GIS and Crop Modeling for Urban Farming Potential

Explore urban farming with GIS, crop models. See how tech boosts rooftop agriculture yield.

How Geospatial Tech and Crop Modeling Are Reshaping Urban Agriculture?  

The increasing global population puts substantial pressure on traditional agricultural systems. This has led to significant interest in novel solutions like urban farming and productive green roofs to help solve problems relating to food security and the environment. The idea of turning rooftops into thriving farms seems very appealing and presents some intriguing possibilities, but practical applications require in-depth planning, detailed knowledge, and strategic planning. Recent advances in geospatial technology alongside the creation of powerful crop simulation models provide us with sophisticated means of evaluating these rooftop agricultural schemes, assisting urban planners and policymakers in creating informed decisions. In this article we will take a look at combining these areas of tech in order to maximise urban farming capacity.

Need for Urban Agriculture  

The world is experiencing unprecedented urbanization and our population is continuing to increase, this translates into higher demands for food in urban areas. This surge has various complications like expansion of cities into vital farmland potentially diminishing overall production. Add into this, evolving diet demands, degrading agricultural land quality, and extensive food waste, and these issues further escalate the pressure on conventional agriculture, placing greater strain on resources. Urban agriculture provides a potential pathway for meeting some of this challenge, integrating food production into urban environments whilst repurposing city waste into nutrients for crop production. The total areas of urban rooftops represent a huge amount of usable space offering substantial possibilities to facilitate local food generation in populated cities.

GIS for Identifying Suitable Green Roof Areas  

The starting point of setting up urban farming capacity lies in being able to accurately evaluate the most ideal spaces within a city for farming activity, and Geographic Information Systems (GIS) plays a vital role in completing this stage. GIS enables urban planners to perform precise mapping and analyses to discover locations of rooftop areas with high potential for green roof conversions. Using the Digital Surface Models (DSM), GIS allows the calculation of slopes, assessment of suitable rooftops, and filtering based on other specific conditions for instance roof surface. Several additional parameters that GIS can be used to assess include:

• Roof Slope Analysis: The identification of rooftop surfaces that do not exceed the required threshold (for instance ≤10 degrees). The lower the angle of a surface the greater the practicality in use for farming due to the ease of constructing containers on flat surfaces.
• Building Footprint Analysis: A look at areas and shapes of rooftop space within individual buildings. Flat areas are most suitable but overall size must also be assessed.
• Surface Characteristics Assessment: Examine of aerial images to accurately confirm locations of the flat surface, and avoid counting surfaces unsuitable due to existing equipment, obstructions, or non-accessible spaces on rooftop.
• Load-bearing Capacity Assessment: The integration of structural info such as building function or build date to allow for additional screening of suitability for converting a roof to urban farm status. This might include industrial and some older constructions, in order to confirm the building could deal with a high weight green-roof system.

All this accurate GIS data assessment significantly increases the efficiency of crop planting and allows for planning with well documented datasets.

Aquacrop for Precise Crop Growth Simulation  

Selecting ideal space to implement crop planting in cities is important, the key is identifying how crops will thrive on a given roof. This stage demands an analysis of the expected yields along with water requirements, and this is where crop modelling solutions such as Aquacrop come into play. The software performs crop yield modeling, simulation in particular of plant responses to soil conditions, weather conditions, water stress and also growth factors, it presents us with several benefits.

• Growth Evaluation of Various Crops: Different crop growth can be simulated under various scenarios that cover things like planting schedule, growth rate and productivity based on each crop’s parameters
• Optimising Water Use: The analysis of a crop model such as Aquacrop also evaluates various irrigation schemes alongside climate forecasts so an informed strategy to best conserve water may be chosen for the urban environment.
• Environmental Sensitivity: Crop models provide ways to understand variations to things like climate by looking at seasonal growth variations, as well as stress related to heat or lack of rainfall and overall weather.

Integrating crop modelling along with real data input, planners gain significant advantages in fine tuning growing strategy. This way they can produce reliable yield, along with more strategic plans for optimal utilisation of city farming systems.

A Case Study: Crop Potential Analysis of Amsterdam Green Roofs  

Using our integrated crop modeling along with the spatial data gathering as outlined we have a very clear framework of data gathering for the study and assessment of city rooftop crop growing. When these methodologies are applied to an individual case study area such as Amsterdam you see how all these principles provide very relevant findings. Here are several details and specifics that outline the power of combined urban agriculture analysis:

The Rooftop Availability of Amsterdam  

Within the overall space of the Dutch city Amsterdam approximately 70.9 % of the rooftop surfaces were noted as being largely flat with around 44.5% suitable for some kind of urban farming initiative. These calculations provided around 396 hectares of potential areas for urban farming that were feasible to support some kind of conversion with regards to their structure and area size. These rooftops make up an estimated 16% of the entire urban space, so quite a large amount.

