scholarly journals Remote Sensing Greenness and Urbanization in Ecohydrological Model Analysis: Asia and Australasia (1982–2015)

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4693
Author(s):  
Danlu Cai ◽  
Klaus Fraedrich ◽  
Yanning Guan ◽  
Shan Guo ◽  
Chunyan Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
General Pattern ◽  
Tree Plantations ◽  
Global Changes ◽  
Illegal Logging ◽  
Vegetation Greenness ◽  
Unique Distribution ◽  
The Subject ◽  
Ecohydrological Model

Linking remote sensing information and ecohydrological models to improve understanding of terrestrial biosphere responses to climate and land use change has become the subject of increased interest due to the impacts of current global changes and the effect on the sustainability of human lifestyles. An application to Asia and Australasia (1982–2015) is presented, revealing the following results: (i) The broad distribution of regions with the enhanced vegetation greenness only follows the general pattern as for the whole, without obvious dependence on regional or climate fluxes ratios. That indicates a prevailing increasing greenness over land due to both the impacts of current global changes and the sustainability of human lifestyles; (ii) regions with vegetation greenness reduction reveal a unique distribution, concentrating in the water-limited domain due to the impacts of external (climatically “dry gets drier and wet gets wetter”) and internal (anthropogenically increased evaporation) changes; (iii) the external changes of dryness diverge at the boundary separating energy from water-limited regimes, and the internal changes indicate large-scale afforestation and deforestation) that occur mainly in China and Russia due to a conservation program and illegal logging, respectively, and a massive conversion of tropical forest to industrial tree plantations in Southeast Asia, leading to an increased evaporation.

Smart Dust and Remote Sensing: The Political Subject in Autonomous Systems

2016 ◽  
Author(s):  
Ryan Bishop
Keyword(s):  
Remote Sensing ◽  
Ubiquitous Computing ◽  
Real Time ◽  
Large Scale ◽  
Autonomous Systems ◽  
The Political ◽  
Sensing Systems ◽  
Smart Dust ◽  
Remote Sensing Systems ◽  
The Subject

A legacy of the ‘Long Cold War’ can be found in the multiple large-scale interrelated remote sensing systems operative in the present. Smart dust, for example, constitutes the basis of polyscalar computer systems of remote sensing at micro-levels and relates to ubiquitous computing, ‘pervasive networks’ and ‘utility fogs’ as potentially transmitting endless streams of ‘real time’ or stored data. Developed initially for DARPA, Smart Dust started with work by Kris Pister's team at UC Berkeley, who refer to the project as ‘autonomous sensing and communication in a cubic millimetre.’ The Limited Test Ban Treaty of 1963 pushed nuclear testing underground, forcing innovations in modes of remote sensing for purposes of verification. Because so much of teletechnological development depends on the understanding of the subject as an agent enacting its will upon a world of objects (including other subjects), the means of imagining extensions of that sensing and acting self invariably fold into and influence the interpretation of that self. The chapter provides a meditation on 'the auto-' and ‘the nomos’ as they pertain to autonomous sensing systems and the immaterial worlds that helped them come into being as well as their continuation into further systems of control at a distance.

scholarly journals Mapping Paddy Rice with Satellite Remote Sensing: A Review

2021 ◽  
Vol 13 (2) ◽  
pp. 503
Author(s):  
Rongkun Zhao ◽  
Yuechen Li ◽  
Mingguo Ma
Keyword(s):  
Remote Sensing ◽  
Data Integration ◽  
Large Scale ◽  
Microwave Remote Sensing ◽  
Paddy Rice ◽  
Data Sources ◽  
Accurate Estimation ◽  
Global Changes ◽  
Optical Remote Sensing ◽  
Advantages And Disadvantages

