scholarly journals Efficient Estimation of Biomass from Residual Agroforestry

2020 ◽  
Vol 9 (1) ◽  
pp. 21 ◽  
Author(s):  
Marco Bascietto ◽  
Giulio Sperandio ◽  
Sofia Bajocco
Keyword(s):  
Remote Sensing ◽  
Central Italy ◽  
Cost Effective ◽  
Simple Random Sampling ◽  
Auxiliary Variable ◽  
Efficient Estimation ◽  
Actual Measurement ◽  
Photo Interpretation ◽  
Residual Biomass ◽  
Biomass Supply

Cost-effective sampling methods for the estimation of variables of interest that are time-consuming are a major concern. Ranked set sampling (RSS) is a sampling method that assumes that a set of sampling units drawn from the population can be ranked by other means without the actual measurement of the variable of interest. We used data on vegetation dynamics from satellite remote sensing as a means in which to rapidly rank sampling units across various land covers and to estimate their residual agroforestry biomass contribution for a small cogeneration facility located in the center of a study area in central Italy. A remote sensing map used as an auxiliary variable in RSS enabled us to cut down the photo-interpretation of the residual biomass present in sampling units from 745 to 139, increase the relative precision of the estimate over common simple random sampling, and avoid individual subjective bias being introduced. The photo-interpretation of the sampling units resulted in a 1.12 Mg ha−1 year−1 mean annual density of residual biomass supply, although unevenly distributed among land cover classes; this led to an estimate of a yearly supply of 132 Gg over the whole 2276 km2 wide study area. Further applications of this study might include the spatial quantification of biomass supply-related ecosystem services.

RATIO ESTIMATION OF THE POPULATION MEAN USING AUXILIARY INFORMATION UNDER THE OPTIMAL SAMPLING DESIGN

2020 ◽  
pp. 1-12
Author(s):  
Chunxian Long ◽  
Wangxue Chen ◽  
Rui Yang ◽  
Dongsen Yao
Keyword(s):  
Sampling Design ◽  
Auxiliary Information ◽  
Cost Effective ◽  
Simple Random Sampling ◽  
Auxiliary Variable ◽  
Ranked Set Sampling ◽  
Study Variable ◽  
Population Mean ◽  
Optimal Sampling Design ◽  
Extreme Ranked Set Sampling

Cost-effective sampling design is a problem of major concern in some experiments especially when the measurement of the characteristic of interest is costly or painful or time-consuming. In this article, we investigate ratio-type estimators of the population mean of the study variable, involving either the first or the third quartile of the auxiliary variable, using ranked set sampling (RSS) and extreme ranked set sampling (ERSS) schemes. The properties of the estimators are obtained. The estimators in RSS and ERSS are compared to their counterparts in simple random sampling (SRS) for normal data. The numerical results show that the estimators in RSS and ERSS are significantly more efficient than their counterparts in SRS.

E-Voting Kepala Desa dan Modal Sosial

2019 ◽  
Vol 2 (6) ◽  
pp. 759
Author(s):  
Khaulah Afifah ◽  
Lala M Kolopaking ◽  
Zessy Ardinal Barlan
Keyword(s):  
Social Capital ◽  
Random Sampling ◽  
Qualitative Data ◽  
Sampling Technique ◽  
Cost Effective ◽  
Simple Random Sampling ◽  
Community Based ◽  
Time Saving ◽  
The Social ◽  
Voting System

Head of a village election with e-voting system is a new thing for community The success level of e-voting system can be reached by fulfil several principles in order to the implementation going effective and the result of the election can be accepted by all. The objectives of this research is to analyze the relation between the success level of e-voting system with social capital of the community. This research is carried out with the quantitative approach and supported by qualitative data. This research takes 60 respondents using simple random sampling technique. The results showed that the success level of e-voting has a correlation with the level of social capital of the community. Based on the field study, the social capital of the community is classified as high. The high social capital makes the implementation of e-voting successful and the success level is also high, because in the election ten years ago occurred a conflict. The community considers e-voting easier and more practical, cost effective and time-saving, and the results of e-voting are also reliable. A practical and fast of e-voting system can be a solution especially for “rural-urban” community who are busy or work outside the village.Keywords: E-voting, the success level of the system, social capital Pemilihan kepala desa dengan sistem e-voting merupakan hal yang baru bagi masyarakat. Keberhasilan penerapan sistem e-voting dilihat dari terpenuhinya beberapa prinsip agar penerapannya berlangsung efektif dan hasilnya dapat diterima oleh seluruh masyarakat. Penelitian ini bertujuan untuk menganalisis hubungan tingkat keberhasilan sistem e-voting dalam pemilihan kepala desa dengan tingkat modal sosial masyarakat. Bentuk penelitian ini adalah penelitian kuantitatif yang didukung oleh analisis data kualitatif. Penelitian ini mengambil enam puluh responden dengan teknik simple random sampling. Hasil penelitian menunjukkan bahwa tingkat keberhasilan e-voting memiliki hubungan dengan tingkat modal sosial masyarakat. Berdasarkan kajian di lapang, modal sosial masyarakat tergolong tinggi. Tingginya modal sosial tersebut membuat pelaksanaan e-voting berhasil dan tingkat keberhasilannya juga tergolong tinggi karena pada pemilihan sepuluh tahun silam sempat terjadi konflik. Masyarakat menganggap sistem evoting lebih mudah dan praktis, hemat dalam segi biaya dan waktu, serta hasil dari pemilihan juga dapat dipertanggungjawabkan. Sistem e-voting yang praktis dan cepat dapat menjadi solusi khususnya bagi masyarakat daerah “desa-kota” yang memiliki kesibukan atau pekerjaan di luar desa.Kata Kunci: E-voting, keberhasilan sistem, modal sosial. 

