Submit here a draft of the last section, where you describe how they have or how they could take into consideration multicultural perspectives when solving the natural resource problem. What tools did they or could they use? What does the implementation of the tool look like? What are the expected outcomes of applying the tool? will provide brief feedback to let you know if you’re on the right path.
Please note, that this is a procedural question, not a determination of the management policy itself. For example, I’m not looking for your suggestion of who should have access to how many fish. | am looking for how the managers would go about determining the needs of the different stakeholders to make this decision. Consider whether they could or did use one of the tools introduced this week: (but please note this is far from an exhaustive list of options – the process should match the needs of the context)
Values and land use mapping
Human Wellbeing monitoring
Week 8 | Draft 2 of Final Paper: Tool Section
With a mix of farming, forests, grasslands, wetland regions, and urban areas, Africa is one of the continents with the most varied land uses. More than 50% of the continent is covered by grassland and forests combined (Carrillo-Niquete et al., 2022). The remaining 32.4% of the land area is made up of “other land,” which includes deserts and arid, unproductive regions.
In terms of total forest area, Africa is the third largest continent in the World. This forest is primarily found in the continent’s central and southern tropical nations. Because of its second-largest rainforest, which covers an area five times the size of France and is believed to be 152 million hectares in size, the Congo Basin has earned the moniker “lungs of the earth.”
In addition, 66% of Africa is categorized as dryland. Due to the hot, dry climate that predominates in these desert regions, only around 17% of the territory is covered with trees (Uning et al. 2022). While global deforestation has declined recently, it has been steadily increasing in Africa since 1990, which has reduced that continent’s ecosystem’s capacity to withstand climate change. Indeed, trees are essential to maintaining a thriving ecosystem. They serve as watersheds, prevent soil erosion, control the local temperature, and gather greenhouse gases, which are crucial in the effort to combat global warming (Gallwey et al. 2022). But what are the primary reasons for deforestation in Africa, and how can it be prevented from having such terrible effects?
“Satellite land monitoring system” is one type of technology that might be used to monitor suburban deforestation in South Africa.
For the World, satellites photograph the whole World every day. The best images from a particular month are stitched together to create a clean, cloudless mosaic. These monthly mosaics allow users to see the places of deforestation and how it has changed over time.
Advantages of using “Satellite land monitoring system”
The “Satellite land monitoring system” has the advantages of characterizing natural features or actual physical objects on the ground, gathering information over vast spatial areas, regularly observing surface areas and objects, tracking changes over time, and combining this information with other data to assist decision-making. At various geographic resolutions, information from “satellite land monitoring systems” can be acquired from aircraft or satellites. Features that are tens to hundreds of metres or bigger than those observed in moderate or lower resolution photos can be detected in “satellite land monitoring system” images. High-resolution images are capable of resolving minute details, which are typically less than a metre in size. Additionally, “satellite land monitoring system” equipment may gather information in different electromagnetic spectrum spectral bands. This information might be used, for example, to help categorize and name plants. The thermal infrared band data is particularly beneficial for water management. Light Detection and Ranging (lidar) device data on topography may be used to create digital elevation models.
National Forest Monitoring Systems (NFMS) may gather data from satellite observations to study suburban deforestation in Africa and generate reliable data on the forest resources that can be utilized to develop long-term national forest policies and goals. Systems for monitoring forests are designed to yield high-quality, reliable data on forests, including estimates of their carbon stocks. One component of these systems is called measurement, reporting, and verification (MRV). These statistics are crucial in the battle against climate change brought on by deforestation and forest degradation.
The satellite measurements will also provide the following data:
Satellite Land Monitoring Systems (SLMS) and other data collection, as well as National Forest Inventories (NFI) and
Other data collections that provide information on Emission Factors provide information on Activity Data (AD).
The findings will help the government appreciate the concept and issue of deforestation. The result will also help them to understand the pattern and, subsequently, the reason behind this predisposition. Furthermore, it will help the government develop focused solutions to the current problem. The results will aid the government in fully understanding the idea and problem of deforestation. The outcome will also assist them in comprehending the pattern and, consequently, the cause of such a propensity. Additionally, it will assist the authorities in formulating targeted, specialized reactions to the present crisis.
Abulude, F. O., Abulude, I. A., Oluwagbayide, S. D., Afolayan, S. D., & Ishaku, D. (2022). Air Quality Index: a Case of 1-Day Monitoring in 253 Nigerian Urban and Suburban Towns. Journal of Geovisualization and Spatial Analysis, 6(1), 1-13.
Carrillo-Niquete, G. A., Andrade, J. L., Valdez-Lazalde, J. R., Reyes-García, C., & Hernández-Stefanoni, J. L. (2022). Characterizing spatial and temporal deforestation and its effects on surface urban heat islands in a tropical city using Landsat time series. Landscape and Urban Planning, 217, 104280.
DE FREITAS, L. S. (2021). Remotely-sensed estimate of groundwater recharge and its correlation with deforestation and fire in eastern Bolivia (Doctoral dissertation, Universidad Católica Boliviana).
Deribew, K. T. (2020). Spatiotemporal analysis of urban growth on forest and agricultural land using geospatial techniques and Shannon entropy method in the satellite town of Ethiopia, the western fringe of Addis Ababa city. Ecological Processes, 9(1), 1-16.
Gallwey, J., Robiati, C., Coggan, J., Vogt, D., & Eyre, M. (2020). A Sentinel-2 based multispectral convolutional neural network for detecting artisanal small-scale mining in Ghana: Applying deep learning to shallow mining. Remote Sensing of Environment, 248, 111970.
Uning, R., Latif, M. T., Othman, M., Juneng, L., Mohd Hanif, N., Nadzir, M. S. M., … & Takriff, M. S. (2020). A review of Southeast Asian oil palm and Its CO2 fluxes. Sustainability, 12(12), 5077.