scholarly journals Ermittlung der Kohlenstoffspeicherung von Bäumen im Siedlungsgebiet am Beispiel der Stadt Bern

2016 ◽  
Vol 167 (2) ◽  
pp. 90-97 ◽  
Author(s):  
Oliver Gardi ◽  
Guillaume Schaller ◽  
Matthias Neuner ◽  
Sophia Mack
Keyword(s):  
Carbon Storage ◽  
Aboveground Biomass ◽  
Urban Areas ◽  
Agricultural Land ◽  
Tree Height ◽  
Urban Trees ◽  
Lidar Data ◽  
Tree Biomass ◽  
A Value ◽  
The City

Determining the carbon storage of trees in urban areas of the city of Bern While the amount carbon stored in tree biomass within Swiss forests is well studied, many uncertainties remain for estimating the carbon stored by trees in settlements. As a part of the project «Urban Green and Climate», various existing biomass models were compared with the measured aboveground biomass of 21 trees within the city of Bern. Traditional forestry models that estimate the biomass based on the diameter at breast height only have a limited capacity to accurately predict the biomass of single urban trees. Good predictions are however achieved by using a biomass model that additionally includes tree height (R2 = 0.96). This model was then used to determine the aboveground tree biomass at 179 sample plots in Bern. The carbon densities (t C/ha) of the plots were used to calibrate a model predicting the carbon storage in the aboveground biomass for urban tree populations based on LiDAR data (R2 = 0.84). A value of 14.9 ± 0.5 t C/ha was obtained for the developed area of Bern (i.e. areas without water, forest and agricultural land). With this model and available LiDAR data, the carbon stored in the aboveground biomass of trees outside forests and its change over time could be determined with high accuracy for all of Switzerland.

scholarly journals Tree height integrated into pantropical forest biomass estimates

2012 ◽  
Vol 9 (8) ◽  
pp. 3381-3403 ◽  
Author(s):  
T. R. Feldpausch ◽  
J. Lloyd ◽  
S. L. Lewis ◽  
R. J. W. Brienen ◽  
M. Gloor ◽  
...  
Keyword(s):  
East Africa ◽  
Carbon Storage ◽  
Stand Structure ◽  
Forest Biomass ◽  
Small Diameter ◽  
Tree Height ◽  
Total Biomass ◽  
Guiana Shield ◽  
Tree Biomass ◽  
Continental Scale

Abstract. Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions: 1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? 2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? 3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates? The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (≤40 cm D) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including H reduces errors from 41.8 Mg ha−1 (range 6.6 to 112.4) to 8.0 Mg ha−1 (−2.5 to 23.0). For all plots, aboveground live biomass was −52.2 Mg ha−1 (−82.0 to −20.3 bootstrapped 95% CI), or 13%, lower when including H estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to H. After accounting for variation in H, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in east-central Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km2 and store 285 Pg C (estimate including H), then applying our regional relationships implies that carbon storage is overestimated by 35 Pg C (31–39 bootstrapped 95% CI) if H is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree H is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of tropical carbon stocks and emissions due to deforestation.

scholarly journals An automated classification system for urban areas matching the ‘city country fingers’ pattern: the cases of Kamakura (Japan) and Acireale (Italy) cities

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Roberto Spina ◽  
Emiliano Tramontana
Keyword(s):  
Urban Area ◽  
Urban Areas ◽  
Agricultural Land ◽  
Google Earth ◽  
Classification Model ◽  
Complete Analysis ◽  
City Development ◽  
Essential Condition ◽  
Green Areas ◽  
The City

Abstract The uncontrolled expansion of urban areas is one of the main factors that reduce the liveability of cities. In recent years, to contrast urban sprawl, several nations have promoted policies aimed at developing urban green spaces. The importance of green oases within cities had already been highlighted, in 1977, by the architect Christopher Alexander who had developed a series of patterns including ‘City Country Fingers’ claiming that city development should consider the prolongation of country land in to the urban area. In several cities, especially in Japan, it is possible to recognize the imprint of urban development based on country fingers. This term refers to extensive urban intersections of agricultural land or wooded hills which, from the peripheral areas, penetrate the city. Inside them, there are urban windows, called city fingers, whose development direction is opposite to those of the country fingers. To recognize and analyze, in an automated way, these particular structures, a Python-based application was created. Starting from the original high-resolution image of Google Earth, a complete analysis was performed, labeling and delimiting urban and vegetational areas and extrapolating the main geometric parameters of the country and city fingers. The finalization of the results obtained was carried out through a classification model whose criteria were based on Alexander’s pattern. Thanks to this classification scheme, the distinction between Active Green Areas (country fingers) and Passive Green Areas (gardens and public parks) have been revealed for the analyzed cities. The tests performed showed almost ideal conditions for the city of Kamakura and a limited match for the urban area of Acireale. The proposed method is suitable for fields of application that require a qualitative and quantitative determination of the vegetation cover present within the city, an essential condition for correct territorial planning.

