scholarly journals Comparison of Landscape Metrics for Three Different Level Land Cover/Land Use Maps

2018 ◽  
Vol 7 (10) ◽  
pp. 408 ◽  
Author(s):  
Elif Sertel ◽  
Raziye Topaloğlu ◽  
Betül Şallı ◽  
Irmak Yay Algan ◽  
Gül Aksu
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Landscape Metrics ◽  
Observation Data ◽  
Landscape Characteristics ◽  
Object Based ◽  
Level 3 ◽  
Level 1 ◽  
The Impact ◽  
Level 2

This research aims to investigate how different landscape metrics are affected by the enhancement of the thematic classes in land cover/land use (LC/LU) maps. For this aim, three different LC/LU maps based on three different levels of CORINE (Coordination of Information on The Environment) nomenclature were created for the selected study area using GEOBIA (Geographic Object Based Image Analysis) techniques. First, second and third level LC/LU maps of the study area have five, thirteen and twenty-seven hierarchical thematic classes, respectively. High-resolution Spot 7 images with 1.5 m spatial resolution were used as the main Earth Observation data to create LC/LU maps. Additional geospatial data from open sources (OpenStreetMap and Wikimapia) were also integrated to the classification in order to identify some of the 2nd and 3rd level LC/LU classes. Classification procedure was initially conducted for Level 3 classes in which we developed decision trees to be used in object-based classification. Afterwards, Level 3 classes were merged to create Level 2 LC/LU map and then Level 2 classes were merged to create the Level 1 LC/LU map according to CORINE nomenclature. The accuracy of Level 1, Level 2, Level 3 maps are calculated as; 93.50%, 89.00%, 85.50% respectively. At the last stage, several landscape metrics such as Number of Patch (NP), Edge Density (ED), Largest Patch Index (LPI), Euclidean Nearest Neighbor Distance (ENN), Splitting Index (SPLIT) and Aggregation Index (AI) metrics and others were calculated for different level LC/LU maps and landscape metrics values were compared to analyze the impact of changing thematic details on landscape metrics. Our results show that, increasing the thematic detail allows landscape characteristics to be defined more precisely and ensure comprehensive assessment of cause and effect relationships between classes.

scholarly journals Integrating structure and function: mapping the hierarchical spatial heterogeneity of urban landscapes

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Yuguo Qian ◽  
Weiqi Zhou ◽  
Steward T. A. Pickett ◽  
Wenjuan Yu ◽  
Dingpeng Xiong ◽  
...  
Keyword(s):  
Land Cover ◽  
Spatial Heterogeneity ◽  
Urban Ecosystem ◽  
Tree Canopy ◽  
Urban Landscapes ◽  
Shenzhen City ◽  
Object Based ◽  
Level 3 ◽  
Industrial Zones ◽  
Level 2

Abstract Background Cities are social-ecological systems characterized by remarkably high spatial and temporal heterogeneity, which are closely related to myriad urban problems. However, the tools to map and quantify this heterogeneity are lacking. We here developed a new three-level classification scheme, by considering ecosystem types (level 1), urban function zones (level 2), and land cover elements (level 3), to map and quantify the hierarchical spatial heterogeneity of urban landscapes. Methods We applied the scheme using an object-based approach for classification using very high spatial resolution imagery and a vector layer of building location and characteristics. We used a top-down classification procedure by conducting the classification in the order of ecosystem types, function zones, and land cover elements. The classification of the lower level was based on the results of the higher level. We used an object-based methodology to carry out the three-level classification. Results We found that the urban ecosystem type accounted for 45.3% of the land within the Shenzhen city administrative boundary. Within the urban ecosystem type, residential and industrial zones were the main zones, accounting for 38.4% and 33.8%, respectively. Tree canopy was the dominant element in Shenzhen city, accounting for 55.6% over all ecosystem types, which includes agricultural and forest. However, in the urban ecosystem type, the proportion of tree canopy was only 22.6% because most trees were distributed in the forest ecosystem type. The proportion of trees was 23.2% in industrial zones, 2.2% higher than that in residential zones. That information “hidden” in the usual statistical summaries scaled to the entire administrative unit of Shenzhen has great potential for improving urban management. Conclusions This paper has taken the theoretical understanding of urban spatial heterogeneity and used it to generate a classification scheme that exploits remotely sensed imagery, infrastructural data available at a municipal level, and object-based spatial analysis. For effective planning and management, the hierarchical levels of landscape classification (level 1), the analysis of use and cover by urban zones (level 2), and the fundamental elements of land cover (level 3), each exposes different respects relevant to city plans and management.

