Cover Area Research Articles

Assessing the impact of land use land cover changes on soil moisture and vegetation cover in Southern Punjab, Pakistan using multi-temporal satellite data

ABSTRACT Change in land use land cover (LULC) is driven by human activities and drives changes that limit the accessibility of services and products for livestock and humans. This study aimed to develop the spatio-temporal changes in LULC, vegetation cover, and moisture index using multi-temporal satellite data in Southern Punjab, Pakistan. Analysis of satellite data was accomplished using ArcGIS 10.4 software. Based on ground-truthing, the supervised classification technique (maximum likelihood algorithm) was used to achieve the LULC classification. The LULC change analysis revealed that vegetation area converted to the build-up area by 7.17 % and bare soil converted to urban areas by 1.68 % from 2000 to 2021. Average NDVI values were calculated at 0.23, 0.17, 0.19, and 0.14 for 2000, 2007, 2014, and 2021, respectively. In the study area, average NDMI values were observed at 0.28, 0.25, 0.2, and 0.15 for 2000, 2007, 2014, and 2021, respectively. Based on our study, the general trend in Southern Punjab is a decrease in vegetation cover, moisture index, and forest area due to an increase in build-up areas. Assessments of LULC and NDMI changes, as well as estimates of the effect on the environment, are necessary for many policy decisions and planning.

Characterizing diurnal roosts of male Little Brown Myotis (Myotis lucifugus) during summer

Abstract Shelter is one critical aspect of an animal’s habitat, providing refuge from predators and weather, protection for offspring, and aiding in physiological homeostasis. During the day, bats find shelter in roosts—spaces created under tree bark, in tree cavities, or between rocks—after spending the night searching for food. Finding a roost with a microclimate that enables bats to remain in their thermoneutral zone could reduce energetic demands or allow bats to allocate energy to other activities such as reproduction and fighting disease. We aimed to characterize the structural features and microclimate (i.e., temperature) of roosts used by male Little Brown Myotis (Myotis lucifugus) during the summer and determine whether bats select certain characteristics disproportionally to what is available at different spatial scales. During the summers of 2017 and 2018, we radio-tracked 34 male M. lucifugus in Lodgepole Pine-dominated forests. We located at least 1 roost for 20 individuals (average = 2.85 roosts/bat, range = 1 to 6). Although snags were available, most of the roosts were in rock features (86% in rocks, 14% in trees or snags). Male M. lucifugus were more likely to select rock roosts with less canopy closure that were closer to water compared to available roosts on the landscape. They also selected roosts in rock features occurring within larger areas of rock cover that had wider entrances and access to crevices that faced the sky; these roosts also had warmer microclimates relative to other locations available on the landscape. Crevices that allow the bat to bask in the sun and change locations within a roost, minimizing energy needed for active thermoregulation, could be very beneficial for individuals recovering from diseases such as white-nose syndrome. Our work indicates that rock features provide habitat for male M. lucifugus during summer; other studies have shown that bats roost in these features during autumn and winter, further supporting their importance. By protecting these important rock structures, managers can help bats meet their habitat needs throughout the year.

A Typical Small Watershed in Southwestern China Is Demonstrated as a Significant Carbon Sink

Small watersheds are fundamental units for natural processes and social management in Southwestern China. Accurately assessing carbon sinks in small watersheds is crucial for formulating carbon sink management policies. However, there has been a lack of assessment of the dynamics of carbon fluxes in the major ecosystems of small watersheds. Here, we selected the Reshuihe River watershed, which is a typical small watershed in Southwestern China, to measure carbon fluxes using eddy covariance systems for two years (October 2021 to September 2023) from three major ecosystems, namely forest, cropland, and non-timber forest. We compared variations and controlling factors of net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (Re) among different ecosystems, and estimated annual watershed carbon flux based on the land cover areas of the three ecosystems. This study found that three ecosystems were net annual carbon sinks during the study period. Forest was the strongest (−592.8 and −488.1 gC m−2 a−1), followed by non-timber forest (−371.0 gC m−2 a−1), and cropland was the smallest (−92.5 and −71.6 gC m−2 a−1), after taking fallow period into account. Weeds were a significant source of carbon flux in non-timber forest ecosystems. It was also found that variations in daily NEE were controlled by photosynthetically active radiation and soil volumetric water content, with weak effects related to temperature also being observed. However, when the temperature exceeded 21 °C, GPP and Re were significantly reduced in cropland. Finally, it was discovered that the total carbon sink of the three ecosystems in the watershed for one year was −52.15 Gg C. Overall, we found that small watersheds dominated by forest ecosystems in Southwestern China have a strong carbon sink capacity.

