (SSY) and suspended sediment concentration (SSC) during the past five decades. The state-space model was developed to predict monthly Q, SSY and SSC during 1982–2011 by precipitation, potential evapotranspiration and normalized difference vegetation index. The results indicated that the monthly Q, SSY and SSC in summer season decreased significantly in nearly all the catchments (p < 0.01). The periodicity of monthly Q, SSY and SSC reduced, and especially the periodicity was not detected after 2003. The precipitation and previous Q were the two main state variables to estimate monthly Q with transition coefficients of 0.56 and 0.25, respectively, whereas Q and previous SSC were the most important state variables to estimate monthly SSY and SSC with transition coefficients of 0.50 and 0.34, respectively. The state-space model was satisfactory to simulate monthly Q, SSY and SSC with Nash-Sutcliffe model efficiency (NSE) over 0.85 in model calibration and validation. Furthermore, the model performance was best for predicting monthly Q, followed by predicting monthly SSY and SSC with the average NSE of 0.90, 0.89 and 0.87, respectively. The reductions of monthly streamflow and sediment load were mainly derived by soil and water conservation measures (SWCMs) and especially check-dams. The catchment runoff and sediment coefficient decreased significantly and linearly with the percentages of area affected by SWCMs (p < 0.01). This study indicates that the state-space model is a useful tool to predict streamflow and sediment load time series with the hydrological and land surface informations.

Radiative feedbacks on land surface change and associated tropical precipitation shifts

AbstractChanges in land surface albedo and land surface evaporation modulate the atmospheric energy budget by changing temperatures, water vapor, clouds, snow and ice cover, and the partitioning of surface energy fluxes. Here idealized perturbations to land surface properties are imposed in a global model to understand how such forcings drive shifts in zonal mean atmospheric energy transport and zonal mean tropical precipitation. For a uniform decrease in global land albedo, the albedo forcing and a positive water vapor feedback contribute roughly equally to increased energy absorption at the top of the atmosphere (TOA), while radiative changes due to the temperature and cloud cover response provide a negative feedback and energy loss at TOA. Decreasing land albedo causes a northwards shift in the zonal mean intertropical convergence zone (ITCZ). The combined effects on ITCZ location of all atmospheric feedbacks roughly cancel for the albedo forcing; the total ITCZ shift is comparable to that predicted for the albedo forcing alone. For an imposed increase in evaporative resistance that reduces land evaporation, low cloud cover decreases in the northern mid-latitudes and more energy is absorbed at TOA there; longwave loss due to warming provides a negative feedback on the TOA energy balance and ITCZ shift. Imposed changes in land albedo and evaporative resistance modulate fundamentally different aspects of the surface energy budget. However, the pattern of TOA radiation changes due to the water vapor and air temperature responses are highly correlated for these two forcings because both forcings lead to near-surface warming.

Making Landsat 5, 7 and 8 reflectance consistent using MODIS nadir-BRDF adjusted reflectance as reference

The Landsat satellite data applications have been broadened by the improvement in data consistency, e.g., advances in calibration and atmospheric correction algorithms. However, there are still inter-sensor inconsistencies of surface reflectance caused by differences in sensor spectral response and residuals in calibration and atmospheric correction. Such inconsistencies tend to entangle with the land surface change, especially for the subtle changes such as vegetation responses to climate change. We propose a Bayesian approach to reduce inter-sensor inconsistencies by making Landsat 5, 7 and 8 reflectance consistent with MODIS nadir BRDF-adjusted reflectance (NBAR). The Bayesian MODIS-consistent Landsat reflectance should be similar to the MODIS NBAR when it is degraded to the MODIS resolution considering the point spread function (PSF). The MODIS NBAR PSF is modelled as a Gaussian function with empirically derived and band specific parameters. The relationships between the MODIS-consistent Landsat reflectance and the two available reflectance (i.e., the MODIS NBAR and observed Landsat reflectance) are built in the Bayesian framework. The Bayesian MODIS-consistent Landsat reflectance is then derived using the computationally efficient conjugate gradient descent method. The algorithm was applied to Landsat 5, 7 and 8 surface reflectance over five study areas in Brazil, China, France, Russia and USA, and compared with a linear regression-based reflectance adjustment method. Visual difference was evident in the MODIS NBAR and the observed Landsat reflectance and the relative root-mean-squared differences (rRMSD) ranged from 3.16% to 67.72% and R2 from 0.037 to 0.934. Both the Bayesian and linearly MODIS-consistent Landsat reflectance are visually more consistent with the MODIS NBAR. The average rRMSD and R2 improvements of the Bayesian MODIS-consistent Landsat reflectance over the observed Landsat reflectance were 21.36% and 0.19, 3.38% and 0.11, 5.25% and 0.07, 3.14% and 0.11, 3.49% and 0.08, and 5.72% and 0.09 for the blue, green, red, near infrared, and two shortwave infrared bands, respectively. The linearly MODIS-consistent Landsat reflectance had less rRMSD improvements: 18.26%, 1.46%, 3.02%, 1.86%, 1.97% and 3.36% for the six bands respectively, and had no R2 improvements. The linear regression derived using the whole image pixels has low performance in adjusting some extreme reflectance values that are not well represented in the image. In contrast, the Bayesian method derives the reflectance image that is consistent to MODIS at pixel level.

