GIS-Based Virtual Testbeds and Their Application to Forestry and City Simulation

2010 ◽  
Author(s):  
Ju¨rgen Roßmann ◽  
Michael Schluse ◽  
Martin Hoppen ◽  
Ralf Waspe
Keyword(s):  
Remote Sensing ◽  
Interdisciplinary Approach ◽  
Remote Sensing Data ◽  
Natural Environments ◽  
Data Sets ◽  
New Approach ◽  
New Class ◽  
Time Simulation ◽  
New Ideas ◽  
Remote Sensing Methods

In this paper we present a new interdisciplinary approach to geographic information systems. The integration of object-oriented data modeling, 3D real-time simulation, virtual reality techniques and remote sensing methods with new semantic world modeling techniques and well known geo information system (GIS) functionalities provides the basis for a new class of “Virtual Testbeds”. These testbeds build on a new approach which combines state-of-the-art GIS functionalities to deal with complex and large geographical data sets with the intuitive operability and the advanced simulation capabilities of latest robotic and automation simulation components. Besides the simulation algorithms, the testbeds take advantage of advanced modeling capabilities to (semi) automatic ally generate models of “natural” environments in e.g. forests or cities. Based on remote sensing data, not only geometric shapes are derived, but also an object’s “function” or “semantics”. The new ideas have already been applied to various applications of which the most successful will also be described in this paper.

scholarly journals The predictability of reported drought events and impacts in the Ebro Basin using six different remote sensing data sets

2017 ◽  
Vol 21 (9) ◽  
pp. 4747-4765 ◽  
Author(s):  
Clara Linés ◽  
Micha Werner ◽  
Wim Bastiaanssen
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Data Sets ◽  
Drought Management ◽  
Ebro Basin ◽  
Sensing Data ◽  
Drought Impacts ◽  
Management Plans ◽  
Drought Indicators ◽  
Selection Of

Abstract. The implementation of drought management plans contributes to reduce the wide range of adverse impacts caused by water shortage. A crucial element of the development of drought management plans is the selection of appropriate indicators and their associated thresholds to detect drought events and monitor the evolution. Drought indicators should be able to detect emerging drought processes that will lead to impacts with sufficient anticipation to allow measures to be undertaken effectively. However, in the selection of appropriate drought indicators, the connection to the final impacts is often disregarded. This paper explores the utility of remotely sensed data sets to detect early stages of drought at the river basin scale and determine how much time can be gained to inform operational land and water management practices. Six different remote sensing data sets with different spectral origins and measurement frequencies are considered, complemented by a group of classical in situ hydrologic indicators. Their predictive power to detect past drought events is tested in the Ebro Basin. Qualitative (binary information based on media records) and quantitative (crop yields) data of drought events and impacts spanning a period of 12 years are used as a benchmark in the analysis. Results show that early signs of drought impacts can be detected up to 6 months before impacts are reported in newspapers, with the best correlation–anticipation relationships for the standard precipitation index (SPI), the normalised difference vegetation index (NDVI) and evapotranspiration (ET). Soil moisture (SM) and land surface temperature (LST) offer also good anticipation but with weaker correlations, while gross primary production (GPP) presents moderate positive correlations only for some of the rain-fed areas. Although classical hydrological information from water levels and water flows provided better anticipation than remote sensing indicators in most of the areas, correlations were found to be weaker. The indicators show a consistent behaviour with respect to the different levels of crop yield in rain-fed areas among the analysed years, with SPI, NDVI and ET providing again the stronger correlations. Overall, the results confirm remote sensing products' ability to anticipate reported drought impacts and therefore appear as a useful source of information to support drought management decisions.

