Role of Geospatial Technologies in Circular Agriculture
The concept of the Linear Economy is nothing new: natural resources are used to create products, and products are disposed of when they are no longer useful. This is the conventional economic model, which has no regard for the effects it will have on the environment.
In a linear economy, products are designed to be discarded after use and put profit before sustainability. According to statistics, 68% of input raw materials are non-renewable, which creates a serious environmental risk considering that these items are either exploded or burned.
Because of its singular focus on products as consumables, their mass manufacturing and consumption, which results in the exploitation of people and the environment, this system is doomed to failure.
The alternative? Circular economy.
What is the Circular Economy?
With an ever-growing prominence, circular economic practices have quickly emerged as solutions to the world’s most cross-cutting sustainable development challenges. In contrast to the linear economy, the circular economy’s primary goal is to preserve the added value of raw materials while minimizing waste.
The circular economy emphasizes viewing products as resources instead of consumables alone. It upholds the “reduce, reuse, recycle” model to reduce the harmful effects of production on the environment.
Products are delivered using minimum resources, especially refraining from draining resources. Even outdated and discarded goods are put to their best possible use. Products are recycled or reused to the best of their feasibility rather than being thrown away directly. The pool of resources is thus used more sustainably, and the ecosystem is served more judiciously.
Circular Agriculture: Need, Concept, Characteristics
The environment has suffered greatly because of the recent enormous increase in global food production. Agriculture now occupies around half of the land that is habitable. According to the UN, a third of the world’s forest cover has been lost over the past century due to the rapid expansion of agricultural output, and global freshwater usage has increased six times, more than twice as fast as population growth.
Without adjustments to current unsustainable agricultural and food consumption practices, global CO2 emissions might only treble by 2050.
In this view, Circular Agriculture promotes the use of scientific advancements, innovations, and new technology for sustainable farming. It emphasizes using as little external input as possible, closing nutrient loops, regenerating soils, and reducing environmental impact, according to the United Nations Department of Economic and Social Affairs.
“Applying circular economy principles to the development of the Indian food system could create annual benefits of ₹3.9 lakh crore (US$ 61 billion) in 2050; reduce GHG emissions, water usage, and environmental degradation; and play a vital role in securing the long-term food supply,” according to UNCTAD.
Characterized by more diversity and environment-friendly farming practices, circular agriculture is also linked to better health and nutrition. Some salient aspects of circular agriculture include agroforestry, mixed crop-livestock farming, organic farming, water recycling, and wastewater reuse.
Over time, circular agricultural practices can reduce both resource usage and the negative environmental impacts of farming. It can also bring about a marked decrease in waste, chemical fertilizers, and land exploitation, eventually enabling a significant reduction in world CO2 emissions.
Critical Role of Geospatial Technologies in Realizing the Circular Agriculture Vision
Over the last decade, technological interventions have already made their way into agriculture. Globally, farmers are using Geospatial tools and other cutting-edge technologies to manage their agricultural production and carry out crop predictions.
They are also using it to examine agricultural surroundings, land resources, and workflows visually and determine how to get maximum profit while preserving soil fertility. Due to the availability of open-source satellite imagery by the agencies like ESA & USGS, the time-series analysis of agricultural crops and soil parameters has become easier and faster.
Full Lifecycle Monitoring from Farm to Table
The goal of circular agriculture is to promote sustainable development at every stage of the food system, including producing, harvesting, packaging, processing, transporting, marketing, consuming, and disposing of food.
Crop monitoring systems can use high-level precision ground-based observations and remote sensing data to classify crops, assess their health, map the features of the soil, and keep tabs on farming activities. Geospatial technology also makes it simple to locate areas that are heavily or moderately affected by insects and pests, allowing for the accurate application of fertilizer or pesticide to the afflicted region while minimizing loss.
High-resolution remote sensing imagery along with machine & deep learning algorithms produce robust outcomes pertaining to crop acreage, crop emerging & harvesting dates, and yield. The accurate estimation of crop biomass by applying complex modeling techniques leads to efficient crop health assessment and crop loss assessment in case of any natural calamity. As management practices vary crop-wise and region-wise, remote sensing-based estimates play a vital role in generating advisories for individual farmers.
Global logistics and supply chain management are being transformed by Geospatial technology, which is helping track products, maintain visibility, suggest best and alternate routing, inventory management, and so on.
