69 Tyukavina, A., Baccini, A., Hansen, M.C. et al. (2015). Aboveground carbon loss in natural and managed tropical forests from 2000 to 2012. Environmental Research Letters 10: 074002. https://doi.org/10.1088/1748‐9326/10/7/074002.
70 UN Climate Summit (2014). The New York Declaration on Forest: Action Statements and Action Plans, Climate Summit 2014. New York, USA: United Nations.
71 van Noordwijk, M., Agus, F., Dewi, S., and Purnomo, H. (2014). Reducing emissions from land use in Indonesia: motivation, policy instruments and expected funding streams. Mitigation and Adaptation Strategies for Global Change 19: 677–692. https://doi.org/10.1007/s11027‐013‐9502‐y.
72 Venter, O. and Koh, L.P. (2012). Reducing emissions from deforestation and forest degradation (REDD+): game changer or just another quick fix? Annals of the New York Academy of Sciences 1249: 137–150. https://doi.org/10.1111/j.1749‐6632.2011.06306.x.
73 Verstegen, J.A., van der Laan, C., Dekker, S.C. et al. (2019). Recent and projected impacts of land use and land cover changes on carbon stocks and biodiversity in East Kalimantan, Indonesia. Ecological Indicators 103: 563–575. https://doi.org/10.1016/j.ecolind.2019.04.053.
74 Verchot, L.V., Petkova, E., Obidzinski, K. et al. (2010). Reducing Forestry Emissions in Indonesia. Bogor, Indonesia: Center for International Forestry Research (CIFOR).
75 Zarin, D.J. (2012). Carbon from tropical deforestation. Science 336: 1518–1519. https://doi.org/10.1126/science.1223251.
76 Zarin, D.J., Harris, N.L., Baccini, A. et al. (2016). Can carbon emissions from tropical deforestation drop by 50% in 5 years? Global Change Biology 22: 1336–1347. https://doi.org/10.1111/gcb.13153.
77 Zhuravleva, I., Turubanova, S.A., Potapov, P.V. et al. (2013). Satellite‐based primary forest degradation assessment in the Democratic Republic of the Congo, 2000–2010. Environmental Research Letters 8 https://doi.org/10.1088/1748‐9326/8/2/024034.
2 Role of Geospatial Technologies in Natural Resource Management
Abhishek K. Kala1 and Manoj Kumar2
1 Advanced Environmental Research Institute, University of North Texas, Denton, TX, USA
2 GIS Centre, Forest Research Institute, PO New Forest, Dehradun, 248006, India
2.1 Introduction
Natural resources are essential to a nation's economy as they are a source of food, energy, medicine, and raw materials for industries. The ever‐increasing human population has overstretched the use of these natural resources, thus creating pressure on existing forest cover, increasing human‐wildlife conflicts, and creating desert‐like conditions. The depletion of our limited resources has led to changes in local weather patterns, apart from declining benefits in terms of social, economic, and cultural aspects of utilizing these resources. Therefore, it is crucial to understand how to use these resources sustainably to ensure that future generations enjoy their benefits (Oisebe 2012). Sustainable resources development plan starts with the assessment of the natural resources' availability. The assessment process involves four essential functions:
1 Mapping: the collection of qualitative and quantitative data in the spatial format.
2 Measuring: the process of quantifying the attributes of a phenomena and documenting them.
3 Modeling: the process of representing a phenomenon through a set of mathematical equations and simulating the past, present, or future behavior.
4 Monitoring: the routine assessment of the conditions by recording natural phenomena and human activities changes.
Geospatial assessment supported by the Geographic Information System (GIS), Remote Sensing (RS), and Global Positioning System (GPS) caters for compelling techniques of mapping, monitoring, surveying, classification, characterization, and change detection of natural resources. These techniques provide a platform for generating valuable data, creating cartographic products, and performing timely analysis to make sound sustainable development decisions. Remote sensing involves the recording of information distantly without coming in contact with the object using the various electromagnetic spectrum. It employs the use of cameras, lasers, scanners, and specialized sensors that are located on the ground or aerial platforms (Jensen and Im 2007). The principle geospatial components of a study are derived using various methods such as aerial photographs, satellite imaging, Light Detection and Ranging (LiDAR) data, Unmanned Aerial Systems (UAS)/Drone data, GPS survey, etc., based on the study's objective. Figure 2.1 displays different remote sensing components for collecting NRM data. Remotely sensed data captured through different satellites and other platforms such as drones platforms has wide applications in natural resource management disciplines. Multiple data from various sources also serve as input for other environmental models (Melesse and Graham 2004). The combined use of GIS, remote sensing data, and GPS has enabled researchers and natural resource managers to establish management plans for various applications (Philipson et al. 2003). The rest of this chapter will focus on multiple geospatial technologies and their application in different natural resource management areas.
Figure 2.1 Different components of remote sensing used for collecting a wide range of information. Based on Manfreda et al. (2018).
2.2 Applications of Geospatial Technology in Natural Resource Management
2.2.1 Forest Management
Forests are critical habitats for a variety of living organisms and provide multiple ecosystem services. Despite their crucial role in the ecosystem, many countries are experiencing forest degradation, deforestation, and impacts at different levels due to various geographically distributed factors. Geospatial technology can be utilized to generate information for forest cover, forest types, the extent of human encroachment into forested areas, and monitoring the progression of desert‐like conditions. This information is vital for developing forest management plans and to develop a decision support system that can be used effectively for the sustainable use of natural resources. A multicriteria analysis approach using remote sensing data can also be used for site suitability analysis of important plant and animal species. Some recent studies utilizing geospatial technologies for natural resource management include the studies by Bogdanov et al. (2018), Kumar et al. (2019a,b,c), Olokeogun and Kumar (2020), Pokhriyal et al. (2020), Polevshchikova (2019), Rasooli et al. (2018), San Juan and Domingo‐Santos (2018), Shrestha (2020), Singh et al. (2020), and Singh et al. (2020a,b). A flow diagram of geospatial techniques for forest management and forest health mapping is shown in Figure 2.2.