scholarly journals Evaluation and Monitoring of Urban Public Greenspace Planning Using Landscape Metrics in Kunming

2021 ◽  
Vol 13 (7) ◽  
pp. 3704
Author(s):  
Min Liu ◽  
Xiaoma Li ◽  
Ding Song ◽  
Hui Zhai
Keyword(s):  
Google Earth ◽  
Living Standard ◽  
Visual Interpretation ◽  
Plan Implementation ◽  
Planning Decisions ◽  
Object Based ◽  
Urban Greenspaces ◽  
Evaluation And Monitoring ◽  
Interpretation Of Satellite Images

Urban greenspace planning plays a crucial role in improving the quality of human settlements and the living standard of citizens. Urban public greenspace (UPGS) is an important part of urban greenspaces. Existing literature rarely includes a scientific evaluation of greenspace plans (including of UPGS) and plan implementation effects. To bridge this gap, this study evaluated and monitored the UPGS plan enacted in 2010 in Kunming, China. Object-based image classification and visual interpretation of satellite images and Google Earth imagery were used to quantify the different periods of UPGS implementation. Six indicators and monitoring at four classic sites were applied to explore the change at two scales (overall scale and district scale) for monitoring the UPGS plan execution. The results showed that UPGS structure greatly improved after plan implementation. However, UPGS provision per capita has not reached the level of greenspace planning and the connectivity was poor. Significant implementation inequalities existed in each district and implementation has lagged behind schedule. This study contributes to a better understanding of greenspace planning and urban planning in general, which can help improve future planning and planning decisions.

scholarly journals DEFORESTATION MONITORING IN DIFFERENT BRAZILIAN BIOMES: CHALLENGES AND LESSONS

2020 ◽  
Vol IV-3/W2-2020 ◽  
pp. 47-52
Author(s):  
C. A. Almeida ◽  
D. M. Valeriano ◽  
L. Maurano ◽  
L. Vinhas ◽  
L. M. G. Fonseca ◽  
...  
Keyword(s):  
Satellite Images ◽  
Computational Technique ◽  
Native Vegetation ◽  
Annual Data ◽  
Visual Interpretation ◽  
Brazilian Government ◽  
New Challenges ◽  
Amazonian Forests ◽  
Interpretation Of Satellite Images

Abstract. Monitoring the conversion of native vegetation has challenged Brazilian government and scientists since the 1980s. In the case of the Amazonian forests, the Amazon Gross Deforestation Monitoring Project - PRODES has developed an effective methodology that provides consistent annual data on deforestation areas on a scale of 1:250,000, since 1988. In this article, we present some aspects of the evolution of this methodology, the key processes to produce accurate deforestation maps during the last 30 years and the new challenges that the Project would face. A central lesson is that no computational technique has, to date, been able to achieve the quality of deforestation maps produced by visual interpretation of satellite images and manual mapping.

scholarly journals Pixel- vs. Object-Based Landsat 8 Data Classification in Google Earth Engine Using Random Forest: The Case Study of Maiella National Park

2021 ◽  
Vol 13 (12) ◽  
pp. 2299
Author(s):  
Andrea Tassi ◽  
Daniela Gigante ◽  
Giuseppe Modica ◽  
Luciano Di Martino ◽  
Marco Vizzari
Keyword(s):  
Land Cover ◽  
National Park ◽  
Time Window ◽  
Central Italy ◽  
Google Earth ◽  
Data Cube ◽  
Landsat 8 ◽  
Change Analysis ◽  
Object Based ◽  
Google Earth Engine