scholarly journals 3D BUILDING CHANGE DETECTION BETWEEN CURRENT VHR IMAGES AND PAST LIDAR DATA

2018 ◽  
Vol XLII-2 ◽  
pp. 1229-1235 ◽  
Author(s):  
K. Zhou ◽  
B. Gorte ◽  
R. Lindenbergh ◽  
E. Widyaningrum
Keyword(s):  
Change Detection ◽  
Urban Areas ◽  
Color Difference ◽  
False Alarms ◽  
Lidar Data ◽  
Stereo Pair ◽  
3D City Model ◽  
Sharp Edges ◽  
City Model ◽  
The City

Change detection is an essential step to locate the area where an old model should be updated. With high density and accuracy, LiDAR data is often used to create a 3D city model. However, updating LiDAR data at state or nation level often takes years. Very high resolution (VHR) images with high updating rate is therefore an option for change detection. This paper provides a novel and efficient approach to derive pixel-based building change detection between past LiDAR and new VHR images. The proposed approach aims notably at reducing false alarms of changes near edges. For this purpose, LiDAR data is used to supervise the process of finding stereo pairs and derive the changes directly. This paper proposes to derive three possible heights (so three DSMs) by exploiting planar segments from LiDAR data. Near edges, the up to three possible heights are transformed into discrete disparities. A optimal disparity is selected from a reasonable and computational efficient range centered on them. If the optimal disparity is selected, but still the stereo pair found is wrong, a change has been found. A Markov random field (MRF) with built-in edge awareness from images is designed to find optimal disparity. By segmenting the pixels into plane and edge segments, the global optimization problem is split into many local ones which makes the optimization very efficient. Using an optimization and a consecutive occlusion consistency check, the changes are derived from stereo pairs having high color difference. The algorithm is tested to find changes in an urban areas in the city of Amersfoort, the Netherlands. The two different test cases show that the algorithm is indeed efficient. The optimized disparity images have sharp edges along those of images and false alarms of changes near or on edges and occlusions are largely reduced.

scholarly journals Sistem Budidaya Urban Farming dalam Optimalisasi Lahan di Kota Surakarta

2019 ◽  
Author(s):  
Maria Lintang Chrismas Ayu
Keyword(s):  
Urban Areas ◽  
Agricultural Land ◽  
Qualitative Description ◽  
Housing Conditions ◽  
Urban Farming ◽  
Literature Study ◽  
Related Research ◽  
Study Approach ◽  
The City ◽  
Planting System

Agricultural land in urban areas has become increasingly narrow, especially with the advent of housing which has replaced the function of agricultural land. Housing conditions in cities are very diferent from those in villages that have large plots of land and agricultural land, so we need a way to plant those that do not require large tracts of land. Urban farming is a way of cultivating plants that is done by utilizing narrow land in urban areas. Urban farming can be done in various ways such as hydroponics and verticuluture. This research was conducted to describe how to optimize the narrow yard of land in urban areas so that it can be better utilized, especially as an easy and effective planting medium. The method used in this research is to use a qualitative description with a literature study approach. Literature study is a way of collecting data with cases that are relevant to related research. The results of this study describe the cultivation of urban farming that is applied in urban areas, especially in the city of Surakarta. Urban farming planting system can add insight related to urban farming among the community and can be widely applied in Surakarta City.

scholarly journals Residents' attitudes towards tree care programs in cityscapes

2021 ◽  
Vol 7 ◽  
Author(s):  
Oghenekevwe Joy Arabomen ◽  
Folaranmi Dapo Babalola ◽  
Felix Oaikhena Idumah ◽  
Chinyere Salome Ofordu
Keyword(s):  
Urban Areas ◽  
Quantitative Information ◽  
Urban Trees ◽  
Logit Analysis ◽  
Public Expectations ◽  
The City ◽  
Residents Attitudes ◽  
Reduced Water ◽  
Tree Care