High-resolution triplet network with dynamic multiscale feature for change detection on satellite images

Change detection in remote sensing images aims to accurately determine any significant land surface changes based on acquired multi-temporal image data, being a pivotal task of remote sensing image processing. Over the past few years, owing to its powerful learning and expression ability, deep learning has been widely applied in the general field of image processing and has demonstrated remarkable potentials in performing change detection in images. However, a majority of the existing deep learning-based change detection mechanisms are modified from single-image semantic segmentation algorithms, without considering the temporal information contained within the images, thereby not always appropriate for real-world change detection. This paper proposes a High-Resolution Triplet Network (HRTNet) framework, including a dynamic inception module, to tackle such shortcomings in change detection. First, a novel triplet input network is introduced, which is capable of learning bi-temporal image features, extracting the temporal information reflecting the difference between images over time. Then, a network is employed to extract high-resolution image features, ensuring the learned features preserving high-resolution characteristics with minimal reduction of information. The paper also proposes a novel dynamic inception module, which helps improve the feature expression ability of HRTNet, enriching the multi-scale information of the features extracted. Finally, the distances between feature pairs are measured to generate a high-precision change map. The effectiveness and robustness of HRTNet are verified on three popular high-resolution remote sensing image datasets. Systematic experimental results show that the proposed approach outperforms state-of-the-art change detection methods.

Multi-Decadal Deltaic Land-Surface Changes: Gauging the Vulnerability of a Selection of Mediterranean and Black Sea River Deltas

Areal changes over delta surfaces determined by land and water ratios are a promising tool for identifying spatial and temporal changes in deltas that may reveal subsidence and shoreline erosion. Such changes can also provide the basis for more detailed studies on variations in land-cover and vegetation. Changes in land and water areas over a 35-year period (1984–2019) were determined for a selection of ten river deltas in the Mediterranean (Nile, Rhône, Po, Ebro, Moulouya, Ceyhan-Seyhan, Medjerdja, Ombrone, Arno) and the Black Sea (Danube), with a particular focus on aspects of subsidence and shoreline erosion. With the exception of the Ombrone, Arno, and Moulouya, and to lesser extent the Medjerdja, where notable changes dominate in the coastal zone and are tantamount to net erosion, the spatial pattern is largely dominated by delta-plain changes characterized by increasing areas of water. The pattern reflects a mix of shoreline erosion, land-use and land-cover changes, such as the ecological restoration of wetlands, but also increasing subsidence in these deltas, all of which have been exposed to a declining fluvial sediment supply due to human influence. The use of data on land-water ratios needs to be complemented by more detailed studies devoted to each delta in order to clearly disentangle changes related to land-use, vegetation, and subsidence. It is also important to determine how wetlands are interpreted in such ratios, as these important ecological elements are sensitive to ratio variations. It would also be interesting in future studies to examine how these variations play out over time, notably in deltas where changes have been significant over the period 1984–2019.

Deforestation strengthens atmospheric transport of mineral dust and phosphorus from North Africa to the Amazon

AbstractPhosphorus contained in atmospheric mineral dust aerosol originating from Africa fertilizes tropical forests in Amazonia. However, the mechanisms influencing this nutrient transport pathway remain poorly understood. Here we use the Community Earth System Model to investigate how large-scale deforestation affects mineral dust aerosol transport and deposition in the tropics. We find that the surface biophysical changes that accompany deforestation produce a warmer, drier and windier surface environment that perturbs atmospheric circulation and enhances long-range dust transport from North Africa to the Amazon. Tropics-wide deforestation weakens the Hadley circulation, which in turn, leads to a northward expansion of the Hadley cell and increases surface air pressure over the Sahara Desert. The high pressure anomaly over the Sahara, in turn, increases northeasterly winds across North Africa and the tropical North Atlantic Ocean, which subsequently increases dust transport to the South America continent. We estimate that the annual atmospheric phosphorus deposition from dust significantly increases by 27% (P &lt; 0.01) in the Amazon under a scenario of complete deforestation. These interactions exemplify how land surface changes can modify tropical nutrient cycling, which in turn, may have consequences for long-term changes in tropical ecosystem productivity and biodiversity.

