The radar group at the Department of Environmental Sciences, Wageningen
University, has several research activities to investigate radar tree mapping and data
integration, and one of them is the study of “Analysis of Forest Spatial Structure
using Spatial Decision Rule”. The objective of this study is to investigate the tree
grouping level using the spatial decision rule based on tree information derived from
the interferometric SAR (InSAR) images. The results showed that tree objects could

The present research was conceived and developed within the framework of the “Tree Resources Outside the Forest” (TROF) project funded by the European Commission (Project number ERB3514PL973202). Most of the raw data was provided for this research initiative and some of the results obtained in the project were used with the consent of the authors.

Based on the detection of storm losses in Swiss alpine forest areas, two different digital classification approaches were compared. In contrast to the pixel based classification we investigated an object-oriented classification procedure. The eCognition software package of Definiens offers this possibility. The comparison was performed for images with different spatial resolution – very high resolution images of IKONOS, and images of SPOT in the sharpened mode.

After the presentation of new approaches of image analysis for remote sensing data at the symposium of Computer Science for Environmental Protection 2000 in Bonn, Germany (blaschke et al. 2000, Bock/Lessing 2000), now first user experiences using this method were archived.Based on a high resolution satellite imagery of the IKONOS-2-Sensor (1 m ground resolution)and laser scanner elevation data,knowledge about the classification process,the implementation and about data handling of the software system eCognition (Definiens Imaging, Munich, Germany) were gathered.

Ziel der Diplomarbeit war die Entwicklung einer Methode zur Ableitung von Volumsklassen und zur Bestimmung der Baumartenzusammensetzung von Waldbeständen aus Landsat 7- Daten in einem borealen Waldgebiet Sibiriens. Von vier jeweils über 20.000 ha großen Testflächen standen Referenzdaten der Forstinventur zur Verfügung. Durch eine Signaturanalyse wurden die Zusammenhänge zwischen den Bestandesparametern und den spektralen Merkmalen untersucht.

Radar 3D-tree mapping is important for monitoring of certification for sustainable natural forest management (SFM). Evaluation of interferometric radar tree mapping parameters and tree plot parameter measurements is the primary objective in this paper. To achieve this objective, the objects (trees) grouping approach was evaluated using available buffering techniques in Geographic Information Systems (GIS) software.

Estimates of stand height are an integral component of forest inventories. Lidar has been demonstrated as a tool for remotely sensing information on the vertical structure of forests, such as height. The ability to remotely sense height information for forest inventory purposes may allow for procedures such as update, audit, calibration, and validation. With current technologies, lidar data collection and processing are a resource-intensive undertaking.

Forests are very important natural resources, and tropical rain forests are even more important due to the abundance of biodiversity. But the rate of deforestation in the tropics is alarmingly high because of the rapid population growth and economic development. The use of satellite remotely sensed data and image analysis (i.e. classification) has proven its effectiveness in detecting tropical deforestation. In this research, two sets of Landsat-7 ETM+ data acquired on 26 August 2000 and 16 August 2002 were used in this research.

Environmental planning is fundamental for the sustainable developement of cities. In the case of Matinhos, on the Paranánese coast, as well as other Brasilian municipalities, this planning was neglected. For this reason, urban settlements can be found in areas which are actually considered areas of permanent preservation (APP), according to the Forestry Law. The present article describes the preliminary results of a mapping study of the urban occupation, especially in APP along the river line, where under natural condition one would find a riparian forest.

This research aimed to develop forest type classification technique for the mixed forest with coniferous and broad-leaved species using the high resolution satellite data. QuickBird data was used as satellite data. The method of this research was to extractsatellite data for every single tree crown using image segmentation technique, then to evaluate the accuracy of classification by changing grouping criteria such as tree species, families, coniferous or broad-leaved species, and timber prices.