scholarly journals Multidimensional Assessment of Lake Water Ecosystem Services Using Remote Sensing

2021 ◽  
Vol 13 (17) ◽  
pp. 3540
Author(s):  
Donghui Shi ◽  
Yishao Shi ◽  
Qiusheng Wu
Keyword(s):  
Remote Sensing ◽  
Ecosystem Services ◽  
Lake Water ◽  
Assessment Framework ◽  
Low Level ◽  
Multidimensional Assessment ◽  
Water Ecosystem ◽  
Provisioning Ecosystem Services ◽  
High Level ◽  
Provisioning Services

Freshwater is becoming scarce worldwide with the rapidly growing population, developing industries, burgeoning agriculture, and increasing consumption. Assessment of ecosystem services has been regarded as a promising way to reconcile the increasing demand and depleting natural resources. In this paper, we proposed a multidimensional assessment framework for evaluating water provisioning ecosystem services by integrating multi-source remote sensing products. We applied the multidimensional framework to assess lake water ecosystem services in the state of Minnesota, US. We found that: (1) the water provisioning ecosystem services degraded during 1998–2018 from three assessment perspectives; (2) the output, efficiency, and trend indices have stable distribution and various spatial clustering patterns from 1998 to 2018; (3) high-level efficiency depends on high-level output, and low-level output relates to low-level efficiency; (4) Western Minnesota, including Northwest, West Central, and Southwest, degraded more severely than other zones in water provisioning services; (5) human activities impact water provisioning services in Minnesota more than climate changes. These findings can benefit policymakers by identifying the priorities for better protection, conservation, and restoration of lake ecosystems. Our multidimensional assessment framework can be adapted to evaluate ecosystem services in other regions.

scholarly journals Community Based Assessment of the Changes of Provisioning Ecosystem Services of Aral Haor of Sylhet District

2021 ◽  
Vol 04 (09) ◽  
Author(s):  
Tania Siddique Mim ◽  
Keyword(s):  
Ecosystem Services ◽  
Local Authority ◽  
Anthropogenic Activities ◽  
Primary Data ◽  
Community Based ◽  
Community Mapping ◽  
Provisioning Ecosystem Services ◽  
High Sedimentation ◽  
Community People ◽  
Provisioning Services

Haor is a well-known wetland feature in Bangladesh because of its dynamic ecosystem which is changeable with the seasonal variation. The majority people of the community are critically dependent on the haor. This paper attempts to analyse the provisioning ecosystem services of Aral Haor of Sylhet District, their changes and why the changes occurred during the last 30 years since 1990 to 2020 through community assessment. The papers argues that the community based approach integrates the local people to reveal the actual scenario of the livelihood dependency on the provision ecosystem services as they are the main user of the provisioning services. Thus the primary data were collected through observation, FGD, Community Mapping and interview with experts. The study found that community the service providing area of the Aral haor have not been changed in mentionable level over the 30 years, however the shape of the haor have been changed slightly due to high sedimentation. Along with rice cultivation during dry season, natural irrigation, fishing and bird nesting were most important to provisoing services to the community which have been changes due to both natural and anthropogenic activities. The study concludes that even having importance of the Aral hoar, not any measurer has been taken by local authority to conserve the Aral hoar ecosystem services those are very vital for the livelihood of the thousands of community people living nearby.

scholarly journals Village Level Provisioning Ecosystem Services and Their Values to Local Communities in the Peri-Urban Areas of Manila, The Philippines

Land ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 177 ◽  
Author(s):  
Shamik Chakraborty ◽  
Ram Avtar ◽  
Raveena Raj ◽  
Huynh Vuong Thu Minh
Keyword(s):  
Ecosystem Services ◽  
Urban Areas ◽  
The Philippines ◽  
Urban Landscapes ◽  
Rapid Urbanization ◽  
Local Livelihoods ◽  
Provisioning Ecosystem Services ◽  
Laguna De Bay ◽  
Special District ◽  
Provisioning Services

This study investigates different provisioning services in the peri-urban landscapes of Manila conurbation through a case study of two villages in the Jala-Jala municipality of the Laguna de Bay area in the Philippines. Laguna de Bay is an ecologically productive and important watershed for the urban and peri-urban areas of Manila for the provision of food, freshwater, and other materials. However, the lake and its ecosystem are under threat because of rapid urbanization and associated land-use changes. This study is based on a semi-quantitative survey conducted with 90 households in two villages: Special District and Paalaman. It was aimed to capture how provisioning services in the locality are connected with local livelihoods. The results obtained from the study suggest that landscapes in this peri-urban area still has considerable provisioning ecosystem services associated with local biodiversity and that this dependence on provisioning services and their relationship to peri-urban landscapes and biodiversity should be addressed for sustainable landscape management. The results have important implications for the conservation potential of biodiversity on which local livelihoods depend, in urban and peri-urban ecosystems.

