scholarly journals How Has Malaysia Benefited from the High-Resolution Satellite Rainfall? Trends, Gaps and Further Research Opportunities

2019 ◽  
Vol 12 ◽  
pp. 1-11
Author(s):  
Mohd. Rizaludin Mahmud
Keyword(s):  
High Resolution ◽  
Environmental Sustainability ◽  
Rainfall Data ◽  
Tropical Country ◽  
Scientific Review ◽  
Scientific Databases ◽  
Rainfall Trends ◽  
Present Information ◽  
The Status ◽  
Satellite Rainfall

This paper presents a scientific review on how Malaysia has benefited from the high-resolution satellite rainfall since its first launch in 1998. As a tropical country in which the environment is highly characterised by rainfall dynamics, public domain access of high-resolution satellite rainfall data could be very useful to support the hydrologic and related environmental studies. The scope of this paper includes achievements, the trend of studies, as well as gaps and future opportunities for scientific research. Examining this element is crucial in determining the present information on the status quo of the applications of space-based technology to Malaysian hydrologic research. Furthermore, this information is critical to charter the future action for the policymakers and revision of respective disciplines, including climate change, environmental sustainability, disaster resilience, food security, and education. Based on the search throughout the largest scientific databases of Web of Science and Scopus, five major trends have been identified. Those trends were ranked based on the number of research, 1) Satellite rainfall data performance and quality evaluation (40%), 2) Satellite rainfall data as input to environmental modelling (27%), 3) Rain fade & telecommunication (16%), 4) Satellite rainfall data quality improvement (7%), and 5) Rainfall studies. These trends were identified about 11 years after the satellite rainfall project started in 1998. The major achievement till now is validating the accuracy of the satellite rainfall and also downscaling it for local application.

scholarly journals Evaluation of High-resolution Satellite Rainfall Data over Singapore

2016 ◽  
Vol 154 ◽  
pp. 158-167 ◽  
Author(s):  
Jina Hur ◽  
Srivatsan V. Raghavan ◽  
Ngoc Son Nguyen ◽  
Shie-Yui Liong
Keyword(s):  
High Resolution ◽  
Rainfall Data ◽  
Satellite Rainfall

Investigating Error Metrics for Satellite Rainfall Data at Hydrologically Relevant Scales

2008 ◽  
Vol 9 (3) ◽  
pp. 563-575 ◽  
Author(s):  
Faisal Hossain ◽  
George J. Huffman
Keyword(s):  
High Resolution ◽  
Spatial Scales ◽  
The United States ◽  
Space Time ◽  
Probability Of Detection ◽  
Rainfall Data ◽  
True Value ◽  
Error Metrics ◽  
Satellite Rainfall ◽  
New Generation

Abstract This paper addresses the following open question: What set of error metrics for satellite rainfall data can advance the hydrologic application of new-generation, high-resolution rainfall products over land? The authors’ primary aim is to initiate a framework for building metrics that are mutually interpretable by hydrologists (users) and algorithm developers (data producers) and to provide more insightful information on the quality of the satellite estimates. In addition, hydrologists can use the framework to develop a space–time error model for simulating stochastic realizations of satellite estimates for quantification of the implication on hydrologic simulation uncertainty. First, the authors conceptualize the error metrics in three general dimensions: 1) spatial (how does the error vary in space?); 2) retrieval (how “off” is each rainfall estimate from the true value over rainy areas?); and 3) temporal (how does the error vary in time?). They suggest formulations for error metrics specific to each dimension, in addition to ones that are already widely used by the community. They then investigate the behavior of these metrics as a function of spatial scale ranging from 0.04° to 1.0° for the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) geostationary infrared-based algorithm. It is observed that moving to finer space–time scales for satellite rainfall estimation requires explicitly probabilistic measures that are mathematically amenable to space–time stochastic simulation of satellite rainfall data. The probability of detection of rain as a function of ground validation rainfall magnitude is found to be most sensitive to scale followed by the correlation length for detection of rain. Conventional metrics such as the correlation coefficient, frequency bias, false alarm ratio, and equitable threat score are found to be modestly sensitive to scales smaller than 0.24° latitude/longitude. Error metrics that account for an algorithm’s ability to capture rainfall intermittency as a function of space appear useful in identifying the useful spatial scales of application for the hydrologist. It is shown that metrics evolving from the proposed conceptual framework can identify seasonal and regional differences in reliability of four global satellite rainfall products over the United States more clearly than conventional metrics. The proposed framework for building such error metrics can lay a foundation for better interaction between the data-producing community and hydrologists in shaping the new generation of satellite-based, high-resolution rainfall products, including those being developed for the planned Global Precipitation Measurement (GPM) mission.