scholarly journals Assessing a Prototype Database for Comprehensive Global Aquatic Land Cover Mapping

2021 ◽  
Vol 13 (19) ◽  
pp. 4012
Author(s):  
Panpan Xu ◽  
Nandin-Erdene Tsendbazar ◽  
Martin Herold ◽  
Jan G. P. W. Clevers
Keyword(s):  
Land Cover ◽  
Life Form ◽  
Land Cover Mapping ◽  
Commission Errors ◽  
Multiple User ◽  
Level 3 ◽  
Level 1 ◽  
Level 2 ◽  
Global Datasets ◽  
Flooded Areas

The monitoring of Global Aquatic Land Cover (GALC) plays an essential role in protecting and restoring water-related ecosystems. Although many GALC datasets have been created before, a uniform and comprehensive GALC dataset is lacking to meet multiple user needs. This study aims to assess the effectiveness of using existing global datasets to develop a comprehensive and user-oriented GALC database and identify the gaps of current datasets in GALC mapping. Eight global datasets were reframed to construct a three-level (i.e., from general to detailed) prototype database for 2015, conforming with the United Nations Land Cover Classification System (LCCS)-based GALC characterization framework. An independent validation was done, and the overall results show some limitations of current datasets in comprehensive GALC mapping. The Level-1 map had considerable commission errors in delineating the general GALC distribution. The Level-2 maps were good at characterizing permanently flooded areas and natural aquatic types, while accuracies were poor in the mapping of temporarily flooded and waterlogged areas as well as artificial aquatic types; vegetated aquatic areas were also underestimated. The Level-3 maps were not sufficient in characterizing the detailed life form types (e.g., trees, shrubs) for aquatic land cover. However, the prototype GALC database is flexible to derive user-specific maps and has important values to aquatic ecosystem management. With the evolving earth observation opportunities, limitations in the current GALC characterization can be addressed in the future.

scholarly journals PEMETAAN ZONA GEOMORFOLOGI DAN HABITAT BENTIK DI PULAU KOTOK BESAR MENGGUNAKAN KLASIFIKASI BERBASIS OBJEK

2018 ◽  
Vol 8 (2) ◽  
pp. 209-219
Author(s):  
Ike Dori Candra ◽  
Vicentius P. Siregar ◽  
Syamsul B. Agus
Keyword(s):  
Image Analysis ◽  
Reef Flat ◽  
Reef Slope ◽  
Reef Crest ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Level 3 ◽  
Level 1 ◽  
Multiresolution Segmentation ◽  
Level 2

Penelitian ini menggunakan citra satelit resolusi tinggi worldview-2 akuisisi 5 Oktober 2013. Tujuan dari penelitian ini adalah untuk mengkaji kemampuan citra satelit resolusi tinggi worldview-2 dalam memetakan zona geomorfologi dan habitat bentik perairan dangkal di Pulau Kotok Besar. Metode yang digunakan adalah metode klasifikasi Object Based Image Analysis (OBIA). Metode ini mampu mendefinisikan kelas-kelas objek berdasarkan aspek spektral dan spasial. Segmentasi citra menggunakan algoritma multiresolution segmentation dengan parameter skala yang berbeda untuk setiap level, baik level 1, level 2 dan level 3. Shape dan compactness juga disesuaikan untuk setiap level. Penentuan kelas pada level 1 menghasilkan tiga kelas yaitu daratan, perairan dangkal dan perairan dalam. Penentuan kelas pada level 2 untuk zona geomorfologi menghasilkan tiga kelas yaitu reef flat, reef crest dan reef slope. Klasifikasi habitat bentik pada level 3 menghasilkan 7 kelas dengan akurasi keseluruhan yaitu 66.40 %.

Fair value's effects on closed-end funds' discounts and premia: is level 3 the sole perpetrator?

