A pilot project of area sampling frame for maize statistics: Indonesia’s experience1

2020 ◽  
Vol 36 (4) ◽  
pp. 997-1006
Author(s):  
Octavia Rizky Prasetyo ◽  
Kadir ◽  
Ratna Rizki Amalia
Keyword(s):  
Spatial Information ◽  
Food Policy ◽  
Pilot Project ◽  
Critical Issue ◽  
Sampling Frame ◽  
Area Estimation ◽  
Maize Cultivation ◽  
Area Sampling ◽  
Frame Construction ◽  
Different Sources

A critical issue in the context of food policy in Indonesia is the accuracy of crops statistics, particularly rice and maize. In 2018, Statistics Indonesia (BPS), in collaboration with the Indonesian Agency for Assessment and Application of Technology (BPPT), successfully implemented the area sampling frame (ASF) method to improve the accuracy of paddy harvested area estimation, which previously was estimated by conventional methods, mainly by the human eye (‘eye-estimate’). The achievement has encouraged BPS to replicate the method to estimate the harvested area of maize, for which there were indications it suffered from overestimation. In 2019, BPS initiated a pilot project on the implementation of the ASF for maize. One of the most challenging aspects in replicating the ASF method for maize is the frame construction. This issue arises due to insufficient spatial information on land that is specifically dedicated to maize cultivation. To address this challenge, BPS constructed the frame by making use of different sources of spatial information. This paper provides a comprehensive look at the development of the ASF for maize statistics. The discussion in this paper covers two main issues, namely the methodology applied and the business process of data collection.

scholarly journals Remote sensing versus the area sampling frame method in paddy rice acreage estimation in Indramayu regency, West Java province, Indonesia

2020 ◽  
Vol 42 (5) ◽  
pp. 1738-1767
Author(s):  
Laju Gandharum ◽  
Mari E. Mulyani ◽  
Djoko M. Hartono ◽  
Asep Karsidi ◽  
Mubariq Ahmad
Keyword(s):  
Remote Sensing ◽  
Paddy Rice ◽  
Sampling Frame ◽  
West Java ◽  
Acreage Estimation ◽  
Area Sampling ◽  
Frame Method

Accelerated Pavement Rehabilitation and Reconstruction with Long-Life Asphalt Concrete on High-Traffic Urban Highways

2005 ◽  
Vol 1905 (1) ◽  
pp. 56-64 ◽  
Author(s):  
Eul-Bum Lee ◽  
Hojung Lee ◽  
Massod Akbarian
Keyword(s):  
Asphalt Concrete ◽  
Traffic Management ◽  
Pilot Project ◽  
Critical Issue ◽  
The State ◽  
Negative Effects ◽  
Construction Time ◽  
California Department ◽  
Pavement Rehabilitation ◽  
Long Life

Rehabilitation of urban highways is a critical issue confronting the California Department of Transportation because the state has a significant inventory of overaged, heavily trafficked urban highways showing extensive signs of distress. This paper presents the innovative pavement rehabilitation technologies and techniques that the agency applied in the first asphalt concrete (AC) project for its Long-Life Pavement Rehabilitation Strategies (LLPRS) program. A 4.4-km stretch of deteriorated concrete pavement on I-710 in Long Beach was rehabilitated successfully with 230 mm of AC overlay or 325 mm of full-depth AC replacement during eight 55-h weekend closures. The pilot project proved that the accelerated (fast-track) rehabilitation with 55-h weekend closures is a viable option that can drastically shorten the overall construction time and lessen the negative effects of construction in an urban area. The project also proved that AC pavement designed to provide a design life of 30-plus years can be constructed in a series of weekend closures even on the most heavily loaded truck route in the state. The construction-monitoring study indicated that contractor productivities were noticeably improved (through the learning effect) as weekend closures were repeated. In addition, the pay factor clause in the contract effectively encouraged the contractor's awareness of quality. The traffic measurements study showed that traffic operated at free-flow speeds throughout the surrounding highways and arterial roads during the construction weekends. It is expected that the construction and traffic management techniques adopted in this project will be used in LLPRS projects on California urban highways with high-traffic volumes.

scholarly journals Simulation Study of Robust Geographically Weighted Empirical Best Linear Unbiased Predictor on Small Area Estimation

2021 ◽  
Vol 5 (1) ◽  
pp. 50-60
Author(s):  
Naima Rakhsyanda ◽  
Kusman Sadik ◽  
Indahwati Indahwati
Keyword(s):  
Small Area ◽  
Spatial Information ◽  
Mean Squared Error ◽  
Small Area Estimation ◽  
Small Sample ◽  
Population Parameter ◽  
Spatial Effects ◽  
Best Linear Unbiased Predictor ◽  
Area Estimation ◽  
Best Linear Unbiased

Small area estimation can be used to predict the population parameter with small sample sizes. For some cases, the population units that are close spatially may be more related than units that are further apart. The use of spatial information like geographic coordinates are studied in this research. Outlier contaminations can affect small area estimations. This study was conducted using simulation methods on generated data with six scenarios. The scenarios are the combination of spatial effects (spatial stationary and spatial non-stationary) with outlier contamination (no outlier, symmetric outliers, and non-symmetric outliers). The purpose of this study was to compare the geographically weighted empirical best linear unbiased predictor (GWEBLUP) and robust GWEBLUP (RGWEBLUP) with direct estimator, EBLUP, and REBLUP using simulation data. The performance of the predictors is evaluated using relative root mean squared error (RRMSE). The simulation results showed that geographically weighted predictors have the smallest RRMSE values for scenarios with spatial non-stationary, therefore offer a better prediction. For scenarios with outliers, robust predictors with smaller RRMSE values offer more efficiency than non-robust predictors.

