Прикладні аспекти генерації гідрологічно-коректних та екологічно-відповідних цифрових моделей місцевості

Розглянуто ряд прикладних аспектів генерації цифрових моделей місцевості з використанням кросс-валідаційних процедур, застосування яких мінімізує помилки інтерполяції в автоматичному режимі. Показано приклад застосування такого підходу з використанням вільної ГІС GRASS.Рассмотрены прикладные аспекты создания цифровых моделей местности с использованием кросс-валидационных процедур, которые минимизируют ошибки интерполяции в автоматическом режиме. Показан пример применения такого подхода с использованием свободной ГИС GRASS.Practical aspects were considered when creating a digital terrain models using crossvalidation procedures to minimize the interpolation error in the automatic mode. There was an example of such an approach using free GIS GRASS

Error estimates in Sobolev spaces for interpolating thin plate splines under tension

AbstractThis paper discusses Lp-error estimates for interpolation by thin plate spline under tension of a function in the classical Sobolev space on an open bounded set with a Lipschitz-continuous boundary. A property of convergence is also given when the set of interpolating points becomes more and more dense

Use of Descriptive Statistical Indicators for Aggregating Environmental Data in Multi-Scale European Databases

There is a strong need for accurate and spatially referenced information regarding policy making and model linkage. This need has been expressed by land users, and policy and decision makers in order to estimate spatially and locally the impacts of European policy (like the Common Agricultural Policy) and/or global changes on economic agents and consequently on natural resources (Cantelaube et al., 2012). The proposal for a framework Directive (COM (2006) 232) (EC, 2006) sets out common principles for protecting soils across the EU. Within this common framework, the EU Member States will be in a position to decide how best to protect soil and how use it in a sustainable way on their own territory. In this policy document, European Commission identifies 8 soil threats: soil erosion, soil organic carbon decline, salinisation, landslides, soil compaction, biodiversity and soil contamination. The policy document explains why EU action is needed to ensure a high level of soil protection, and what kind of measures must be taken. As the soil threats have been described in the proposed Soil Thematic Strategy for Soil Protection (COM (2006) 231), there is a need to address them and relative issues at various scales; from local/province scale, to regional/national scale, and at the end to continental/global scale. The modeling platform should be constructed in such a way that knowledge and information can be passed along the spatial scales causing the minimum loss of information. Particular interest will be given to outputs from the aggregation model such as organic carbon decline, soil erosion and soil. Soil data and information are highly relevant for the development, implementation and assessment of a number of EU policy areas: agriculture, soil protection, bio-energy, water protection, nature protection, development policy, health and sustainable development. All those policy areas request soil data in various scales depending on the application.JRC.H.5-Land Resources Managemen

IMPLEMENTASI INTERPOLASI LANCZOS DAN ORDINARY KRIGING DALAM PEMETAAN POLUSI CAHAYA: STUDI KASUS PULAU JAWA DAN KOTA BANDUNG

Polusi cahaya adalah masalah yang terus berkembang yang mempengaruhi berbagai aspek kehidupan manusia dan lingkungan alam, termasuk pengamatan astronomi. Pemetaan polusi cahaya yang akurat sangat penting untuk pengembangan kebijakan dan tindakan mitigasi yang efektif. Penelitian ini mengevaluasi dua metode interpolasi-interpolasi Lanczos dan Ordinary Kriging-untuk pemetaan polusi cahaya, dengan menggunakan dua set data yang berbeda: Visible Infrared Imaging Radiometer Suite (VIIRS) dan Sky Quality Meter (SQM). Penelitian ini berfokus pada enam ibu kota provinsi di Pulau Jawa: Serang, Jakarta, Bandung, Yogyakarta, Semarang, dan Surabaya. Interpolasi Lanczos diterapkan pada data VIIRS dan secara efektif mengubah resolusi asli 750m x 750m menjadi resolusi 75m x 75m yang lebih halus. Hal ini menghasilkan peta polusi cahaya yang lebih rinci dan dapat diandalkan untuk kota-kota tersebut. Di sisi lain, Ordinary Kriging diterapkan pada data SQM yang dikumpulkan dari 26 titik berbeda di Kota Bandung. Metode ini terbukti dapat diandalkan untuk menghasilkan peta polusi cahaya berkualitas tinggi, terutama di daerah dengan sampel data yang tidak teratur. Penerapan Interpolasi Lanczos dan Ordinary Kriging pada data Kota Bandung menunjukkan adanya perbedaan terutama dalam hal resolusi dan sumber data. Lanczos lebih cocok untuk data berbasis grid seperti VIIRS, sedangkan Kriging lebih cocok untuk data yang diambil secara acak seperti SQM. Terlepas dari perbedaan ini, kedua metode ini menawarkan peta mendalam yang menunjukkan distribusi spasial polusi cahaya di seluruh area yang diteliti. Temuan dari penelitian ini memberikan wawasan yang berharga untuk proyek pemetaan polusi cahaya di masa depan. Dengan memahami karakteristik data dan metode yang digunakan, para peneliti di masa depan dapat membuat keputusan yang lebih tepat dalam memilih metode interpolasi. Hal ini akan menghasilkan peta polusi cahaya yang lebih akurat dan berkontribusi pada pengembangan strategi mitigasi yang lebih efektif

