Implementing Integrated Land Use Planning: A step-by-step guide for rural areas
PRACTITIONER’S GUIDE: STEP 4
PART 5
4.2. KEY QUESTIONS
What data are needed and available for an adequate characterization of the planning area, its uses, and users?
Data requirements depend on the nature of the planning exercise and the planning level. In most cases—and at each level—required data will include a mix of those described in Section 4.1.
At national level, a wide range of maps, statistical data, and information systems is usually available to support planning efforts. Often, this information is centralized in a GIS. The main challenge is to ensure that the data remain up to date and that source institutions share their data with the central planning authority. Legal agreements are often the best way to secure such data sharing.
In many countries, biophysical information (e.g., soil or topographic maps) exists but is not freely accessible due to intellectual property rights held by ministries or national institutes. In such cases, it may be necessary to establish a data access protocol with the relevant institutions before initiating land use planning activities.
How to deal with data gaps?
The more localized the area of interest, the less likely that all necessary data will be readily available. This increases the need to generate new information specific to the planning project.
One way to address data gaps is to use proxy data from regional or global maps at a coarser scale. This approach can be effective for features that do not vary significantly across space, such as interpolated climate maps. However, using mapping units from reconnaissance-level or, worse, exploratory-level maps for features with high spatial variability—such as soils—is unsuitable, particularly when these features are tied to localized landscape positions.
Where data gaps are significant, it is preferable to fund additional surveys or data acquisition efforts, such as biophysical, social, or integrated surveys, or the procurement of satellite imagery, if the budget permits. At local level, combining participatory fieldwork (see Section 4.1.4.1) with high-resolution satellite imagery offers a cost-effective way to generate planning data. This approach also increases the relevance and accuracy of the information, given its close alignment with actual land users.
4.3. ACTIVITIES
During Step 4, the Land Use Planning Task Force must carry out a set of activities tailored to the planning levels involved in the land use planning project:
- Compile relevant data for the biophysical characterization of the land, including thematic reports, station data, time series, maps, GIS datasets, satellite imagery, aerial photographs, etc.
- Compile relevant data on land users and other stakeholders, covering categories, functions, livelihoods, interests, socio-economic status, power relations, poverty levels, and more.
- Assess data sufficiency: Determine whether existing data are adequate for the planning exercise. If not, define the need for additional thematic surveys and prepare the technical specifications, identify required expertise, and estimate budgets for these surveys.
- Identify potential agents (institutions or private sector actors) capable of conducting recommended studies or providing the necessary data and equipment.
- Supervise and formally approve a comprehensive characterization of both land and land users in the planning area, ensuring each biophysical and socio-economic theme is addressed at the appropriate level of detail required for the planning exercise.
4.4. DELIVERABLES
The main output is a technical characterization report, providing thematic detail sufficient for the planning exercise—but not exceeding its requirements. The report should be structured to fit the planning level and include the following sections:
- Overview of the major land uses in the study area
- Subdivision into land units, with a summary of potentials and constraints (see example in Figure 18)
- Economic characteristics of the land use and production systems in the area
- Results of stakeholder characterization studies
- Description of identified data gaps
- Recommendations, specifications, and budgets for any additional studies, fieldwork, or acquisition of data/equipment
- Identification of agents (institutes or private sector actors) to conduct the recommended studies or provide data/equipment
4.5. TOOLS
4.5.1. Data tools
Climate
- WORLDCLIM: Global average monthly climatic data at 1 km resolution, including downscaled projections from the latest IPCC models. Particularly useful for national and sub-national assessments of minimum/maximum temperature and precipitation. Requires GIS software and climate expertise to work with downscaled projections.
- CCAFS-CLIMATE: Global raster data for key climatic variables (monthly maximum, mean, and minimum temperature, precipitation) at 1 km resolution, covering periods from the 1980s to 2100. Suitable for climate change impact assessment at national level. Requires GIS and climate expertise.
Topography
- SRTM: Global Digital Elevation Model (DEM) data at 90 m and 30 m resolution. Enables extraction of elevation, contours, slopes, aspect, and streamlines in areas lacking detailed topographic coverage. Requires GIS software.
Soils
- ESDAC: Soil-related datasets for Europe at 1 km, 500 m, and 100 m resolution. Requires GIS software.
- HWSD: Global raster layers of soil associations with an MS Access soil attribute database. Contains estimated proportions of component soils and classes for key soil characteristics. Reliability varies by country depending on the source map detail. Requires GIS software.
