**4. Conclusions**

422 International Perspectives on Global Environmental Change

**5 101520253035 -- 2 7 121722273237 -- 1 6 11162126313641**

**260 e. Ramagundam**

**190**

**200**

**210**

**220**

**BTD**

**230**

**240**

**250**

**BTD**

**1999 2000 2001 Day**

**5 10 152025303540 - 2 7 12172227 32 - 1 6 1116 2126313641**

**1999 2000 2001 Day**

The correlation co-efficients between soil wetness and brightness temperature along with the regression expressions for the selected stations for south-west monsoon period (June to September) of 1999 to 2001 are given in Table.2. The degree of relation between soil wetness and BT is an inverse one i.e as the soil wetness increases, BT decreases and vice versa. Anantapur showed minimum correlation of -0.42 while Ongole recorded the maximum

A regression model is developed by taking all the data points of BT and soil wetness from June 1999 to August 2001 to determine the soil wetness using BT over Andhra Pradesh(Figure 14). the correlation in this case is -0.61 which is at 0.01 level of significance

Fig. 13. NDVI and soil wetness – S-W monsoon season of 1999 to 2001

**0**

**0**

correlation of -0.63 compared to the remaining.

and the regression expression is given in the table.

**20**

**40**

**Soil wetness(%)**

**60**

**80**

**100**

**20**

**40**

**60**

**Soil wetness(%)**

**80**

**100 d. Ongole**

It is reported by the scientific community that there is a significant climate change and variability from which one has to learn lessons on how to tackle it. The importance of the rate of climate change can be understood by comparing the affected systems. Satellite-based observations provide a key source of data at global scales of the earth's environment, climate change, and the provision of climate services. However, observational data collected from satellite should be integrated with in-situ data. In many developing countries, a key constraint is the lack of professional and institutional capacity to make the best use of available information and knowledge for decision making. A particular difficulty is providing incentives to attract qualified staff to remote areas, far away from capital cities, where good decision making often is most critical. Local/national networks are useful for taking cognizance of local hotspots and making operational decisions on issues that relate to

Strengthening Regional Capacities for Providing Remote

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Barbosa, H.A. Vegetation dynamics over the Northeast region of Brazil and their

Barbosa, H.A. Spatial and temporal analysis of vegetation index derived from AVHRR-

os eventos El Niño-Oscilação Sul (ENOS), *Revista Brasileira de Meteorologia*, São

region of Brazil and its relationship to ENSO events. *8th International Conference on Southern Hemisphere Meteorology and Oceanography*, 24-28th April, 2006, Foz de

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NOAA and rainfall over Northeastern Brazil during 1982-1985. *Master degree dissertation in Remote Sensing* [in Portuguese]. Divisão de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espacias, São José dos Campos-SP, Brazil, 1998. Boulanger, J.-P., J. Leloup, O. Penalba, M. Rusticucci, F. Lafon and W. Vargas (2005)

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Higgins G M & Kassam A H (1981), *The FAO* agro-ecological zone approach to

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climate variability and change, while global change studies with satellite-based measurements are useful for international comparative assessments. In this context, it ought to strengthen the regional capacities towards decision making about the forthcoming frequent disasters due to climate change. As a result, decision making in the land surface resources could be improved through: i) developing information systems on areas that are prone to drought, and vulnerable to disasters, ii) long term understanding on land degradation because of deforestation and increased urbanization, iii) developing disaster preparedness in view of risk management, iv) development of early warning systems by utilizing the real time satellite data, to mitigate disasters like floods etc, v) assessment of crop failures during early, mid and late seasons, so as to prefix the mitigation measures and vi) educating communities about climate change and variability for better linkage of satellite data with the ground level ones for effective monitoring of drylands.

The use of satellite data into land resources decisions must be driven by the needs of the decision makers. Incorporation of satellite data by the land surface resources community requires an understanding of the particular decisions that are faced and the relevant timescales and skill needed to provide decision support. This can only be accomplished through close collaboration between operational land managers and decision makers. Researchers will not have a sense for whether this is true without understanding the needs of the user community which is achieved through close collaboration. Case studies of the incorporation of satellite land surface techniques, in combination with in-situ data, at international level are needed. In view of the above, the present chapter deals with the utilization of satellite data in i) understanding the vegetation dynamics, ii) vegetation response to climate, iii) connection with the agroclimatic indices and iv) underlying land surface processes. The established relations drawn from this chapter are of immense use in studying arid lands from the remote sensing point of view. Since the satellite indices (NDVI & BTD) are proven as the best variables, in accordance with the agrometeorological indices such as rainfall, soil moisture adequacy and soil wetness, they serve as inputs for policy makers. The relation of Brightness Temperature with soil wetness can be applicable in deciding the water supplement of a region. The crop phenological stages that can be studied by NDVI are of great use in assessing the crop health (fair / optical / poor). The response of NDVI to weather can guide in the designing of the agrometeorological advisories. Thus, the provision of remote sensing decisions over drylands will be strengthened by analysing the satellite data carefully can help in the improvising of systems where such satellite derived data can be used for multiple operations. The "lessons learned" from such studies provides critical guidance for enhancing the monitoring of the effects of climate change on land resources, through exploitation of satellite data. Another valuable impact is the enhancement and broadening of international research partnerships in order to encourage scientific exchange.

#### **5. References**

Aber, J.D (1997) Why don't we believe the models, *Bulletin of the Ecological Society of America*, *78*, 232-233.