With the general objective of producing a 2018–2020 Land Use/Land Cover (LULC) map of the Maiella National Park (central Italy), useful for a future long-term LULC change analysis, this research aimed to develop a Landsat 8 (L8) data composition and classification process using Google Earth Engine (GEE). In this process, we compared two pixel-based (PB) and two object-based (OB) approaches, assessing the advantages of integrating the textural information in the PB approach. Moreover, we tested the possibility of using the L8 panchromatic band to improve the segmentation step and the object’s textural analysis of the OB approach and produce a 15-m resolution LULC map. After selecting the best time window of the year to compose the base data cube, we applied a cloud-filtering and a topography-correction process on the 32 available L8 surface reflectance images. On this basis, we calculated five spectral indices, some of them on an interannual basis, to account for vegetation seasonality. We added an elevation, an aspect, a slope layer, and the 2018 CORINE Land Cover classification layer to improve the available information. We applied the Gray-Level Co-Occurrence Matrix (GLCM) algorithm to calculate the image’s textural information and, in the OB approaches, the Simple Non-Iterative Clustering (SNIC) algorithm for the image segmentation step. We performed an initial RF optimization process finding the optimal number of decision trees through out-of-bag error analysis. We randomly distributed 1200 ground truth points and used 70% to train the RF classifier and 30% for the validation phase. This subdivision was randomly and recursively redefined to evaluate the performance of the tested approaches more robustly. The OB approaches performed better than the PB ones when using the 15 m L8 panchromatic band, while the addition of textural information did not improve the PB approach. Using the panchromatic band within an OB approach, we produced a detailed, 15-m resolution LULC map of the study area.

scholarly journals Planning for the First and Last Mile: A Review of Practices at Selected Transit Agencies in the United States

2021 ◽  
Vol 13 (4) ◽  
pp. 2222
Author(s):  
Hossain Mohiuddin
Keyword(s):  
Los Angeles ◽  
Gap Analysis ◽  
The United States ◽  
Design Guidelines ◽  
Plan Implementation ◽  
Marginalized Communities ◽  
Transit Ridership ◽  
Last Mile ◽  
Transit Agencies

A transit trip involves travel to and from transit stops or stations. The quality of what are commonly known as first and last mile connections (regardless of their length) can have an important impact on transit ridership. Transit agencies throughout the world are developing innovative approaches to improving first and last mile connections, for example, by partnering with ride-hailing and other emerging mobility services. A small but growing number of transit agencies in the U.S. have adopted first and last mile (FLM) plans with the goal of increasing ridership. As this is a relatively new practice by transit agencies, a review of these plans can inform other transit agencies and assist them in preparing their own. Four FLM plans were selected from diverse geographic contexts for review: Los Angeles County Metropolitan Transportation Authority (LA Metro), Riverside (CA) Transit Agency (RTA), and Denver Regional Transit District (RTD), and City of Richmond, CA. Based on the literature, we developed a framework with an emphasis on transportation equity to examine these plans. We identified five common approaches to addressing the FLM issue: spatial gap analysis with a focus on socio-demographics and locational characteristics, incorporation of emerging mobility services, innovative funding approaches for plan implementation, equity and transportation remedies for marginalized communities, and development of pedestrian and bicycle infrastructures surrounding transit stations. Strategies in three of the plans are aligned with regional goals for emissions reductions. LA Metro and Riverside Transit incorporate detailed design guidelines for the improvement of transit stations. As these plans are still relatively new, it will take time to evaluate their impact on ridership and their communities’ overall transit experience.

scholarly journals Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at Plot Scale

2018 ◽  
Vol 10 (8) ◽  
pp. 1285 ◽  
Author(s):  
Reza Attarzadeh ◽  
Jalal Amini ◽  
Claudia Notarnicola ◽  
Felix Greifeneder
Keyword(s):  
Soil Moisture ◽  
Optical Data ◽  
Estimation Accuracy ◽  
Support Vector ◽  
Practical Applications ◽  
Initial Stage ◽  
Object Based ◽  
Single Polarization ◽  
Selection Of