2020 ◽  
Vol 46 (8) ◽  
pp. 1001-1022 ◽  
Author(s):  
Steve Fortin ◽  
Ahmad Hammami ◽  
Michel Magnan
Keyword(s):  
Relevant Information ◽  
Fair Value ◽  
Content Type ◽  
Level 3 ◽  
Closed End Funds ◽  
Level 1 ◽  
Value Hierarchy ◽  
Valuation Uncertainty ◽  
The Impact ◽  
Level 2

PurposeThis study examines the long-term link between fair valuation uncertainty and discounts/premia in closed-end funds. This study argues that, in exploring the close-end funds puzzle, prior research generally omits to consider the uncertainty surrounding the measurement of funds' financial disclosure, as reflected in the fair value hierarchy, when investment specialty differs across funds.Design/methodology/approachRegressions were employed to explore how the fair value hierarchy affects closed-end funds' discounts/premia when investment specialty differs. The authors also examine the effects pre- and post-2012 to explore if that relationship changes due to the additional disclosure requirements enacted at the end of 2011.FindingsThe authors find that the three levels of the fair value hierarchy have effects that vary according to a fund's specialty. For equity specialized funds, Level 3 significantly increases discounts and decreases premia, suggesting the impact of valuation uncertainty that underlies Level 3 estimates; this relationship disappears (decreases in severity) for premia (discount) experiencing funds post-2012. In contrast, Level 1 and Level 2 do not have any significant effect on discounts or premia except that post-2012, Level 2 begins to display discount decreasing effects. For bond specialized funds, no significant association was noted between premia and any of the fair value levels except that post-2012, Level 3 begins to display premium increasing effects. However, results are different for discounts. The authors note that Level 1 valuations significantly increase discounts, but only post-2012; Level 2 valuations significantly decrease discounts (pre- and post-2012), consistent with such estimates incorporating unique and relevant information; and Level 3 valuations do not have a significant effect on discounts.Originality/valueThe results of this study revisit prior evidence and indicate that results about the effects of fair value measurement and the closed-end funds' puzzle are sensitive to the period length being considered and the investment specialty of the fund. The authors also note that additional disclosure regarding Level 3 valuation inputs decreases market concern for valuation uncertainty and increases the liquidity benefits of investing in Level 3 carrying funds.

Managerial ability and fair value accounting: evidence from nonfinancial firms

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wray Bradley ◽  
Li Sun
Keyword(s):  
Design Methodology ◽  
Fair Value ◽  
Managerial Ability ◽  
Fair Value Accounting ◽  
Content Type ◽  
Level 3 ◽  
Level 1 ◽  
The Impact ◽  
Nonfinancial Firms ◽  
Level 2

Purpose The purpose of this study is to examine the relation between managerial ability and fair value inputs (measured as fair value intensity) for nonfinancial firms. Design/methodology/approach This study uses regression analysis to investigate the impact of managerial ability on the level of fair value inputs. Findings This study finds significant and positive relations between managerial ability and use of Level 1 and Level 2 fair value inputs. On the other hand, this study finds an insignificant relation between managerial ability and Level 3 inputs. Originality/value The findings contribute to two research streams. To the best of the author’s knowledge, this is perhaps the first study that directly examines the link between managerial ability and fair value inputs.

Illiquid Assets and the Opacity Discount in Banks’ Valuation

2021 ◽  
Author(s):  
Giulio Anselmi
Keyword(s):  
Negative Relationship ◽  
Relative Weight ◽  
Fair Value ◽  
Book Value ◽  
Valuation Technique ◽  
Level 3 ◽  
Level 1 ◽  
The Impact ◽  
Level 2 ◽  
Illiquid Assets

The paper investigates the impact of fair value accounting for illiquid assets (so-called ‘Level 2’ and ‘Level 3’ assets by accounting rules) on banks’ valuation and focuses on the change in relative weight of Level 3 (the most opaque and illiquid assets) with respect to Level 2 assets. The boundary between Level 3 and Level 2 assets is blurred and less clear than the one between Level 1 and Level 2 assets. Such unclear borderline entails corporate governance issues and provides room for opportunistic behavior by managers to opt for less transparent instruments. The paper proposes the change in Level 3-to-Level 2 assets ratio as a new measure to capture deviations in the opacity of bank assets and suggests a negative relationship between this ratio and bank’s price-to-book value. The rationale behind this relationship is that market participants interpret growth in Level 3-to-Level 2 assets ratio as an increase in bank’s opacity, since Level 3 assets might be as illiquid as Level 2 assets with the benefit of a less transparent model-based valuation technique. Based on a sample of 33 European banks from 2009 to 2018, I find that an increase of 100[Formula: see text]bps in Level 3-to-Level 2 assets ratio is linked to a decrease of about 74[Formula: see text]bps in the price-to-book value. Results are robust for different measures of firm relative valuation and using a different measure of illiquidity in fair value assets holdings (Level 2-to-Level 1 assets ratio).

