Terrestrial ecosystem monitoring in Canada and the greater role for integrated earth observation

2014 ◽  
Vol 22 (2) ◽  
pp. 179-187 ◽  
Author(s):  
Jon Pasher ◽  
Paul A. Smith ◽  
Mark R. Forbes ◽  
Jason Duffe
Keyword(s):  
Ecosystem Services ◽  
Industrial Development ◽  
Large Scale ◽  
National Level ◽  
Terrestrial Ecosystem ◽  
Earth Observation ◽  
Resource Extraction ◽  
Conservation Priorities ◽  
Information Need ◽  
Ecosystem Monitoring

Ecosystems are valuable as well as aesthetic. The natural functions of ecosystems can have profound effects on the economy, and human and wildlife health. The aggregate value of these “ecosystem services” may far exceed the economic value derived from resource extraction or industrial development, especially when considering the costs of restoring ecosystems. There is increasing interest, therefore, in monitoring and protecting ecosystems, and accounting for the biodiversity and services they provide. In 2010, Canada undertook a review of ecosystem status and trends that identified the regions and ecosystems where management is most urgently needed. The authors concluded that more large-scale, long-term, standardized, and spatially complete information is needed for effective monitoring and management. Satellite-based earth observation (EO) tools were seen as a means of addressing this information need. In a separate exercise, a list of priority questions for conservation policy and management at a national level was produced: the resolution of three-quarters of those questions appears to depend on EO tools to a significant or critical extent. Canada has a long and successful history in all aspects of earth observation, placing it amongst the leaders in the international remote sensing community. Whereas the need for measuring ecosystem services to humans and wildlife is increasingly important, the challenges for doing so are increasingly significant and the technology required is increasingly complex. Overcoming these challenges is necessary to address emerging conservation priorities including measurement of ecosystem attributes to support habitat conservation for Species at Risk, measuring functional capacity of ecosystems to mitigate effects of climate change, monitoring and mitigating effects of resource extraction, and supporting industrial development in Canada’s north. Addressing emerging priorities requires dialogue among ecologists and decision makers, coordinated at regional and national scales, and requires drawing on the best EO technologies and infrastructure available. This review highlights the urgency of a coordinated approach for innovative applications of EO tools toward conservation and discusses some of the key elements that might be included and opportunities and challenges that might be encountered, by such an approach.

scholarly journals Resource extraction, resistance, and religion in Nicaragua

2019 ◽  
Author(s):  
◽  
Michael Stephen Hendricks
Keyword(s):  
Social Engagement ◽  
Large Scale ◽  
Qualitative Interviews ◽  
National Level ◽  
Resource Extraction ◽  
Community Resistance ◽  
Individual Level ◽  
Local Opposition ◽  
Role Of Religion

My dissertation examines the causes of protest over resource extraction in Nicaragua, and underlines the role of religion as a catalyst for sustained and successful challenges against resource extraction. With few exceptions, existing research has rarely explored individual-level attitudes related to resource extraction. Opposition and support towards mining are not mutually exclusive from protest success in overturning a mining concession. They build off each other. If a community strongly opposes mining, especially related to economic threats and grievances tied to environmental and agricultural concerns, it will likely continue its resistance movement until it sees policy changes that halt or overturn mining concessions in the community. However, if there is support for mining in the community over economic opportunities and benefits, mining activities will likely prevail because individuals in the community believe they will economically benefit from mining. I examine the causes of opposition and support over resource extraction in two Nicaraguan mining communities through qualitative interviews and public opinion surveys. I am particularly interested in why individuals either support or oppose resource extraction, and how these attitudes are shaped by social engagement (i.e., formed or reinforced) through participation in various types of local organizations. In doing so, scholars can begin to understand different individual responses to mining that underline the aggregate stories of homogenous community resistance and better understand the individual mechanisms that lead citizens in extractive areas to either partake in mining resistance or abstain. Additionally, existing literature has largely ignored the role of religion as a catalyst in fomenting successful resistance against resource extraction. In fact, there are thousands of protests against resource extraction in Latin America and hundreds throughout Nicaragua, but only a small fraction of them are effective in stopping mining concessions. Because there are clear power imbalances between communities and extractive companies, preventing a new mining project from being implemented or ending an existing project is a very difficult endeavor. Large-scale extractive companies often utilize "divide and rule" strategies that successfully break up local opposition to extraction. My dissertation examines how religion acts as a catalyzing agent in providing communities with the organizational tools and resources that assist individuals in effectively and sustainably to unite and organize against mining until the community achieves a successful national-level policy change reversing mining concessions.

