Manual of Landscape Analysis: Volume 2: Procedures for the execution of the quality control of land use and land cover mapping.
Abstract
The National Forest Inventory (IFN-BR) aims to inform the formulation and implementation of public policies for the development, use and conservation of forest resources, as well as the management of these resources, through sufficient, reliable and periodically updated information collected in the field. In this way, the overall objective of the National Environmental Policy is divided into preservation, improvement and recovery of the environment. In order to implement actions related to such objectives, diagnostic and analytical tools are required to map and evaluate ecosystems and the respective services provided in their territories, both spatially explicit. Hence the need to include spatial data and indicators in the analysis. In this evaluation, it is also necessary to translate the results of technical-scientific approaches into information comprehensible for the implementation of public policies and decision making, which can be done through maps, indicators, reports and graphs. Thus, Embrapa Florestas, together with the Brazilian Forest Service (SFB) and supported by the Food and Agriculture Organization of the United Nations (FAO) and the Inter-American Development Bank (IDB), developed a methodology for the spatial analysis of structure in the context of IFN-BR. The objective of the so-called Geospatial Component within the IFN-BR project, over the course of the different editions, is to observe the dynamics of forest use through orbital images, at scales compatible with national and state interests and using indicators such as changes in land use and forest fragmentation. In this way, information must be generated on the importance and quality of forest resources in relation to other land uses, in landscape scale, highlighting their functions, quality and incidental pressures, to subsidize the formulation of public policies that are the region and its scale of approach. Landscape analysis complements two other components of the IFN-BR, field data collection and socioeconomic survey, and is intended to monitor the forest component on a landscape scale over time. In this context, the so-called Landscape Sample Units (UAPs), through which the IFN-BR Geospatial Component is implemented, are designed to offer a tool that allows the user to view aspects of the landscape in the form of indicators and their respective indices. The UAPs are permanent sampling areas of 100 km2, distributed systematically in a grid of 40 km × 40 km over the whole national territory, making a total of approximately 5500 units. All contain an IFN-BR Field Sampling Unit, in the form of a conglomerate, located in its geometric center. Thus, the strategy adopted was to develop the methodology of all IFN-BR components with a view to their integration and subsequent joint analysis. Since they provide the possibility both of static analyzes, that is, in just one date, how much dynamics, when the indices are calculated for successive occasions, the UAPs constitute units of diagnosis and monitoring. The basis for calculating landscape indexes and subsequent analyzes is the map of land use and coverage obtained through object-oriented classification and analysis of images. Thus, the indicators and indexes of the landscape allow to establish an integrated diagnosis of each UAP that, in turn, reflects a certain combination of biogeoclimatic characteristics (territorial class or ecoregion), associated with anthropic or natural factors of influence, occurring in that locality. Despite the use of sophisticated techniques for thematic mapping, some limitations are still encountered, such that, in classifications resulting from automated processes, such as the methodology used in the elaboration of land use and land cover maps in the IFN- BR, errors resulting from complex interactions between landscape spatial structures, sensor resolution, preprocessing algorithms and classification procedures may occur. Thus, the quality of land use and land cover maps.