Value Relevance of FAS No. 157 Fair Value Hierarchy Information and the Impact of Corporate Governance Mechanisms

2010 ◽  
Vol 85 (4) ◽  
pp. 1375-1410 ◽  
Author(s):  
Chang Joon Song ◽  
Wayne B. Thomas ◽  
Han Yi
Keyword(s):  
Corporate Governance ◽  
Value Relevance ◽  
Fair Value ◽  
Governance Mechanisms ◽  
Corporate Governance Mechanisms ◽  
Level 3 ◽  
Level 1 ◽  
The Impact ◽  
Fair Value Measurements ◽  
Level 2

ABSTRACT: Statement of Financial Accounting Standards No. 157 (FAS No. 157), Fair Value Measurements, prioritizes the source of information used in fair value measurements into three levels: (1) Level 1 (observable inputs from quoted prices in active markets), (2) Level 2 (indirectly observable inputs from quoted prices of comparable items in active markets, identical items in inactive markets, or other market-related information), and (3) Level 3 (unobservable, firm-generated inputs). Using quarterly reports of banking firms in 2008, we find that the value relevance of Level 1 and Level 2 fair values is greater than the value relevance of Level 3 fair values. In addition, we find evidence that the value relevance of fair values (especially Level 3 fair values) is greater for firms with strong corporate governance. Overall, our results support the relevance of fair value measurements under FAS No. 157, but weaker corporate governance mechanisms may reduce the relevance of these measures.

scholarly journals Implementasi Proses Bisnis Dalam Upaya Penerapan Green Hospital

2017 ◽  
Vol 18 (2) ◽  
pp. 149
Author(s):  
. Sofiyanurriyanti
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Life Cycle Assessment ◽  
Damage Assessment ◽  
Fossil Fuel ◽  
System Quality ◽  
Level 3 ◽  
Single Score ◽  
Level 1 ◽  
Level 2

Rumah sakit merupakan institusi pelayanan kesehatan yang memberikan jasa pelayanan kesehatan untuk pelayanan umum, tempat berkumpulnya orang sakit maupun sehat. Lingkungan rumah sakit merupakan salah satu aspek yang juga perlu diperhatikan dan juga perlu dikelola dengan baik. Alur aktivitas proses bisnis merupakan kegiatan layanan utama terhadap penanganan rawat inap pasien IDEF0 level 1, proses bisnis tahap verifikasi dan registrasi level 2, menerima pasein dan memberikan tindakan medis level 3, rekomendasi rujuk rawat inap atau rujuk ke instalasi level 4, kegiatan operasional level 5 dan sampai pasien keluar rumah sakit level 6. Salah satu upaya pendekatan untuk mendukung pengelolaan lingkungan yang sehat, bersih dan ramah lingkungan adalah green hospital. Penerapan green hospital ini mencakup lingkungan yang berwawasan lingkungan hijau, efisiensi penggunaan air, energi listrik, penggunaan bahan material yang baik serta pengurangan limbah. Evaluasi dampak lingkungan dirumah sakit terdapat ada lima jenis kategori yaitu limbah medis, limbah non medis, limbah medis tajam, penggunaan air dan penggunaan listrik sedangkan untuk pengolahan data menggunakan software simapro. Penilaiaan dampak lingkungan ada beberapa langkah meliputi characteristization, damage assessment, normalization, weighting dan single score. Metode yang digunakan berdasarkan pada Eco Indikator 99 beberapa dampak lingkungan meliputi carcinogens, respiratory organics, climate change, radiation, ozone layaer, ecotoxity, acidification/ euthrophication, land use, minerals, dan fossil fuel. Sedangkan untuk menilai dampak lingkungan pada limbah dapat dilihat dari hasil life cycle assessment berdasarkan characterization, normalization weighting dan single score.dampak lingkungan yang dihasilkan dirumah sakit yang mempengaruhi human health sebesar 0.153209 Pt, eco system quality sebesar 0.178514 Pt, dan resources 0.359308 Pt.