scholarly journals Operationalization of Remote Sensing Solutions for Sustainable Forest Management

2021 ◽  
Vol 13 (4) ◽  
pp. 572
Author(s):  
Gintautas Mozgeris ◽  
Ivan Balenović
Keyword(s):  
Remote Sensing ◽  
Forest Management ◽  
Natural Resources ◽  
Sustainable Management ◽  
Sustainable Forest Management ◽  
Cost Effective ◽  
Development Trends ◽  
Comprehensive Information ◽  
The Status

The pre-requisite for sustainable management of natural resources is the availability of timely, cost-effective, and comprehensive information on the status and development trends of the management object [...]

scholarly journals Remote Sensing for Land Administration

2020 ◽  
Vol 12 (15) ◽  
pp. 2497
Author(s):  
Rohan Bennett ◽  
Peter van Oosterom ◽  
Christiaan Lemmen ◽  
Mila Koeva
Keyword(s):  
Remote Sensing ◽  
Land Tenure ◽  
Laser Scanning ◽  
Poverty Reduction ◽  
Spatial Information ◽  
Cost Effective ◽  
Terrestrial Lidar ◽  
Land Administration ◽  
Tools And Techniques ◽  
Vertical Development

Land administration constitutes the socio-technical systems that govern land tenure, use, value and development within a jurisdiction. The land parcel is the fundamental unit of analysis. Each parcel has identifiable boundaries, associated rights, and linked parties. Spatial information is fundamental. It represents the boundaries between land parcels and is embedded in cadastral sketches, plans, maps and databases. The boundaries are expressed in these records using mathematical or graphical descriptions. They are also expressed physically with monuments or natural features. Ideally, the recorded and physical expressions should align, however, in practice, this may not occur. This means some boundaries may be physically invisible, lacking accurate documentation, or potentially both. Emerging remote sensing tools and techniques offers great potential. Historically, the measurements used to produce recorded boundary representations were generated from ground-based surveying techniques. The approach was, and remains, entirely appropriate in many circumstances, although it can be timely, costly, and may only capture very limited contextual boundary information. Meanwhile, advances in remote sensing and photogrammetry offer improved measurement speeds, reduced costs, higher image resolutions, and enhanced sampling granularity. Applications of unmanned aerial vehicles (UAV), laser scanning, both airborne and terrestrial (LiDAR), radar interferometry, machine learning, and artificial intelligence techniques, all provide examples. Coupled with emergent societal challenges relating to poverty reduction, rapid urbanisation, vertical development, and complex infrastructure management, the contemporary motivation to use these new techniques is high. Fundamentally, they enable more rapid, cost-effective, and tailored approaches to 2D and 3D land data creation, analysis, and maintenance. This Special Issue hosts papers focusing on this intersection of emergent remote sensing tools and techniques, applied to domain of land administration.

scholarly journals Leveraging machine learning to produce a cost-effective national building height map of Ireland

2021 ◽  
Author(s):  
Eoghan Keany ◽  
Geoffrey Bessardon ◽  
Emily Gleeson
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
High Resolution ◽  
Land Cover ◽  
Urban Areas ◽  
Cost Effective ◽  
Land Cover Classification ◽  
National Scale ◽  
Building Height ◽  
Height Data

