8/2/2019 Poster 4th Symposium in GIS Aquatic Sciences 2008 Rio

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INTEGRATED COASTAL ZONE MANAGEMENT: USE OF GEOGRAPHICAL INFORMATION SYSTEMAS A TOOL FOR CHARACTERIZATION OF SEA SHRIMP FARM AREAS IN SOUTHERN BRAZIL

Rodrigo Randow de FREITAS 1/, Carlos HARTMANN 2/, Lus Henrique da Silva POERSCH 3/ and Paulo Roberto Armanini TAGLIANI1/3/ Universidade Federal do Rio Grande, Estao Marinha de Aquacultura, RS, Brazil. 1/(rodrigorandow@ig.com.br) 3/(lpoersch@mikrus.com.br)

2/ Universidade Federal do Rio Grande, LOG/DGEO/FURG, RS, Brazil. (dgecaco@furg.br)4/ Universidade Federal do Rio Grande, Laboratrio de Gerenciamento Costeiro, RS, Brazil. (paulotagliani@furg.br)

Figure 3 Land cover maps of the study.

* Shrimp farms soil type:HAQd1 = Coastal Dunes; HGPe= Champaign; SK = Floo d areas; HGPe2 = Low land with watercourses.(d) draining; (e) erosion; (c) climate; (u) water excess; e (s) ground limitations.

Legend

Restinga

Salt marsh

Swamp

vegetation

Coastalfields

Dunevegetation

Agriculture-

Onion

399870L

6448286s

398429L

6446954s

Figure 2 - Shrimp farm 5 area.

he present study performed the identification of licensed and operating farms, based on the available images (ADAR 1000, Landsat TM and ETM+ and Googlearth). Afterwards, images were overlapped in layers in order to characterize the stage, form of occupation and soil use of the aquaculture enterprises. With thenalysis and interpretation of the images, it was possible to map and survey the areas occupied by the carciniculture activity at the Patos Lagoon estuary.

Study area:The study area corresponded to the municipal districts of Rio Grande and So Jos do Norte, located at the Southern portion of the Patos Lagoon

estuary (3100'N and 5116'W) and comprising an area of approximately 10144 km (Figure1).

Results & discussion:Amongst all the obtained results, we can detach that the farms were built on coastal fields or obliterated dunes areas, which are favorable for farming.

The proximity of possible consuming markets and local labor, relatively good access roads, available electric network and local technical support (FURG-EMA)are also favorable to the projects. However, there is concern as to changes in the original projects, causing environmental impacts and noncompliance ofenvironmental norms. An example is the occupation of a salt marsh area near to shrimp farm 5 (Figure 2); this habitat is legally protected by law and playsmportant ecological and economical functions, such as structural protection of the coast against erosion, hydrological regulation and habitats for biota.

The soil use capacity map (Figure 3) aimed towards proving if the opportunity cost was the lowest possible (soils preferably above class V). Becausehe best option for farm construction must contemplate adequate areas, while preserving noble soils for agriculture. Therefore, conflicts of use and continuity

of food production, a problem of worldwide order, are avoided. In terms of farm locations, it was evidenced that all farms were above class V, confirming thathe locations had been chosen in a sufficiently satisfactory manner.

Concerning the obligation of a 15 meters-distance reserve away from public domain roads, in farm 6 it was not adopted. Fact which provoked sanctionsby the local environmental agency. The evidence of irregularity was detected only in loco, due to the fact that the available images (ADAR1000, Landsat andGoogle Earth) are previous to the installation of the enterprise. Again, this fact demonstrates that the conjunction of the analysts experience allied toechnological advances (software and hardware) does not exempt it of errors in interpretation. Therefore, there is nothing more necessary than the in loco

verification of the areas.

Conclusions: The organization of the diverse methods of information acquisition,management tools, information searches and analysis in only one data base generatedimportant understanding of the study area and the inherent characteristics of the localactivity. This fact will help especially in a future study, for classification of areas inbetter conditions for the implantation of new farms which will generate minoreconomical and environmental impacts, productivity increase and conservation of theareas sensible to environmental alterations.

Shrimp Farm 5Shrimp Farm 5 Shrimp Farm 6Shrimp Farm 6Shrimp Farm 6 Shrimp Farm 6 Shrimp Farm 5 Shrimp Farm 6 EMA-FURG Green House Shrimp Farm 2 Shrimp Farm 2

Financial Support: CNPQ (CT-HIDRO) 552947/2007-5.

ADAR1000

RS

6438455s

421655L374260L

6480123s

SJN

4

5

6RG

PatosLagoonEstuary

(1-7)ShrimpFarmAreas

(RG)RioGrandecity

(SJN)SoJosdo NorteCity

(RS)RioGrandedo SulState

1

2

3

7

Atlantic

Ocean

UniversalTransversalMercator(UTM)Projection

Ricoh

ADAR1000

ADAR1000 ADAR1000

Google Earth

Ricoh

Google Earth

Google Earth

Google Earth

31 5440.27S 52 0100.01W

31 5537.14S 52 0020.05W

31 5620.61S 51 5957.71W

32 0540.00S 52 0320.00W32 0622.20S 52 0354.19W

32 0311.00S 52 1427.00W

31 5509.00S 52 0839.00W

Figure 1. Study area