Namibia's community-based natural resource management programme: an unrecognized payments for ecosystem services scheme

2011 ◽  
Vol 38 (4) ◽  
pp. 445-453 ◽  
Author(s):  
ROBIN NAIDOO ◽  
L. CHRIS WEAVER ◽  
MARIE DE LONGCAMP ◽  
PIERRE DU PLESSIS
Keyword(s):  
Ecosystem Services ◽  
Large Scale ◽  
National Level ◽  
Natural Resources Management ◽  
Payments For Ecosystem Services ◽  
Community Based ◽  
Resources Management ◽  
Financial Benefits ◽  
Wildlife Populations ◽  
Definition Of

SUMMARYPayments for ecosystem services (PES) programmes are widely recognized as novel and innovative mechanisms that seek to promote the conservation of biodiversity while simultaneously improving human livelihoods. A number of national-level PES programmes have made significant contributions to advancing knowledge of these mechanisms. Namibia's community-based natural resources management (CBNRM) programme effectively operates as one such large-scale PES programme, making it one of the world's longest-standing schemes. In this review, Namibia's CBNRM scheme is compared and contrasted with the formal definition of a PES programme, some of the outcomes that the programme has produced illustrated by examples, and the challenges that must still be faced identified. Most of the requirements for a PES programme are present in Namibia's CBNRM programme, and when it does not meet these criteria, it is not exceptional. Notwithstanding the increases in wildlife populations and financial benefits that have been associated with the programme, a major challenge going forward revolves around diversifying the number of services produced. Namibia's CBNRM programme has much to contribute to the design of large-scale PES schemes.

scholarly journals Sectoral strategy financing: strategic principles and efficiency

2021 ◽  
pp. 77-87
Author(s):  
Nikita I. Sasaev ◽  
Keyword(s):  
Industrial Development ◽  
Large Scale ◽  
Structural Changes ◽  
National Level ◽  
Social Utility ◽  
Financial Resources

Structural changes and transformation of society, reindustrialization and digitalization of the economy, coupled with the manifestation of trends at the global, national and regional levels, emerge new strategic opportunities. Often, such opportunities, decomposed to the level of strategic priorities affecting both industrial development within a particular region and industrial development at the national level, declare the need to develop and implement large-scale projects that require the involvement of a large amount of resources and, above all, financial resources. In this regard, this research examines the main strategic principles, following which contributes to effective financing in industrial strategizing. Among such principles, the author distinguishes: social utility, complementarity of interests, hierarchy and integration, innovation, efficiency and multiplicativity. It is noted that compliance with these principles significantly simplifies the attraction of financial resources for the implementation of industrial strategies through increasing investment attractiveness.

HOME VISITS DURING THE FIRST MONTH OF DELIVERY FOR RECENTLY DELIVERED WOMEN IN UTTAR PRADESH, INDIA

2020 ◽  
Vol 6 (5) ◽  
pp. 1183-1189
Author(s):  
Dr. Tridibesh Tripathy ◽  
Dr. Umakant Prusty ◽  
Dr. Chintamani Nayak ◽  
Dr. Rakesh Dwivedi ◽  
Dr. Mohini Gautam
Keyword(s):  
Large Scale ◽  
National Level ◽  
Uttar Pradesh ◽  
Life Time ◽  
Structured Interview ◽  
The Other ◽  
Registration System ◽  
Action Group ◽  
Current Article ◽  
The Impact