Paddy rice is a staple food of three billion people in the world. Timely and accurate estimation of the paddy rice planting area and paddy rice yield can provide valuable information for the government, planners and decision makers to formulate policies. This article reviews the existing paddy rice mapping methods presented in the literature since 2010, classifies these methods, and analyzes and summarizes the basic principles, advantages and disadvantages of these methods. According to the data sources used, the methods are divided into three categories: (I) Optical mapping methods based on remote sensing; (II) Mapping methods based on microwave remote sensing; and (III) Mapping methods based on the integration of optical and microwave remote sensing. We found that the optical remote sensing data sources are mainly MODIS, Landsat, and Sentinel-2, and the emergence of Sentinel-1 data has promoted research on radar mapping methods for paddy rice. Multisource data integration further enhances the accuracy of paddy rice mapping. The best methods are phenology algorithms, paddy rice mapping combined with machine learning, and multisource data integration. Innovative methods include the time series similarity method, threshold method combined with mathematical models, and object-oriented image classification. With the development of computer technology and the establishment of cloud computing platforms, opportunities are provided for obtaining large-scale high-resolution rice maps. Multisource data integration, paddy rice mapping under different planting systems and the connection with global changes are the focus of future development priorities.

scholarly journals A Review of Remote Sensing of Submerged Aquatic Vegetation for Non-Specialists

2021 ◽  
Vol 13 (4) ◽  
pp. 623
Author(s):  
Gillian S. L. Rowan ◽  
Margaret Kalacska
Keyword(s):  
Remote Sensing ◽  
Water Column ◽  
Large Scale ◽  
Submerged Aquatic Vegetation ◽  
Aquatic Vegetation ◽  
Global Climate ◽  
Training Data ◽  
Suspended Particulate ◽  
The Subject

Submerged aquatic vegetation (SAV) is a critical component of aquatic ecosystems. It is however understudied and rapidly changing due to global climate change and anthropogenic disturbances. Remote sensing (RS) can provide the efficient, accurate and large-scale monitoring needed for proper SAV management and has been shown to produce accurate results when properly implemented. Our objective is to introduce RS to researchers in the field of aquatic ecology. Applying RS to underwater ecosystems is complicated by the water column as water, and dissolved or suspended particulate matter, interacts with the same energy that is reflected or emitted by the target. This is addressed using theoretical or empiric models to remove the water column effect, though no model is appropriate for all aquatic conditions. The suitability of various sensors and platforms to aquatic research is discussed in relation to both SAV as the subject and to project aims and resources. An overview of the required corrections, processing and analysis methods for passive optical imagery is presented and discussed. Previous applications of remote sensing to identify and detect SAV are briefly presented and notable results and lessons are discussed. The success of previous work generally depended on the variability in, and suitability of, the available training data, the data’s spatial and spectral resolutions, the quality of the water column corrections and the level to which the SAV was being investigated (i.e., community versus species.)

scholarly journals Large Scale Agricultural Plastic Mulch Detecting and Monitoring with Multi-Source Remote Sensing Data: A Case Study in Xinjiang, China

2019 ◽  
Vol 11 (18) ◽  
pp. 2088 ◽  
Author(s):  
Yuankang Xiong ◽  
Qingling Zhang ◽  
Xi Chen ◽  
Anming Bao ◽  
Jieyun Zhang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Crop Production ◽  
Large Scale ◽  
General Pattern ◽  
Temporal Analysis ◽  
Classification And Regression Tree ◽  
Plastic Mulch ◽  
Temporal And Spatial Distribution ◽  
Plastic Mulching ◽  
Multi Temporal

Plastic mulching has been widely practiced in crop cultivation worldwide due to its potential to significantly increase crop production. However, it also has a great impact on the regional climate and ecological environment. More importantly, it often leads to unexpected soil pollution due to fine plastic residuals. Therefore, accurately and timely monitoring of the temporal and spatial distribution of plastic mulch practice in large areas is of great interest to assess its impacts. However, existing plastic-mulched farmland (PMF) detecting efforts are limited to either small areas with high-resolution images or coarse resolution images of large areas. In this study, we examined the potential of cloud computing and multi-temporal, multi-sensor satellite images for detecting PMF in large areas. We first built the plastic-mulched farmland mapping algorithm (PFMA) rules through analyzing its spectral, temporal, and auxiliary features in remote sensing imagery with the classification and regression tree (CART). We then applied the PFMA in the dry region of Xinjiang, China, where a water resource is very scarce and thus plastic mulch has been intensively used and its usage is expected to increase significantly in the near future. The experimental results demonstrated that the PFMA reached an overall accuracy of 92.2% with a producer’s accuracy of 97.6% and a user’s accuracy of 86.7%, and the F-score was 0.914 for the PMF class. We further monitored and analyzed the dynamics of plastic mulch practiced in Xinjiang by applying the PFMA to the years 2000, 2005, 2010, and 2015. The general pattern of plastic mulch usage dynamic in Xinjiang during the period from 2000 to 2015 was well captured by our multi-temporal analysis.

