A Simple Tags Categorization Framework Using Spatial Coverage to Discover Geospatial Semantics

Economic growth is one indicator to measure the success of economic development in a country. Economic development is closely related to infrastructure. Infrastructure development will have an impact on economic growth both directly and indirectly. Therefore, the role of the government in determining infrastructure development policies is very important to increase economic growth in Indonesia. The purpose of this study is to determine the effect of infrastructure on economic growth in Indonesia including road infrastructure, electricity infrastructure, investment, water infrastructure, education infrastructure and health infrastructure in Indonesia in 2015-2017.The analytical tool used in this study is panel data regression with the approach of Fixed Effect Model. The spatial coverage of this study is all provinces in Indonesia, namely 34 provinces, with a series of data from 2015 to 2017 with a total of 102 observations. The data used is secondary data obtained from BPS Indonesia.The results of the study show that (1) the road infrastructure variables have a negative and not significant effect on GDRP. (2) electrical infrastructure variables have a negative and not significant effect on GDRP. (3) investment variables have a positive and significant effect on GDRP. (4) water infrastructure variables have a positive and not significant effect on GDRP. (5) educational infrastructure variables have a positive and not significant effect on GDRP. (6) health infrastructure variables have a positive and significant effect on GDRP. Keywords: development, infrastructure, investment, GDRP, panel data

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A near-global, high resolution land surface parameter dataset for the variable infiltration capacity model

Scientific Data ◽

10.1038/s41597-021-00999-4 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Jacob R. Schaperow ◽

Dongyue Li ◽

Steven A. Margulis ◽

Dennis P. Lettenmaier

Keyword(s):

Land Surface ◽

Global Scale ◽

Radiation Budget ◽

Soil Parameters ◽

Variable Infiltration Capacity ◽

Infiltration Capacity ◽

Vic Model ◽

Spatial Coverage ◽

Land Surface Parameter ◽

Vegetation Parameters

AbstractHydrologic models predict the spatial and temporal distribution of water and energy at the land surface. Currently, parameter availability limits global-scale hydrologic modelling to very coarse resolution, hindering researchers from resolving fine-scale variability. With the aim of addressing this problem, we present a set of globally consistent soil and vegetation parameters for the Variable Infiltration Capacity (VIC) model at 1/16° resolution (approximately 6 km at the equator), with spatial coverage from 60°S to 85°N. Soil parameters derived from interpolated soil profiles and vegetation parameters estimated from space-based MODIS measurements have been compiled into input files for both the Classic and Image drivers of the VIC model, version 5. Geographical subsetting codes are provided, as well. Our dataset provides all necessary land surface parameters to run the VIC model at regional to global scale. We evaluate VICGlobal’s ability to simulate the water balance in the Upper Colorado River basin and 12 smaller basins in the CONUS, and their ability to simulate the radiation budget at six SURFRAD stations in the CONUS.

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Tropical cyclones over the western north Pacific since the mid-nineteenth century

Climatic Change ◽

10.1007/s10584-021-02984-7 ◽

2021 ◽

Vol 164 (3-4) ◽

Author(s):

Hisayuki Kubota ◽

Jun Matsumoto ◽

Masumi Zaiki ◽

Togo Tsukahara ◽

Takehiko Mikami ◽

...

Keyword(s):