Precision agriculture techniques allow farmers to determine the most effective use of resources for farming on both small and large scales. The integrated approach involves mapping and tracking every aspect of agricultural output using drones, LiDAR, SAR data, and other tools.
Farmers may make more precise decisions about what resources should be used where and how much using these Geospatial technologies. With this knowledge, they can use resources like water, fertilizer, pesticides, and herbicides judiciously, maximizing production while lowering costs and increasing their profits. Poorer sections of the agricultural population may benefit significantly from increased productivity, employment, and income thanks to Geospatial technologies in precision agriculture.
Soil Health and Condition Monitoring
Global soil fertility has decreased because of an increasing population, limited land resources, and increased usage of chemical fertilizers. A lot of resources are ultimately wasted on underproductive land, or arable land that could have been used for other purposes is misused.
Geospatial technology can be used to pinpoint regions with good soil fertility for agriculture, those where soil fertility could be increased, and those that are completely barren. Based on a specific region, trace minerals and micronutrients can be found to assess a crop’s compatibility.
Crop simulation models, land tenure data, satellite-obtained precipitation data, and historical meteorological data can be superimposed to create predictive models that can help farmers plan their activities. Soil Moisture estimation based on satellite data (especially SAR) along with such predictive models gives the temporal picture of any agricultural area. This can be supplemented by the soil parameters estimation (pH, nitrogen, etc.) using hyperspectral data to assess soil health.
One of the critical components of circular agriculture includes the recycling and reuse of irrigation water. Potential benefits of using wastewater in agriculture include the ability to irrigate an extra 40 million hectares, or 15% of all irrigated areas, as per the UN-DESA, while lowering pollution, promoting water conservation, and providing more resources for recharging aquifers.
Large, irrigated areas can benefit from the development of decision support systems for irrigation water management using Geospatial technologies. In addition to information on crop development stage (Phenology) and health, GIS and Remote Sensing data can be used to determine land use/land cover, crop mapping, and irrigated center pivots.
The temporal Soil moisture estimates (using SAR) can also be used to determine the crop water availability and crop water requirement parameters. The difference between these two parameters is nothing but either surplus or deficiency of the water depending on their values. If crop water deficiency exists, then its temporal modeling depicts an agricultural drought-like situation over a cropping season. This information can be visualized using temporal maps with cadastral boundaries overlaid on them.
Agroforestry is yet another crucial component of circular agriculture, defined as the planting of trees alongside crops or pastures. Planting trees can improve soil fertility with its reuse of organic waste as manure and restore biodiversity to agricultural areas. It can also increase the circularity of agriculture by lowering reliance on synthetic pesticides and fertilizers.
From a financial standpoint, agroforestry can provide more varied goods and a steadier flow of income for farmers, particularly female farmers for whom agroforestry is more accessible.
Geospatial technologies can offer fresh perspectives on how to assess, decide, and create policies for agroforestry resources. Remote sensing is being increasingly employed in agroforestry for mapping the suitability of tree plantations, producing tree species spectral signatures, and mapping their geographical coverage.
Simultaneously, satellite data are being used to provide more precise estimates of gross primary productivity at various scales. Unmanned aerial systems (UAVs) with a variety of sensors like multispectral, LiDAR, hyperspectral, and thermal can offer further accuracy and potential in this aspect. Studies on plant biochemistry, chlorophyll fluorescence, and water stress can be conducted using these advanced datasets in the future to monitor the health of agroforestry systems.
The relevance of circular agriculture for the Indian economy and environment can best be described as pivotal and immediate. India has the second-largest arable land area in the world, with more than half of the population engaged in agriculture and related industries (Census 2011). The segment not just accounts for enormous portions of world production, consumption, and export, but also has a pronounced environmental and ecological impact on the country.
Geospatial technologies along with cutting-edge techniques like data science and machine learning are a critical drivers for “closing the loop” through responsible agricultural practices. Apart from the methods and applications described above, Geospatial technologies can also be leveraged for efficient water and land resource management – equally crucial for sustainable agricultural development.
The need of the hour is to persuade farmers and organizations to adopt innovative agricultural practices on the shoulders of Geospatial technologies that can guarantee them both resource optimization and profitable outcomes. Geospatial technology is bringing about transparency and traceability in supply chains, an overall waste reduction, and maximizing the use of underused assets in alignment with circular agriculture. It is time that both Governments and Users start seeing this as a major return on investment.