The current article of Uttar Pradesh (UP) is about the ASHAs who are the daughters-in-law of a family that resides in the same community that they serve as the grassroots health worker since 2005 when the NRHM was introduced in the Empowered Action Group (EAG) states. UP is one such Empowered Action Group (EAG) state. The current study explores the actual responses of Recently Delivered Women (RDW) on their visits during the first month of their recent delivery. From the catchment area of each of the 250 ASHAs, two RDWs were selected who had a child in the age group of 3 to 6 months during the survey. The response profiles of the RDWs on the post- delivery first month visits are dwelled upon to evolve a picture representing the entire state of UP. The relevance of the study assumes significance as detailed data on the modalities of postnatal visits are available but not exclusively for the first month period of their recent delivery. The details of the post-delivery first month period related visits are not available even in large scale surveys like National Family Health Survey 4 done in 2015-16. The current study gives an insight in to these visits with a five-point approach i.e. type of personnel doing the visit, frequency of the visits, visits done in a particular week from among those four weeks separately for the three visits separately. The current study is basically regarding the summary of this Penta approach for the post- delivery one-month period.     The first month period after each delivery deals with 70% of the time of the postnatal period & the entire neonatal period. Therefore, it does impact the Maternal Mortality Rate & Ratio (MMR) & the Neonatal Mortality Rates (NMR) in India and especially in UP through the unsafe Maternal & Neonatal practices in the first month period after delivery. The current MM Rate of UP is 20.1 & MM Ratio is 216 whereas the MM ratio is 122 in India (SRS, 2019). The Sample Registration System (SRS) report also mentions that the Life Time Risk (LTR) of a woman in pregnancy is 0.7% which is the highest in the nation (SRS, 2019). This means it is very risky to give birth in UP in comparison to other regions in the country (SRS, 2019). This risk is at the peak in the first month period after each delivery. Similarly, the current NMR in India is 23 per 1000 livebirths (UNIGME,2018). As NMR data is not available separately for states, the national level data also hold good for the states and that’s how for the state of UP as well. These mortalities are the impact indicators and such indicators can be reduced through long drawn processes that includes effective and timely visits to RDWs especially in the first month period after delivery. This would help in making their post-natal & neonatal stage safe. This is the area of post-delivery first month visit profile detailing that the current article helps in popping out in relation to the recent delivery of the respondents.   A total of four districts of Uttar Pradesh were selected purposively for the study and the data collection was conducted in the villages of the respective districts with the help of a pre-tested structured interview schedule with both close-ended and open-ended questions.  The current article deals with five close ended questions with options, two for the type of personnel & frequency while the other three are for each of the three visits in the first month after the recent delivery of respondents. In addition, in-depth interviews were also conducted amongst the RDWs and a total 500 respondents had participated in the study.   Among the districts related to this article, the results showed that ASHA was the type of personnel who did the majority of visits in all the four districts. On the other hand, 25-40% of RDWs in all the 4 districts replied that they did not receive any visit within the first month of their recent delivery. Regarding frequency, most of the RDWs in all the 4 districts received 1-2 times visits by ASHAs.   Regarding the first visit, it was found that the ASHAs of Barabanki and Gonda visited less percentage of RDWs in the first week after delivery. Similarly, the second visit revealed that about 1.2% RDWs in Banda district could not recall about the visit. Further on the second visit, the RDWs responded that most of them in 3 districts except Gonda district did receive the second postnatal visit in 7-15 days after their recent delivery. Less than half of RDWs in Barabanki district & just more than half of RDWs in Gonda district received the third visit in 15-21 days period after delivery. For the same period, the majority of RDWs in the rest two districts responded that they had been entertained through a home visit.

scholarly journals Analysis of 220 Years of Floodplain Population Dynamics in the US at Different Spatial Scales

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 141
Author(s):  
Firoza Akhter ◽  
Maurizio Mazzoleni ◽  
Luigia Brandimarte
Keyword(s):  
Population Dynamics ◽  
Large Scale ◽  
Spatial Scales ◽  
National Level ◽  
State Level ◽  
Economic Activities ◽  
Protection Measures ◽  
Management Planning ◽  
The Us ◽  
Over Time

