<p> </p> <p>As a result of Shadow NeRF and Sat-NeRF, it is possible to take the solar angle into account in a NeRF-based framework for rendering a scene from a novel viewpoint using satellite images for training. Our work extends those contributions and shows how one can make the renderings season-specific. Our main challenge was creating a Neural Radiance Field (NeRF) that could render seasonal features independently of viewing angle and solar angle</p> <p>while still being able to render shadows. We teach our network to render seasonal features by introducing one more input variable — time of the year. However, the small training datasets typical of satellite imagery can introduce ambiguities in cases where shadows are present in the same location for every image of a particular season. We add additional terms to the loss function to discourage the network from using seasonal features for accounting for shadows. We show the performance of our network on eight Areas of Interest containing images captured by the Maxar WorldView-3 satellite. This evaluation includes tests measuring the ability of our framework to accurately render novel views, generate height maps, predict shadows, and specify seasonal features independently from shadows. Our ablation</p> <p>studies justify the choices made for network design parameters. Also included in this work is a novel approach to space carving which merges multiple features and consistency metrics</p> <p>at different spatial scales to create higher quality digital surface map than is possible using standard RGB features.</p>

Flygfotografering med Unmanned Aircraft System (UAS) är i jämförelse med traditionell fotogrammetri effektivare, billigare och säkrare vilket har medfört att denna teknik föredras av många aktörer. Ett tidskrävande arbete som varit svårt att kringgå är att etablera flygsignaler på marken som används för att georeferera och kontrollera flygbilderna med. Under 2018 presenterade UAS-tillverkaren DJI sin nya quadcopter med integrerad Real-Time Kinematic (RTK)-modul. I samband med detta kan kontinuerliga och noggranna positioner levereras via Nätverks-RTK (NRTK) och behovet av markstödpunkter reduceras. I denna studie undersöktes lägesosäkerheterna i plan för ortofoton som framställdes med hjälp av en DJI Phantom 4 RTK där flygbilderna georefererades med begränsat antal eller utan markstödpunkter. Lägesosäkerheterna beräknades och kontrollerades enligt Handbok i mät- och kartfrågor (HMK) – Ortofoto, vilket är ett stöddokument inom ämnet. Vid framställning av ett ortofoto krävs även en digital terrängmodell (DTM) eller en digital ytmodell (Digital Surface Model, DSM) och kvaliteten av denna har stor inverkan på ortofotots kvalitet. I denna studie kontrollerades och utvärderades därför en del av den DSM som användes vid ortofotoframställning för respektive uppsättning enligt den tekniska specifikationen SIS-TS 21144:2016. Resultatet från studien visar att ett ortofoto går att framställas utan markstödpunkter och samtidigt klara kraven på specificerad lägesosäkerhet enligt HMK-standardnivå 3. Den sammanlagda lägesosäkerheten beräknades till 0,029 m vilket är 5 mm högre i jämförelse med ett ortofoto som baserats på traditionell georefereringsmetod, dvs. med markstödpunkter. Kravet på kvalitet i höjddata uppfylldes också för ortofotoframställning trots att en systematisk effekt i höjd uppkom. Denna effekt påverkade inte ortofotots koordinater i plan då standardosäkerheterna i höjd var låga. Resultatet visade att om två markstödpunkter adderades i vardera änden av området, kunde de systematiska effekterna i höjd minimeras och det var då möjligt att skapa en DSM som uppfyller kraven för detaljprojektering (noggrannhetsklass 1–3) enligt SIS-TS 21144:2016. / Aerial photography with UAS is in comparison with traditional photogrammetry more efficient, cheaper and safer which has led to this technology being preferred by many performers. A time-consuming job that has been difficult to avoid is to establish signals at the ground that are used for georeferencing and evaluate the results. In 2018, the UAS manufacturer DJI presented its new quadcopter with integrated Real-Time Kinematic (RTK) module. This allows continuous and accurate positions delivered via Network RTK (NRTK) and the need of ground control points can be reduced. In this study, investigations of the position uncertainties in orthophotos produced using