Using RPC Block Adjustment models for the accuracy of environmental research, cartography and geomarketing: a new concept of cartography

Kuan, Fu-Yung; Ho, Yen-Ping; Wang, Ruei-Yuan; Chen, Cheng-Wu

doi:10.1007/s00477-012-0668-8

Cited by 8 publications

(6 citation statements)

References 67 publications

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“…As emphasized by the Rio de Janeiro Declaration on Environment and Development (1992), people's needs and aspirations must be balanced with healthy ecological systems. To address this challenge, models for measuring sustainability must more explicitly address the fundamental importance of environmental issues at all levels of society, including individual companies (Kuan et al, 2013). This is further supported by the green economics paradigm, which recognizes that the economy operates within social relationships that are embedded in nature (Cato, 2009).…”

Section: Assessing Sustainability Performance Under the Strong Sustainability Perspectivementioning

confidence: 99%

“…As noted by Pearce (1988, P. 599), "constancy of natural capital or more specifically, the non-negativity of the rate of change in the natural capital relates probabilistically to sustainability". Deteriorating natural resources may therefore be correlated with declines in sustainability at all levels of society, and hence, environmental sustainability is deemed to be a crucial subject of concern in the current century (Kuan et al, 2013). This would highlight the need for research on methods of measuring sustainability that adopt the strong sustainability concept at all levels of society, including individual companies.…”

Section: Assessing Sustainability Performance Under the Strong Sustainability Perspectivementioning

confidence: 99%

“…Considering all of the above, by taking the strong sustainability perspective, the proposed model is based on the assumption that evaluating sustainability performance based on environmentally related factors as the main affecting players can provide a suitable representation for sustainability. This assumption builds on a point that has also been highlighted by Kuan et al (2013). Therefore, in order to evaluate the sustainability performance of a company under the green economics paradigm, the environmentally related factors can be assumed to be the primary factors affecting the challenge and capacity of the company independently.…”

Section: Figure 7-1: Green Economics Paradigmmentioning

confidence: 99%

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Sustainability analysis and assessment in the supply chain

Ahi¹

2021

Preprint

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The purpose of this research is to investigate how sustainability is integrated into supply chain management (SCM). Emphasis is particularly devoted to determining how the sustainability of supply chains may be assessed. Four key objectives were developed to support this purpose: (1) define sustainable supply chain management (SSCM), (2) identify and analyze the published metrics for SSCM, (3) develop a comprehensive approach for assessing sustainability performance at the company level, and (4) develop an integrative sustainability performance framework for the broader context of supply chain. The first two objectives were accomplished through two different sets of in-depth literature reviews. The reviews focused on analyzing the convergences and divergences in the literature on green supply chain management (GSCM), SSCM, and the metrics used in these areas. The reviews helped provide the basis for accomplishing the remaining research objectives. Accordingly, stochastic models for measuring sustainability performance at the company and supply chain levels were developed. This research addresses several important gaps in the literature. As research on the integration of sustainability into SCM continues to expand, it becomes increasingly important to highlight the inconsistencies in the various definitions and metrics used to measure GSCM and SSCM. The lack of reasonably consistent definitions and metrics may lead to confusion regarding the appropriate scope in theory and practice of SSCM initiatives. Exploring the implications of and potential resolutions to the many differences in the published definitions and metrics provide much needed reference points, and further provide the foundation necessary to support the development of scientifically-sound sustainability models. By providing relatively simple and informative measurement, the model developed in Objective 3 presents a unique method of adopting the strong sustainability concept to assessing sustainability at the company level. Furthermore, by providing an original and straightforward analytical approach, the SSCM models developed in Objective 4 are one of the first to explicitly adopt probabilistic approaches for sustainability assessment in the supply chain context. Given their unique ability to accommodate any number of SSCM characteristics, the models can be employed as integrative, multi-dimensional tools for evaluating changes in the sustainability status of a supply chain over time.