Ahmed N.U (1995) Estimating soil moisture from 6.6GHz dual polarization and / or satellite derived vegetation index, *International Journal of Remote Sensing*, 16, 4, 687 – 708.

Al-Bakri, J.T & Suleiman, A.S (2004) NDVI response to rainfall in different ecological zones in Jordan, *International Journal of Remote Sensing*, 25(19), 3897-3912.

climate variability and change, while global change studies with satellite-based measurements are useful for international comparative assessments. In this context, it ought to strengthen the regional capacities towards decision making about the forthcoming frequent disasters due to climate change. As a result, decision making in the land surface resources could be improved through: i) developing information systems on areas that are prone to drought, and vulnerable to disasters, ii) long term understanding on land degradation because of deforestation and increased urbanization, iii) developing disaster preparedness in view of risk management, iv) development of early warning systems by utilizing the real time satellite data, to mitigate disasters like floods etc, v) assessment of crop failures during early, mid and late seasons, so as to prefix the mitigation measures and vi) educating communities about climate change and variability for better linkage of satellite

The use of satellite data into land resources decisions must be driven by the needs of the decision makers. Incorporation of satellite data by the land surface resources community requires an understanding of the particular decisions that are faced and the relevant timescales and skill needed to provide decision support. This can only be accomplished through close collaboration between operational land managers and decision makers. Researchers will not have a sense for whether this is true without understanding the needs of the user community which is achieved through close collaboration. Case studies of the incorporation of satellite land surface techniques, in combination with in-situ data, at international level are needed. In view of the above, the present chapter deals with the utilization of satellite data in i) understanding the vegetation dynamics, ii) vegetation response to climate, iii) connection with the agroclimatic indices and iv) underlying land surface processes. The established relations drawn from this chapter are of immense use in studying arid lands from the remote sensing point of view. Since the satellite indices (NDVI & BTD) are proven as the best variables, in accordance with the agrometeorological indices such as rainfall, soil moisture adequacy and soil wetness, they serve as inputs for policy makers. The relation of Brightness Temperature with soil wetness can be applicable in deciding the water supplement of a region. The crop phenological stages that can be studied by NDVI are of great use in assessing the crop health (fair / optical / poor). The response of NDVI to weather can guide in the designing of the agrometeorological advisories. Thus, the provision of remote sensing decisions over drylands will be strengthened by analysing the satellite data carefully can help in the improvising of systems where such satellite derived data can be used for multiple operations. The "lessons learned" from such studies provides critical guidance for enhancing the monitoring of the effects of climate change on land resources, through exploitation of satellite data. Another valuable impact is the enhancement and broadening of international research partnerships in order to encourage

Aber, J.D (1997) Why don't we believe the models, *Bulletin of the Ecological Society of America*,

Ahmed N.U (1995) Estimating soil moisture from 6.6GHz dual polarization and / or satellite derived vegetation index, *International Journal of Remote Sensing*, 16, 4, 687 – 708. Al-Bakri, J.T & Suleiman, A.S (2004) NDVI response to rainfall in different ecological zones

in Jordan, *International Journal of Remote Sensing*, 25(19), 3897-3912.

data with the ground level ones for effective monitoring of drylands.

scientific exchange.

*78*, 232-233.

**5. References** 


**21** 

*Greece* 

**Using Fuzzy Cognitive Mapping in** 

**Management: A Methodological** 

Elpiniki Papageorgiou1 and Areti Kontogianni2

*Department of Informatics and Computer Technology, Lamia,* 

*2University of Aegean, Department of Marine Sciences, Mytilini, Lesvos,* 

Widespread concerns over the integrity of natural ecosystems worldwide have initiated numerous attempts at developing new tools of monitoring present conditions, assessing future risks and visualizing alternative futures. Reports on the 'state of the world' abound and so do policy proposals and sustainability strategies. Amidst this plenty of ideas, our ability to reverse the trend and secure a safe, minimum stock of valuable natural capital seems counterproductive. A better understanding of ecosystem dynamics at both the quantitative (biochemical cycling) as well as the qualitative (ecological structure of food webs) levels, without artificial divisions between them, is needed. We also need to understand better the institutional failures leading to a growing number of 'tragedies of the

To tackle these challenges appropriately, current environmental management strategies need to 'navigate' through an apparent tension: On the one hand they must meet the demand for scientific knowledge-based policy, expressed under the motto 'science speaks to policy'. On the other hand, the very same strategies urge for stakeholder involvement and sponsor initiatives to elicit lay-people attitudes, beliefs and visions for the future. This tension seems to reflect the ever lasting stand-off of bottom up and top down approaches. The motivation for this chapter comes from the authors' uneasiness with the present methodological arsenal in the domain of environmental stakeholder analysis. Previous research on non-market valuation of environmental assets has shown the importance of complementing the neoclassical microeconomic framework of choice in stated preference surveys with qualitative - both ex ante and ex post – analysis of individual mental processes, perceptions and beliefs (Kontogianni et al, 2001, 2005, 2008). Especially applications of contingent valuation have benefited from in-depth interviews and focus groups conducted ex ante in order for the researcher to understand the cultural, social and psychological background of choices elicited through structured interviews. (Desvousges & Smith 1988, Brouwer, 1999). In spite though of the importance of stakeholder qualitative analysis in

**1. Introduction** 

commons'.

**Primer and an Application** 

*1Technological Educational Institution of Lamia,* 

**Environmental Decision Making and** 