Purpose: Examine residents’ attitude towards urban trees from the perspective of funding or voluntarily contributing time for tree care programs. Majority of global populace live in cities, hence, the rise in public expectations for liveable, sustainable and greener communities and urban areas all over the world, Nigeria inclusive. With proper planning and management, cities may become more liveable, but the rapid loss of large urban green areas cause havoc, and has ushered in several problems such as adverse climatic condition, reduced water and air quality, amongst others. Metodology: A questionnaire survey was conducted to understand how residents rank and rate the benefits of urban trees as well as individual willingness to support conservation initiatives, using Benin metropolis, Nigeria as a case study. Findings: Using binary logit analysis, the study identified that residents who are aware of ecosystem services, had a profession and have spent at least 20 years in the city, had a significant relationship with personal willingness to volunteer time and/or donate money toward urban tree care programs and activities. Contribution to knowledge: Provided quantitative information to demonstrate the importance of conserving trees in development projects towards Global SDGs.

scholarly journals SPATIAL SIMULATION BASED ON GEOGRAPHIC INFORMATION SYSTEM (GIS) AND CELLULAR AUTOMATA (CA) FOR LAND USE CHANGE MODELING IN SINGARAJA CITY AND ITS SURROUNDING AREA

2019 ◽  
Author(s):  
Nyoman Arto Suprapto
Keyword(s):  
Land Use ◽  
Cellular Automata ◽  
Land Use Change ◽  
Urban Areas ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Geographic Information ◽  
Spatial Simulation ◽  
Land Use Change Modeling ◽  
The City

Singaraja is the second largest city after Denpasar in Bali. The magnitude of the potential of the region both trade and services, agriculture and tourism in Buleleng Regency has given a very broad impact not only on the economy but also the use of land. Economic development in the city of Singaraja cause some effects such as population growth, an increasing number of facilities (social, economic, health, and others), as well as changes in land use.Changes in land use have a serious impact on the environment in the city of Singaraja. The development of urban areas of Singaraja has given the excesses of increasing the land conversion. Suburb dominated by wetland agriculture has now turned into buildings to meet the needs of shelter, trade and services as well as urban utilities. This study was conducted by mean to determine how changes in land use from agricultural land into build up land during twelve years (period of 2002 - 2014) and the prediction of land use within the next 12 years (period of 2020 and 2026). Prediction of land use changes will be done using spatial simulation method which is integrating Cellular Automata (CA) and Geographic Information Systems (GIS) which analyzed based on land requirement, the driving variable of land use changes (population and road) and the inhabiting variable of land use change (slope steepness and rivers).Keywords : Land Use Change, Land Use Change Modeling, Celullar Automata, GIS

scholarly journals 3D Solar Potential in the Urban Environment: A Case Study in Lisbon

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3457 ◽  
Author(s):  
Miguel Centeno Brito ◽  
Paula Redweik ◽  
Cristina Catita ◽  
Sara Freitas ◽  
Miguel Santos
Keyword(s):  
Renewable Energy ◽  
Urban Environment ◽  
Urban Areas ◽  
Potential Model ◽  
Photovoltaic Performance ◽  
Policy Decision ◽  
3D Models ◽  
Lidar Data ◽  
The City

The assessment of solar potential in the urban environment is an important instrument for policy decision regarding renewable energy deployment in the city. This paper presents an experimentally validated 3D solar potential model for rooftops and facades from LIDAR data considering anisotropic diffuse irradiation. The data visualization is rendered in the ArcGIS platform using CityEngine to automatically generate 3D models from 2D geometries. The model is validated against summer and winter measurements of photovoltaic performance on a facade. A case study for two densely packed urban areas in Lisbon, Portugal, are presented. Facades are shown to increase the solar potential by 10 to 15%.

scholarly journals Prediction of Aboveground Biomass from Low-Density LiDAR Data: Validation over P. radiata Data from a Region North of Spain

Forests ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 819 ◽  
Author(s):  
Tojal ◽  
Bastarrika ◽  
Barret ◽  
Espeso ◽  
Lopez-Guede ◽  
...  
Keyword(s):  
Aboveground Biomass ◽  
Tree Height ◽  
National Forest Inventory ◽  
Biomass Estimation ◽  
Lidar Data ◽  
Low Density ◽  
Cloud Data ◽  
Public Data ◽  
The Government ◽  
North Of Spain