Sensitivity of insectivorous bat foraging guilds to urbanization and implications for sustainable development

Substantial urban expansion is expected in global biodiversity hotspots over the next decade, especially in Asia. One such hotspot is Sulawesi, Indonesia, which hosts a diverse array of wild mammals, including bats. While urbanization may threaten some bats, species are not uniformly sensitive to urbanization. Many bat species’ sensitivity to urbanization is associated with their foraging strategies (or foraging guild), but information from Asia, generally, is severely lacking. Here we address this knowledge gap regarding urban sensitivity among insectivorous, echolocating bats within the context of urban informal settlements around the city of Makassar, South Sulawesi. Globally and in Makassar, informal settlements often exist on the fringe of cities, forming an urban-undeveloped land interface. Consequently, they may present opportunities to support conservation for some bats, given a growing focus on nature-based sustainable development solutions to improve the lives of informal settlement residents. We examined how, among informal settlements across Makassar, relative activity of bat sonotypes (in lieu of taxonomic species) from different foraging guilds was related to environmental factors associated with urban expansion. We found bat activity was influenced by processes interacting across multiple spatial scales ranging from the landscape- (e.g., spatial location relative to dense development in the urban core) to local-level (e.g., particular environmental features within 500 m). Broadly, we found some foraging guilds had lower overall relative activity, as well lower activity within the urban core compared to the peri-urban zone, indicating differential sensitivity to urbanization among Makassar’s bats that matches findings elsewhere. However, intensity of both urban and peri-urban informal settlement habitat use by particular bats was driven by a combination of landscape- and local-scale features. At the local scale, tree cover and inland water area frequently influenced sonotype activity in settlements, including urban core habitat use by urban-sensitive bats. Our work demonstrates that, especially if coordinated across broader spatial scales, local nature-based upgrades in informal settlements incorporating diverse green and blue spaces have the potential to enhance suitability of urban zones for both bats and for people.

General Manifestations of Tick-Borne Infections in the Amur Region in 2014–2023

Introduction: Tick-borne infections (TBI) require special attention of health professionals owing to their high epidemic significance. High rates of tick bite visits are registered in Russia while the incidence rates of tick-borne diseases range dramatically across different regions of the country. Objective: To describe several features of epidemiological manifestations of tick-borne infections in the Amur Region. Materials and methods: The analysis of TBI incidence rates registered in the population of the Amur Region by disease, age, sex, and administrative area was based on data of statistical observation forms No. 1, 2 “Information about infectious and parasitic diseases” and annual state reports on sanitary and epidemiological well-being of the population of the Amur Region for the years 2014 to 2023. Annual rates of tick bite visits and frequency of pathogen detection in the removed ticks were calculated. Statistical data analysis was carried out in Excel 2013. Results: Epidemiological analysis revealed a trend towards a decrease in TBI incidence from 4.81 %000 in 2014 to 0.26 %000 in 2021; predominance of tick-borne rickettsiosis (56.77 %; 95 % CI: 48.98–64.57 %) in the structure of long-term incidence of the regional population; registration of most disease cases in steppe landscape zones (57.42 %; 95 % CI: 48.38–66.46 %) and among the adult population (85.81 %; 95 % CI: 80.32–91.30 %); a statistical correlation between tick bite visits and TBI prevalence (r = 0.64) and ixodid tick-borne borreliosis (r = 0.82), as well as the correlation between the incidence of ixodid tick-borne borreliosis and the frequency of detecting borrelia in ticks removed from patients (r = 0.677). Conclusion: Further development of the TBI situation in the Amur Region will be defined by changes in forest cover area related to both anthropogenic transformations and natural emergencies.