scholarly journals VLBI in Australia ? A Review

1991 ◽  
Vol 44 (6) ◽  
pp. 785 ◽  
Author(s):  
DL Jauncey
Keyword(s):  
High Resolution ◽  
Very Long Baseline Interferometry ◽  
Research Field ◽  
Asia Pacific ◽  
Vital Function ◽  
Future Developments ◽  
Long Baseline ◽  
The Status ◽  
Formal Basis ◽  
Fruitful Research

After two decades of Australian VLBI (very long baseline interferometry), high-resolution radio astronomy continues to be an active and fruitful research field. The status of Australian VLBI programs in astrophysics, astrometry and geodesy is reviewed and likely future developments are outlined. In addition to research programs with the Australian VLBI network, a number of successful collaborative projects are underway with overseas VLBI observatories. The inception of the Asia-Pacific Telescope will provide an important formal basis for fostering and extending international VLBI experiments in the Australian hemisphere. The APT will also serve a vital function in coordinating ground-based observations when the Soviet and Japanese VLBI space missions, Radioastron and VSOP, are launched in the middle of this decade. However, continued viable Australian participation in VLBI into the nineties will require new wide-bandwidth recording systems and an Australian VLBI correlator.

scholarly journals Environmental Sustainability in New Zealand Museums: A Case Study of Te Manawa Museum, Gallery and Science Centre

2021 ◽  
Author(s):  
◽  
Nina Helen Finigan
Keyword(s):  
New Zealand ◽  
Environmental Sustainability ◽  
Local Context ◽  
Bottom Line ◽  
Staff Members ◽  
Current State ◽  
Science Centre ◽  
The Status ◽  
The Many

<p>Environmental sustainability is becoming an increasingly essential component of modern life. The contemporary museums’ role as public educators, and as guardians of tangible and intangible culture, places them in a unique position to address the various issues surrounding environmental sustainability, from climate change, to bio-diversity loss, to conservation. There is increasing momentum behind the idea that museums should not only engage with environmental sustainability, but that they indeed have a responsibility to. Although museums throughout New Zealand are addressing environmental sustainability, there is currently no thorough examination of how they are doing this. Therefore, the aim of this dissertation was so find out the current state of environmental sustainability in New Zealand museums, and specifically how staff are approaching it. Through engaging in a case study of Te Manawa Museum, Gallery and Science Centre, Palmerston North, and specifically the environmentally themed exhibition Te Awa/The River: Heart of the Manawatu, this dissertation analyses and discusses the realities of addressing institutional environmental sustainability. While the previous literature surrounding this topic has addressed the many reasons why museums should engage with environmental sustainability, this dissertation has expanded on this by analysing and discussing the realities of addressing environmental sustainability from a staff perspective. Through interviews with five Te Manawa staff members, this dissertation has revealed that while museum professionals agree that engagement with environmental sustainability should become part of bottom line holistic sustainable development, the status of museums as trusted democratic institutions can place them in a conflicted space ‘in-between’ when dealing with polarising issues such as the environment. This is particularly relevant to the discussion around new-museological theory, and the importance of local context and reflexive community engagement, where the community essentially help drive museological direction and content.</p>

Sustainability in Asian Countries: Perspectives from Economics

2015 ◽  
Vol 10 (1) ◽  
pp. 81-102
Author(s):  
Youngho Chang ◽  
Jiesheng Tan ◽  
Letian Chen
Keyword(s):  
Sustainable Development ◽  
Environmental Sustainability ◽  
Technological Progress ◽  
Natural Capital ◽  
Asian Countries ◽  
Weak Sustainability ◽  
Hartwick Rule ◽  
The Status ◽  
Environmental Sustainability Index ◽  
Selection Of