EVALUASI PELATIHAN DI PT. PUPUK KUJANG CIKAMPEK

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Lania Muharsih ◽  
Ratih Saraswati
Keyword(s):  
Training Evaluation ◽  
Work Productivity ◽  
Learning Behavior ◽  
Level 3 ◽  
Level 1 ◽  
Four Levels ◽  
A Company ◽  
Level 2 ◽  
Evaluation Sheet ◽  
Assessment Factor

This study aims to determine the training evaluation at PT. Kujang Fertilizer. PT. Pupuk Kujang is a company engaged in the field of petrochemicals. Evaluation sheet of PT. Fertilizer Kujang is made based on Kirkpatrick's theory which consists of four levels of evaluation, namely reaction, learning, behavior, and results. At level 1, namely reaction, in the evaluation sheet is in accordance with the theory of Kirkpatrick, at level 2 that is learning should be held pretest and posttest but only made scale. At level 3, behavior, according to theory, but on assessment factor number 3, quantity and work productivity should not need to be included because they are included in level 4. At level 4, that is the result, here is still lacking to get a picture of the results of the training that has been carried out because only based on answers from superiors without evidence of any documents.   Keywords: Training Evaluation, Kirkpatrick Theory.    Penelitian ini bertujuan mengetahui evaluasi training di PT. Pupuk Kujang. PT. Pupuk Kujang merupakan perusahaan yang bergerak di bidang petrokimia. Lembar evaluasi PT. Pupuk Kujang dibuat berdasarkan teori Kirkpatrick yang terdiri dari empat level evaluasi, yaitu reaksi, learning, behavior, dan hasil. Pada level 1 yaitu reaksi, di lembar evaluasi tersebut sudah sesuai dengan teori dari Kirkpatrick, pada level 2 yaitu learning seharusnya diadakan pretest dan posttest namun hanya dibuatkan skala. Pada level 3 yaitu behavior, sudah sesuai teori namun pada faktor penilaian nomor 3 kuantitas dan produktivitas kerja semestinya tidak perlu dimasukkan karena sudah termasuk ke dalam level 4. Pada level 4 yaitu hasil, disini masih sangat kurang untuk mendapatkan gambaran hasil dari pelatihan yang sudah dilaksanakan karena hanya berdasarkan dari jawaban atasan tanpa bukti dokumen apapun.   Kata kunci: Evaluasi Pelatihan, Teori Kirkpatrick.

scholarly journals An Atmospheric Visibility Grading Method Based on Ensemble Learning and Stochastic Weight Average

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 869
Author(s):  
Xiuguo Zou ◽  
Jiahong Wu ◽  
Zhibin Cao ◽  
Yan Qian ◽  
Shixiu Zhang ◽  
...  
Keyword(s):  
Ensemble Learning ◽  
Traffic Accidents ◽  
Feature Sets ◽  
Atmospheric Visibility ◽  
Average Accuracy ◽  
Level 3 ◽  
Visual Characteristics ◽  
Level 1 ◽  
Grading Model ◽  
Level 2

In order to adequately characterize the visual characteristics of atmospheric visibility and overcome the disadvantages of the traditional atmospheric visibility measurement method with significant dependence on preset reference objects, high cost, and complicated steps, this paper proposed an ensemble learning method for atmospheric visibility grading based on deep neural network and stochastic weight averaging. An experiment was conducted using the scene of an expressway, and three visibility levels were set, i.e., Level 1, Level 2, and Level 3. Firstly, the EfficientNet was transferred to extract the abstract features of the images. Then, training and grading were performed on the feature sets through the SoftMax regression model. Subsequently, the feature sets were ensembled using the method of stochastic weight averaging to obtain the atmospheric visibility grading model. The obtained datasets were input into the grading model and tested. The grading model classified the results into three categories, with the grading accuracy being 95.00%, 89.45%, and 90.91%, respectively, and the average accuracy of 91.79%. The results obtained by the proposed method were compared with those obtained by the existing methods, and the proposed method showed better performance than those of other methods. This method can be used to classify the atmospheric visibility of traffic and reduce the incidence of traffic accidents caused by atmospheric visibility.

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