Solute fluxes in headwater catchments with contrasting anthropogenic impact

Understanding the response of headwater catchments to increasing anthropogenic influences is one of the key issues in hydrological and geomorphological research. Two headwater catchments with contrasting human impacts on the environment were chosen to determine changes in surface water chemistry and solute fluxes. In one catchment, 22 % of the forest area was cleared in 2013 and in the other, 75 % of the arable lands was converted to grassland and forest in the last 25 years. Atmospheric input and solute mass balance were analysed using homogeneity Pettitt test. It seems that in both areas, a very important factor affecting solute fluxes was most likely changes, or lack thereof, in soil erosion. In the partially clear-cut catchment, a small clear-cut area and adequate protection of the soil cover had little effect on the stream water chemistry, and the total solute mass balance remained unchanged during the study period. In this catchment, the more pronounced effect on solute fluxes was using de-icing salts in winter, which contributed to a 62 % increase in total solute flux (mainly by supplying Na+ and Cl−, but also Ca2+, Mg2+ and K+). In a catchment with a decrease in arable lands, there was a 55 % decrease in total solute mass balance (including mass balance of Ca2+, Mg2+, Na+, K+, NH4+, SO4−, NO3−, Cl−) in the stream likely associated with a decrease in soil erosion and fertilization. In both catchments there was a decrease in total monthly atmospheric input (especially in input of NH4+, SO4− and NO3−) of 53 % and 21 %, respectively, over the study period. To summarize, the road salting has increased the amount of transported solutes in the stream and deteriorated surface water chemistry, while the reduction of arable land area has reduced the amount of transported solutes in the stream and improved surface water quality.

Performance analysis on the heating performance of CPV/T-air dual source heat pump system with finned microchannels heat exchanger

Solar-assisted heat pump technology is a clean building energy conserving technique with high efficiency, but it often has limitations such as large evaporator cover area and significant susceptibility to weather conditions, preventing it from being widely used. In this paper, a concentrated photovoltaic/thermal-air dual source heat pump system integrated with finned microchannel heat exchanger (CPV/T-FMC-SAHP) is proposed to solve these problems. A mathematical model for the CPV/T-FMC-SAHP system is developed, and sensitivity analysis of different environmental parameters on system performance is conducted by numerical simulation. Performance comparisons are made under dual-source and solar heating modes to explore the optimal operating conditions. The results suggest that changes in ambient temperature have a relatively minor impact, primarily attributed to the limited surface area of the evaporator. On the other hand, increased irradiance, facilitated by the concentrator, significantly improves the system's performance. In the case of solar irradiation at 600 W/m2 and an ambient temperature of 13 °C, the system's heating capacity is 1747.38 W, with a COP reaching 5.31. In comparison, the COP of existing solar-assisted heat pump systems under this condition are about 4.5, so there is an improvement of about 18 %. Furthermore, activating the air blower on the weather with bad irradiation but relatively warm can further increase the system's heating capacity. To sum up, the CPV/T-FMC-SAHP system exhibits a substantial improvement in performance and high level of integration compared to traditional solar-assisted heat pumps. Therefore, this system can provide ideas for improving the performance of heat pumps in the case of limited space. It is not only meaningful in the field of building energy conserving, but also conducive to addressing global energy challenges.

Integrated modeling of snow-covered areas and hydrological processes in the Larji Sub-Basin, Himachal Pradesh, India, using SRM and SWAT models

Abstract Alpine snow is crucial for the water cycle, as the runoff and environment of arid and semi-arid regions rely entirely on these glaciers. Mountain-fed rivers provides the water for domestic, agricultural irrigation, hydroelectric power, and other uses. Due to climate variability, river catchment flows may shift, causing floods and droughts that will aggravate the economy. This study estimated the SCA using Google Earth Engine (GEE) for the Larji River basin, situated in Himachal Pradesh, from the year 2001 to 2021. The snow cover area (SCA) varies from 0.7–22% in the basin. The present study highlights the effectiveness of cloud computing for assessing trends in snow-cover regions in the basin. Moderate Resolution Imaging Spectroradiometer (MODIS) snow product (MOD10A1 V6 Snow Cover Daily Global 500m product) is utilized for SCA calculation. This study simulates runoff from the Larji river, using Snow-melt Runoff Model (SRM) and Soil Water Assessment Tool (SWAT) for years (2019-2021). Furthermore, the Coefficient of determination (R2) Coefficient of corelation (r), Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) were used to evaluate the efficacy of models. This study will help the policymakers and stakeholders to carry out the water resource management practices in the study area.

