**7. Acknowledgement**

This work was made possible by several flight campaigns carried out by the Deutsches Zentrum für Luft- und Raumfahrt (DLR) Oberpfaffenhofen, Germany. We further thank the people of the Geomatics Lab of the Humboldt University of Berlin for providing the HyMap data of Berlin. We also acknowledge financial support for AISA flight campaigns at Helgoland of the BIS Bremerhaven and the WFB Bremen in the framework of the projects 'Innohyp' and 'CoastEye'.

#### **8. References**


influenced areas under the shadow which is a problem that has not yet been regarded in the

Another open issue is the detection of white water pixels which are usually to bright to be included in the low albedo mask (section 4.1). This can be seen in the top left side of the test

Overall, it can be seen from Tab. 3 that the accuracies of the independent datasets is not less than the accuracies of the datasets analyzed during the algorithm development. Thus, the

A new algorithm for the detection and delineation of surface water bodies based on high spatial resolution airborne VNIR imaging spectroscopy data has been developed. In contrast to existing methods the proposed approach does not require *a priori* knowledge nor user input, manual thresholding or fine-tuning of input parameters and is able to automatically detect and delineate surface water bodies with a very high accuracy. Thus, the developed algorithm is suitable for implementation in automated processing chains. The algorithm was tested on different sensor data (AISA Eagle and HyMap), works for different types of landscapes (tested: urban, rural and coastal) and is not influenced by different atmospheric correction methods (tested: ATCOR-4 (Richter, 2011), MIP (Heege & Fischer, 2004), ACUM-R (unpublished in-house development by K. Segl), the method of L. Guanter et al. (Guanter *et al.*, 2009), and empirical line correction). Future issues will be to improve the detection of small and narrow water bodies, the detection of white water and of water under shadow. Furthermore, the proposed method will be tested on hyperspectral VNIR satellite data.

This work was made possible by several flight campaigns carried out by the Deutsches Zentrum für Luft- und Raumfahrt (DLR) Oberpfaffenhofen, Germany. We further thank the people of the Geomatics Lab of the Humboldt University of Berlin for providing the HyMap data of Berlin. We also acknowledge financial support for AISA flight campaigns at Helgoland of the BIS Bremerhaven and the WFB Bremen in the framework of the projects

Alesheikh A.A., A. Ghorbanali & N. Nouri (2007). Coastline change detection using remote

Buiteveld H., J.H.M. Hakvoort & M. Donze (1994). The optical properties of pure water. In: *Ocean Optics XII Proc. Soc. Photoopt. Inst. Eng.*, Vol. 2258, 174-183 pp. Bukata R.P., J. Jerome, K.Y. Kondratyev & D.V. Pozdnyakov (1991). Optical properties and

Bukata R.P., J. Jerome, K.Y. Kondratyev & D.V. Pozdnyakov (1995). *Optical properties and remote sensing of inland and coastal waters*. CRC Press, Boca Raton, FL

sensing. *International Journal of Environmental Science and Technology*, Vol. 4, No. 1,

remote sensing of inland and coastal waters. *J. of Great Lakes Res.*, Vol. 17, pp. 461-

water-shadow separation (section 4.3.1) and is still an open issue for the future.

algorithm seems to be robust and generalizes well to unknown datasets.

site Mönchsgut.

**6. Conclusion** 

**7. Acknowledgement** 

'Innohyp' and 'CoastEye'.

pp. 61-66

469

**8. References** 


**0**

**2**

<sup>1</sup>*Universidade Federal de Minas Gerais*

<sup>2</sup>*Instituto Inhotim*

*Brazil*

**Remote Sensing for Mapping and Monitoring**

**Wetlands and Small Lakes in Southeast Brazil**

Philippe Maillard1, Marco Otávio Pivari2 and Carlos Henrique Pires Luis1

Wetlands and small lakes are areas with great ecological value that are increasingly threatened through excessive pressure on water resources. In some cases, this pressure can lower the aquifer and result in a significant reduction of the area of small lakes or the drying out of wetlands. In other cases, logging, road building and other degradations of the surroundings of lakes can increase nutrients loads that reach the water and alter the state of these lakes towards eutrophication and reduction of the open water surface through colonization by aquatic plants. The first requirement to help protect these areas is a thorough mapping and monitoring of the changes that affects them: past, present and future. Many of these areas are poorly known and have not been mapped thoroughly and most have never been monitored. Remote sensing is the only effective means to perform both tasks by enabling rapid mapping of their situation both past and present. While images from the recent generations of Earth observing satellite and sensors come in a wide range of spatial resolution up to about half a meter, historical data at medium-scale resolution can provide a record of past situations and

This chapter is dedicated to the description of methods for the cartography of small lakes using high-resolution data for actual or near-actual mapping and medium-resolution historical data for determining the evolutionary path of these areas in the last three decades. In particular, the accent is given to two distinct approaches: 1) the use of region-based unsupervised segmentation and classification to delineate small lakes, and 2) multi-temporal image analysis of long sequences of images to assess changes of both small lakes and wetlands

It as been observed in the Brazilian Pantanal, that the process of aquatic plant succession starts with the emergence of free floating macrophytes followed by colonization of epiphytes. The latter can be subtituted by paludian plant of higher stature. Eventually, if this process is pursued without interruption, it can culminate by the emergence of floating island and the constitution of an organic soil (Pivari et al., 2008; Pott & Pott, 2003). Pantanal wetlands are subject to alternate flooding and drought that cause these floating islands to drift with the current and wind or to dry out causing the death of its vegetation (Junk & Silva, 1999). Conversely, in the "Rio Doce" lake system of the present study (Figure 1), the water level is

communities. Two case studies are described to illustrate these methods.

**2. First case study: The Rio Doce lake system**

**1. Introduction**

help determine an evolutionary trend.

