Farklı sayısal yüzey modellerinin doğruluk değerlendirmesi
Accuracy assessment of different digital surface models
Yazar: BARIŞ BEŞOL
Danışman: DOÇ. DR. UĞUR ALGANCI
İstanbul Teknik Üniversitesi / Lisansüstü Eğitim Enstitüsü / Geomatik Mühendisliği Ana Bilim Dalı / Geomatik Mühendisliği Bilim Dalı
Derece: Yüksek Lisans, 2021
Konu: Jeodezi ve Fotogrametri = Geodesy and Photogrammetry
Dizin: Sayısal yükseklik modelleri = Digital elevation models

Özet:
Dünyamızın ve faklı gök cisimlerinin topoğrafyası hakkında bilgiler barındıran dijital verilerilere sayısal yükseklik modeli adı verilmektedir. Sayısal yükseklik modelleri, sayısal yüzey modeli (SYM) veya sayısal arazi modeli (SAM) şeklinde karşımıza çıkmaktadır. Ayrıca sayısal yükseklik modelleri, çeşitli uzaktan algılama uygulamaları için önemli coğrafi bilgi kaynakları olarak yaygın şekilde kullanılmaktadır. Bu uygulamalara örnek olarak; yüksek çözünürlüklü uydu görüntülerinin hassas ortorektifikasyonu, üç boyutlu (3B) mekansal analizler, çok kriterli karar destek sistemleri ve deformasyon izleme konuları gösterilebilir. Sayısal yükseklik modellerinin doğruluğunun bahsi geçen uzaktan algılama analizleri üzerinde doğrudan etkisi vardır. Bu nedenle, her çalışmanın amacı, doğruluk gereksinimleri ve ölçeği göz önünde bulundurularak en uygun sayısal yükseklik modelinin seçilmesi önemlidir. Bu araştırma kapsamında, çeşitli uydu sensörlerinden elde edilen sayısal yükseklik modellerinin doğruluklarını ve performanslarını analiz edilmesi, birbirlerine göre avantajlarını ve dejavantajlarını karşılaştırılması hedeflenmiştir. Bu amaçla, oldukça yaygın kullanılan açık kaynak sayısal yükseklik modellerinden Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m, Shuttle Radar Topography Mission (SRTM) 30 m, ve Advanced Land Observing Satellite (ALOS) 30 m testlere dahil edilmiştir. Ayrıca, SPOT 6 ve Pleiades high-resolution (PHR) 1A uyduları ile algılanan tri-stereo görüntülerden üretilen 3 m ve 1 m mekansal çözünürlüklü SYM'ler de araştımada test edilerek hem açık kaynaklı hem de ticari verilerin doğruluk analizi sonuçlarına ulaşılmıştır. Çalışmada beş farklı yüzey modeli kullanılmasıyla farklı sensör ve çözünürlük kombinasyonları kıyaslanmıştır. Doğruluk değerlendirmesinde, Türkiye'nin ulusal haritalama ajansı olan Haritalama Genel Müdürlüğü (HGM) tarafından raster formatta sağlanan SYM verisi referans olarak kullanılmıştır., Bu veri, 30 cm mekansal çözünürlüklü stereo hava fotoğraflarından üretilmiş olup, 5 m çözünürlüklü ve %90 güven aralığında ±3 m veya daha iyi düşey doğruluğa sahiptir. Karadaki ve su yüzeylerindeki kaba hatalar referans veride arındırılmış olarak servis edilmektedir. Farklı sayısal yükseklik modellerinin relatif doğrulukları, çeşitli yöntemlerle belirlenen farklı sayıdaki kontrol noktaları (KN) kullanılarak test edilmiştir. KN'lerin seçilmesindeki ilk yöntem, çıplak toprak alanlarından 25 adet kontrol noktası seçilmiştir. İkinci yötemde ise tüm çalışma alanı için SYM doğruluklarını değerlendirmek üzere rastgele seçilen 1030 adet kontrol noktası kullanılmıştır. Bu rastgele seçilen noktalardan hata değeri çok yüksek olan kaba hatalı ve su yüzeyideki eşleme kaynaklı hataları içeren 30 nokta çıkartılarak 1000 KN ile devam edilmiştir. Ayrıca, SYM'lerden kesitler alarak görsel değerledirmeler yapılmıştır. Değerlendirme metotları, test alanın arazi kullanımı/örtüsü şekillerine göre de sınıflandırılarak başarımları ölçülmüştür. SYM'ler, yükseklik farklarının önemli olmadığı seyrek yerleşim ve yol sınıflarında daha iyi doğruluk değerlerine ulaşıldığı tespitedilmiştir. PHR ve SPOT verilerinden üretilen SYM'ler, tüm test yöntemlerine göre en yüksek doğruluk değerlerine ulaşmıştır. Bu sonuçlara en yakın performansa ALOS SYM ulaşmıştır. ALOS SYM'sinin 30 m mekansal çözünürlüğe sahip olmasına rağmen, 2,5 m optik görüntülerden üretilen orijinal 5 m mekansal çözünürlüklü SYM'den üretilmiş olmasından kaynaklandığla açıklanabilir. Elde edilen diğer sonuçlarda, SRTM ve ASTER SYM'leri en düşük doğrulukla değerlendirmede yer almıştır. Genellikle yüksek çözünürlüklü SYM'ler özellikle insan yapımı yapıların sınırlarında ve köşelerinde eşleme kaynaklı hatalar mevcut olduğundan bu verilere düzeltme uygulanmıştır. Farklı SYM'ler karşılaştırılırken, özellikle dinamik bölgeler için verilerin kaynağı daha önemli hale gelmektedir. Zamansal değişimden kaynaklı farklılıkları en aza indirebilmek için yakın tarihli test verileri seçilmesi gerekmektedir. Bu çalışmada da verilerin el verdiği ölçüde yakın tarihli sayısal yükseklik modelleri kullanılmıştır. Mutlak doğruluk ölçütleri için LIDAR tabanlı nokta bulutları ve yersel ölçme gibi oldukça hassas referans verilerinin kullanılmasıyla elde edilebilmektedir.