Measuring Universities’ Sustainability Performance with Using UI GreenMetric World Ranking: A Case Study of Düzce University

The university campus is a dynamic system in which the concept of sustainability can be applied to all the needs of the university. Universities with the "green campus" approach provide effective use of their resources. As part of the study, the data of the main campus of the Düzce University for 2021 was evaluated based on the UI GreenMetric Ranking. Calculations and assessments were made for the campus land cover, structural and vegetative areas. A general assessment of the entire campus was carried out using the sustainability and green campus approach with dataset. As a result, Düzce University is progressing towards the realisation of a sustainable/green campus, facilitated by the discernible impact of the survey components. The creation of a sustainable/green campus will make a difference in the province of Düzce and accelerate local development actions.

Deep Learning-Based Spatiotemporal Fusion Architecture of Landsat 8 and Sentinel-2 Data for 10 m Series Imagery

Medium- to high-resolution imagery is indispensable for various applications. Combining images from Landsat 8 and Sentinel-2 can improve the accuracy of observing dynamic changes on the Earth’s surface. Many researchers use Sentinel-2 10 m resolution data in conjunction with Landsat 8 30 m resolution data to generate 10 m resolution data series. However, current fusion techniques have some algorithmic weaknesses, such as simple processing of coarse or fine images, which fail to extract image features to the fullest extent, especially in rapidly changing land cover areas. Facing the aforementioned limitations, we proposed a multiscale and attention mechanism-based residual spatiotemporal fusion network (MARSTFN) that utilizes Sentinel-2 10 m resolution data and Landsat 8 15 m resolution data as auxiliary data to upgrade Landsat 8 30 m resolution data to 10 m resolution. In this network, we utilized multiscale and attention mechanisms to extract features from coarse and fine images separately. Subsequently, the features outputted from all input branches are combined and further feature information is extracted through residual networks and skip connections. Finally, the features obtained from the residual network are merged with the feature information of the coarsely processed images from the multiscale mechanism to generate accurate prediction images. To assess the efficacy of our model, we compared it with existing models on two datasets. Results demonstrated that our fusion model outperformed baseline methods across various evaluation indicators, highlighting its ability to integrate Sentinel-2 and Landsat 8 data to produce 10 m resolution data.

Isotope data-constrained hydrological model improves soil moisture simulation and runoff source apportionment

Multiple-objective calibration helps constrain the parameter uncertainties and improve the performances of hydrological models. Previous studies have indicated that calibration toward soil moisture data could improve the streamflow simulation, but its influence on the runoff source apportionment quantification still needs to be analyzed. Meanwhile, although isotope calibration has proved to improve the representation of internal hydrological processes, the value of isotope on the simulation of internal state variables such as soil moisture has yet to be examined. This study utilized the tracer-aided hydrological model THREW-T (Tsinghua Representative Elementary Watershed – Tracer-aided version) in two mountainous basins on the Tibetan Plateau (The Upper Brahmaputra and Upper Yangtze basins) to evaluate the value of soil moisture and isotope data on model calibration. The result shows that: (1) The THREW-T model produced good simulation on streamflow, snow cover area, soil moisture, and stream water isotope simultaneously in the two study areas. Calibration toward soil moisture and isotope caused slight (∼0.03) but statistically significant (p < 0.01) decrease on the Nash-Sutcliffe coefficient of streamflow simulation compared to the baseline calibration variant only toward streamflow. (2) Calibration toward soil moisture brought no improvement to streamflow simulation for the validation period and stations in both basins, only improving soil moisture simulation. However, calibration toward the isotope improved the simulations of internal streamflow and soil moisture's spatiotemporal variation. (3) Different calibration variants resulted in different estimations of the runoff source apportionment, and independent evidence indicated that the results obtained by isotope calibration were most reasonable. Calibrations toward streamflow and soil moisture underestimated and overestimated the contributions from subsurface runoff, respectively. Isotope was the most sensitive objective to the runoff source apportionment and significantly reduced the uncertainty. Our study found a lower value of soil moisture data than the isotope on model calibration. However, we believe that the full potential of soil moisture data was not utilized due to the current limitations in soil moisture simulation and measurement methods, and the development of relevant technologies will make the soil moisture data more valuable for model calibration.