Expenditure Per Capita Model with Spatial Small Area Estimation

2021 ◽  
Vol 1 (2) ◽  
pp. 38-47
Author(s):  
Ahmad Risal
Keyword(s):  
Small Area ◽  
Spatial Information ◽  
Small Area Estimation ◽  
Random Effect ◽  
Development Program ◽  
Data Availability ◽  
Estimation Model ◽  
Policy Makers ◽  
Area Estimation ◽  
Direct Estimation

Indonesia is one of many countries around the world that attempt to suffer from high poverty rates. Since, poverty information in a certain area is a point of interest to researchers and policy makers. One problem faced is for the development program to be carried out more effectively and efficiently, it is necessary to have data availability up to the micro-scale. The technique used to reach the goal is Small Area Estimation (SAE). Fay-herriot (FH) model is one method on Small Area Estimation. Since, the SAE techniques require “borrow strength” across neighbor areas so thus Fay-Herriot model approach was developed by integrating spatial information into the model. This method known as Spatial Fay-Herriot Model (SFH) or Spatial Empirical Best Linear Unbiased Prediction (SEBLUP). This study aims to compare MSE of direct estimation, FH, and SFH Model to see which method gives the best result in estimating expenditure. The MSE value of the estimated SFH is smaller than direct estimation and FH, but it does not significant. It means adding spatial information in the small area estimation model does not give a better prediction than the simple small area estimation which is takes account the area as a specific random effect.

Beyond the Public Meeting

2011 ◽  
pp. 43-65 ◽  
Author(s):  
Timothy L. Hawthorne ◽  
Michael Dougherty ◽  
Gregory Elmes ◽  
Christopher Fletcher ◽  
Brent McCusker ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Planning ◽  
Spatial Information ◽  
Smart Growth ◽  
Pilot Project ◽  
Mental Maps ◽  
The Public ◽  
Public Meeting ◽  
Spatial Decision Making ◽  
Community Input

This chapter describes how community-based qualitative information about local land use is being incorporated into a Participatory Geographic Information System (PGIS) for the Cheat Lake Planning District of Monongalia County, West Virginia. The research demonstrates how PGIS can be an effective methodology for promoting community input into land use planning and for augmenting spatial decision-making for “smart growth.” The Cheat Lake PGIS is field-based and provides residents with an opportunity to discuss and map their priority land use issues and to identify land use hotspots in a way that is not typically possible in a general public meeting. This project also provides a useful example of the integration of academic PGIS research with an emerging county planning infrastructure and related set of regulations. This is achieved through multimedia representation of local knowledge with formal spatial information; for example, traditional GIS raster and vector data, community narratives, mental maps, GPS transect walks, geo-referenced photos, and sound. The Cheat Lake PGIS pilot project also offers important lessons for participatory land use planning.

Submarine landslide catalogue onshore/offshore harmonization: Spain as a case study

2018 ◽  
Vol 477 (1) ◽  
pp. 497-510 ◽  
Author(s):  
Ricardo León ◽  
Juan Carlos García-Davalillo ◽  
David Casas ◽  
Carmen Julia Giménez-Moreno
Keyword(s):  
Spatial Information ◽  
Submarine Landslide ◽  
Submarine Landslides ◽  
Data Types ◽  
Landslide Event ◽  
Data Source ◽  
Geological Timescale ◽  
Different Sources

AbstractThis paper presents a Geographic Information System catalogue of the submarine landslides of the Spanish continental margin and describes the problems associated with harmonizing the catalogue with its onshore homologue. The data model structure is described to explain how to apply the rules and specifications following the Infrastructure for Spatial Information in Europe (INSPIRE). Because of the singularities of the marine environment compared with those of land, integrating the submarine landslide catalogues into INSPIRE specifications requires the following procedures: (1) simplification of the list of values of state of activity into three categories: active, dormant and relict; and (2) inclusion of debris avalanches and turbidites as new typologies of landslides. This paper discusses the problems associated with harmonizing different data types and units from different sources, such as the thickness (metres and seismic two travel time) or the age of the event, and a numeric code for the geological timescale is proposed to harmonize these data. We establish whether an item is required based on the reliability of the landslide event, which is categorized by three levels (high–middle–low) depending on the precision of the data source, methodology used and quality of the publication where the data are obtained.

Book Reviews

2016 ◽  
Vol 54 (3) ◽  
pp. 946-948
Keyword(s):  
Social Exclusion ◽  
Small Area ◽  
Spatial Information ◽  
Local Level ◽  
Small Area Estimation ◽  
Material Deprivation ◽  
Absolute Poverty ◽  
Time Dimension ◽  
Area Estimation ◽  
New Methods

Enrica Chiappero-Martinetti of the University of Pavia reviews “Poverty and Social Exclusion: New Methods of Analysis,” by Gianni Betti and Achille Lemmi. The Econlit abstract of this book begins: “Fifteen papers explore new methods for estimating poverty at the local level and examine recent multidimensional methods of the dynamics of poverty. Papers discuss measuring multidimensional deprivation with dichotomized and ordinal variables; poverty and the dimensionality of welfare; income, material deprivation, and social exclusion in Israel; multidimensional and fuzzy measures of poverty and inequality at the national and regional level in Mozambique; assessing the time-dimension of poverty; intertemporal material deprivation; measuring chronic poverty; measuring intertemporal poverty—policy options for the poverty analyst; measuring levels and trends in absolute poverty in the world—open questions and possible alternatives; small area methodology in poverty mapping—an introductory overview; small area estimation of poverty using the ELL/PovMap method and its alternatives; estimation of poverty measures in small areas; the use of spatial information for the estimation of poverty indicators at the small area level; outlier robust semiparametric small area methods for poverty estimation; and poverty and social exclusion in 3D—multidimensional, longitudinal, and small area estimation.”

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