Nineteenth Century ◽

East China Sea ◽

North Pacific ◽

Western North Pacific ◽

East China ◽

Pressure Data ◽

The East China Sea ◽

China Sea ◽

Spatial Coverage ◽

Landfall Location

AbstractTropical cyclone (TC) activities over the western North Pacific (WNP) and TC landfall in Japan are investigated by collecting historical TC track data and meteorological observation data starting from the mid-nineteenth century. Historical TC track data and TC best track data are merged over the WNP from 1884 to 2018. The quality of historical TC data is not sufficient to count the TC numbers over the WNP due to the lack of spatial coverage and different TC criteria before the 1950s. We focus on TC landfall in Japan using a combination of TC track data and meteorological data observed at weather stations and lighthouses from 1877 to 2019. A unified TC definition is applied to obtain equivalent quality during the whole analysis period. We identify lower annual TC landfall numbers during the 1970s to the 2000s and find other periods have more TC landfall numbers including the nineteenth century. No trend in TC landfall number is detected. TC intensity is estimated by an annual power dissipation index (APDI). High APDI periods are found to be around 1900, in the 1910s, from the 1930s to 1960s, and after the 1990s. When we focus on the period from 1977 to 2019, a significant increasing trend of ADPI is seen, and significant northeastward shift of TC landfall location is detected. On the other hand, TC landfall location shifts northeastward and then southwestward in about 100-year interval. European and US ships sailed through East and Southeast Asian waters before the weather station network was established in the late nineteenth century. Then, we focus on TC events in July 1853 observed by the US Naval Japan Expedition of Perry’s fleet and August 1863 by a UK Navy ship that participated in two wars in Japan. A TC moved slowly westward over the East China Sea south of the Okinawa Islands from 21 to 25 July 1853. Another TC was detected in the East China Sea on 15–16 August 1863 during the bombardment of Kagoshima in southern Japan. Pressure data are evaluated by comparing the observations made by 10 naval ships in Yokohama, central Japan during 1863–1864. The deviation of each ship pressure data from the 10 ships mean is about 2.7–2.8 hPa.

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Multispectral Remote Sensing of Wetlands in Semi-Arid and Arid Areas: A Review on Applications, Challenges and Possible Future Research Directions

Remote Sensing ◽

10.3390/rs12244190 ◽

2020 ◽

Vol 12 (24) ◽

pp. 4190

Author(s):

Siyamthanda Gxokwe ◽

Timothy Dube ◽

Dominic Mazvimavi

Keyword(s):

Remote Sensing ◽

Arid Regions ◽

Remote Sensing Data ◽

Sub Saharan Africa ◽

Future Research ◽

Multispectral Imagery ◽

Aquatic Life ◽

Sensing Data ◽

Spatial Coverage ◽

Semi Arid

Wetlands are ranked as very diverse ecosystems, covering about 4–6% of the global land surface. They occupy the transition zones between aquatic and terrestrial environments, and share characteristics of both zones. Wetlands play critical roles in the hydrological cycle, sustaining livelihoods and aquatic life, and biodiversity. Poor management of wetlands results in the loss of critical ecosystems goods and services. Globally, wetlands are degrading at a fast rate due to global environmental change and anthropogenic activities. This requires holistic monitoring, assessment, and management of wetlands to prevent further degradation and losses. Remote-sensing data offer an opportunity to assess changes in the status of wetlands including their spatial coverage. So far, a number of studies have been conducted using remotely sensed data to assess and monitor wetland status in semi-arid and arid regions. A literature search shows a significant increase in the number of papers published during the 2000–2020 period, with most of these studies being in semi-arid regions in Australia and China, and few in the sub-Saharan Africa. This paper reviews progress made in the use of remote sensing in detecting and monitoring of the semi-arid and arid wetlands, and focuses particularly on new insights in detection and monitoring of wetlands using freely available multispectral sensors. The paper firstly describes important characteristics of wetlands in semi-arid and arid regions that require monitoring in order to improve their management. Secondly, the use of freely available multispectral imagery for compiling wetland inventories is reviewed. Thirdly, the challenges of using freely available multispectral imagery in mapping and monitoring wetlands dynamics like inundation, vegetation cover and extent, are examined. Lastly, algorithms for image classification as well as challenges associated with their uses and possible future research are summarised. However, there are concerns regarding whether the spatial and temporal resolutions of some of the remote-sensing data enable accurate monitoring of wetlands of varying sizes. Furthermore, it was noted that there were challenges associated with the both spatial and spectral resolutions of data used when mapping and monitoring wetlands. However, advancements in remote-sensing and data analytics provides new opportunities for further research on wetland monitoring and assessment across various scales.