Effect of marine ecological compensation policy on coastal water pollution: Evidence from China based on a multiple period difference-in-differences approach

With the development and utilization of marine resources, coastal water pollution has become increasingly prominent. The marine ecological compensation (MEC) is a key measure to balance the utilization of marine resources and the protection of marine environment. This paper attempts to explore the governance effect of MEC policy on coastal water pollution. Based on panel data of coastal cities in China from 2006 to 2020, a multiple period difference-in-differences (DID) model is used to estimate the impact of MEC policy on coastal water pollution. The research results show that the coastal water pollution has decreased significantly in the polit cities after implementing the MEC policy. The governance effect of MEC policy on coastal water pollution will last for three year and cover areas within a geographical distance of 200 km. The transmission mechanisms of MEC policy on coastal water pollution are the reduction of land-based sewage, marine technological progress and optimization of industrial structure. Further, this paper provides operational suggestions for strengthening the governance effect of MEC policy on coastal water pollution.

Identifying components and controls of streamflow in a cold and arid headwater catchment

Streamflow is increasingly vulnerable to climate change over cold-arid regions. To understand the underlying mechanisms of streamflow changes, it is essential to distinguish streamflow components and identify their drivers due to various meltwater and rainfall runoff processes. This study combines the conceptual temperature-index Snowmelt Runoff Model (SRM) and wavelet coherence analysis to unravel the impacts of environmental factors on streamflow and its components over the semiarid-and-cold headwater catchment of the Manas River in Northwest China during 2001–2015. Our results show that SRM reproduces monthly observed streamflow with determination coefficients of > 0.91, Nash-Sutcliffe Efficiency of > 0.82, and absolute relative error of < 5 % during SRM calibration (2001–2007) and validation (2008–2015) periods. The meltwater runoff and rainfall runoff contribute to 42 % and 31 % of the total streamflow, respectively. The wavelet-based spectral analysis, partial wavelet coherency analysis, and multiple-wavelet coherence together demonstrate that total streamflow (rainfall runoff) is predominantly influenced by snow cover area (precipitation) at a scale of 32 (4–16) months. But the meltwater runoff is simultaneously controlled by precipitation, potential evapotranspiration, and normalized difference vegetation index on scales of 4–16 and > 32 months. Our study provides technical support for streamflow partitioning and controlling factors identification, and has implication to sustainable water resources management in cold and arid regions.

Response of ecosystem water-use efficiency to global vegetation greening

Global vegetation has been greening during the past two decades. However, relatively less is known concerning the change of carbon–water cycle coupling in response to vegetation greening. A key indicator that can characterize this coupling is water-use efficiency (WUE) of ecosystems. Therefore, we explored the impact of global vegetation greening on ecosystem WUE using Theil-Sen trend analysis, Mann-Kendall (M−K) test, stepwise regression and Lindeman Merenda Gold model (LMG) model based on the remote sensing data from 1982 to 2018. Our results showed that global vegetation greening had a positive effect on the gross primary productivity (GPP), evapotranspiration (ET) and WUE during the past thirty years. The WUE in 70 % of these vegetation greening areas, including India, China, Russia, Japan, North Korea, Europe and North America, was increased, and the WUE was increased by 0.002 g C kg H2O yr−1, which was twice as much as that of the global vegetation cover areas. Results of stepwise regression analysis showed that vegetation greening contributed 80 % of the changes in WUE, much higher than the contribution of the climate factors. GPP contributes approximately 81 % to the changes in WUE as a result of vegetation greening. In addition, we also found that, in the greening areas around the world, leaf area index (LAI) explained 80 % of the changes in WUE, and that vegetation has a positive effect WUE. Therefore, the WUE should be considered in the design of ecological restoration programs in the future, and vegetation of low water consumption would be favored to realize sustainable ecosystem services and regional development.

Assessment of Woody Plants Species and Ground Cover Status of Mandara Hills as Major Determinants of Wildlife Conservation