Abstract:
Digital Several applications where surface height information is requires, Digital Elevation Models (DEMs) can be used as essential data sources. A DEM can be defined as the projection of the Earth surface in 3 dimensions (3D). DEMs can be classified in 2 groups: Digital Terrain Models (DTMs); where there is no trees, building and all other objects on the surface, and Digital Surface Models (DSMs); where all of the Earth surface combined with all artificial and natural objects are represented. A DEM can be in a raster format, having square cells which are named pixels, with a height value related to each pixel.
DEMs, in DSM or DTM forms, are important sources of geospatial information and they can be used in various remote sensing applications such as precise orthorectification of high resolution satellite images, spatial analysis of 3D information, multi-criteria decision support systems, and monitoring of deformation. The importance of selecting the most suitable DEM according to the aim, accuracy requirement and scale of the study is crucial; as the accuracy of DEMs directly affects the specific calculations and processing chains. In this study, different DSMs acquired from various satellite sensors were compared and analyzed in terms of their accuracy and performance.
A part of Istanbul metropolitan city is selected as the study area for this study. The reason for selecting this area was the availability of data, and also the various land cover types such as forest, residential and industrial areas which experienced minimum changes in recent decades. Particularly, the residential areas having high-rise and diverse types of buildings were considerable candidates for the assessment of extreme conditions.
For this objective, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m, Shuttle Radar Topography Mission (SRTM) 30 m, and Advanced Land Observing Satellite (ALOS) 30 m resolution DSM data which all are freely available, were acquired. Furthermore, 3 m and 1 m resolution DSMs were generated by using tri-stereo SPOT 6 and Pleiades High Resolution (PHR) 1A satellites, respectively. The accuracy assessment was conducted with elevation reference data provided by the General Directorate of Mapping, the national mapping agency of Turkey-produced from 30 cm spatial resolution stereo aerial photos, with a 5 m grid spacing and ±3 m or better overall vertical accuracy at the 90% confidence interval (CI). Gross errors and water surfaces were eliminated from the reference DSM.
Processing of high resolution satellite optical imagery for DSM generation can be done with various kinds of commercial and scientific software. OthoEngine module of the PCI Geomatica software was used for the processing of tri-stereo satellite image for DSM extraction. The generation of DSM was done by using image correlation of the epipolar geometry and a rational function model was used for the application of the acquisition geometry. The contrast and matching ratio was improved by applying the Wallis filter to the DSM generation. Matching points from the pixels in the image pairs were produced with the automated image matching algorithm. The algorithm used a mean cross correlation with a multiscale strategy. Then, three epipolar images at the spatial resolution of the source images were produced, namely fore-nadir, nadir-after and fore-after. In the last step, the DSM was generated in accordance with the mean sea level datum, with a sampling factor that is two times of the spatial resolution, which is equal to 2.