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Assessment of the EUMETSAT Multi Decadal Land Surface Albedo Data Record from Meteosat Observations

Remote Sensing ◽

10.3390/rs13101992 ◽

2021 ◽

Vol 13 (10) ◽

pp. 1992

Author(s):

Alessio Lattanzio ◽

Michael Grant ◽

Marie Doutriaux-Boucher ◽

Rob Roebeling ◽

Jörg Schulz

Keyword(s):

Land Surface ◽

Surface Albedo ◽

Time Range ◽

Essential Variable ◽

Spatial Coverage ◽

Data Record ◽

Moderate Resolution Imaging Spectroradiometer ◽

Cloud Mask ◽

Cloud Screening

Surface albedo, defined as the ratio of the surface-reflected irradiance to the incident irradiance, is one of the parameters driving the Earth energy budget and it is for this reason an essential variable in climate studies. Instruments on geostationary satellites provide suitable observations allowing long-term monitoring of surface albedo from space. In 2012, EUMETSAT published Release 1 of the Meteosat Surface Albedo (MSA) data record. The main limitation effecting the quality of this release was non-removed clouds by the incorporated cloud screening procedure that caused too high albedo values, in particular for regions with permanent cloud coverage. For the generation of Release 2, the MSA algorithm has been replaced with the Geostationary Surface Albedo (GSA) one, able to process imagery from any geostationary imager. The GSA algorithm exploits a new, improved, cloud mask allowing better cloud screening, and thus fixing the major limitation of Release 1. Furthermore, the data record has an extended temporal and spatial coverage compared to the previous release. Both Black-Sky Albedo (BSA) and White-Sky Albedo (WSA) are estimated, together with their associated uncertainties. A direct comparison between Release 1 and Release 2 clearly shows that the quality of the retrieval improved significantly with the new cloud mask. For Release 2 the decadal trend is less than 1% over stable desert sites. The validation against Moderate Resolution Imaging Spectroradiometer (MODIS) and the Southern African Regional Science Initiative (SAFARI) surface albedo shows a good agreement for bright desert sites and a slightly worse agreement for urban and rain forest locations. In conclusion, compared with MSA Release 1, GSA Release 2 provides the users with a significantly more longer time range, reliable and robust surface albedo data record.

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Gap Filling of the CALYPSO HF Radar Sea Surface Current Data through Past Measurements and Satellite Wind Observations

International Journal of Navigation and Observation ◽

10.1155/2016/2605198 ◽

2016 ◽

Vol 2016 ◽

pp. 1-9 ◽

Cited By ~ 4

Author(s):

Adam Gauci ◽

Aldo Drago ◽

John Abela

Keyword(s):

Oil Spills ◽

Surface Current ◽

Radar Data ◽

Current Data ◽

Hf Radar ◽

Sea Surface ◽

Machine Learning Techniques ◽

Learning Techniques ◽

Spatial Coverage ◽

Essential Components

High frequency (HF) radar installations are becoming essential components of operational real-time marine monitoring systems. The underlying technology is being further enhanced to fully exploit the potential of mapping sea surface currents and wave fields over wide areas with high spatial and temporal resolution, even in adverse meteo-marine conditions. Data applications are opening to many different sectors, reaching out beyond research and monitoring, targeting downstream services in support to key national and regional stakeholders. In the CALYPSO project, the HF radar system composed of CODAR SeaSonde stations installed in the Malta Channel is specifically serving to assist in the response against marine oil spills and to support search and rescue at sea. One key drawback concerns the sporadic inconsistency in the spatial coverage of radar data which is dictated by the sea state as well as by interference from unknown sources that may be competing with transmissions in the same frequency band. This work investigates the use of Machine Learning techniques to fill in missing data in a high resolution grid. Past radar data and wind vectors obtained from satellites are used to predict missing information and provide a more consistent dataset.