This paper presents an approach for retrieval of soil moisture content (SMC) by coupling single polarization C-band synthetic aperture radar (SAR) and optical data at the plot scale in vegetated areas. The study was carried out at five different sites with dominant vegetation cover located in Kenya. In the initial stage of the process, different features are extracted from single polarization mode (VV polarization) SAR and optical data. Subsequently, proper selection of the relevant features is conducted on the extracted features. An advanced state-of-the-art machine learning regression approach, the support vector regression (SVR) technique, is used to retrieve soil moisture. This paper takes a new look at soil moisture retrieval in vegetated areas considering the needs of practical applications. In this context, we tried to work at the object level instead of the pixel level. Accordingly, a group of pixels (an image object) represents the reality of the land cover at the plot scale. Three approaches, a pixel-based approach, an object-based approach, and a combination of pixel- and object-based approaches, were used to estimate soil moisture. The results show that the combined approach outperforms the other approaches in terms of estimation accuracy (4.94% and 0.89 compared to 6.41% and 0.62 in terms of root mean square error (RMSE) and R2), flexibility on retrieving the level of soil moisture, and better quality of visual representation of the SMC map.

AN EXPLORATION OF THE RELATIONSHIP BETWEEN THE QUALITY OF PUBLIC GOVERNANCE AND INCOME INEQUALITY: A CASE STUDY OF VIETNAM

2021 ◽  
pp. 1-15
Author(s):  
PHUC VAN PHAN
Keyword(s):  
Income Inequality ◽  
Local Governance ◽  
Low Cost ◽  
Generalized Method Of Moments ◽  
Dynamic Panel Data ◽  
Living Standard ◽  
Public Governance ◽  
The Relationship

Public governance and income inequality relationship is complex and debatable. This paper examines the extent to which the quality of local governance affects inequality in Vietnam spanning the 2006–2016 period. I apply a generalized method of moments (GMM) estimators to a dynamic panel data extracted from the Vietnam’s provincial competitiveness index and the Vietnam household living standard surveys. The findings are that there is a positive inequality — corruption link but no statistically significant correlation coefficient between the overall level of governance and income disparity. The study, therefore, suggests that the Vietnamese Government at all levels should consider both more effective legal practices and economic low-cost solutions to mitigate corruption.

Kajian Kualitas Permukiman Kawasan Pesisir Kecamatan Marobo Kabupaten Muna

2021 ◽  
Vol 5 (2) ◽  
pp. 149
Author(s):  
Halija Halija ◽  
Jufri Karim ◽  
Sawaludin Sawaludin
Keyword(s):  
Physical Condition ◽  
Coastal Area ◽  
Residential Buildings ◽  
Residential Building ◽  
Earth Satellite ◽  
Google Earth ◽  
Wall Material ◽  
Floor Area ◽  
Medium Quality

