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Jones, K. Bruce; Heggem, Daniel T.; Wade, Timothy G.; Neale, Anne C.; Ebert, Donald W.; Nash, Maliha S.; Mehaffey, Megan; Goodman, Iris A.; Hermann, Karl A.; Selle, Anthony R.; Bolgrien, David W.; Augustine, Scott; Pedersen, Joel A.; Lin, Cindy J.; Viger, J. Max; Chiang, Dean; Zhong, Yehong; Baker, Joan P.; Remortel, R.D. Van

doi:10.1023/a:1006448400047

Cited by 34 publications

(3 citation statements)

References 49 publications

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“…A common derivative from high resolution DEM data is topographic position index (TPI). TPI is a measure of the difference between the elevation value of a cell and the average elevation of nearby (neighboring) cells (within a defined radius) [34][35][36][37]. A positive value indicates higher elevation than its surrounding, whereas negative indicates it is lower.…”

Section: Airborne Lidar Processingmentioning

confidence: 99%

SAR and Lidar Temporal Data Fusion Approaches to Boreal Wetland Ecosystem Monitoring

et al. 2019

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The objective of this study was to develop a decision-based methodology, focused on data fusion for wetland classification based on surface water hydroperiod and associated riparian (transitional area between aquatic and upland zones) vegetation community attributes. Multi-temporal, multi-mode data were examined from airborne Lidar (Teledyne Optech, Inc., Toronto, ON, Canada, Titan), synthetic aperture radar (Radarsat-2, single and quad polarization), and optical (SPOT) sensors with near-coincident acquisition dates. Results were compared with 31 field measurement points for six wetlands at riparian transition zones and surface water extents in the Utikuma Regional Study Area (URSA). The methodology was repeated in the Peace-Athabasca Delta (PAD) to determine the transferability of the methods to other boreal environments. Water mask frequency analysis showed accuracies of 93% to 97%, and kappa values of 0.8–0.9 when compared to optical data. Concordance results comparing the semi-permanent/permanent hydroperiod between 2015 and 2016 were found to be 98% similar, suggesting little change in wetland surface water extent between these two years. The results illustrate that the decision-based methodology and data fusion could be applied to a wide range of boreal wetland types and, so far, is not geographically limited. This provides a platform for land use permitting, reclamation monitoring, and wetland regulation in a region of rapid development and uncertainty due to climate change. The methodology offers an innovative time series-based boreal wetland classification approach using data fusion of multiple remote sensing data sources.

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Section: Airborne Lidar Processingmentioning

confidence: 99%

SAR and Lidar Temporal Data Fusion Approaches to Boreal Wetland Ecosystem Monitoring

et al. 2019

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“…The metrics included number of patches, patch density, largest patch index, landscape shape index, mean perimeter to area ratio and mean Euclidean distance of the patches. These were chosen based on the ease of their interpretation, their relevance and frequency of use in the literature (Bruce Jones et al, 2000;Hernandez et al, 2003;Li et al, 2005;Richert et al, 2007;Bianchin et al, 2011).…”

Section: Assessment Of Runoff Volume and Landscape Metricsmentioning

confidence: 99%

ulating Hydrologic Impacts of Urban Growth Using SLEUTH, Multi Criteria Evaluation and Runoff Modeling

Mahiny

Clarke

2013

J ENV INFORM

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Research on the sustainability of future urban environments has shown not only the value of simulation modeling, but also the strength of coupling their forecasts together into loosely integrated models. In this research we propose a way to improve modeling of urban futures by using enhanced land use change modeling as an input to a hydrological model. Our forecasts of hydrologic impacts are based on the L-THIA model, but this model is sensitive in turn to the land uses associated with urbanization, especially impervious surfaces and other urban uses. In order to improve the performance of the SLEUTH land use/cover change model, we modified one of that model's inputs using multi-criteria evaluation (MCE). The data basis for the modeling used land cover classes mapped for the years 1987, 1992, 2000 and 2005 in the Gorgan Township of northeastern Iran using Landsat TM and ETM+ remotely sensed images. A hybrid unsupervised, supervised and on-screen classification method was used to generate land use/cover maps of the area. To test the value of enhanced modeling, we compared the results from three model forecasts of the year 2040, an original SLEUTH forecast, an urban suitability-informed SLEUTH forecast, and a hydrologic plus urban suitability-informed SLEUTH forecast. As a control, we also used standard MCE to forecast urban growth for the year 2040. The integrated model comparison was made based on two future urban landscape descriptors: (1) potential surface runoff volume; and (2) landscape metrics. Results indicate that the integrated modeling approach produces a land use arrangement through SLEUTH that can be better directed towards higher land suitability and more favorable hydrologic conditions. The results for the combined hydrologic plus urban suitability-informed SLEUTH modeling were superior to the other three methods in terms of lower potential for runoff volume generation and more sustainable landscape metrics of shape, size and proximity. We demonstrate that the self-organizing cellular automata method behind SLEUTH is capable of better informed land use planning when compared to the simple MCE method. The approach can also be improved by using suitability layers for other land use practices to achieve a more comprehensive land use plan.