Investigating the land surface temperature reaction to the land cover patterns during three decades using landsat data

Land use Land cover changes have a momentous influence on land surface temperature. Therefore, investigating spatial distribution of heat islands is a remarkable issue in environmental studies. The purpose of this study was to assess the interaction between land surface temperature variations with land cover change by using Landsat time-series and utilizing Normalized Vegetation Difference Index in Arsanjan County, Fars, Iran from 1987 to 2018. After estimating Normalized Vegetation Difference Index and land surface temperature time-series value in the experimental areas, index differencing technique was applied to identify their changes. Based on the findings, the reducing or rising trends of land surface temperature in vegetation stratums was related to the increasing or decreasing trend of Normalized Vegetation Difference Index from 1987 to 2003 and 2003 to 2018, respectively. Compared to the period 1987–2003, it is noteworthy that the noticeable increase in changed land surface temperature in the rangeland, farmland and Bakhtegan Lake by 18.2 °C, 21.2 °C and 18.3 °C, respectively, were attributed to the significant shift of Normalized Vegetation Difference Index by − 0.04, − 0.33 and + 0.6 in the mentioned area during the period 2003–2018. The correlations between land cover and land surface temperature were considerably positive in the water area by 0.95 and 0.83 from 1987 to 2003 and 2003 to 2018, respectively, while some negative coefficients were estimated by − 0.95 and − 0.94 in farmland in the mentioned period. These results are applicable with regard to managing heat islands by improving the cultivated area, afforestation and artificial Bakhtegan Lake recharge.

Application of Different Coherence Threshold on PS-InSAR Technique for Monitoring Deformation on the LUSI Affected Area During 2017 and 2019

Difficulties encountered in the DInSAR technique is the temporal and geometric decorrelation. This method’s main objective is to identify a single-pixel called Permanent Scatter (PS) over a long-time-interval and for a wide-angle of view variation. In this study, we aim to use the PS-InSAR technique to monitor land surface changes in the LUSI mud volcano area with coherence threshold difference analysis using the Sentinel 1A data set using SARPROZ as a tool. The land surface change that is our focus is west and east of the LUSI. Sentinel 1A data processing with different coherence threshold, affecting the number of PS points formed. Based on Fisher’s test on each coherence threshold showed that cumulative displacement and velocity did not differ significantly. During the 3 years since 2017 - 2019, the West LUSI region experienced average cumulative subsidence of -47.95 mm with an average velocity decline of 19.20 mm/year. The East LUSI region experiences average cumulative subsidence of 60.86 mm in the year, with an average velocity decline of 24.37 mm/year. The results of subsidence and velocity in this study are still in the line of sight (LOS)

Urbanization increased annual precipitation in temperate climate zone: A case in Beijing-Tianjin-Hebei region of North China

Rapid urbanization plays important roles in modifying regional climate. The effects of urbanization on annual precipitation in temperate climate zone were complicated and have not been fully investigated. In this study, Beijing-Tianjin-Hebei (BTH) region of North China was selected as research area and field observations of inter-annual precipitation from 1980 to 2015 were utilized to conduct the spatiotemporal analysis and to extract the urbanization effects. Combined statistical methods were applied and the urbanization effects indicator (UE) was created to quantify the roles of urban development on annual precipitation by combining the land cover change of cities and urban–rural precipitation differences. The paper found following main results: (1) In 2000 s, annual precipitation increased faster in urban areas (slope = 7.165 mm/yr) than in rural areas (slope = 4.954 mm/yr). The urbanization effects on the increasing of precipitation have been implied by comparisons of urban–rural difference between 2000 s (slope = 2.211 mm/yr) and 1980 s (slope = 0.165 mm/yr). (2) Rapid urbanization led to increasing of annual precipitation. Built-up areas correlated higher with urban precipitation than with rural precipitation in 9 of 13 cities, and were used as weights to improve the urbanization effects indicator (UE). (3) As the largest and the most developed city, Beijing presented the highest urbanization effects (UE = 44.5) on the increasing inter-annual precipitation, which was 51% higher than the secondary city of Chengde (UE = 21.71). The coastal cities such as Tianjin, Qinhuangdao and Tangshan presented negative UE values probably due to the strong sea-land energy interactions. This study contributes new findings to the effects of urbanization on annual precipitation in temperate climate zone and could help understand the feedback of land surface changes to variations of atmospheric circulation.