The Impact of Quantitative Easing on Emerging Markets – Literature Review

e-Finanse ◽  
2018 ◽  
Vol 14 (4) ◽  
pp. 67-76
Author(s):  
Piotr Bartkiewicz
Keyword(s):  
Emerging Markets ◽  
Large Scale ◽  
Empirical Literature ◽  
Quantitative Easing ◽  
Methodological Choices ◽  
The Subject ◽  
Methodological Approaches ◽  
The Impact ◽  
Sufficient Precision

AbstractThe article presents the results of the review of the empirical literature regarding the impact of quantitative easing (QE) on emerging markets (EMs). The subject is of interest to policymakers and researchers due to the increasingly larger role of EMs in the world economy and the large-scale capital flows occurring after 2009. The review is conducted in a systematic manner and takes into consideration different methodological choices, samples and measurement issues. The paper puts the summarized results in the context of transmission channels identified in the literature. There are few distinct methodological approaches present in the literature. While there is a consensus regarding the direction of the impact of QE on EMs, its size and durability have not yet been assessed with sufficient precision. In addition, there are clear gaps in the empirical findings, not least related to relative underrepresentation of the CEE region (in particular, Poland).

Gentrification and functional change in Budapest – ‘ruin bars’ and the commodification of housing in a post-socialist context

2020 ◽  
Vol 65 (1) ◽  
pp. 17-26
Author(s):  
Gergely Olt ◽  
Adrienne Csizmady
Keyword(s):  
Ownership Structure ◽  
Hospitality Industry ◽  
Housing Stock ◽  
Field Research ◽  
Functional Change ◽  
Global Changes ◽  
Heritage Buildings ◽  
The Subject ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality

AbstractThe growth of the tourism and hospitality industry played an important role in the gentrification of the post-socialist city of Budapest. Although disinvestment was present, reinvestment was moderate for decades after 1989. Privatisation of individual tenancies and the consequent fragmented ownership structure of heritage buildings made refurbishment and reinvestment less profitable. Because of local contextual factors and global changes in consumption habits, the function of the dilapidated 19th century housing stock transformed in the 2000s, and the residential neighbourhood which was the subject of the research turned into the so called ‘party district’. The process was followed in our ongoing field research. The functional change made possible speculative investment in inner city housing and played a major role in the commodification of the disinvested housing stock.

Development of public-private partnerships in the regional dimension

2020 ◽  
Vol 93 (4) ◽  
pp. 133-145
Author(s):  
T. M. Barbysheva ◽  
Keyword(s):  
Public Administration ◽  
Russian Federation ◽  
Large Scale ◽  
Public Private Partnership ◽  
Financial Resources ◽  
Business And Society ◽  
Private Business ◽  
Private Partnership ◽  
The Subject ◽  
The Russian Federation

Public-private partnership (PPP) in the conditions of the set strategic tasks by the President of the Russian Federation until 2030 can become one of the sources of attracting financial resources for implementation of the large-scale projects. In this regard, it is relevant to systematize the forms of PPPs and the scope of their application. Based on a study of different views on the essence of PPP, as well as taking into account the development of public administration in Russia, the author proposed the use of public-public-private partnership as a form of development of cooperation between the state, private business and society. The polyformism of PPPs is reflected in the presented classification. Based on the analysis of PPP development in the regional context, hypothesis on the correlation between the level of PPP and the socio-economic development of the subject of the Russian Federation was confirmed.