The study assessed the woody plants species and ground cover status of Mandara hills to seek necessary information for its sustenance. Information on woody plants resources and ground cover will help in the design of management strategies for wildlife conservation and biodiversity preservation. The investigation involved the identification and inventory of woody plant species, assessment of crown area and the ground cover of the Mandara hills. Woody plants’ species status was presented using species richness, frequency, species richness index and Simpson’s diversity index. Girth and height classes, ground cover and crown area were presented using percentages. 40 species of woody plants belonging to 21 families were inventoried. The species richness was highest in Kwalkuga (24) while the lowest was in Kuthu with 18. Among the woody plant’s species identified; Acacia kirkii (224) had the highest frequency, followed by Anogeissus leiocarpus (211). The highest diversity index was recorded in Kwalkuga (0.09) while Fafuma and Makwan with 0.02 each were the lowest. The majority of the trees and shrubs were recorded in the girth classes of 1.0-1.99 and 2.0-2.99 and that of height in 1.1-3.0, 3.1-5.0 and 5.1-7.0 respectively. Results of crown area showed highest value in Kwalkuga (20.92%) and Fafuma had the highest ground cover of grass (34.02%). This study recommends establishment of buffer zones where partial human activity can take place and the improvement of the livelihood of the residents to reduce human pressure on the resources of the hills.

Climate changes impact on the distribution of vegetation in Wasit and Nineveh regions of Iraq

Climate changes have a direct or indirect impact on many vital systems, including human and animal, as well as vegetation. The monthly precipitation and temperature for the period (1981-2021) and vegetation images (NDVI) for the period (2000-2022) from the satellite (NASA) for the regions of Ninevah and Wasit of Iraq were used to find out their variations over the space and time. It was found that the temperature was increasing with time, but the precipitation was in a state of turbulent increase in the two study areas. The distribution of vegetation was also in a state of change with time as well as within a region. The vegetation area increased with increase in precipitation which was greater in the Ninevah region than in the Wasit region. When there was a lack of precipitation, the vegetation cover area decreased in the two study areas. The increase in temperature also resulted in a decrease in the density and area of vegetation. It was found that the change in the amount of precipitation was more influential than the change in temperature on the vegetative distribution.

Vegetation Type Mapping in Southern Patagonia and Its Relationship with Ecosystem Services, Soil Carbon Stock, and Biodiversity

Vegetation Type (VT) mapping using Optical Earth observation data is essential for the management and conservation of natural resources, as well as for the evaluation of the supply of provisioning ecosystem services (ESs), the maintenance of ecosystem functions, and the conservation of biodiversity in anthropized environments. The main objective of the present work was to determine the spatial patterns of VTs related to climatic, topographic, and spectral variables across Santa Cruz province (Southern Patagonia, Argentina) in order to improve our understanding of land use cover at the regional scale. Also, we examined the spatial relationship between VTs and potential biodiversity (PB), ESs, and soil organic content (SOC) across our study region. We sampled 59,285 sites sorted into 19 major categories of land cover with a reliable discrimination level from field measurements. We selected 31 potential predictive environmental dataset covariates, which represent key factors for the spatial distribution of land cover such as climate (four), topography (three), and spectral (24) factors. All covariate maps were generated or uploaded to the Google Earth Engine cloud-based computing platform for subsequent modeling. A total of 270,292 sampling points were used for validation of the obtained classification map. The main land cover area estimates extracted from the map at the regional level identified about 142,085 km2 of grasslands (representing 58.1% of the total area), 38,355 km2 of Mata Negra Matorral thicket (15.7%), and about 25,189 km2 of bare soil (10.3%). From validation, the Overall Accuracy and the Kappa coefficient values for the classification map were 90.40% and 0.87, respectively. Pure and mixed forests presented the maximum SOC (11.3–11.8 kg m−2), followed by peatlands (10.6 kg m−2) and deciduous Nothofagus forests (10.5 kg m−2). The potential biodiversity was higher in some shrublands (64.1% in Mata Verde shrublands and 63.7% in mixed shrublands) and was comparable to those values found for open deciduous forests (Nothofagus antarctica forest with 60.4%). The provision of ESs presented maximum values at pure evergreen forests (56.7%) and minimum values at some shrubland types (Mata Negra Matorral thicket and mixed shrubland) and steppe grasslands (29.7–30.9%). This study has provided an accurate land cover and VT map that provides crucial information for ecological studies, biodiversity conservation, vegetation management and restoration, and regional strategic decision-making.