<p>To represent surface thermal, turbulent and humidity exchanges, Numerical Weather Prediction (NWP) systems require a land-cover classification map to calculate sur-face parameters used in surface flux estimation. The latest land-cover classification map used in the HARMONIE-AROME configuration of the shared ALADIN-HIRLAMNWP system for operational weather forecasting is ECOCLIMAP-SG (ECO-SG). The first evaluation of ECO-SG over Ireland suggested that sparse urban areas are underestimated and instead appear as vegetation areas (1). While the work of (2) on land-cover classification helps to correct the horizontal extent of urban areas, the method does not provide information on the vertical characteristics of urban areas. ECO-SG urban classification implicitly includes building heights (3), and any improvement to ECO-SG urban area extent requires a complementary building height dataset.</p><p>Openly accessible building height data at a national scale does not exist for the island of Ireland. This work seeks to address this gap in availability by extrapolating the preexisting localised building height data across the entire island. The study utilises information from both the temporal and spatial dimensions by creating band-wise temporal aggregation statistics from morphological operations, for both the Sentinel-1A/B and Sentinel-2A/B constellations (4). The extrapolation uses building height information from the Copernicus Urban Atlas, which contains regional coverage for Dublin at 10 m x10 m resolution (5). Various regression models were then trained on these aggregated statistics to make pixel-wise building height estimates. These model estimates were then evaluated with an adjusted RMSE metric, with the most accurate model chosen to map the entire country. This method relies solely on freely available satellite imagery and open-source software, providing a cost-effective mapping service at a national scale that can be updated more frequently, unlike expensive once-off private mapping services. Furthermore, this process could be applied by these services to reduce costs by taking a small representative sample and extrapolating the rest of the area. This method can be applied beyond national borders providing a uniform map that does not depends on the different private service practices facilitating the updates of global or continental land-cover information used in NWP.</p><p> </p><p>(1) G. Bessardon and E. Gleeson, “Using the best available physiography to improve weather forecasts for Ireland,” in Challenges in High-Resolution Short Range NWP at European level including forecaster-developer cooperation, European Meteorological Society, 2019.</p><p>(2) E. Walsh, et al., “Using machine learning to produce a very high-resolution land-cover map for Ireland, ” Advances in Science and Research,  (accepted for publication).</p><p>(3) CNRM, "Wiki - ECOCLIMAP-SG" https://opensource.umr-cnrm.fr/projects/ecoclimap-sg/wiki</p><p>(4) D. Frantz, et al., “National-scale mapping of building height using sentinel-1 and sentinel-2 time series,” Remote Sensing of Environment, vol. 252, 2021.</p><p>(5) M. Fitrzyk, et al., “Esa Copernicus sentinel-1 exploitation activities,” in IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium, IEEE, 2019.</p>

scholarly journals Modelling Acacia saligna invasion on the Adriatic coastal landscape: An integrative approach using LTER data

2019 ◽  
Vol 34 ◽  
pp. 127-144 ◽  
Author(s):  
Flavio Marzialetti ◽  
Manuele Bazzichetto ◽  
Silvia Giulio ◽  
Alicia T.R. Acosta ◽  
Angela Stanisci ◽  
...  
Keyword(s):  
Propagule Pressure ◽  
Vascular Plant ◽  
Central Italy ◽  
Coastal Dunes ◽  
Cost Effective ◽  
Theory And Practice ◽  
Integrative Approach ◽  
Distribution Models ◽  
Adriatic Coast ◽  
The Impact

Invasive Alien Species (IAS) pose a major threat to biodiversity and ecosystem services worldwide. Even if preventing biological invasions should be the most cost-effective way to minimise the impact of IAS on biodiversity, new efforts are necessary to identify early signs of invasion and to assess invasion risk. In this context, the implementation of invasive Species Distribution Models (iSDMs) could represent a sound instrument that merits further research. Acaciasaligna is an Australian vascular plant introduced into Europe during the last half century and is one of the most aggressive IAS in the Mediterranean basin. In this work, we model the occurrence of A.saligna in the coastal landscapes of central Italy (Adriatic coast) while accounting for the simultaneous effect of multiple factors (propagule pressure, abiotic, biotic factors). The iSDM for A.saligna was implemented on a representative tract of the Adriatic coast in central Italy (Molise region), largely included in two Long-Term Ecological Research (LTER) sites which actively contribute to the description of the considered ecosystem status and possible future trends. By using a Generalised Linear Model (GLM) with a binomial distribution of errors based on field and cartographic geo-referenced data, we examined the statistical relationship between the occurrence of A.saligna and a comprehensive set of environmental factors. The iSDM effectively captured the role of the different variables in determining the occurrence of A.saligna in the coastal dunes. Its occurrence is primarily related to Wooded dunes with Pinuspinea and/or P.pinaster (EU Habitat 2270) and distance from the sea and, to a lesser extent, with distance from roads and rivers. This research provides a first exploratory analysis of the environmental characteristics that promote the rapid growth and development of A.saligna in Italian dune ecosystems, identifying the habitats that are mainly affected by the invasive process in coastal areas and, by doing so, contributing to filling the gap between theory and practice in conservation decision-making. Finally, the LTER network benefitted from this research, confirming its relevance in providing useful information for modelling and monitoring invasion processes.