In this study, we explore the long-term trends of floodplain population dynamics at different spatial scales in the contiguous United States (U.S.). We exploit different types of datasets from 1790–2010—i.e., decadal spatial distribution for the population density in the US, global floodplains dataset, large-scale data of flood occurrence and damage, and structural and nonstructural flood protection measures for the US. At the national level, we found that the population initially settled down within the floodplains and then spread across its territory over time. At the state level, we observed that flood damages and national protection measures might have contributed to a learning effect, which in turn, shaped the floodplain population dynamics over time. Finally, at the county level, other socio-economic factors such as local flood insurances, economic activities, and socio-political context may predominantly influence the dynamics. Our study shows that different influencing factors affect floodplain population dynamics at different spatial scales. These facts are crucial for a reliable development and implementation of flood risk management planning.

scholarly journals Neural methods for effective, efficient, and exposure-aware information retrieval

2021 ◽  
Vol 55 (1) ◽  
pp. 1-2
Author(s):  
Bhaskar Mitra
Keyword(s):  
Information Retrieval ◽  
Language Processing ◽  
Large Scale ◽  
Web Search ◽  
Real Life ◽  
Inverted Index ◽  
Information Need ◽  
Product Model ◽  
Performance Improvements ◽  
Deep Model

Neural networks with deep architectures have demonstrated significant performance improvements in computer vision, speech recognition, and natural language processing. The challenges in information retrieval (IR), however, are different from these other application areas. A common form of IR involves ranking of documents---or short passages---in response to keyword-based queries. Effective IR systems must deal with query-document vocabulary mismatch problem, by modeling relationships between different query and document terms and how they indicate relevance. Models should also consider lexical matches when the query contains rare terms---such as a person's name or a product model number---not seen during training, and to avoid retrieving semantically related but irrelevant results. In many real-life IR tasks, the retrieval involves extremely large collections---such as the document index of a commercial Web search engine---containing billions of documents. Efficient IR methods should take advantage of specialized IR data structures, such as inverted index, to efficiently retrieve from large collections. Given an information need, the IR system also mediates how much exposure an information artifact receives by deciding whether it should be displayed, and where it should be positioned, among other results. Exposure-aware IR systems may optimize for additional objectives, besides relevance, such as parity of exposure for retrieved items and content publishers. In this thesis, we present novel neural architectures and methods motivated by the specific needs and challenges of IR tasks. We ground our contributions with a detailed survey of the growing body of neural IR literature [Mitra and Craswell, 2018]. Our key contribution towards improving the effectiveness of deep ranking models is developing the Duet principle [Mitra et al., 2017] which emphasizes the importance of incorporating evidence based on both patterns of exact term matches and similarities between learned latent representations of query and document. To efficiently retrieve from large collections, we develop a framework to incorporate query term independence [Mitra et al., 2019] into any arbitrary deep model that enables large-scale precomputation and the use of inverted index for fast retrieval. In the context of stochastic ranking, we further develop optimization strategies for exposure-based objectives [Diaz et al., 2020]. Finally, this dissertation also summarizes our contributions towards benchmarking neural IR models in the presence of large training datasets [Craswell et al., 2019] and explores the application of neural methods to other IR tasks, such as query auto-completion.

scholarly journals Estimating the Earth’s Outgoing Longwave Radiation Measured from a Moon-Based Platform

2021 ◽  
Vol 13 (11) ◽  
pp. 2201
Author(s):  
Hanlin Ye ◽  
Huadong Guo ◽  
Guang Liu ◽  
Jinsong Ping ◽  
Lu Zhang ◽  
...  
Keyword(s):  
Outgoing Longwave Radiation ◽  
Large Scale ◽  
Single Point ◽  
Longwave Radiation ◽  
Earth Observation ◽  
Artificial Satellites ◽  
Earth Observations ◽  
The Earth ◽  
Observation Geometry ◽  
Global Mean