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“…Yıllık ortalama yağış miktarı 551.0 mm'dir ve aylara-mevsimlere göre düzensiz bir dağılış göstermektedir.Guisan vd. 1999;Jones vd. 2000;Weiss 2001).…”

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Landform Analysis using Topographic Characteristics: An Example of Usak Ulubey Canyon

Çilek

Berberoğlu

ÇİLEK

et al. 2019

Bilge International Journal of Science and Technology Research

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Özet: Yeryüzü şekilleri, geçmişte fizyografik ve morfometrik haritalar el yöntemleri ile çizilerek konumsal teknolojilerin gelişmesiyle arazi formlarının otomatik üretilmesi, veri tabanlarında depolanması kolaylaşarak, jeomorfoloji, toprak, ekoloji, peyzaj mimarlığı gibi fiziki planlarla ilgilenen pek çok bilim dalı tarafından daha etkin kullanılmaya başlamıştır. Bu çalışmada Ulubey Kanyonlarının arazi formlarını Coğrafi Bilgi Sistemleri aracılığıyla Topografik Pozisyon İndeksi (TPI) ile morfolojik analizler yaparak sınıflandırmak amaçlanmıştır. Uşak Ulubey Kanyonu, Amerika Birleşik Devletleri'nin Arizona eyaletinde bulunan Büyük Kanyon'dan (Grand Canyon) sonra dünyanın en büyük ikinci kanyonu unvanına sahiptir. Uşak'ın Ulubey ilçesinde yer alan kanyon, Ulubey ve Banaz çayları boyunca devam eden bir ana kanyon ve buna bağlanan onlarca büyük yan kanyonlardan oluşmaktadır. Morfolojik sınıflandırmaların oluşturulmasında 30 m çözünürlükte ASTER Sayısal Yükseklik Modeli (SYM) kullanılmıştır. Arazi morfolojisinin oluşturulmasında SYM verilerinden üretilen eğim, eğrisellik, yükseklik farkı, topografik açıklık vb. morfolojik parametreler kullanılmaktadır. TPI hesaplanmasında kullanılan Jennes algoritması, en küçük kareleri kullanarak belirlenen pencere boyutuna ikinci dereceden bir polinom yerleştirerek çok ölçekli bir yaklaşım kullanmaktadır. Araştırmada farklı ölçekteki SYM verileri için 300 m ve 2000 m pencere genişliği kullanılarak sonuçlar karşılaştırılmıştır. Oluşturulan morfolojk sınıflar kanyonlar, sığ vadiler, yaylalar, tabanlı vadiler, ovalar, açık yamaçlar, dik yamaçlar, vadilerde tepeler, orta eğimli sırtlar veya ovalardaki küçük tepeler, zirveler olmak üzere 10 sınıfta toplanmaktadır. Bu çalışmadan elde edilen bilgiler, farklı özelliklere sahip arazi değişkenleri (toprak, bitki örtüsü, yükseklik vb.) için doğal sınırlar olarak kabul edilen yüzey morfolojisinin sınıflandırılması özellikle arazi bozulması ve jeomorfolojide belirlenmesinde faydalı olacaktır.

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Cited by 34 publications

References 49 publications

SAR and Lidar Temporal Data Fusion Approaches to Boreal Wetland Ecosystem Monitoring

SAR and Lidar Temporal Data Fusion Approaches to Boreal Wetland Ecosystem Monitoring

ulating Hydrologic Impacts of Urban Growth Using SLEUTH, Multi Criteria Evaluation and Runoff Modeling

Landform Analysis using Topographic Characteristics: An Example of Usak Ulubey Canyon

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