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Spatio-temporal impacts of aerial adulticide applications on populations of West Nile virus vector mosquitoes

Parasites & Vectors ◽

10.1186/s13071-021-04616-6 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Karen M. Holcomb ◽

Robert C. Reiner ◽

Christopher M. Barker

Keyword(s):

West Nile Virus ◽

Temporal Trends ◽

Larval Habitat ◽

Post Treatment ◽

Additive Models ◽

Dispersal Ability ◽

Stochastic Variation ◽

West Nile ◽

Spatial Coverage ◽

Spatio Temporal

Abstract Background Aerial applications of insecticides that target adult mosquitoes are widely used to reduce transmission of West Nile virus to humans during periods of epidemic risk. However, estimates of the reduction in abundance following these treatments typically focus on single events, rely on pre-defined, untreated control sites and can vary widely due to stochastic variation in population dynamics and trapping success unrelated to the treatment. Methods To overcome these limitations, we developed generalized additive models fitted to mosquito surveillance data collected from CO2-baited traps in Sacramento and Yolo counties, California from 2006 to 2017. The models accounted for the expected spatial and temporal trends in the abundance of adult female Culex (Cx.) tarsalis and Cx. pipiens in the absence of aerial spraying. Estimates for the magnitude of deviation from baseline abundance following aerial spray events were obtained from the models. Results At 1-week post-treatment with full spatial coverage of the trapping area by pyrethroid or pyrethrin products, Cx. pipiens abundance was reduced by a mean of 52.4% (95% confidence intrval [CI] − 65.6, − 36.5%) while the use of at least one organophosphate pesticide resulted in a mean reduction of 76.2% (95% CI − 82.8, − 67.9%). For Cx. tarsalis, at 1-week post-treatment with full coverage there was a reduction in abundance of 30.7% (95% CI − 54.5, 2.5%). Pesticide class was not a significant factor contributing to the reduction. In comparison, repetition of spraying over three to four consecutive weeks resulted in similar estimates for Cx. pipiens and estimates of somewhat smaller magnitude for Cx. tarsalis. Conclusions Aerial adulticides are effective for achieving a rapid short-term reduction of the abundance of the primary West Nile virus vectors, Cx. tarsalis and Cx. pipiens. A larger magnitude of reduction was estimated in Cx. pipiens, possibly due to the species’ focal distribution. Effects of aerial sprays on Cx. tarsalis populations are likely modulated by the species’ large dispersal ability, population sizes and vast productive larval habitat present in the study area. Our modeling approach provides a new way to estimate effects of public health pesticides on vector populations using routinely collected observational data and accounting for spatio-temporal trends and contextual factors like weather and habitat. This approach does not require pre-selected control sites and expands upon past studies that have focused on the effects of individual aerial treatment events.

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Oxygen isotopes in terrestrial gastropod shells track Quaternary climate change in the American Southwest

Quaternary Research ◽

10.1017/qua.2021.18 ◽

2021 ◽

pp. 1-11

Author(s):

Jason A. Rech ◽

Jeffrey S. Pigati ◽

Kathleen B. Springer ◽

Stephanie Bosch ◽

Jeffrey C. Nekola ◽

...

Keyword(s):

Climate Change ◽

Oxygen Isotopic Composition ◽

American Southwest ◽

Quaternary Climate ◽

San Pedro ◽

Spatial Coverage ◽

Oxygen Isotopic ◽

The Last Glacial Maximum ◽

The Last Glacial ◽

Terrestrial Gastropod

Abstract Recent studies have shown the oxygen isotopic composition (δ18O) of modern terrestrial gastropod shells is determined largely by the δ18O of precipitation. This implies that fossil shells could be used to reconstruct the δ18O of paleo-precipitation as long as the isotopic system, including the hydrologic pathways of the local watershed and the gastropod systematics, is well understood. In this study, we measured the δ18O values of 456 individual gastropod shells collected from paleowetland deposits in the San Pedro Valley, Arizona that range in age from ca. 29.1 to 9.8 ka. Isotopic differences of up to 2‰ were identified among the four taxa analyzed (Succineidae, Pupilla hebes, Gastrocopta tappaniana, and Vallonia gracilicosta), with Succineidae shells yielding the highest values and V. gracilicosta shells exhibiting the lowest values. We used these data to construct a composite isotopic record that incorporates these taxonomic offsets, and found shell δ18O values increased by ~4‰ between the last glacial maximum and early Holocene, which is similar to the magnitude, direction, and rate of isotopic change recorded by speleothems in the region. These results suggest the terrestrial gastropods analyzed here may be used as a proxy for past climate in a manner that is complementary to speleothems, but potentially with much greater spatial coverage.

