Landsat-8 uydu görüntüsüne uygulanan farklı topografik düzeltme yöntemlerinin performanslarının orman alanlarında karşılaştırılması
Abstract
Uydu görüntülerinden bilgi çıkartılmasında, yeryüzündeki topografik değişkenliklerden kaynaklanan olumsuz etkilerin topografik düzeltme yöntemleri ile giderilmesi en önemli ön işleme adımlarından biridir. Bu çalışmada, uydu görüntülerine uygulanan farklı topografik düzeltme yöntemlerinin orman alanlarında gösterdikleri performanslar karşılaştırılmıştır. Bu amaçla İstanbul Avrupa Yakası’nda engebeli topografyaya sahip ve hâkim meşcere türlerinin meşe (Quercus), gürgen (Carpinus) ve kayın (Fagus) olduğu 3 farklı test alanı seçilmiştir. Test alanlarına ait Landsat-8 OLI görüntülerine altı farklı topografik düzeltme yöntemi uygulanmış sonuçlar görsel ve istatistiksel olarak değerlendirilmiştir. Yapılan değerlendirmeler sonucunda, Cosine, Sun Canopy Sensor (SCS), Path Length Correction (PLC) ve Minnaert+SCS yöntemlerinin engebeli orman alanlarında yeterince yüksek doğruluk sağlamadığı, her 3 test alanında da Minnaert ve Piksel Tabanlı Minnaert yöntemlerinin (PBM) en yüksek doğruluğu sağladığı görülmüştür.
Keywords
Landsat-8 Topografik düzeltme Sayısal yükseklik modeli Görüntü ön işleme Minnaert düzeltmesi
Thanks
Bu çalışmaya katkı sağlayan “Orman Yangınlarında Uydu Tabanlı Duyarlılık/Etkilenebilirlik ve Risk Analizi: Antalya Örneği” Projesi’ne (MGA-2021-43241) teşekkür ederiz.
References
- Chi H, Yan K, Yang K, Du S, Li H, Qi J, Zhou W (2022) Evaluation of topographic correction models based on 3-D radiative transfer simulation. IEEE Geoscience and Remote Sensing Letters, 19, 1-5
- Gu D, and Gillespie A (1998) Topographic normalization of Landsat TM images of forest based on subpixel sub-canopy sensor geometry. Remote Sensing of Environment, 64 (2) ,166–175
- Hurni K, Hoek JV, Fox J (2019) Assessing the spatial, spectral, and temporal consistency of topographically corrected Landsat time series composites across the mountainous forests of Nepal. Remote Sensing of Environment, 231, 111225
- Jimenez RV, Calcerrada RR, Bernal RN, Funes PA, Novillo CJ (2017) Topographic correction to Landsat imagery through slope classification by applying the SCS + C method in mountainous forest areas. ISPRS International Journal of Geo-Information, 6(9), 287
- Koç A, Yener H, Çoban HO (2006) Landsat Etm+ Verilerinde Topografik normalizasyonun sınıflandırma doğruluğu üzerindeki etkisi. İstanbul Üniversitesi Orman Fakültesi Dergisi, 56(2), 58-73
- Lu D, Ge H, He S, Xu A, Zhou G, Du H (2014) Pixel-based Minnaert correction method for reducing topographic effects on a Landsat 7 ETM+ image. Photogrammetric Engineering & Remote Sensing, 74(11), 1343–1350
- Ma Y, He T, Li A, Li S (2021) Evaluation and intercomparison of topographic correction methods based on Landsat images and simulated data. Remote Sensing 2021, 13(20), 4120
- María Luisa E, Frédéric B, Marie W (2008) Slope correction for LAI estimation from Gap Fraction measurements. Agricultural and Forest Meteorolgy, 148(10), 1553–1562
- Minnaert, M (1941) The reciprocity principle in lunar photometry. Astrophys. J., 93, 403–410
- Mishra VD, Sharma JK, Khanna R (2010) Review of topographic analysis methods for the western Himalaya using AWiFS and MODIS satellite imagery. Annals of Glaciology, 51(54), 153-160
- Reeder DH, (2002) Topographic correction of satellite images: Theory and application. Ph.D. Dissertation, Dartmouth College, Hanover, NH, USA
- Smith JA, Tzeu LL, Ranson KJ (1980) The Lambertian assumption and Landsat data. Photogrammetric Engineering & Remote Sensing, 46(10), 1183–1189
- Teillet PM, Guindon B, Goodenough DG (1982) On the slope-aspect correction of multispectral scanner data. Canadian Journal of Remote Sensing, 8(2), 84–106
- USGS (2022), Landsat Missions - Landsat 8, URL: https://www.usgs.gov/landsat-missions/landsat-8
- Vanonckelen S, Lhermitte S, Rompaey AV (2013) The effect of atmospheric and topographic correction methods on land cover classification accuracy. International Journal of Applied Earth Observation and Geoinformation, 24, 9–21
- Vanonckelen S, Lhermitte S, Balthazar V, Rompaey AV (2014) Performance of atmospheric and topographic correction methods on landsat imagery in mountain areas. International Journal of Remote Sensing, 35(13), 4952–4972
- Yin G, Cao B, Li J, Fan W, Zeng Y, Xu B, Zhao W (2020) Path Length Correction for improving leaf area index measurements over sloping terrains: A deep analysis through computer simulation. IEEE Transactions on Geoscience And Remote Sensing, 58(7), 4573-4588
- Zylshal Z, Bayanuddin AA, Nugroho FS, Munawar ST (2021) Correcting the topographic effect on Spot-6/7 multispectral imageries: A comparison of different digital elevation models. Geomatics Application for Geography, (Special Issue), 163-179
Comparison of the performances of different topographic correction methods applied to Landsat-8 satellite image in forest areas
Abstract
In order to extract information from satellite images, removing the effects caused by topographic variability with topographic correction methods is one of the most important image preprocessing steps. In this study, the performances of topographic correction methods in forest areas with different topographic characteristics were compared. For this purpose, 3 different forest areas with rugged topography on the European Side of Istanbul were selected as the test area, where the dominant stand species are oak (Quercus), hornbeam (Carpinus), and beech (Fagus). Six different topographic correction methods were applied to the Landsat-8 OLI images containing the test areas, and the results were evaluated visually and statistically. As a result of the evaluations, it was determined that Cosine, Sun Canopy Sensor (SCS), Path Length Correction (PLC) and Minnaert+SCS methods did not provide high enough accuracy in rugged forest areas. The Minnaert and Pixel Based Minnaert methods (PBM) provided the highest accuracy in all 3 test areas.