How free-ranging Indian Flying Fox (Pteropus medius) forage in urban areas? A study from Kolkata, India

Abstract Foraging behaviour plays a significant role in the fitness of animals and is influenced by habitat quality. Habitat change due to rapid urbanization often results in altered behaviour and resource use patterns in animals thriving in such changed habitats. Bats play a crucial role as tree pollinators, seed dispersers and forest regenerators. Particularly in urban areas they are among the few pollinators that help regenerating the urban green spaces. Therefore, it is crucial to understand their foraging patterns in these human-dominated landscapes. Loss and degradation of roost and foraging resources threatens the survival of many bat species, including Indian Flying Foxes (IFF). Still, very few studies have been carried out on their feeding behaviour and ecology. Hence, we carried out this study to (i) identify the foraging sites of IFF, (ii) find out the urban land cover features influencing their foraging site selection and (iii) to identify the foraging trees used by them in urban areas. IFFs were observed to forage on 16 species of trees belonging to 10 families in four different sites in urban areas, of which Ficus species are most important. Amongst various urban land covers, the area of tree cover in the foraging sites were found to significantly influence the number of foraging IFFs. Our findings strongly advocate for the protection of the trees preferred by IFFs along with overall urban tree canopy covers, as these are essential resources for the survival of bats, as well as many other species in urban areas.

Long-Term Monitoring of Surface Water Dynamics and Analysis of Its Driving Mechanism: A Case Study of the Yangtze River Basin

In-depth insights into the profound impacts of climate change and human activities on water resources are garnered through the dynamic changes in surface water, a crucial aspect of effective water resource management and the preservation of aquatic ecosystems. This paper introduces an innovative approach employing the random forest algorithm for the systematic extraction and monitoring of surface water at large regional or national scales. This method integrates spectral bands, spectral indices, and digital elevation model data, offering a novel perspective on this critical task. A data-filling model is proposed to mitigate the impact of missing data due to cloud cover. Leveraging the capabilities of the Google Earth Engine (GEE), detailed information on surface water dynamics during the rainy and dry seasons in the Yangtze River Basin (YRB) from 1991 to 2021 is extracted using Landsat time series imagery. The analysis encompasses spatial-temporal variation characteristics and trends, with a specific focus on the intricate interplay between the areal extent of surface water and hydro-meteorological factors in each sub-basin of the YRB. Importantly, this includes considerations of potential groundwater contributions to surface water. Key findings from our research include: (1) Achieving a remarkable overall classification accuracy of 0.96 ± 0.03 in obtaining reliable surface water datasets with the support of GEE. (2) Identifying significant trends, such as a noteworthy increase in rainy season surface water bodies (+248.0 km2·yr−1) and a concerning decrease in surface ice/snow cover during both rainy and dry seasons, with change rates of −39.7 km2·yr−1 and −651.3 km2·yr−1, respectively. (3) Uncovering the driving mechanisms behind these changes, revealing positive correlations between the areal extent of rainy season surface water bodies and precipitation, as well as negative correlations between surface ice/snow cover area and average surface skin temperature. It is crucial to note that these driving factors exhibit variation among secondary river systems, underscoring the complexity of surface water dynamics. Furthermore, comparative analyses with existing surface water products are conducted, contributing to a deeper understanding of the advantages and uncertainties inherent in our proposed extraction method. The proposed method for large-scale surface water extraction not only enhances the monitoring of spatio-temporal surface water dynamics in the YRB but also provides valuable insights for the sustainable utilization and protection of water resources, considering the potential role of groundwater in supplementing surface water.

A Deep Learning Based Platform for Remote Sensing Images Change Detection Integrating Crowdsourcing and Active Learning.

Remote sensing images change detection technology has become a popular tool for monitoring the change type, area, and distribution of land cover, including cultivated land, forest land, photovoltaic, roads, and buildings. However, traditional methods which rely on pre-annotation and on-site verification are time-consuming and challenging to meet timeliness requirements. With the emergence of artificial intelligence, this paper proposes an automatic change detection model and a crowdsourcing collaborative framework. The framework uses human-in-the-loop technology and an active learning approach to transform the manual interpretation method into a human-machine collaborative intelligent interpretation method. This low-cost and high-efficiency framework aims to solve the problem of weak model generalization caused by the lack of annotated data in change detection. The proposed framework can effectively incorporate expert domain knowledge and reduce the cost of data annotation while improving model performance. To ensure data quality, a crowdsourcing quality control model is constructed to evaluate the annotation qualification of the annotators and check their annotation results. Furthermore, a prototype of automatic detection and crowdsourcing collaborative annotation management platform is developed, which integrates annotation, crowdsourcing quality control, and change detection applications. The proposed framework and platform can help natural resource departments monitor land cover changes efficiently and effectively.