# Remote Sensing for International Peace and Security: Its Role and Implications
## 3 Results  
### Remote Sensing for Refugee Relief Operations  
Mapping displaced zones and refugee camps are vital to relief operations. The satellite data to map and monitor inaccessible conflict-riddled areas for relief work activities has been used by the United Nations High Commissioner for Refugees (UNHCR). It allows for tracking the affected communities and physical as well as environmental impact on the infrastructure at the refugee camps. For instance, the Sudan conflict left more than 2.5 million people displaced internally and approximately 600,000 refugees outside the country. Similarly, 5.5 million displaced Syrians were registered by UNHCR in Lebanon, Turkey, Jordan, Egypt, and Iraq. Furthermore, about 33,000 Syrian refugees were related in North Africa. According to UNHCR, to provide data on refugees-related numbers, food, and logistics, precise land use and individual refugee tents and buildings in the camp have been mapped. [PERSON] et al. [42] and [PERSON] et al. [43] have employed European Remote Sensing satellite (ERS) and commercial very high spatial resolution (VHSR) satellite data from the Russian KVR-1000 sensor to demonstrate the pre-operational use of satellite remote sensing techniques. It helped in appropriately planning the strategies at the refugee camps. High-resolution is used for automatic mapping of refugee tents and camps by applying object-based image analysis [44]. Figure 4 shows the mapped tents of Al Zaatari refugee camps in Mafraq Governorate, Jordan using satellite images. As of 3 January 2013, a total of 11,966 shelters were detected within the 314 ha of the camp (Figure 3(a)). By 4 May 2013, a total of 28,243 shelters were detected within the 530.95 ha of the camp (Figure 3(b)), indicating that the number of shelters increased by about 16,000. Previously, United Nations Institute for Training and Research (UNITAR)/UNITAR's Operational  
Figure 3: An increasing trend of the role of remote sensing in international peace and security. Satellite Applications Programme (UNOSAT) found that the number of shelters is about 5138 on 15 November 2012. Thus, the shelters in the camp increased by 450% within less than five months. Besides, the total area of the camp grew from 216 hectares to 531 hectares in the same period, which is a 146% increase. This information, together with the data on the number of people living in each tent, is especially critical for assessing the food and medical aid. The number of refugees in each shelter can be inferred by the size of the structures and total population by multiplying the number of shelters in each camp [45]. Nevertheless, there are difficulties in practice on object detection from medium-coarse resolution data. According to [PERSON] et al. [46], the following challenges are typical in refugee shelter mapping: (i) higher range of variation among refugees locations, (ii) small and clustered close-together shelters, and (iii) a higher log of accuracy is required owing to the critical decision support demanded. Automated machine learning models, such as Mask-Region Based Convolutional Neural Network (RCNN), can detect refugee settlements from high-resolution satellite images with an average Area Under the Curve (AUC) of 0.78 [46]. Apart from the relief operations, the satellites also aid site selection by providing baseline information of the terrain for refugee camps and also by identifying favorable areas with access to drinking water and firewood. Images acquired from high-resolution satellite data can help in monitoring environmental degradation due to the movement of displaced persons from the conflict area. For instance, PlanetScope data shows an increase in the built-up area near the Kutupalong refugee camp in Cox's Bazar, Bangladesh. Figure 5a,b show the PlanetScope images acquired on 25 November 2016 and 15 November 2020, respectively. The development of the 32 Km\({}^{2}\) of Rohingya refugee camps destroyed also harmed biodiversity.