Moon-based Earth observations have attracted significant attention across many large-scale phenomena. As the only natural satellite of the Earth, and having a stable lunar surface as well as a particular orbit, Moon-based Earth observations allow the Earth to be viewed as a single point. Furthermore, in contrast with artificial satellites, the varied inclination of Moon-based observations can improve angular samplings of specific locations on Earth. However, the potential for estimating the global outgoing longwave radiation (OLR) from the Earth with such a platform has not yet been fully explored. To evaluate the possibility of calculating OLR using specific Earth observation geometry, we constructed a model to estimate Moon-based OLR measurements and investigated the potential of a Moon-based platform to acquire the necessary data to estimate global mean OLR. The primary method of our study is the discretization of the observational scope into various elements and the consequent integration of the OLR of all elements. Our results indicate that a Moon-based platform is suitable for global sampling related to the calculation of global mean OLR. By separating the geometric and anisotropic factors from the measurement calculations, we ensured that measured values include the effects of the Moon-based Earth observation geometry and the anisotropy of the scenes in the observational scope. Although our results indicate that higher measured values can be achieved if the platform is located near the center of the lunar disk, a maximum difference between locations of approximately 9 × 10−4 W m−2 indicates that the effect of location is too small to remarkably improve observation performance of the platform. In conclusion, our analysis demonstrates that a Moon-based platform has the potential to provide continuous, adequate, and long-term data for estimating global mean OLR.

scholarly journals Using the Global Hydrodynamic Model and GRACE Follow-On Data to Access the 2020 Catastrophic Flood in Yangtze River Basin

2021 ◽  
Vol 13 (15) ◽  
pp. 3023
Author(s):  
Jinghua Xiong ◽  
Shenglian Guo ◽  
Jiabo Yin ◽  
Lei Gu ◽  
Feng Xiong
Keyword(s):  
River Basin ◽  
Hydrodynamic Model ◽  
Yangtze River ◽  
Large Scale ◽  
Yangtze River Basin ◽  
The Yangtze River ◽  
Ecosystem Monitoring ◽  
Catastrophic Flood ◽  
Basin Scale ◽  
The Yangtze River Basin

Flooding is one of the most widespread and frequent weather-related hazards that has devastating impacts on the society and ecosystem. Monitoring flooding is a vital issue for water resources management, socioeconomic sustainable development, and maintaining life safety. By integrating multiple precipitation, evapotranspiration, and GRACE-Follow On (GRAFO) terrestrial water storage anomaly (TWSA) datasets, this study uses the water balance principle coupled with the CaMa-Flood hydrodynamic model to access the spatiotemporal discharge variations in the Yangtze River basin during the 2020 catastrophic flood. The results show that: (1) TWSA bias dominates the overall uncertainty in runoff at the basin scale, which is spatially governed by uncertainty in TWSA and precipitation; (2) spatially, a field significance at the 5% level is discovered for the correlations between GRAFO-based runoff and GLDAS results. The GRAFO-derived discharge series has a high correlation coefficient with either in situ observations and hydrological simulations for the Yangtze River basin, at the 0.01 significance level; (3) the GRAFO-derived discharge observes the flood peaks in July and August and the recession process in October 2020. Our developed approach provides an alternative way of monitoring large-scale extreme hydrological events with the latest GRAFO release and CaMa-Flood model.

Dryland Degradation and Expansion: Implications for Mexican Policies from the Earth System Perspective

2020 ◽  
pp. 1-4
Author(s):  
Gabriel Lopez Porras
Keyword(s):  
Climate Change ◽  
Ecosystem Services ◽  
Science Policy ◽  
Land Degradation ◽  
Water Scarcity ◽  
Large Scale ◽  
Earth System ◽  
Sustainable Land Management ◽  
System Perspective ◽  
The Earth

Despite international efforts to stop dryland degradation and expansion, current dryland pathways are predicted to result in large-scale migration, growing poverty and famine, and increasing climate change, land degradation, conflicts and water scarcity. Earth system science has played a key role in analysing dryland problems, and has been even incorporated in global assessments such as the ones made by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. However, policies addressing dryland degradation, like the ‘Mexican programme for the promotion of sustainable land management’, do not embrace an Earth system perspective, so they do not consider the complexity and non-linearity that underlie dryland problems. By exploring how this Mexican programme could integrate the Earth system perspective, this paper discusses how ’Earth system’ policies could better address dryland degradation and expansion in the Anthropocene.

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