Keywords
Landsat-8 Topographic correction Digital elevation model Image preprocessing Minnaert correction
References
- Chi H, Yan K, Yang K, Du S, Li H, Qi J, Zhou W (2022) Evaluation of topographic correction models based on 3-D radiative transfer simulation. IEEE Geoscience and Remote Sensing Letters, 19, 1-5
- Gu D, and Gillespie A (1998) Topographic normalization of Landsat TM images of forest based on subpixel sub-canopy sensor geometry. Remote Sensing of Environment, 64 (2) ,166–175
- Hurni K, Hoek JV, Fox J (2019) Assessing the spatial, spectral, and temporal consistency of topographically corrected Landsat time series composites across the mountainous forests of Nepal. Remote Sensing of Environment, 231, 111225
- Jimenez RV, Calcerrada RR, Bernal RN, Funes PA, Novillo CJ (2017) Topographic correction to Landsat imagery through slope classification by applying the SCS + C method in mountainous forest areas. ISPRS International Journal of Geo-Information, 6(9), 287
- Koç A, Yener H, Çoban HO (2006) Landsat Etm+ Verilerinde Topografik normalizasyonun sınıflandırma doğruluğu üzerindeki etkisi. İstanbul Üniversitesi Orman Fakültesi Dergisi, 56(2), 58-73
- Lu D, Ge H, He S, Xu A, Zhou G, Du H (2014) Pixel-based Minnaert correction method for reducing topographic effects on a Landsat 7 ETM+ image. Photogrammetric Engineering & Remote Sensing, 74(11), 1343–1350
- Ma Y, He T, Li A, Li S (2021) Evaluation and intercomparison of topographic correction methods based on Landsat images and simulated data. Remote Sensing 2021, 13(20), 4120
- María Luisa E, Frédéric B, Marie W (2008) Slope correction for LAI estimation from Gap Fraction measurements. Agricultural and Forest Meteorolgy, 148(10), 1553–1562
- Minnaert, M (1941) The reciprocity principle in lunar photometry. Astrophys. J., 93, 403–410
- Mishra VD, Sharma JK, Khanna R (2010) Review of topographic analysis methods for the western Himalaya using AWiFS and MODIS satellite imagery. Annals of Glaciology, 51(54), 153-160
- Reeder DH, (2002) Topographic correction of satellite images: Theory and application. Ph.D. Dissertation, Dartmouth College, Hanover, NH, USA
- Smith JA, Tzeu LL, Ranson KJ (1980) The Lambertian assumption and Landsat data. Photogrammetric Engineering & Remote Sensing, 46(10), 1183–1189
- Teillet PM, Guindon B, Goodenough DG (1982) On the slope-aspect correction of multispectral scanner data. Canadian Journal of Remote Sensing, 8(2), 84–106
- USGS (2022), Landsat Missions - Landsat 8, URL: https://www.usgs.gov/landsat-missions/landsat-8
- Vanonckelen S, Lhermitte S, Rompaey AV (2013) The effect of atmospheric and topographic correction methods on land cover classification accuracy. International Journal of Applied Earth Observation and Geoinformation, 24, 9–21
- Vanonckelen S, Lhermitte S, Balthazar V, Rompaey AV (2014) Performance of atmospheric and topographic correction methods on landsat imagery in mountain areas. International Journal of Remote Sensing, 35(13), 4952–4972
- Yin G, Cao B, Li J, Fan W, Zeng Y, Xu B, Zhao W (2020) Path Length Correction for improving leaf area index measurements over sloping terrains: A deep analysis through computer simulation. IEEE Transactions on Geoscience And Remote Sensing, 58(7), 4573-4588
- Zylshal Z, Bayanuddin AA, Nugroho FS, Munawar ST (2021) Correcting the topographic effect on Spot-6/7 multispectral imageries: A comparison of different digital elevation models. Geomatics Application for Geography, (Special Issue), 163-179
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Environmental Sciences |
| Journal Section | Research Article |
| Authors | |
| Publication Date | May 15, 2023 |
| Acceptance Date | January 24, 2023 |
| Published in Issue | Year 2023 Volume: 24 Issue: 1 |
Cite
Artvin Coruh University Journal of Forestry Faculty is licensed under a Creative Commons Attribution 4.0 International License.