Estimation of water stress in olive orchards through remote sensing data analysis

2021 ◽  
Author(s):  
Luz Karime Atencia ◽  
María Gómez del Campo ◽  
Gema Camacho ◽  
Antonio Hueso ◽  
Ana M. Tarquis
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Water Potential ◽  
Statistical Tests ◽  
Remote Sensing Data ◽  
Olive Tree ◽  
Fruit Trees ◽  
Data Sets ◽  
Stem Water Potential ◽  
Stem Water

<p>Olive is the main fruit tree in Spain representing 50% of the fruit trees surface, around 2,751,255 ha. Due to its adaptation to arid conditions and the scarcity of water, regulated deficit irrigation (RDI) strategy is normally applied in traditional olive orchards and recently to high density orchards. The application of RDI is one of the most important technique used in the olive hedgerow orchard. An investigation of the detection of water stress in nonhomogeneous olive tree canopies such as orchards using remote sensing imagery is presented.</p><p>In 2018 and 2019 seasons, data on stem water potential were collected to characterize tree water state in a hedgerow olive orchard cv. Arbequina located in Chozas de Canales (Toledo). Close to the measurement’s dates, remote sensing images with spectral and thermal sensors were acquired. Several vegetation indexes (VI) using both or one type of sensors were estimated from the areas selected that correspond to the olive crown avoiding the canopy shadows.</p><p>Nonparametric statistical tests between the VIs and the stem water potential were carried out to reveal the most significant correlation. The results will be discussing in the context of robustness and sensitivity between both data sets at different phenological olive state.</p><p><strong>ACKNOWLODGEMENTS</strong></p><p>Financial support provided by the Spanish Research Agency co-financed with European Union FEDER funds (AEI/FEDER, UE, AGL2016-77282-C3-2R project) and Comunidad de Madrid through calls for grants for the completion of Industrial Doctorates, is greatly appreciated.</p>

scholarly journals Remote Sensing for Property Valuation: A Data Source Comparison in Support of Fair Land Taxation in Rwanda

2021 ◽  
Vol 13 (18) ◽  
pp. 3563
Author(s):  
Mila Koeva ◽  
Oscar Gasuku ◽  
Monica Lengoiboni ◽  
Kwabena Asiama ◽  
Rohan Mark Bennett ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Aerial Images ◽  
Primary Data ◽  
Structured Interviews ◽  
Remotely Sensed Data ◽  
Quality Of Data ◽  
New Approach ◽  
Property Valuation ◽  
Land Administration

Remotely sensed data is increasingly applied across many domains, including fit-for-purpose land administration (FFPLA), where the focus is on fast, affordable, and accurate property information collection. Property valuation, as one of the main functions of land administration systems, is influenced by locational, physical, legal, and economic factors. Despite the importance of property valuation to economic development, there are often no standardized rules or strict data requirements for property valuation for taxation in developing contexts, such as Rwanda. This study aims at assessing different remote sensing data in support of developing a new approach for property valuation for taxation in Rwanda; one that aligns with the FFPLA philosophy. Three different remote sensing technologies, (i) aerial images acquired with a digital camera, (ii) WorldView2 satellite images, and (iii) unmanned aerial vehicle (UAV) images obtained with a DJI Phantom 2 Vision Plus quadcopter, are compared and analyzed in terms of their fitness to fulfil the requirements for valuation for taxation purposes. Quantitative and qualitative methods are applied for the comparative analysis. Prior to the field visit, the fundamental concepts of property valuation for taxation and remote sensing were reviewed. In the field, reference data using high precision GNSS (Leica) was collected and used for quantitative assessment. Primary data was further collected via semi-structured interviews and focus group discussions. The results show that UAVs have the highest potential for collecting data to support property valuation for taxation. The main reasons are the prime need for accurate-enough and up-to-date information. The comparison of the different remote sensing techniques and the provided new approach can support land valuers and professionals in the field in bottom-up activities following the FFPLA principles and maintaining the temporal quality of data needed for fair taxation.

scholarly journals Giovanni: The Bridge Between Data and Science

Eos ◽  
2017 ◽  
Author(s):  
Zhong Liu ◽  
James Acker
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Earth Science ◽  
Remote Sensing Data ◽  
Data Sets ◽  
Science Data ◽  
Web Based ◽  
Sensing Data ◽  
Daunting Task ◽  
Earth Science Data

Using satellite remote sensing data sets can be a daunting task. Giovanni, a Web-based tool, facilitates access, visualization, and exploration for many of NASA’s Earth science data sets.

scholarly journals Forest areas remote monitoring within the limits of transport objects impact

2021 ◽  
pp. 109-118
Author(s):  
Dmytro Liashenko ◽  
◽  
Dmytro Pavliuk ◽  
Vadym Belenok ◽  
Vitalii Babii ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Remote Monitoring ◽  
Forest Cover ◽  
Landsat Imagery ◽  
Remote Sensing Data ◽  
Transport Infrastructure ◽  
Nature Management ◽  
Collecting Methods ◽  
Remote Sensing Methods