a DJI Phantom 4 RTK carried out where the aerial images were georeferenced with limited numbers or without ground control points. The position uncertainties were calculated and controlled according to the Swedish HMK – Ortofoto (Orthophoto) which is a document within the subject. When producing an orthophoto, a digital terrain model (DTM) or a digital surface model (DSM) is also required and the quality of this has a great impact on the result. Therefore, a part of the DSM used for orthophoto production for each set was checked and evaluated according to the Swedish technical specification, SIS-TS 21144:2016. The result of the study shows that an orthophoto can be produced without ground control points and at the same time meet the requirements for specified position uncertainty according to HMK standard level 3. The total position uncertainty was calculated to be 0,029 m, which is 5 mm higher compared to the orthophoto based on the traditional georeferencing method, i.e. with ground control points. The requirement for quality in height data was also met for orthophoto production even though a systematic effect in height occurred. This effect did not affect the plane coordinates in the orthophoto because of the low standard uncertainties in height. The result showed that if two ground control points were added at each end of the area, the systematic effects were minimized, and it was possible to produce a DSM that fulfils the requirements for accuracy class 1-3 according to SIS-TS 21144:2016.

No description available.

點雲（point cloud）為以大量三維坐標描述地表實際情形的資料形式，其中包含其三維坐標及相關屬性。通常點雲資料取得方式為光達測量，其以單一波段雷射光束掃描獲取資料，以光達獲取點雲，常面臨掃描時間差、缺乏多波段資訊、可靠邊緣線及角點資訊、大量離散點雲又缺乏語意資訊（semantic information）難以直接判讀及缺乏多餘觀測量等問題。 攝影測量藉由感測反射自太陽光或地物本身放射之能量，可記錄為二維多光譜影像，透過地物在不同光譜範圍表現之特性，可輔助分類，改善分類成果。若匹配多張高重疊率的多波段影像，可以獲取包含多波段資訊且位於明顯特徵點上的點雲，提供光達以外的點雲資料來源。 傳統空中三角測量平差解算地物點坐標及產製數值表面模型（Digital Surface Model, DSM）時，多採用可見光影像為主；而目前常見之高空間解析度數值航照影像，除了記錄可見光波段之外，亦可蒐集近紅外光波段影像。但較少採用近紅外光波段影像，以求解地物點坐標及建立DSM。 因此本研究利用多波段影像所蘊含的豐富光譜資訊，以取像方式簡易及低限制條件的近景攝影測量方式，匹配多張可見光、近紅外光及紅外彩色影像，分別建立可見光、近紅外光及紅外彩色之DSM，其目的在於探討加入近紅外光波段後，所產生的近紅外光及紅外彩色DSM，和可見光DSM之異同；並比較該DSM是否更能突顯植被區。 研究顯示，以可見光點雲為檢核資料，計算近紅外光與紅外彩色點雲的均方根誤差為其距離門檻值之相對檢核方法，可獲得約21%的點雲增加率；然而使用近紅外光或紅外彩色影像，即使能增加點雲資料量，但對於增加可見光影像未能匹配的資料方面，其效果仍屬有限。 / Point cloud represents the surface as mass 3D coordinates and attributes. Generally, these data are usually collected by LIDAR (LIght Detection And Ranging), which acquires data through single band laser scanning. But the data collected by LIDAR could face problems, such as scanning process is not instantaneous, lack of multispectral information, breaklines, corners, semantic information and redundancies. However, photogrammetry record the electromagnetic energy reflected or emitted from the surface as 2D multispectral images, via ground features with different characteristics differ in spectrum, it can be classified more efficiently and precisely. By matching multiple high overlapping multispectral images, point cloud including multispectral information and locating on obvious feature points can be acquired. This provides another point cloud source aparting from LIDAR. In most studies, visible light (VIS) images are used primarily, while calculating ground point coordinates and generating digital surface models （DSM） through aerotriangulation. Although nowadays, high spatial resolution digital aerial images can acquire not only VIS channel, but also near infrared (NIR) channel as well. But there is lack of research doing the former procedures by using NIR images. Therefore, this research focuses on the rich spectral information in multispectral images, by using easy image collection and low restriction close range photogrammetry method. It matches several VIS, NIR and color infrared (CIR) images, and generate DSMs respectively. The purpose is to analyze the difference between VIS, NIR and CIR data sets, and whether it can emphasize the vegetation area, after adding NIR channel in DSM generation. The result shows that by using relative check points between NIR, CIR data with VIS one. First, VIS point cloud was set as check point data, then, the RMSE (Root Mean Square Error) of NIR and CIR point cloud was calculated as distance threshold. Its data increment is 21% ca. However, the point cloud data amount can be increased, by matching NIR and CIR images. But the effect of increasing data, which was not being matched from VIS images are limited.