Estimation of forestry aboveground biomass (AGB) by means of aerial Light Detection and Ranging (LiDAR) data uses high-density point sampling data obtained in dedicated flights, which are often too costly for available research budgets. In this paper we exploit already existing public low-density LiDAR data obtained for other purposes, such as cartography. The challenge is to show that such low-density data allows accurate biomass estimation. We demonstrate the approach on data available from plantations of Pinus radiata in the Arratia-Nervión region, located in Biscay province located in the North of Spain. We use public data gathered from the low-density (0.5 pulse/m2) LiDAR flight conducted by the Basque Government in 2012 for cartographic production. We propose a linear regression model based on explanatory variables obtained from the LiDAR point cloud data. We calibrate the model using field data from the Fourth National Forest Inventory (NFI4), including the selection of the optimal model variables. The results revealed that the best model depends on two variables extracted from LiDAR data: One directly related with tree height and a second parameter with the canopy density. The model explained 80% of its variability with a standard error of 0.25 ton/ha in logarithmic units. We validate the predictions against the biomass measurements provided by the government institutions, obtaining a difference of 8%. The proposed approach would allow the exploitation of the periodic available low-density LiDAR data, collected with territorial and cartographic purposes, for a more frequent and less expensive control of the forestry biomass.

scholarly journals FOREST STEM VOLUME CALCULATION USING AIRBORNE LIDAR DATA

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 265-270
Author(s):  
I. Büyüksalih ◽  
S. Bayburt ◽  
M. Schardt ◽  
G. Büyüksalih
Keyword(s):  
Near Infrared ◽  
Tree Height ◽  
Airborne Lidar ◽  
Stem Volume ◽  
Lidar Data ◽  
Allometric Functions ◽  
Airborne Lidar Data ◽  
The City ◽  
Field Plots

Airborne LiDAR data have been collected for the city of Istanbul using Riegl laser scanner Q680i with 400&amp;thinsp;kHz and an average flight height of 600&amp;thinsp;m. The flight campaign was performed by a helicopter and covers an area of 5400&amp;thinsp;km<sup>2</sup>. According to a flight speed of 80 knot a point density of more than 16 points/m<sup>2</sup> and a laser footprint size of 30&amp;thinsp;cm could be achieved. As a result of bundle adjustment, in total, approximately 17,000 LAS files with the file size of 500&amp;thinsp;m by 700&amp;thinsp;m have been generated for the whole city. The main object classes Ground, Building, Vegetation (medium, high) were derived from these LAS files using the macros in Terrasolid software. The forest area under investigation is located northwest of the city of Istanbul, main tree species occurring in the test site are pine (pinus pinaster), oak (quercus) and beech (fagus). In total, 120 LAS tiles covering the investigation area have been analysed using the software IMPACT of Joanneum Research Forschungsgesellschaft, Graz, Austria. First of all, the digital terrain model (DTM) and the digital surface models (DSM) were imported and converted into a raster file from the original laser point clouds with a spatial resolution of 50&amp;thinsp;cm. Then, a normalized digital surface model (nDSM) was derived as the difference between DSM and the DTM. Tree top detection was performed by multi – resolution filter operations and tree crowns were segmented by a region growing algorithms develop specifically for this purpose. Breast Height Diameter (BHD) was calculated on the base of tree height and crown areas derived from image segmentation applying allometric functions found in literature. The assessment of stem volume was then calculated as a function of tree height and BHD. A comparison of timber volume estimated from the LiDAR data and field plots measured by the Forest Department of Istanbul showed R2 of 0.46. The low correlation might arise either from the low quality of the field plots or from the inadequacy of the allometric functions used for BHD and stem volume modelling. Further investigations therefore will concentrate both on improving the quality of field measurements and the adoption of the allometric functions to the specific site condition of the forests under investigation. Finally stand boundaries of the forest area made available by the forest department of Istanbul were superimposed to the LiDAR data and the single tree measurements aggregated to the stand level. <br><br> Aside from the LiDAR data, a Pleiades multispectral image characterized by four spectral bands (blue, green, red and near infrared) and a GSD of 2.8&amp;thinsp;m has been used for the classification of different tree species. For this purpose the near infrared band covering the spectral range of 0.75&amp;thinsp;μm to 0.90&amp;thinsp;μm has been utilized and the IMPACT software used.

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