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A Disease Control-Oriented Land Cover Land Use Map for Myanmar

Data ◽

10.3390/data6060063 ◽

2021 ◽

Vol 6 (6) ◽

pp. 63

Author(s):

Dong Chen ◽

Varada Shevade ◽

Allison Baer ◽

Jiaying He ◽

Amanda Hoffman-Hall ◽

...

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Population Distribution ◽

Large Spatial Scale ◽

The Public ◽

Spatial Coverage ◽

Vector Borne ◽

Do So ◽

Control And Eradication

Malaria is a serious infectious disease that leads to massive casualties globally. Myanmar is a key battleground for the global fight against malaria because it is where the emergence of drug-resistant malaria parasites has been documented. Controlling the spread of malaria in Myanmar thus carries global significance, because the failure to do so would lead to devastating consequences in vast areas where malaria is prevalent in tropical/subtropical regions around the world. Thanks to its wide and consistent spatial coverage, remote sensing has become increasingly used in the public health domain. Specifically, remote sensing-based land cover/land use (LCLU) maps present a powerful tool that provides critical information on population distribution and on the potential human-vector interactions interfaces on a large spatial scale. Here, we present a 30-meter LCLU map that was created specifically for the malaria control and eradication efforts in Myanmar. This bottom-up approach can be modified and customized to other vector-borne infectious diseases in Myanmar or other Southeastern Asian countries.

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Revisit of a Case Study of Spilled Oil Slicks Caused by the Sanchi Accident (2018) in the East China Sea

Journal of Marine Science and Engineering ◽

10.3390/jmse9030279 ◽

2021 ◽

Vol 9 (3) ◽

pp. 279

Author(s):

Zhehao Yang ◽

Weizeng Shao ◽

Yuyi Hu ◽

Qiyan Ji ◽

Huan Li ◽

...

Keyword(s):

East China Sea ◽

Oil Spill ◽

Oil Spills ◽

Ocean Model ◽

Sea Surface ◽

East China ◽

The East China Sea ◽

Sar Images ◽

China Sea ◽

Spatial Coverage

Marine oil spills occur suddenly and pose a serious threat to ecosystems in coastal waters. Oil spills continuously affect the ocean environment for years. In this study, the oil spill caused by the accident of the Sanchi ship (2018) in the East China Sea was hindcast simulated using the oil particle-tracing method. Sea-surface winds from the European Centre for Medium-Range Weather Forecasts (ECMWF), currents simulated from the Finite-Volume Community Ocean Model (FVCOM), and waves simulated from the Simulating WAves Nearshore (SWAN) were employed as background marine dynamics fields. In particular, the oil spill simulation was compared with the detection from Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) images. The validation of the SWAN-simulated significant wave height (SWH) against measurements from the Jason-2 altimeter showed a 0.58 m root mean square error (RMSE) with a 0.93 correlation (COR). Further, the sea-surface current was compared with that from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2), yielding a 0.08 m/s RMSE and a 0.71 COR. Under these circumstances, we think the model-simulated sea-surface currents and waves are reliable for this work. A hindcast simulation of the tracks of oil slicks spilled from the Sanchi shipwreck was conducted during the period of 14–17 January 2018. It was found that the general track of the simulated oil slicks was consistent with the observations from the collected GF-3 SAR images. However, the details from the GF-3 SAR images were more obvious. The spatial coverage of oil slicks between the SAR-detected and simulated results was about 1 km2. In summary, we conclude that combining numerical simulation and SAR remote sensing is a promising technique for real-time oil spill monitoring and the prediction of oil spreading.

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