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Section: Assessing Sustainability Performance Under the Strong Sustainability Perspectivementioning

confidence: 99%

Section: Assessing Sustainability Performance Under the Strong Sustainability Perspectivementioning

confidence: 99%

Section: Figure 7-1: Green Economics Paradigmmentioning

confidence: 99%

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Sustainability analysis and assessment in the supply chain

Ahi¹

2021

Preprint

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“…The RFM model, in the form of rational polynomial coefficients (RPCs), connects the object coordinate (B, L, H) with the image coordinate (l, s) [22][23][24][25][26][27][28]. B, L, and H are the longitude, latitude, and ellipsoid height, respectively; l and s are the line and sample coordinates, respectively.…”

Section: Rational Polynomial Coefficients Model For Combined Geopositmentioning

confidence: 99%

Geometric Accuracy Improvement Method for High-Resolution Optical Satellite Remote Sensing Imagery Combining Multi-Temporal SAR Imagery and GLAS Data

et al. 2020

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With the widespread availability of satellite data, a single region can be described using multi-source and multi-temporal remote sensing data, such as high-resolution (HR) optical imagery, synthetic aperture radar (SAR) imagery, and space-borne laser altimetry data. These have become the main source of data for geopositioning. However, due to the limitation of the direct geometric accuracy of HR optical imagery and the effect of the small intersection angle of HR optical imagery in stereo pair orientation, the geometric accuracy of HR optical imagery cannot meet the requirements for geopositioning without ground control points (GCPs), especially in uninhabited areas, such as forests, plateaus, or deserts. Without satellite attitude error, SAR usually provides higher geometric accuracy than optical satellites. Space-borne laser altimetry technology can collect global laser footprints with high altitude accuracy. Therefore, this paper presents a geometric accuracy improvement method for HR optical satellite remote sensing imagery combining multi-temporal SAR Imagery and GLAS data without GCPs. Based on the imaging mechanism, the differences in the weight matrix determination of the HR optical imagery and SAR imagery were analyzed. The laser altimetry data with high altitude accuracy were selected and applied as height control point in combined geopositioning. To validate the combined geopositioning approach, GaoFen2 (GF2) optical imagery, GaoFen6 (GF6) optical imagery, GaoFen3 (GF3) SAR imagery, and the Geoscience Laser Altimeter System (GLAS) footprint were tested. The experimental results show that the proposed model can be effectively applied to combined geopositioning to improve the geometric accuracy of HR optical imagery. Moreover, we found that the distribution and weight matrix determination of SAR images and the distribution of GLAS footprints are the crucial factors influencing geometric accuracy. Combined geopositioning using multi-source remote sensing data can achieve a plane accuracy of 1.587 m and an altitude accuracy of 1.985 m, which is similar to the geometric accuracy of geopositioning of GF2 with GCPs.

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“…According to Fu-Yung, maps are a graphic presentation of geographic and spatial information. Being a data carrier, it stores and makes the analyses of such data available [1].…”

Section: Introductionmentioning

confidence: 99%

Data generation of vector maps using a hybrid method of analysis and selection of geodata necessary to optimize the process of spatial planning

Strumiłło-Rembowska

Bednarczyk

Cieślak

2014

The 9th International Conference "Environmental Engineering 2014"

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Throughout the years GIS has developed a number of very useful cartographic tools for the computerized storage, management and graphic display of many thematic layers of particular data and information. The aim of the paper was both to present the possibility of generating data of vector maps and to give an example of hybrid method of analysis and selection of geodata extracted from raster image necessary to optimize the process of spatial planning. The study shows how by using vector maps, fast spatial analysis can be proceeded.

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Using RPC Block Adjustment models for the accuracy of environmental research, cartography and geomarketing: a new concept of cartography

Cited by 8 publications

References 67 publications

Sustainability analysis and assessment in the supply chain

Sustainability analysis and assessment in the supply chain

Geometric Accuracy Improvement Method for High-Resolution Optical Satellite Remote Sensing Imagery Combining Multi-Temporal SAR Imagery and GLAS Data

Data generation of vector maps using a hybrid method of analysis and selection of geodata necessary to optimize the process of spatial planning

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