Visual interpretation of on-screen digitization with the 30 cm orthophotos, created with the same aerial photographs that are used in HGM DSM data was performed for the land cover classification of the study area. The unpublished reports from the producer indicates that the HGM orthophotos provide ±2.5 m horizontal positional accuracy. Class generalization was done according to the quantity of the land cover inside the patch. A comparative accuracy analysis were conducted for the DSMs associated to the land cover classes, using the resulted map. According to the reference data, the test area was between 0 m (sea level) and 190 m. Random checkpoints were created with a stratified sampling method based on the elevation intervals.
It is important to establish a horizontal location matching for the vertical accuracy assessment of several DSMs. The horizontal accuracies of ASTER, SRTM, and ALOS data were acceptable, as regards to their spatial resolution. The geometric accuracy of the PHR and SPOT DSMs were increased by using GCPs during the production. Visual control was applied to check the co-registration of the DSMs by analyzing locational fit of streambeds and roads which are apparent in the DSM data. Therefore, all of the DSM data acquired from various sources were horizontally matched with one another.
Vertical accuracy assessment of the DSMs was carried out after the pre-processing procedures were completed. This is done by using three different aspects. Firstly, a point-based evaluation was conducted on bare lands to assess the accuracy of the DSMs for representing the terrain. For this aim, 25 checkpoints belonging to bare lands were collected from the HGM orthophotos. After, height calues of GCPs were extracted for every DSM datum, along with the reference DSM by using an overlay analysis. After the derivation of height information, RMSE, accuracy (at the 95% CI), and standard deviation were calculated for each of the DSM data separately.
The second approach to assess the vertical accuracy of the DSMs was done by using selected 1030 random checkpoints from the entire study area. 30 of the inadequate points were removed from the checkpoints. Then, remaining 1000 points were used. According to the different elevation intervals obtained from the reference DSM, stratified sampling was performed. The checkpoints were collected homogeneously. The accuracy metrics which were determined in the first approach were likewise calculated here. Additionally, intersection analysis with the provided land cover map was used to create land cover labels. The accuracy metric assumes that the vertical errors are normally distributed. Frequency histograms of height differences (theoretically, the errors) were produced for each DSM to test this situation. The results showed that the ALOS, ASTER, and SPOT DSMs presents normal distribution traits, while PHR DSM has a very slight positive skew to a normal distribution. This is also detected for the SRTM DSM with a slight negative skew. By interpreting these results, it can be said that the accuracy metric is suitable for use in this study.
In the last approach, geographical directions complementing to 450 angular intervals for the entire DSM dataset were taken into account for generating vertical profiles. Then, under various topographic conditions and land cover scenarios, elevation chance features for every DSM in1 km length fragments were discovered.
Additionally, to the control point approach, the accuracies relating to the land cover, were evaluated with vertical cross-sections derived from the DSMs. The highest accuracies were obtained with the PHR and SPOT DSMs, on every testing methods. Then, ALOS DSM also showed reassuring results. Although, when compared with others SRTM and ASTER DSMs had the worst results in terms of accuracy. Furthermore, the PHR and SPOT DSMs were better at capturing man-made objects and above-terrain structures which signifies the requirement for post-processing for improved representations.
The analysis of the accuracy of DSMs is very important as they are crucial data sources for many remote sensing and geospatial applications. A comparative assessment of DSMs in terms of vertical agreement was done in this study by using accuracy metrics. The results of the study showed that higher accuracy values of PHR and SPOT DSMs was consistent with the spatial resolution. Mostly, vertical accuracy is higher with a high spatial resolution. Although, several noise effects were seen in the DSMs, especially at the borders and corners of artificial surfaces, which indicates a need for processing high resolution DSMs. Compared to other freely available DSMs, ALOS DSM gave the most promising results. This result can be due to the fact that the data has 5 m DSM, produced with 2.5 m images, and has strong signals originally.
The DSM accuracies were dissimilar on different Land Use Land Cover (LU/LC) categories. A better accuracy was seen on rare residential and road classes where there were no considerable elevation differences. The source of the data becomes more important in especially constantly changing areas. The availability of different datasets obtained at identical times is not always possible. Thus, finding a stable region in the study area is more efficient to compare and evaluate different DSMs. It is possible to determine absolute accuracy metrics by using highly accurate data such as LIDAR based point clouds.