4  Policy

4.1 Summary

Rasjahi is one of the major urban centers in Bangladesh with a population of around 500,000 people. It is located in the west of the country on the Indian-Bangladesh border and part of the Barind Tract, an area that experiences hot and dry climate. The most pressing climate challenges in the city are flooding during the monsoon season due to a poorly designed and maintained drainage system as well as extreme and dangerous heat.

According to the Word Health Organisation, heatwaves are among the deadliest climate risk globally. In fact, more than 166,000 people died due to extreme temperatures between 1998-2017. (WHO 2024) In cities heat stress can be exacerbated due to so called urban heat island effects (UHI). UHI is a phenomenon where urban areas experience higher temperatures compared to their surrounding rural areas due to human activities and the way the city is built (e.g. heat retention in buildings, infrastructure, sealed surfaces). With climate change temperatures in Bangladesh are expected to increase and extreme weather events, such as heat waves, are expected to become more frequent and more intense.

At the national level, the Government of Bangladesh has acknowledged the risk posed by increasing heat. In its National Adaptation Plan from 2023 (NAP), heat features as an adaptation priority for urban areas. One of the action items in the urban area strategy of the NAP is to develop “heatwave and disease outbreak advisory services for city dwellers”. No further guidance on how to tackle heat in cities is given and it is up to the local level governments to improve heat risk planning. City budgets in Bangladesh tend to be very small, mainly dependent on national government funding transfers. It is often Multilateral Development Banks or donors, who finance urban plans or strategies, as part of the preparation of larger loan programs.

At the local level in Rajshahi, the City Cooperation has understood the importance of including climate change related hazards, including heat, into urban management. In recent years they have developed three important plans:

  1. A Masterplan that incorporate climate change issues (not publicly available, therefore will not discuss further),
  2. The city government worked with ICLEI to develop a Climate Resilient Action Plan (CAP), and with
  3. the Red Cross Climate Center to develop a heat threshold assessment for Rajshahi.

The ICLEI CAP provides a high level climate risk assessment. It describes UHI as an issue in the city but not spatially. Therefore, suggested mitigation and adaptation actions on heat remain vague.

4.2 Application

The Red Cross Climate Center study expands ICLEI’s work by looking more closely at urban heat in the city and mapping it spatially. The authors used Landsat images between 2010 to 2020 to map Land Surface Temperature in the city to identify heat hot spots and Normalised Difference Water Index (NDWI) and normalized difference vegetation index (NDVI) to analyse the relationship between land-cover changes and urban heat island effect (UHI). The findings are combined with demographic and socioeconomic data to understand vulnerability. However, the demographic and socioeconomic data sets from the national census are only available by ward. To develop specific actions for mitigating and adapting to the identified hotpots, we need data on the neighborhood, street and building level. The study presents some high level policy options for mitigation, including increasing green space, housing retrofit and street design.

Remote sensing data could be used to improve the existing heat vulnerability assessment by identifying specific neighborhoods with poor housing conditions, such as informal settlements, where residents are at higher risk of extreme indoor heat. This would take the Red Cross Climate Center to the next level.

It is likely that Rajshahi does not have high resolution remote sensing data, such a LiDAR data. Therefore, it is important to rely on publicly available data to ensure that the local government could reproduce the study. As demonstrated by Zahra Assarkhaniki, Soheil Sabriand, and Abbas Rajabifard (2021) in a study conducted in Jakarta, Landsat 8, data can be used to identify informal settlements, despite lower resolution. A similar approach could be taken here:

Several recent (e.g. from 2023) cloud-free images of the city should be obtained with a resolution of 30m. The relevant bands include: band 1-coastal aerosol, band 2-blue, band 3-green, band 4-red, band 5-near infrared (NIR), and bands 6 & 7-shortwave infrared (SWIR). The classification of land cover types could be done using Random Forest (RF) classifier combined available survey data of the city’s informal settlements and Open Street Map data. If no survey data exists, the local government could identify known informal areas that can be manually identified on the image and used for training the classifier. The sample should cover approximately 0.25% of the total study area to reach high accuracy. (Zahra Assarkhaniki, Soheil Sabriand, and Abbas Rajabifard 2021)

4.3 Reflection

The identified neighborhoods could be prioritized in investment planning. Incremental upgrading of buildings to reduce indoor temperature or planting of trees in most vulnerable areas could be possible policy options to battle heat stress in an equitable manner, where those most vulnerable are prioritized to achieve more equal living standards across the city.

It is very important to understand vulnerability spatially to take robust planning decisions. Many planning documents, including climate action plans, lack specification in terms of location of specific measures. The ICLEI Climate Action Plan for Rajshahi, for example, suggests increasing green space, but does not specify where.

The goal of planning decisions is usually to maximize the benefit of an investment while minimizing costs (cost benefit analysis). The next step after identifying where informal settlements are would be to understand benefits of specific interventions, e.g. by modelling the effects of tree planting in different locations.