Analysis of Thematic Classified Aerial Images Trough Multispectral and LIDAR Data

The application of thematic maps obtained through the classification of remote images needs the obtained products with an optimal accuracy. The registered images from the airplanes display a very satisfactory spatial resolution, but the classical methods of thematic classification not always give better results than when the registered data from satellite are used. In order to improve these results of classification, in this work, the LIDAR sensor data from first return (Light Detection And Ranging) registered simultaneously with the spectral sensor data from airborne are jointly used. The final results of the thematic classification of the scene object of study have been obtained, quantified and discussed with and without LIDAR data, after applying different methods: Maximum Likehood Classification, Support Vector Machine with four different functions kernel and Isodata clustering algorithm (ML, SVM-L, SVM-P, SVM-RBF, SVM-S, Isodata). The best results are obtained for SVM with Sigmoide kernel. These allow the correlation with others different physical parameters with great interest like Manning hydraulic coefficient, for their incorporation in a GIS and their application in hydraulic modeling.

Propuesta de metodología de trabajo para la obtención de cartografía a partir de datos LiDAR registrados en una zona rústica.

Tras la llegada de la medición mediante LiDAR, la obtención de cartografía se ha visto facilitada, obteniendo modelos digitales con gran rapidez y precisión. No obstante, para poder tratar la gran cantidad de información registrada, se necesita emplear un conjunto de algoritmos que permita extraer los detalles importantes y necesarios de la zona registrada. Por ello, se presenta este trabajo donde se expondrá una metodología de actuación para obtener cartografía a escala 1/1000 de una zona rústica, basada en el cálculo de mapas de curvas de nivel y ortofotografías, generadas a partir de los MDT y MDS de la zona. Todas las pruebas se han realizado mediante el software MDTopX. Abstract: After the arrival of the LiDAR measurement, mapping has been facilitated, obtaining digital models very quickly and accurately. However, in order to manage the great amount of recorded information, a set of algorithms is required which allows the extracting of important and necessary details of the recorded area. Therefore, a methodology is presented for mapping at 1/1000 scale of a rural area, based on contour maps and orthophotos, generated from the DTM and DSM of the area. All tests were performed using MDTopX software.

Metodología para ejecución y control de calidad para ortofotos, mediante combinación de sensor digital con LIDAR en zonas rurales

La utilización de una cámara fotogramétrica digital redunda en el aumento demostrable de calidad radiométrica debido a la mejor relación señal/ruido y a los 12 bits de resolución radiométrica por cada pixel de la imagen. Simultáneamente se consigue un notable ahorro de tiempo y coste gracias a la eliminación de las fases de revelado y escaneado de la película y al aumento de las horas de vuelo por día. De otra parte, el sistema láser aerotransportado (LIDAR - Light Detection and Ranging) es un sistema con un elevado rendimiento y rentabilidad para la captura de datos de elevaciones para generar un modelo digital del terreno (MDT) y también de los objetos sobre el terreno, permitiendo así alcanzar alta precisión y densidad de información. Tanto el sistema LIDAR como el sistema de cámara fotogramétrica digital se combinan con otras técnicas bien conocidas: el sistema de posicionamiento global (GPS - Global Positioning System) y la orientación de la unidad de medida inercial (IMU - Inertial Measure Units), que permiten reducir o eliminar el apoyo de campo y realizar la orientación directa de los sensores utilizando datos de efemérides precisas de los satélites. Combinando estas tecnologías, se va a proponer y poner en práctica una metodología para generación automática de ortofotos en países de América del Sur. Analizando la precisión de dichas ortofotos comparándolas con fuente de mayor exactitud y con las especificaciones técnicas del Plan Nacional de Ortofotografía Aérea (PNOA) se determinará la viabilidad de que dicha metodología se pueda aplicar a zonas rurales. ABSTRACT Using a digital photogrammetric camera results in a demonstrable increase of the radiometric quality due to a better improved signal/noise ratio and the radiometric resolution of 12 bits per pixel of the image. Simultaneously a significant saving of time and money is achieved thanks to the elimination of the developing and film scanning stages, as well as to the increase of flying hours per day. On the other hand, airborne laser system Light Detection and Ranging (LIDAR) is a system with high performance and yield for the acquisition of elevation data in order to generate a digital terrain model (DTM), as well as objects on the ground which allows to achieve high accuracy and data density. Both the LIDAR and the digital photogrammetric camera system are combined with other well known techniques: global positioning system (GPS) and inertial measurement unit (IMU) orientation, which are currently in a mature evolutionary stage, which allow to reduce and/or remove field support and perform a direct guidance of sensors using specific historic data from the satellites. By combining these technologies, a methodology for automatic generation of orthophotos in South American countries will be proposed and implemented. Analyzing the accuracy of these orthophotos comparing them with more accurate sources and technical specifications of the National Aerial Orthophoto (PNOA), the viability of whether this methodology should be applied to rural areas, will be determined.