Estimating daily land surface temperatures in mountainous environments by reconstructured MODIS LST data

Continuous monitoring of extreme environments, such as the European Alps, is hampered by the sparse and/or irregular distribution of meteorological stations, the difficulties in performing ground surveys and the complexity of interpolating existing station data. Remotely sensed Land Surface Temperature (LST) is therefore of major interest for a variety of environmental and ecological applications. But while MODIS LST data from the Terra and Aqua satellites are aimed at closing the gap between data demand and availability, clouds and other atmospheric disturbances often obscure parts or even the entirety of these satellite images. A novel algorithm is presented in this paper, which is able to reconstruct incomplete MODIS LST maps. All nine years of the available daily LST data (2000–2008) have been processed, allowing the original LST map resolution of 1,000 m to be improved to 200 m, which means the resulting LST maps can be applied at a regional level. Extracted time series and aggregated data are shown as examples and are compared to meteorological station time series as an indication of the quality obtained

Deriving Bounds on the Size of Spatial Areas

Many application domains such as surveillance, environmental monitoring or sensor-data processing need upper and lower bounds on areas that are covered by a certain feature. For example, a smart-city infrastructure might need bounds on the size of an area polluted with fine-dust, to re-route combustion-engine traffic. Obtaining such bounds is challenging, because in almost any real-world application, information about the region of interest is incomplete, e.g., the database of sensor data contains only a limited number of samples. Existing approaches cannot provide upper and lower bounds or depend on restrictive assumptions, e.g., the area must be convex. Our approach in turn is based on the natural assumption that it is possible to specify a minimal diameter for the feature in question. Given this assumption, we formally derive bounds on the area size, and we provide algorithms that compute these bounds from a database of sensor data, based on geometrical considerations. We evaluate our algorithms both with a real-world case study and with synthetic data

Deriving Bounds on the Size of Spatial Areas

Many application domains such as surveillance, environmental monitoring or sensor-data processing need upper and lower bounds on areas that are covered by a certain feature. For example, a smart-city infrastructure might need bounds on the size of an area polluted with fine-dust, to re-route combustion-engine traffic. Obtaining such bounds is challenging, because in almost any real-world application, information about the region of interest is incomplete, e.g., the database of sensor data contains only a limited number of samples. Existing approaches cannot provide upper and lower bounds or depend on restrictive assumptions, e.g., the area must be convex. Our approach in turn is based on the natural assumption that it is possible to specify a minimal diameter for the feature in question. Given this assumption, we formally derive bounds on the area size, and we provide algorithms that compute these bounds from a database of sensor data, based on geometrical considerations. We evaluate our algorithms both with a real-world case study and with synthetic data

DEFINITION OF CONTOUR LINES INTERPOLATION OPTIMAL METHODS FOR E-GOVERNMENT SOLUTIONS

Citizens expect high quality and rich e-Government solutions. Map based applications could be significantly improved by utilization of digital elevation models (DEMs). DEMs can be produced using expensive modern remote sensing solutions (e.g., LIDAR). Such data are not available for the wide public. Thus, it is very effective to use contour line maps to derive high-quality DEMs. For many cities around the world, contour line maps available under liberal licenses. Defining an optimal algorithm of contour line interpolation and evaluation of the quality of DEM is an important challenge. In this article, we propose a simple method allowing users to evaluate the quality of DEM produced from a contour line map and define an optimal interpolation algorithm. This method was tested on Turin (Italy) data sets. The results were proved by a visual analysis. The approach is utilized in existing e-Government WebGIS services. This work introduces an information theory-based approach to DEM quality assessment. The results can be utilized in various domains related to DEM quality assurance