Abstrak: Penataan ruang kawasan pesisir harus dipandang sebagai upaya dalam peningkatan kualitas kawasan fisik dan kesejahteraan masyarakat.Permasalahan dalam penelitian ini, yaitu tidak berfungsinya drainase secara optimal belum terdapatnya sarana mandi, cuci, kakus (MCK) dan kondisi faktor fisik rumah yang masih berstruktur kayu dan semi permanan. Tujuan dari penelitian ini, yaitu: (1) menganalisis kondisi fisik permukiman kawasan pesisir; (2) menganalisis kualitas permukiman kawasan pesisir dan merumuskan strategi pemecahan masalah permukiman kawasan pesisir Kecamatan Marobo Kabupaten Muna. Metode penelitian ini, yaitu: (1) kondisi fisik permukiman diketahui dengan melakukan interpertasi citra satelit Google Earth:(2)kualitas permukimandiketahui denganpendekatan keruangan dengan menggunakan Sistem Informasi Geografi pada aplikasi ArcGIS dengan melakukan teknik analisis scoring. Hasil penelitian ini menunjukkan bahwa: (1)nilai kelayakan bangunan rumah hunian Desa Marobo, yaitu 70% dengan luas lantai >7,2, skor  5 bisa di kategorikan cukup luas, kemudian kelurahan Paroha 50 %, dengan luas lantai >7,2 skor  3,  Kelurahan Wadolau nilai kelayakan bangunan rumah hunian, yaitu 30% dengan luas lantai >7,2 skor  2  dan terakhir Kelurahan Tapi-Tapi nilai kelayakan bangunan rumah hunian, yaitu <10% dengan luas lantai>7,2 skor  1, sehingga bisa di kategorikan cukup kecil/sempit; (2) permukiman penduduk di Pesisir Desa Tapi-Tapi, Desa Wadolau, dan Desa Marobo didominasi oleh rumah nelayan, dengan luas pekarangan dan luas rumah tinggal cukup kecil/sempit.  Kondisi fisik rumah tinggal penduduk di Kecamatan Marobo termasuk kategori semipermanen yang tercermin dari jenis bahan dinding rumah yang mayoritas terbuat dari  papan kayu berkualitas sedang.Kata kunci: kondisi fisik, kualitas permukiman, kawasan pesisirAbstract: Coastal spatial planning must be seen as an effort to improve the quality of physical areas and the welfare of the community. The problem in this study are the drainage does not function optimally, among others there are no facilities for bathing, washing, latrines and the physical condition of the house which is still structured in wood and semi-permanent. The purpose of this study are: (1) to analyze the physical condition of the coastal area settlement in Marobo District Muna Regency; (2) to analyze the quality of coastal area settlements and formulate strategies for solving the problem of coastal area settlements in Marobo District Muna Regency. The research methods are: (1) the physical condition of the settlement is known by interpreting Google Earth satellite imagery; (2) settlement quality is known by spatial approach using Geographic Information Systems with ArcGIS by conducting a scoring analysis technique. The results of this study are: (1)the feasibility value of Marobo Village residential building is 70% with a floor area >7,2 score 5 can be categorized quite broadly, Paroha Village 50%, with a floor area >7,2 score 3 Wadolau Village the feasibility value of residential building is 30% with a floor area >7,2, score 2 and lastly the Tapi-Tapi Village feasibility value of residential buildings is <10% with a floor area >7,2 score 1 so that it can be categorized quite small/narrow; (2) the residential settlements in the Tapi-Tapi Village, Wadolau Village and Marobo Village are dominated by fishermen's houses, with a large yard area and a small/narrow residential area. The physical condition of resident houses in Marobo District belongs to the semi-permanent category, which is reflected in the type of wall material of the house which is mostly made of medium quality wood plasterKeywords: physical condition, quality of settlements, coastal area

scholarly journals Characterizing the Spatial and Temporal Availability of Very High Resolution Satellite Imagery in Google Earth and Microsoft Bing Maps as a Source of Reference Data

Land ◽  
2018 ◽  
Vol 7 (4) ◽  
pp. 118 ◽  
Author(s):  
Myroslava Lesiv ◽  
Linda See ◽  
Juan Laso Bayas ◽  
Tobias Sturn ◽  
Dmitry Schepaschenko ◽  
...  
Keyword(s):  
High Resolution ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Reference Data ◽  
Temporal Distribution ◽  
Google Earth ◽  
Training Data ◽  
Visual Interpretation ◽  
The Usa ◽  
Very High

Very high resolution (VHR) satellite imagery from Google Earth and Microsoft Bing Maps is increasingly being used in a variety of applications from computer sciences to arts and humanities. In the field of remote sensing, one use of this imagery is to create reference data sets through visual interpretation, e.g., to complement existing training data or to aid in the validation of land-cover products. Through new applications such as Collect Earth, this imagery is also being used for monitoring purposes in the form of statistical surveys obtained through visual interpretation. However, little is known about where VHR satellite imagery exists globally or the dates of the imagery. Here we present a global overview of the spatial and temporal distribution of VHR satellite imagery in Google Earth and Microsoft Bing Maps. The results show an uneven availability globally, with biases in certain areas such as the USA, Europe and India, and with clear discontinuities at political borders. We also show that the availability of VHR imagery is currently not adequate for monitoring protected areas and deforestation, but is better suited for monitoring changes in cropland or urban areas using visual interpretation.