The article studies the issues of using remote sensing data for the tasks of ensuring sustainable nature management in the territories within the influence of transport infrastructure objects. Peculiarities of remote monitoring for tasks of transport networks design and in the process of their operation are determined. The paper analyzes the development of modern remote sensing methods (satellite imagery, the use of mobile sensors installed on cars or aircraft). A brief overview of spatial data collecting methods for the tasks of managing the development of territories within the influence of transport infrastructure (roads, railways, etc.) has made. The article considers the experience of using remote sensing technologies to monitor changes in the parameters of forest cover in the Transcarpathian region (Ukraine) in areas near to highways, by use Landsat imagery.

scholarly journals Analyses of the Prądnik riverbed Shape Based on Archival and Contemporary Data Sets—Old Maps, LiDAR, DTMs, Orthophotomaps and Cross-Sectional Profile Measurements

2020 ◽  
Vol 12 (14) ◽  
pp. 2208 ◽  
Author(s):  
Stanisław Szombara ◽  
Paulina Lewińska ◽  
Anna Żądło ◽  
Marta Róg ◽  
Kamil Maciuk
Keyword(s):  
Remote Sensing ◽  
Survey Methods ◽  
Remote Sensing Data ◽  
Sufficient Information ◽  
Data Sets ◽  
Time Step ◽  
Mountain Areas ◽  
Cross Sectional ◽  
Sensing Data ◽  
Old Maps

Analyses of riverbed shape evolution are crucial for environmental protection and local water management. For narrow rivers located in forested, mountain areas, it is difficult to use remote sensing data used for large river regions. We performed a study of the Prądnik River, located in the Ojców National Park (ONP), Poland. A multitemporal analysis of various data sets was performed. Light detection and ranging (LiDAR)-based data and orthophotomaps were compared with classical survey methods, and 78 cross-sectional profiles were done via GNSS and tachymetry. In order to add an extra time step, the old maps of this region were gathered, and their content was compared with contemporary data. The analysis of remote sensing data suggests that they do not provide sufficient information on the state and changes of riverbanks, river course or river depth. LiDAR data sets do not show river bottoms, and, due to plant life, do not document riverbanks. The orthophotomaps, due to tree coverage and shades, cannot be used for tracking the whole river course. The quality of old maps allows only for general shape analysis over time. This paper shows that traditional survey methods provide sufficient accuracy for such analysis, and the resulted cross-sectional profiles can and should be used to validate other, remote sensing, data sets. We diagnosed problems with the inventory and monitoring of such objects and proposed methods to refine the data acquisition.

The debris cover surface of Ponkar glacier: a laboratory for learning

2020 ◽  
Author(s):  
Adina E. Racoviteanu ◽  
Neil F. Glasser ◽  
Smriti Basnett ◽  
Rakesh Kayastha ◽  
Stephan Harrison
Keyword(s):  
Remote Sensing ◽  
Scientific Knowledge ◽  
Interdisciplinary Approach ◽  
Surface Features ◽  
Ice Melt ◽  
Supraglacial Lakes ◽  
High Asia ◽  
Glacier Ice ◽  
Building Activities ◽  
Remote Sensing Methods

<p>Understanding the evolution of debris-covered glaciers, including their evolution over time, the distribution of surface features such as exposed ice walls and supraglacial lakes, and their contributions to glacier ice melt and to glacier-related hazards such as Glacier Lake Outburst Flood (GLOF) events requires an interdisciplinary approach, with a combination of remote sensing methods and collaborative fieldwork.</p><p>Since 2017, the IGCP 672 /UNESCO project led has been focussing on the transfer of scientific knowledge on monitoring debris-covered glaciers to local partner institutions in high Asia through trainings, workshops and field collaborations. Our long-term goal is to disseminate methodologies developed under this project to local institutions in high Asia and to embed scientific knowledge into local communities. Here we report on recent capacity building activities held within the context of this new project involved local participants from universities in Nepal and Sikkim. The training included remote sensing/GIS modules, temperature measurements, sediment logging and drone surveys of the ablation zone, which will allow us to better quantify the surface features and their evolution.</p><p> </p>

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