Nesting In The Clouds: Evaluating And Predicting Sea Turtle Nesting Beach Parameters From Lidar Data

Humans' desire for knowledge regarding animal species and their interactions with the natural world have spurred centuries of studies. The relatively new development of remote sensing systems using satellite or aircraft-borne sensors has opened up a wide field of research, which unfortunately largely remains dependent on coarse-scale image spatial resolution, particularly for habitat modeling. For habitat-specialized species, such data may not be sufficient to successfully capture the nuances of their preferred areas. Of particular concern are those species for which topographic feature attributes are a main limiting factor for habitat use. Coarse spatial resolution data can smooth over details that may be essential for habitat characterization. Three studies focusing on sea turtle nesting beaches were completed to serve as an example of how topography can be a main deciding factor for certain species. Light Detection and Ranging (LiDAR) data were used to illustrate that fine spatial scale data can provide information not readily captured by either field work or coarser spatial scale sources. The variables extracted from the LiDAR data could successfully model nesting density for loggerhead (Caretta caretta), green (Chelonia mydas), and leatherback (Dermochelys coriacea) sea turtle species using morphological beach characteristics, highlight beach changes over time and their correlations with nesting success, and provide comparisons for nesting density models across large geographic areas. Comparisons between the LiDAR dataset and other digital elevation models (DEMs) confirmed that fine spatial scale data sources provide more similar habitat information than those with coarser spatial scales. Although these studies focused solely on sea turtles, the underlying principles are applicable for many other wildlife species whose range and behavior may be influenced by topographic features.

Boston, Massachusetts Region, Digital Elevation Model with Bathymetry

This raster layer represents surface elevation and bathymetry data for the Boston Region, Massachusetts. It was created by merging portions of MassGIS Digital Elevation Model 1:5,000 (2005) data with NOAA Estuarine Bathymetric Digital Elevation Models (30 m.) (1998). DEM data was derived from the digital terrain models that were produced as part of the MassGIS 1:5,000 Black and White Digital Orthophoto imagery project. Cellsize is 5 meters by 5 meters. Each cell has a floating point value, in meters, which represents its elevation above or below sea level.

Boston, Massachusetts Region, Digital Elevation Model (1:5,000), 2005 - Integer version

This raster layer represents surface elevation for the Boston Region, Massachusetts. This datalayer is a subset (covering only the Boston region) of the Massachusetts statewide digital elevation model. It was created from the digital terrain models that were produced as part of the 1:5,000 Black and White Digital Orthophoto imagery project. Cellsize is 5 meters by 5 meters. Each cell has an integer value, in meters, which represents its elevation above or below sea level.

Boston, Massachusetts Region 1:5,000 Color Ortho Imagery (1/2-meter Resolution), 2001

1/2-meter resolution 1:5,000 orthophoto image of the Boston region from April 2001. This datalayer is a subset (covering only the Boston region) of the Massachusetts statewide orthophoto image series available from MassGIS. It consists of 23 orthophoto quads mosaicked together (MassGIS orthophoto quad ID: 229890, 229894, 229898, 229902, 233886, 233890, 233894, 233898, 233902, 233906, 233910, 237890, 237894, 237898, 237902, 237906, 237910, 241890, 241894, 241898, 241902, 245898, 245902). These medium resolution true color images are considered the new "basemap" for the Commonwealth by MassGIS and the Executive Office of Environmental Affairs (EOEA). MassGIS/EOEA and the Massachusetts Highway Department jointly funded the project. The photography for the mainland was captured in April 2001 when deciduous trees were mostly bare and the ground was generally free of snow. The geographic extent of this dataset is the same as that of the MassGIS dataset: Boston, Massachusetts Region LIDAR First Return Elevation Data, 2002 [see cross references].