Studies on sustainable development rely on diverse and seemingly conflicting concepts that yield contrasting results. The root of these conflicting concepts is the lack of agreement on the path toward achieving sustainable development (SD), namely, weak (or economic) versus strong (or ecological) sustainability. This article revisits the Solow-Hartwick model (Solow 1974, 1986; Hartwick 1977, 1978a, 1978b), which suggests that an economy can achieve intergenerational equity by mandating the Hartwick rule of investing the amount of rents from natural capital into renewable capital. It constructs a modified Solow-Hartwick model in which the assumptions of constant population and no technological progress are relaxed and from which it derives a more general form of the Hartwick rule. The modified Solow-Hartwick investment rule presents how weak sustainability can be attained and explains how the residual Hotelling rents (or proceeds from natural resources) could be utilized in order to achieve strong sustainability. In this article, we apply the modified Solow-Hartwick investment rule to a selection of developing and developed Asian economies to assess their sustainability. We then compare our results with two existing measures of sustainability, the genuine savings (GS) model and the Environmental Sustainability Index (ESI), both of which frequently present contradicting evaluations on the status of sustainability.

Towards the effective use of Artificial Neural Networks for accessing rainfall thresholds for rainfall-induced landslides, a study based on in-situ and satellite merged rainfall data

2021 ◽  
Author(s):  
Luísa Vieira Lucchese ◽  
Guilherme Garcia de Oliveira ◽  
Olavo Correa Pedrollo
Keyword(s):  
Neural Network ◽  
Rainfall Event ◽  
Rainfall Data ◽  
Extreme Rainfall Event ◽  
Ann Model ◽  
Antecedent Rainfall ◽  
Rainfall Thresholds ◽  
Satellite Rainfall ◽  
Artificial Neural

&lt;p&gt;Rainfall-induced landslides have caused destruction and deaths in South America. Accessing its triggers can help researchers and policymakers to understand the nature of the events and to develop more effective warning systems. In this research, triggering rainfall for rainfall-induced landslides is evaluated. The soil moisture effect is indirectly represented by the antecedent rainfall, which is an input of the ANN model. The area of the Rolante river basin, in Rio Grande do Sul state, Brazil, is chosen for our analysis. On January 5&lt;sup&gt;th&lt;/sup&gt;, 2017, an extreme rainfall event caused a series of landslides and debris flows in this basin. The landslide scars were mapped using satellite imagery. To calculate the rainfall that triggered the landslides, it was necessary to compute the antecedent rainfall that occurred within the given area. The use of satellite rainfall data is a useful tool, even more so if no gauges are available for the location and time of the rainfall event, which is the case. Remote sensing products that merge the data from in situ stations with satellite rainfall data are increasingly popular. For this research, we employ the data from MERGE (Rozante et al., 2010), that is one of these products, and is focused specifically on Brazilian gauges and territory. For each 12.5x12.5m raster pixel, the rainfall is interpolated to the points and the rainfall volume from the last 24h before the event is accumulated. This is added as training data in our Artificial Neural Network (ANN), along with 11 terrain attributes based on ALOS PALSAR (ASF DAAC, 2015) elevation data and generated by using SAGA GIS. These attributes were presented and analyzed in Lucchese et al. (2020). Sampling follows the procedure suggested in Lucchese et al. (2021, in press). The ANN model is a feedforward neural network with one hidden layer consisting of 20 neurons. The ANN is trained by backpropagation method and cross-validation is used to ensure the correct adjustment of the weights. Metrics are calculated on a separate sample, called verification sample, to avoid bias. After training, and provided with relevant information, the ANN model can estimate the 24h-rainfall thresholds in the region, based on the 2017 event only. The result is a discretized map of rainfall thresholds defined by the execution of the trained ANN. Each pixel of the resulting map should represent the volume of rainfall in 24h necessary to trigger a landslide in that point. As expected, lower thresholds (30 - 60 mm) are located in scarped slopes and the regions where the landslides occurred. However, lowlands and the plateau, which are areas known not to be prone to landslides, show higher rainfall thresholds, although not as high as expected (75 - 95 mm). Mean absolute error for this model is 16.18 mm. The inclusion of more variables and events to the ANN training should favor achieving more reliable outcomes, although, our results are able to show that this methodology has potential to be used for landslide monitoring and prediction.&lt;/p&gt;

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