Building a Culture of Ethical, Comparable, Authentic Assessment

2019 ◽  
pp. 463-481
Author(s):  
Andrew Reid ◽  
Julie Ballantyne
Keyword(s):  
Teaching And Learning ◽  
Large Scale ◽  
Authentic Assessment ◽  
Subject Area ◽  
Music Educators ◽  
System Level ◽  
Diverse Range ◽  
Effective Learning ◽  
School Based ◽  
The Subject

In an ideal world, assessment should be synonymous with effective learning and reflect the intricacies of the subject area. It should also be aligned with the ideals of education: to provide equitable opportunities for all students to achieve and to allow both appropriate differentiation for varied contexts and students and comparability across various contexts and students. This challenge is made more difficult in circumstances in which the contexts are highly heterogeneous, for example in the state of Queensland, Australia. Assessment in music challenges schooling systems in unique ways because teaching and learning in music are often naturally differentiated and diverse, yet assessment often calls for standardization. While each student and teacher has individual, evolving musical pathways in life, the syllabus and the system require consistency and uniformity. The challenge, then, is to provide diverse, equitable, and quality opportunities for all children to learn and achieve to the best of their abilities. This chapter discusses the designing and implementation of large-scale curriculum as experienced in secondary schools in Queensland, Australia. The experiences detailed explore the possibilities offered through externally moderated school-based assessment. Also discussed is the centrality of system-level clarity of purpose, principles and processes, and the provision of supportive networks and mechanisms to foster autonomy for a diverse range of music educators and contexts. Implications for education systems that desire diversity, equity, and quality are discussed, and the conclusion provokes further conceptualization and action on behalf of students, teachers, and the subject area of music.

MILL: Channel Attention–based Deep Multiple Instance Learning for Landslide Recognition

2021 ◽  
Vol 17 (2s) ◽  
pp. 1-11
Author(s):  
Xiaochuan Tang ◽  
Mingzhe Liu ◽  
Hao Zhong ◽  
Yuanzhen Ju ◽  
Weile Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Large Scale ◽  
Remote Sensing Image ◽  
Disaster Risk ◽  
Multiple Instance Learning ◽  
Remote Sensing Images ◽  
Loess Area ◽  
Remote Sensing Image Classification ◽  
Natural Disaster Risk

Landslide recognition is widely used in natural disaster risk management. Traditional landslide recognition is mainly conducted by geologists, which is accurate but inefficient. This article introduces multiple instance learning (MIL) to perform automatic landslide recognition. An end-to-end deep convolutional neural network is proposed, referred to as Multiple Instance Learning–based Landslide classification (MILL). First, MILL uses a large-scale remote sensing image classification dataset to build pre-train networks for landslide feature extraction. Second, MILL extracts instances and assign instance labels without pixel-level annotations. Third, MILL uses a new channel attention–based MIL pooling function to map instance-level labels to bag-level label. We apply MIL to detect landslides in a loess area. Experimental results demonstrate that MILL is effective in identifying landslides in remote sensing images.

scholarly journals Remote Sensing Methods for the Biophysical Characterization of Protected Areas Globally: Challenges and Opportunities

2021 ◽  
Vol 10 (6) ◽  
pp. 384
Author(s):  
Javier Martínez-López ◽  
Bastian Bertzky ◽  
Simon Willcock ◽  
Marine Robuchon ◽  
María Almagro ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Protected Areas ◽  
Large Scale ◽  
Anthropogenic Activities ◽  
Global Scale ◽  
Area Network ◽  
Biophysical Characterization ◽  
Challenges And Opportunities ◽  
Scale Characterization

Protected areas (PAs) are a key strategy to reverse global biodiversity declines, but they are under increasing pressure from anthropogenic activities and concomitant effects. Thus, the heterogeneous landscapes within PAs, containing a number of different habitats and ecosystem types, are in various degrees of disturbance. Characterizing habitats and ecosystems within the global protected area network requires large-scale monitoring over long time scales. This study reviews methods for the biophysical characterization of terrestrial PAs at a global scale by means of remote sensing (RS) and provides further recommendations. To this end, we first discuss the importance of taking into account the structural and functional attributes, as well as integrating a broad spectrum of variables, to account for the different ecosystem and habitat types within PAs, considering examples at local and regional scales. We then discuss potential variables, challenges and limitations of existing global environmental stratifications, as well as the biophysical characterization of PAs, and finally offer some recommendations. Computational and interoperability issues are also discussed, as well as the potential of cloud-based platforms linked to earth observations to support large-scale characterization of PAs. Using RS to characterize PAs globally is a crucial approach to help ensure sustainable development, but it requires further work before such studies are able to inform large-scale conservation actions. This study proposes 14 recommendations in order to improve existing initiatives to biophysically characterize PAs at a global scale.

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