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Register a new userAccuracy of interpolation methods for the derivation of digital elevation models based on gridding observations
دقة طرق الاستيفاء في إنتاج النماذج الارتفاعية الرقمية من قياسات شبكية حقلية
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في هذه الدراسة تم التركيز على المقارنة بين عدة طرق استيفاء لتشكيل سطح التضاريس لمنطقة الدراسة انطلاقاً من قياسات حقلية لشبكات تربيعية ذات تباعدات مختلفة.
In this study, we focused on the interpolation methods for the derivation of digital elevation models, based on field gridding observations with different spacing.
References used
AGUILAR, F and et al 2005 Effects of Terrain Morphology, Sampling Density, and Interpolation Methods on Grid DEM Accuracy, Photogrammetric Engineering and Remote Sensing, 71(7).805-816
CARTER, J.R 1988 Digital representations of topographic surfaces, Photogrammetric Engineering and Remote Sensing, 54(11).1577–1580
CHAPLOT, V DARBOUX, F BOURENNANE, H LEGUÉDOIS, S SILVERA, N PHACHOMPHON, K 2006 Accuracy of interpolation techniques for the derivation of digital elevation models in relation to landform types and data density, Geomorphology ,77(1). 126-140
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In this paper, we
describe an algorithm to register the retinal images by employing a relatively
cross-correlation function. Pixel to pixel accuracy has been investigated and
evaluated among registered images by calculating the local cross-correla
tion
between extracted vessels profiles along tracked vessels after transforming
the images into alignment.
This research aimed for using Geographic Information System (GIS) in producing
Digital Elevation Model (DEM) for Dimas District, By applying various methods: Spatial
Analyst, Geo Statistical Analyst, Triangulated Irregular Network (TIN), and interp
olating
DEM from contour lines.
The study showed that the best methods for interpolating DEM is Kriging method,
Which interpolated an evaluated surface for scattered points which had (Z values) whether
they were closed or scattered from each other. And (TIN) method which required less area
on hard disc to be stored comparing with other methods, and it's perfect for representing
surfaces in wide areas, Also generating DEM from contour lines produced DEM which had
very accurate representing for surfaces.
نظم المعلومات الجغرافية
(Geographic Information System (GIS
التحليل المكاني
Kriging
نموذج الارتفاع الرقمية
المسافة الموزونة المعكوسة
الاشتقاق المكاني
المنهجية المنتظمة
المنهجية المتواترة
التحليل الجيو إحصائي
السطح المستمر
التخمين الإحصائي
التحليل ثلاثي الأبعاد
الشبكة المثلثاتية غير المنتظمة
خطوط التسوية
(Digital Elevation Model (DEM
Contour Lines
(Triangulated Irregular Network (TIN
3D Analyst
Continuous Surface
المزيد..
3D GIS can be realized as an actual building platform of the urban space. This research develops automated 3D urban models that fit large-scale digital photogrammetry. Originally, modeling used manual or semi-manual techniques, and there is a need to
for a development of an approach that automates the transformation of vector linear data, optimized by digital photogrammetry stations to create the 3D volume model in 3DGIS. This approach consists of three main phases:
roof modeling, wall modeling and volume structuring. During the first phase, local and conditional "Delaunay Triangulation" method is used to deal with the majority of roof types regardless of its geometry. The second phase is completely automated to create the walls by the
vertical projection (Top-Down) of the outer line of the roof into the Digital Terrain Model (DTM), and then by the selection of the bottom base level as the default level. Finally, different elements of the structure can be aggregated using spatial relationships (many-to-many) already supported by GIS software. The new approach is created and completely automated. It doesn't require roof geometric-types library, which asserts the GIS is a valid platform to build, to view
and to store 3D urban models.
نظم معلومات جغرافية
GIS
نظم تصميم بمعونة الحاسب
تمثيل شعاعي
CAD
RDBMS
Vector
النماذج الرقمية ثلاثية الأبعاد
المساحة التصويرية الجوية الرقمية
الرؤية الاستريوسكوبية
المسح الجوي الليزري
قواعد البيانات المكانية العلائقية
تلثيث دولوني
3D Digital Model
Digital Aerial Photogrammetry
Stereoscopic Viewing
LIDAR
Delaunay Triangulation
المزيد..
International river basins are characterized by their wide extent where mapping earth
surface features and drawing contours by topographic team become–somehow- impossible
because the cost and efforts consumed to execute it become very high and may
exceed
reasonable limits. Here it becomes necessary to use digital elevation models (DEM)
inferred by specialized scientific organizations using remote sensing.
There are several DEMs available on the internet and downloadable for free. The
primary factor in defining the models efficiency in building hydrological models not the
least cost but the maximum reliable results and better resolution that adequate to the
capabilities of the PCs.
In this study, three DEMs were used to derive and build hydrological models for the
Euphrates-Tigris basin using Geographic information system techniques. The resulted
boundaries of Euphrates-Tigris basin were compared with three boundaries implemented
by international research organizations (UNEP, ESCWA, and FAO). As a conclusion of
this comparison, the SRTM—3arc DEM was the most efficient model among used models.
In addition, this study indicated the necessity to reevaluate Basin’s boundaries and correct
the spatial distribution of proportion for basin area between the riparian countries.
Deep learning models exhibit a preference for statistical fitting over logical reasoning. Spurious correlations might be memorized when there exists statistical bias in training data, which severely limits the model performance especially in small da
ta scenarios. In this work, we introduce Counterfactual Adversarial Training framework (CAT) to tackle the problem from a causality perspective. Particularly, for a specific sample, CAT first generates a counterfactual representation through latent space interpolation in an adversarial manner, and then performs Counterfactual Risk Minimization (CRM) on each original-counterfactual pair to adjust sample-wise loss weight dynamically, which encourages the model to explore the true causal effect. Extensive experiments demonstrate that CAT achieves substantial performance improvement over SOTA across different downstream tasks, including sentence classification, natural language inference and question answering.
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