Submitted by Luciana Ferreira (lucgeral@gmail.com) on 2016-12-27T11:27:00Z No. of bitstreams: 2 Dissertação - Avilmar Antonio Rodrigues - 2016.pdf: 13580117 bytes, checksum: 2b78a395b4bd955f8d72e83399bcc578 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2016-12-27T11:27:20Z (GMT) No. of bitstreams: 2 Dissertação - Avilmar Antonio Rodrigues - 2016.pdf: 13580117 bytes, checksum: 2b78a395b4bd955f8d72e83399bcc578 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2016-12-27T11:27:20Z (GMT). No. of bitstreams: 2 Dissertação - Avilmar Antonio Rodrigues - 2016.pdf: 13580117 bytes, checksum: 2b78a395b4bd955f8d72e83399bcc578 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2016-11-25 / This research aimed to evaluate the use of Unmanned Aerial Vehicle (UAV) as a platform for taking aerial photographs for mapping erosion planialtimetric located in urban areas. In addition, we evaluated the need to use or not to field control points for the generation of Digital Surface Model (DSM) and ortomosaico as tools to evaluate the erosive process. Despite the wide variation in attitude of aerial photographs that make up the aerophotogrammetric block arising from the instability of the UAV, it was possible to generate the MDS and ortomosaico with or without control points. This research was conducted in two urban erosions located in Goiania in Sector Fonte Nova in the stream of grass and the other in Silvânia called foot-washing. Whole generation of MDS, Digital Surface Model (MDT) and ortomosaico were performed in Agisoft PhotoScan program in semi-automatic processing, if used control points, or automatic without control points. The ortomosaicos generated without control points presented rotation, translation and scale of different generated with support. In addition, MDS generated without control points showed elevation or lowering of the reference surface with respect to the generated control, it is emphasized that these discrepancies are not constant. When performing automatic conversion of MDS to MDT, it was realized that the program was not able to eliminate the shrub vegetation located within the erosion. The vegetation or tree, shrub or undergrowth (grass) prevents proper limitation of erosion to the volume calculation. But unlike the MDS generated between two distinct epochs identifies the changes in the interval of time in areas without vegetation. The use of control points was essential to ensure the orientation, scale and the reference plane in the products generated from aerial photographs and thus evaluate the changes. Anyway, the UAV can be used as a platform for taking aerial photographs for generating cartographic products that enable the mapping and evaluation of erosions. / Esta pesquisa teve por objetivo avaliar a utilização do Veículo Aéreo Não Tripulado (VANT) como plataforma para a tomada de fotografias aéreas para o mapeamento planialtimétrico de erosão situada em zona urbana. Além disso, analisou-se a necessidade de utilização ou não de pontos de controle de campo para a geração de Modelo Digital de Superfície (MDS) e ortomosaico como instrumentos para examinar o processo erosivo. Apesar da grande variação da atitude da aeronave durante a obtenção das fotografias aéreas que compõem o bloco aerofotogramétrico, foi possível gerar o MDS e o ortomosaico com ou sem pontos de controle. Este estudo foi realizado em duas erosões urbanas, uma situada em Goiânia-GO, no Setor Fonte Nova/Córrego do Capim, e a outra em Silvânia-GO, denominada de Lava-Pés. Toda a geração dos MDS, Modelo Digital de Terreno (MDT) e ortomosaico foram realizados no programa Agisoft PhotoScan, em processamento semiautomático (i.e., com pontos de controle) e automático (i.e., sem pontos de controle). Os ortomosaicos gerados sem pontos de