scholarly journals X-rays Image reconstruction using Proximal Algorithm and adapted TV Regularization

2021 ◽  
Vol 348 ◽  
pp. 01011
Author(s):  
Aicha Allag ◽  
Redouane Drai ◽  
Tarek Boutkedjirt ◽  
Abdessalam Benammar ◽  
Wahiba Djerir
Keyword(s):  
Structural Information ◽  
X Rays ◽  
Reconstruction Algorithms ◽  
Reconstruction Problem ◽  
Tv Regularization ◽  
Object Based ◽  
Suggested Technique ◽  
Reconstruction Image ◽  
Ill Posed

Computed tomography (CT) aims to reconstruct an internal distribution of an object based on projection measurements. In the case of a limited number of projections, the reconstruction problem becomes significantly ill-posed. Practically, reconstruction algorithms play a crucial role in overcoming this problem. In the case of missing or incomplete data, and in order to improve the quality of the reconstruction image, the choice of a sparse regularisation by adding l1 norm is needed. The reconstruction problem is then based on using proximal operators. We are interested in the Douglas-Rachford method and employ total variation (TV) regularization. An efficient technique based on these concepts is proposed in this study. The primary goal is to achieve high-quality reconstructed images in terms of PSNR parameter and relative error. The numerical simulation results demonstrate that the suggested technique minimizes noise and artifacts while preserving structural information. The results are encouraging and indicate the effectiveness of the proposed strategy.

scholarly journals A Comparison of Methods for Determining Forest Composition from High-Spatial-Resolution Remotely Sensed Imagery

Forests ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1290
Author(s):  
Benjamin T. Fraser ◽  
Russell G. Congalton
Keyword(s):  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Remotely Sensed ◽  
Local Scale ◽  
Google Earth ◽  
Forest Composition ◽  
Visual Interpretation ◽  
Individual Tree ◽  
Remotely Sensed Imagery ◽  
Composition Classes

Remotely sensed imagery has been used to support forest ecology and management for decades. In modern times, the propagation of high-spatial-resolution image analysis techniques and automated workflows have further strengthened this synergy, leading to the inquiry into more complex, local-scale, ecosystem characteristics. To appropriately inform decisions in forestry ecology and management, the most reliable and efficient methods should be adopted. For this reason, our research compares visual interpretation to digital (automated) processing for forest plot composition and individual tree identification. During this investigation, we qualitatively and quantitatively evaluated the process of classifying species groups within complex, mixed-species forests in New England. This analysis included a comparison of three high-resolution remotely sensed imagery sources: Google Earth, National Agriculture Imagery Program (NAIP) imagery, and unmanned aerial system (UAS) imagery. We discovered that, although the level of detail afforded by the UAS imagery spatial resolution (3.02 cm average pixel size) improved the visual interpretation results (7.87–9.59%), the highest thematic accuracy was still only 54.44% for the generalized composition groups. Our qualitative analysis of the uncertainty for visually interpreting different composition classes revealed the persistence of mislabeled hardwood compositions (including an early successional class) and an inability to consistently differentiate between ‘pure’ and ‘mixed’ stands. The results of digitally classifying the same forest compositions produced a higher level of accuracy for both detecting individual trees (93.9%) and labeling them (59.62–70.48%) using machine learning algorithms including classification and regression trees, random forest, and support vector machines. These results indicate that digital, automated, classification produced an increase in overall accuracy of 16.04% over visual interpretation for generalized forest composition classes. Other studies, which incorporate multitemporal, multispectral, or data fusion approaches provide evidence for further widening this gap. Further refinement of the methods for individual tree detection, delineation, and classification should be developed for structurally and compositionally complex forests to supplement the critical deficiency in local-scale forest information around the world.

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