- ISRIC_SOILS: Geo-referenced global soil profile data and attributes. Requires soil expertise.
- AFSIS: A regional subset of ISRIC’s SoilGrids database for Africa, offering digital soil property data at 250 m resolution. Data derived through statistical models integrating field/lab data with covariates (DEM, geological maps, climate, satellite imagery). Reliability at local levels is variable. Requires GIS and soil expertise.
Statistics
- FAOSTAT: Free access to national-level food and agriculture data for over 245 countries/territories, from 1961 to the most recent year.
Land cover
- CCI_LC: Annual global land cover maps at 300 m resolution from 1992 to 2015. Requires GIS software.
- Copernicus_LC: Global land cover maps at 100 m resolution from 2015 to 2019. Data are downloadable in 20°x20° tiles. Requires GIS software.
- GFW: High-resolution global datasets for assessing and monitoring forest resources at national level. Requires GIS software.
Population and livelihoods
- L-ZONES: Maps and descriptions of livelihood zones in ~30 countries (mostly Africa), integrating socio-economic and biophysical factors.
- WORLDPOP: Global spatial estimates of population attributes at 1 km resolution, along with development and health indicators for selected countries (mostly Africa). Requires GIS software.
4.5.2. Case study
- ILC_ID: Case study from Indonesia on participatory mapping of customary forest use, evaluating methodological, social, and institutional outcomes.
4.5.3. Guideline tools
- COMAP: Informal community mapping tool for non-professionals, focused on local infrastructure, especially water and sanitation, while also addressing land tenure, employment, and housing.
- ELMO: Assists in understanding social and economic drivers behind farmers’ land use decisions, capturing preferences, perceptions, and land management trade-offs.
- FUTURE_LAND: Offers ideas for data collection on land, land use, and land users in Step 4.
- ILC_PM: Overview of community mapping technologies, combining PRA methods (interviews, sketch-mapping) with GPS, GIS, satellite imagery, and 3D modeling to support land rights.
- LADA_LOC: Guidelines for assessing human-induced land degradation at local level in collaboration with communities.
- LADA-WOCAT QM: Questionnaire and guideline tool for national/sub-national assessment of land degradation and potential remediation, integrated with GIS using a land use systems framework.
- PLUD: Includes guidelines on negotiation platform development (Step 6), and explanation of Economic-Ecological Zones (EEZ).
- PMAP_ECOS: Method for participatory use of Google Earth Pro imagery by local communities to map resource features and ecosystem services. Requires printed maps for field use and GIS for digitization.
- SEAGA: Handbook for participatory assessment of village resources, livelihoods, and stakeholder priorities.
- SPMLI: Guide to help communities interpret different maps (satellite, topographic, land use/cover) in relation to real landscapes, supporting sustainable landscape planning.
- VSA: Field guide for rapid soil quality appraisal using visual scoring and simple household tools.
| CHECKLIST | |
| Step 4 Characterize the land, its uses and users | |
| Responsibility | Land use planning task force |
| Key questions | What data are needed and available for an adequate characterization of the planning area, its uses and users? |
| How to address data gaps? | |
| Activities | Compile relevant data for the biophysical characterization of the land (e.g. thematic reports, station data, time series, maps, GIS data, satellite imagery, aerial photos). |
| Assess whether existing data are sufficient; if not, prepare technical specifications, identify required expertise, and estimate budgets for additional surveys. | |
| Conduct a comprehensive characterization of the land (climate, geology, soils, water resources, land use, natural vegetation, fauna, pests/diseases) at a detail appropriate to the planning exercise. | |
| Identify potentials and constraints of different land tracts under relevant land use/management systems. | |
| Identify land use types or land improvements with potential from a biophysical perspective. | |
| Deliverable | Comprehensive technical characterization report, with thematic detail up to, but not exceeding, the needs of the planning exercise. |
| Tools | Biophysical data: AFSIS, CCAFS-CLIMATE, ESDAC, HWSD, ISRIC_SOILS, SRTM, WORLDCLIM Statistical/population data: FAOSTAT, WORLDPOP, L-ZONES Mapping/land cover: CCI_LC, COMAP, Copernicus_LC, GFW, PMAP_ECOS, SPMLI Degradation/land use: LADA_LOC, LADA-WOCAT QM, PLUD, VSA Participatory tools: ELMO, FUTURE_LAND, SEAGA, ILC_PM, ILC_ID |