scholarly journals Application of remote sensing and GIS in land use/land cover mapping and change detection in Shasha forest reserve, Nigeria

2014 ◽  
Vol XL-8 ◽  
pp. 613-616 ◽  
Author(s):  
O. S. Olokeogun ◽  
K. Iyiola ◽  
O. F. Iyiola
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Sustainable Forest Management ◽  
Cost Effective ◽  
Remote Sensing And Gis ◽  
Clear Understanding ◽  
Forest Reserve ◽  
Landsat Satellite

Mapping of LULC and change detection using remote sensing and GIS techniques is a cost effective method of obtaining a clear understanding of the land cover alteration processes due to land use change and their consequences. This research focused on assessing landscape transformation in Shasha Forest Reserve, over an 18 year period. LANDSAT Satellite imageries (of 30 m resolution) covering the area at two epochs were characterized into five classes (Water Body, Forest Reserve, Built up Area, Vegetation, and Farmland) and classification performs with maximum likelihood algorithm, which resulted in the classes of each land use. <br><br> The result of the comparison of the two classified images showed that vegetation (degraded forest) has increased by 30.96 %, farmland cover increased by 22.82 % and built up area by 3.09 %. Forest reserve however, has decreased significantly by 46.12 % during the period. <br><br> This research highlights the increasing rate of modification of forest ecosystem by anthropogebic activities and the need to apprehend the situation to ensure sustainable forest management.

High-resolution root zone soil moisture-based indices for drought monitoring in the Ebro basin

2021 ◽  
Author(s):  
Vivien-Georgiana Stefan ◽  
Maria-José Escorihuela ◽  
Pere Quintana-Seguí
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
High Resolution ◽  
Root Zone ◽  
Cost Effective ◽  
Strong Relationship ◽  
Drought Indices ◽  
Ebro Basin ◽  
Small Areas ◽  
Cost Effective Approach

&lt;h3&gt;Agriculture is an important factor on water resources, given the constant population growth and the strong relationship between water availability and food production. In this context, root zone soil moisture (RZSM) measurements are used by modern irrigators in order to detect the onset of crop water stress and to trigger irrigations. Unfortunately, in situ RZSM measurements are costly; combined with the fact they are available only over small areas and that they might not be representative at the field scale, remote sensing is a cost-effective approach for mapping and monitoring extended areas. A recursive formulation of an exponential filter was used in order to derive 1 km resolution RZSM estimates from SMAP (Soil Moisture Active Passive) surface soil moisture (SSM) over the Ebro basin. The SMAP SSM was disaggregated to a 1 km resolution by using the DISPATCH (DISaggregation based on a Physical And Theoretical scale CHange) algorithm. The pseudodiffusivity parameter of the exponential filter was calibrated per land cover type, by using ISBA-DIF (Interaction Soil Biosphere Atmosphere) surface and root zone soil moisture data as an intermediary step. The daily 1 km RZSM estimates were then used to derive 1 km drought indices such as soil moisture anomalies and soil moisture deficit indices (SMDI), on a weekly time-scale, covering the entire 2020 year. Results show that both drought indices are able to capture rainfall and drying events, with the weekly anomaly being more responsive to sudden events such as heavy rainfalls, while the SMDI is slower to react do the inherent inertia it has. Moreover, a quantitative comparison with drought indices derived from a model-based RZSM estimates has also been performed, with results showing a strong correspondence between the different indices. For comparison purposes, the weekly soil moisture anomalies and SMDI derived using 1 km SMAP-derived SSM were also estimated. The analysis shows that the anomalies and SMDI based on the RZSM are more representative of the hydric stress level of the plants, given that the RZSM is better suited than the SSM to describe the moisture conditions at the deeper layers, which are the ones used by plants during growth and development.&lt;/h3&gt;&lt;h3&gt;The study provides an insight into obtaining robust, high-resolution remote-sensing derived drought indices based on remote-sensing derived RZSM estimates. The 1 km resolution proves an improvement from other currently available drought indices, such as the European Drought Observatory&amp;#8217;s 5 km resolution drought index, which is not able to capture as well the spatial variability present within heterogeneous areas. Moreover, the SSM-derived drought indices are currently used in a drought observatory project, covering a region in the Tarragona province of Catalonia, Spain. The project aims at offering irrigation recommendations to water agencies, and the introduction of RZSM-derived drought indices will further improve such advice.&lt;/h3&gt;

Sign in / Sign up

Export Citation Format

Share Document