Simulating crop Yield in Amsterdam  

Within the studies crop modeling framework, various varieties were analysed focusing on varieties suited to urban environment: bean, broccoli, cabbage, cauliflower, leek, lettuce, onion, pea, spinach and strawberries. Analysis showed the range for yields within the simulated output for those that have the most potential including cabbage showing an impressive yield, followed by a series of high performing varieties with some variations depending on planting choice. Some showed particularly water efficiency including Lettuce as opposed to a crop like Pea which did not demonstrate particularly strong performance during simulated trials. In summation:

• Cabbage: Stands as top performer by potential harvest yields between 30.8 to 75.9 tonnes per hectare, an outstanding number for rooftop cultivation.
• Broccoli and Leeks: Also shows robust outcomes ranging 7.52 to 29.3 tonnes and 21.3 to 45.7 tonnes per hectare
• Lettuce and Onion: Follow suit ranging 14.8 to 42.7 and 8.11 to 26.0 tonnes per hectare respectively.
• Bean and Strawberry: Show more moderate potential, however will provide strong returns. ranging 8.38 –17.16 and 13.1 to 34.1 tonnes per hectare
• Lower Performing Variety: With Pea which range between a minimum harvest at 1.74 and a high potential yield of only 6.44 per hectare making it a lower value crop for the scheme.

Optimised Irrigation Strategies  

Water management is particularly essential for successful roof planting so analysing various ways to manage it forms part of urban analysis using models. Full irrigation methods for instance whilst offering full productivity for crops, can lead to over irrigation therefore less optimized methods, where irrigation water may be regulated for maximum yields and conserving water use efficiency becomes very essential for success, this is particularly true when there are variations with the local climate. Here are some water-efficient strategies that crop models allow analysis for:

• Deficit Irrigation: Providing reduced irrigation volume particularly during more water resistant periods to save resource, for some varieties the amount will have a very minor impact on performance during this stage.
• Adaptive Irrigation: Modifying water strategy as needed based on weather models to best make water usage flexible, whilst anticipating need in varying conditions for all types of growth cycle.
• Drip Systems: Implement water distribution technology to allow for high targeting at root zone level of crops that will save water through eliminating evaporation or excessive coverage.
• Monitoring: Use the modeling to predict required soil moisture needs and manage system for water delivery and make adaptations and adjustments during differing stages and to anticipate requirements of seasonal growth.

Applying these strategic plans and also looking at a full spectrum approach that may account for variables as diverse as variety selection and regional climate provides better ways of adapting to diverse regional urban environments.

From Potential to Action  

The urban rooftop analysis and planning we have looked at shows not only the immense opportunity for rooftop farming but demonstrates a methodology that converts theoretical numbers and possibilities into well founded realistic and viable programs. It gives several points that decision-makers may draw useful direction from:

Crop Selection Guidance  

Selecting suitable varieties is particularly essential for maximum output on an urban farm, crop models and suitability mapping gives detailed analysis and gives practical guidance on choosing variety as mentioned above. For Amsterdam Cabbage would prove particularly beneficial compared with for instance Pea that should perhaps be excluded based on crop yields.

Strategic Resource Planning  

Water systems can be managed more precisely. Urban food-production plans benefit substantially when incorporating irrigation strategies along with data driven planting selections. Such a combination makes sustainable urban agricultural strategies, making the systems resilient when responding to issues like drought or the changing local climate conditions.

Policy Advice and Planning  

The method demonstrated that there are many viable city wide projects that when informed with a planning stage may integrate the systems for better urban community growth alongside city level agriculture planning that enhances public spaces in the city and promotes environmental and wellbeing sustainability within population hubs. The kind of city level planning and use of models would enhance sustainable programs by supporting them from conceptualisation all the way to long term community development.

Conclusion  

We have now analysed combining methods in geographic and agricultural tech through spatial evaluation with sophisticated modelling we gain new tools in the development and assessment of urban agriculture systems, this is applicable to other case study areas in order to assess city urban crop viability, or to analyse an array of crops for regional variations and yields, when applied they allow urban space for food production schemes. This brings significant advantage in planning from urban farming implementation and may very possibly revolutionize food planning alongside resource usage in cities.

Urban Agriculture schemes using these advanced technical methods will increase sustainability whilst at the same time provide fresh produce for residents within communities with more resilient food system capacity in cities, promoting green environment growth, alongside health and nutritional wellbeing through food availability that provides maximum yield in optimal and strategic systems for any given area.

Integrating planning alongside practical systems to convert concepts into city action schemes through geospatial technology, and the power of crop models will lead to an innovative new future in urban space for sustainable agricultural systems that will also be more efficient than ever previously possible. The results show the power of information analysis. This kind of model driven future holds an enormous amount of untapped potential.