scholarly journals An Ontology-Based Framework for Complex Urban Object Recognition through Integrating Visual Features and Interpretable Semantics

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Xiao Xie ◽  
Xiran Zhou ◽  
Jingzhong Li ◽  
Weijiang Dai
Keyword(s):  
Remote Sensing ◽  
Object Recognition ◽  
Probabilistic Models ◽  
Satellite Image ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Low Level ◽  
Level Data ◽  
Major Disadvantage ◽  
High Level

Although previous works have proposed sophisticatedly probabilistic models that has strong capability of extracting features from remote sensing data (e.g., convolutional neural networks, CNN), the efforts that focus on exploring the human’s semantics on the object to be recognized are required more explorations. Moreover, interpretability of feature extraction becomes a major disadvantage of the state-of-the-art CNN. Especially for the complex urban objects, which varies in geometrical shapes, functional structures, environmental contexts, etc, due to the heterogeneity between low-level data features and high-level semantics, the features derived from remote sensing data alone are limited to facilitate an accurate recognition. In this paper, we present an ontology-based methodology framework for enabling object recognition through rules extracted from the high-level semantics, rather than unexplainable features extracted from a CNN. Firstly, we semantically organize the descriptions and definitions of the object as semantics (RDF-triple rules) through our developed domain ontology. Secondly, we exploit semantic web rule language to propose an encoder model for decomposing the RDF-triple rules based on a multilayer strategy. Then, we map the low-level data features, which are defined from optical satellite image and LiDAR height, to the decomposed parts of RDF-triple rules. Eventually, we apply a probabilistic belief network (PBN) to probabilistically represent the relationships between low-level data features and high-level semantics, as well as a modified TanH function is used to optimize the recognition result. The experimental results on lacking of the training process based on data samples show that our proposed approach can reach an accurate recognition with high-level semantics. This work is conducive to the development of complex urban object recognition toward the fields including multilayer learning algorithms and knowledge graph-based relational reinforcement learning.

Remote sensing imaging simulation and cloud removal

2017 ◽  
Vol 31 (16-19) ◽  
pp. 1744079 ◽  
Author(s):  
Xifang Zhu ◽  
Feng Wu ◽  
Tao Wu ◽  
Chunyu Zhao
Keyword(s):  
Remote Sensing ◽  
Wavelet Transform ◽  
High Frequency ◽  
Low Frequency ◽  
Simulation Method ◽  
Complex Wavelet Transform ◽  
Remote Sensing Images ◽  
Low Level ◽  
Cloud Removal ◽  
High Level

Cloud obstacles obscure ground information frequently during remote sensing imaging which leads to valuable information losses. Removing clouds from a single image becomes challenging since no reference images containing cloud-free regions are available. In order to study cloud removal technologies and evaluate their performances, a method to simulate evenly and unevenly distributed clouds was proposed by analyzing the physical model of remote sensing imaging. Dual tree complex wavelet transform (DTCWT) and its features were introduced briefly. According to the frequency relationships between clouds and ground objects in remote sensing images, a novel cloud removal algorithm was proposed. The algorithm divided the cloud-contaminated image into low-level high frequency sub-bands, high-level high frequency sub-bands and low frequency sub-band by DTCWT. Low-level high frequency sub-bands were filtered to enhance the ground object information by Laplacian sharpening. The other two types of sub-bands were processed to remove clouds by cloud cover coefficient weighting (CCCW). The experiments were implemented to process cloud disturbed images produced by the proposed simulation method. The results of cloud removal from remote sensing images were analyzed. It proved the proposed algorithm is greatly superior to algorithms based on traditional wavelet transform and dark channel prior.

scholarly journals Water Ecosystem Service Quality Evaluation and Value Assessment of Taihu Lake in China

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 618
Author(s):  
Qingjian Zhao ◽  
Qiuyan Wang
Keyword(s):  
Ecosystem Services ◽  
Evaluation System ◽  
Taihu Lake ◽  
Water Environment ◽  
Human Society ◽  
Ecological Quality ◽  
Value Assessment ◽  
Service Value ◽  
Water Ecosystem ◽  
Provisioning Services

Taihu Lake is the third largest freshwater lake in China. Water ecosystems play an important role in the survival and development of human society. The evaluation of water ecosystem services is helpful to understand and grasp the changing rules of Taihu Lake’s ecosystem services value in recent years. First, we used the Water Environment Qualities Index (WQI) to evaluate the water ecological quality of Taihu Lake; second, on the basis of the survey data from 2010 to 2018, we combined economic and ecological methods to evaluate the water ecosystem of Taihu Lake. The evaluation system includes four major service functions, 11 second-class evaluation indicators and 19 index factor. Research indicates that, (1) in the past 8 years, the WQI of Taihu Lake increased year by year and Taihu Lake changed from moderate pollution to light pollution; (2) provisioning services are the main service of Taihu Lake’s water ecosystem and the order of various service values was provisioning service value > regulation service value > cultural service value > support service value, with water supply as the core function of provisioning services; and (3) the total values in 2010, 2014, and 2018 were 115.39 billion yuan, 113.31 billion yuan, and 119.96 billion yuan, respectively, showing a trend of first decreasing and then increasing. To a certain extent, the improvement in Taihu Lake’s water ecological quality has led to an increase in the value of regulation services.