controle apresentaram rotação, translação e escala diferente dos gerados com apoio. Ademais, os MDS gerados sem pontos de controle apresentaram elevação ou rebaixamento da superfície de referência em relação aos gerados com controle. Ressalta-se, ainda, que essas discrepâncias não foram constantes. Ao realizar a conversão automática do MDS para o MDT, percebeu-se que o programa não foi capaz de eliminar a vegetação arbustiva localizada no interior da erosão. As vegetações arbórea, arbustiva ou rasteira (gramíneas) impedem a correta delimitação da erosão para o cálculo do volume. Porém, a diferença dos MDS gerados entre duas épocas distintas propicia identificar as alterações ocorridas nesse intervalo de tempo nas regiões sem cobertura vegetal. O uso de pontos de controle foi essencial para garantir a orientação, a escala e o plano de referência nos produtos gerados a partir das fotografias aéreas e, assim, avaliar as modificações da erosão. Por fim, o VANT pode ser utilizado como plataforma para a tomada de fotografias aéreas para gerar produtos cartográficos que possibilitem o mapeamento e as avaliações das erosões, sobretudo em áreas urbanas.

<p>Emerging mobile mapping systems include a wide range of platforms, for instance, manned aircraft, unmanned aerial vehicles (UAV), terrestrial systems like trucks, tractors, robots, and backpacks, that can carry multiple sensors including LiDAR scanners, cameras, and georeferencing units. Such systems can maneuver in the field to quickly collect high-resolution data, capturing detailed information over an area of interest. With the increased volume and distinct characteristics of the data collected, practical quality control procedures that assess the agreement within/among datasets acquired by various sensors/systems at different times are crucial for accurate, robust interpretation. Moreover, the ability to derive semantic information from acquired data is the key to leveraging the complementary information captured by mobile mapping systems for diverse applications. This dissertation addresses these challenges for different systems (airborne and terrestrial), environments (urban and rural), and applications (agriculture, archaeology, hydraulics/hydrology, and transportation).</p> <p>In this dissertation, quality control procedures that utilize features automatically identified and extracted from acquired data are developed to evaluate the relative accuracy between multiple datasets. The proposed procedures do not rely on manually deployed ground control points or targets and can handle challenging environments such as coastal areas or agricultural fields. Moreover, considering the varying characteristics of acquired data, this dissertation improves several data processing/analysis techniques essential for meeting the needs of various applications. An existing ground filtering algorithm is modified to deal with variation in point density; digital surface model (DSM) smoothing and seamline control techniques are proposed for improving the orthophoto quality in agricultural fields. Finally, this dissertation derives semantic information for diverse applications, including 1) shoreline retreat quantification, 2) automated row/alley detection for plant phenotyping, 3) enhancement of orthophoto quality for tassel/panicle detection, and 4) point cloud semantic segmentation for mapping transportation corridors. The proposed approaches are tested using multiple datasets from UAV and wheel-based mobile mapping systems. Experimental results verify that the proposed approaches can effectively assess the data quality and provide reliable interpretation. This dissertation highlights the potential of modern mobile mapping systems to map challenging environments for a variety of applications.</p>