Teknik Data Mining Dalam Clustering Produksi Susu Segar Di Indonesia Dengan Algoritma K-Means

2019 ◽  
Vol 1 (1) ◽  
pp. 31-39
Author(s):  
Ilham Safitra Damanik ◽  
Sundari Retno Andani ◽  
Dedi Sehendro
Keyword(s):  
Data Mining ◽  
Milk Production ◽  
Clustering Algorithm ◽  
Clustering Method ◽  
Data Mining Techniques ◽  
Low Level ◽  
Fresh Milk ◽  
Nutritional Needs ◽  
High Level ◽  
Level Cluster

Milk is an important intake to meet nutritional needs. Both consumed by children, and adults. Indonesia has many producers of fresh milk, but it is not sufficient for national milk needs. Data mining is a science in the field of computers that is widely used in research. one of the data mining techniques is Clustering. Clustering is a method by grouping data. The Clustering method will be more optimal if you use a lot of data. Data to be used are provincial data in Indonesia from 2000 to 2017 obtained from the Central Statistics Agency. The results of this study are in Clusters based on 2 milk-producing groups, namely high-dairy producers and low-milk producing regions. From 27 data on fresh milk production in Indonesia, two high-level provinces can be obtained, namely: West Java and East Java. And 25 others were added in 7 provinces which did not follow the calculation of the K-Means Clustering Algorithm, including in the low level cluster.

Determinants of Abuse of the Bodies of the Dead

2019 ◽  
pp. 71-77
Author(s):  
Margarita Khomyakova
Keyword(s):  
Low Income ◽  
Criminal Code ◽  
Value Judgments ◽  
Legal Norms ◽  
Low Level ◽  
Medical Institutions ◽  
Specific Object ◽  
The Subject ◽  
The Dead ◽  
High Level

The author analyzes definitions of the concepts of determinants of crime given by various scientists and offers her definition. In this study, determinants of crime are understood as a set of its causes, the circumstances that contribute committing them, as well as the dynamics of crime. It is noted that the Russian legislator in Article 244 of the Criminal Code defines the object of this criminal assault as public morality. Despite the use of evaluative concepts both in the disposition of this norm and in determining the specific object of a given crime, the position of criminologists is unequivocal: crimes of this kind are immoral and are in irreconcilable conflict with generally accepted moral and legal norms. In the paper, some views are considered with regard to making value judgments which could hardly apply to legal norms. According to the author, the reasons for abuse of the bodies of the dead include economic problems of the subject of a crime, a low level of culture and legal awareness; this list is not exhaustive. The main circumstances that contribute committing abuse of the bodies of the dead and their burial places are the following: low income and unemployment, low level of criminological prevention, poor maintenance and protection of medical institutions and cemeteries due to underperformance of state and municipal bodies. The list of circumstances is also open-ended. Due to some factors, including a high level of latency, it is not possible to reflect the dynamics of such crimes objectively. At the same time, identification of the determinants of abuse of the bodies of the dead will reduce the number of such crimes.

scholarly journals EXPRESS: Marketers Project Their Personal Preferences onto Consumers: Overcoming the Threat of Egocentric Decision Making

2021 ◽  
pp. 002224372199837
Author(s):  
Walter Herzog ◽  
Johannes D. Hattula ◽  
Darren W. Dahl
Keyword(s):  
Decision Making ◽  
Consumer Preferences ◽  
Research Question ◽  
Pilot Studies ◽  
Low Level ◽  
Marketing Managers ◽  
False Consensus Effect ◽  
False Consensus ◽  
High Level

This research explores how marketing managers can avoid the so-called false consensus effect—the egocentric tendency to project personal preferences onto consumers. Two pilot studies were conducted to provide evidence for the managerial importance of this research question and to explore how marketing managers attempt to avoid false consensus effects in practice. The results suggest that the debiasing tactic most frequently used by marketers is to suppress their personal preferences when predicting consumer preferences. Four subsequent studies show that, ironically, this debiasing tactic can backfire and increase managers’ susceptibility to the false consensus effect. Specifically, the results suggest that these backfire effects are most likely to occur for managers with a low level of preference certainty. In contrast, the results imply that preference suppression does not backfire but instead decreases false consensus effects for managers with a high level of preference certainty. Finally, the studies explore the mechanism behind these results and show how managers can ultimately avoid false consensus effects—regardless of their level of preference certainty and without risking backfire effects.

Sign in / Sign up

Export Citation Format

Share Document