Rodrigo Peçanha Demonte Ferraz

Remote sensing and cropping practices: a review.

For agronomic, environmental, and economic reasons, the need for spatialized information about agricultural practices is expected to rapidly increase. In this context, we reviewed the literature on remote sensing for mapping cropping practices. The reviewed studies were grouped into three categories of practices: crop succession (crop rotation and fallowing), cropping pattern (single tree crop planting pattern, sequential cropping, and intercropping/agroforestry), and cropping techniques (irrigation, soil tillage, harvest and post-harvest practices, crop varieties, and agro-ecological infrastructures). We observed that the majority of the studies were exploratory investigations, tested on a local scale with a high dependence on ground data, and used only one type of remote sensing sensor. Furthermore, to be correctly implemented, most of the methods relied heavily on local knowledge on the management practices, the environment, and the biological material. These limitations point to future research directions, such as the use of land stratification, multi-sensor data combination, and expert knowledge-driven methods. Finally, the new spatial technologies, and particularly the Sentinel constellation, are expected to improve the monitoring of cropping practices in the challenging context of food security and better management of agro-environmental issues.

Assessing Ecosystem Integrity in the Brazilian Amazon Rainforest to Indicate Biodiversity Loss and Highlight Areas for Adaptation Policies

Ecosystem integrity (EI) may be defined as an equilibrium state of a given natural system able to self-regulate throughout many functional processes. The concept of biodiversity is quite diverse, and it is related to different levels of biological systems ranging from the level of genes, species taxonomic richness to functional groups. In this way, depending on the approach, several indicators, conceptually unrelated, can be used to characterize and quantify the biodiversity of a given natural system. However, in practical terms, the biodiversity, as a characteristic of ecosystems, is an indicator of the ecosystem´s stage regarding its pristine conditions. Then, Ecosystem Integrity has emerged as an important indicator to assess the relationship between biodiversity loss and the impacts on ecosystem services in tropical forests, once EI represents a connection between biodiversity and the ability of ecosystems to maintain the self-organization process. The objective of this chapter is to present a methodological approach developed for generating an Ecosystem Integrity index at regional scale, for different phyto-physiognomies patterns of landscapes, using a probabilistic model based on Bayesian Belief Networks (BBN), and totally free web-available satellite products. The methodology was applied to Brazil’s Legal Amazon region. The results show that it is possible to quantify areas of the Amazon rainforest with high or low Ecosystem Integrity. Using the same Bayesian network, with updated satellite data, it becomes possible to monitor the EI over time, and may even serve to establish a monitoring protocol and planning of mitigation/adaptation procedures.

Interoperability among Heterogeneous Geographic Objects

The integration of geographic objects stored as distinct data sources with heterogeneous syntactic and semantic structures has been target for researchers that with computing systems in distributed environment of geoprocessing over the last years. This fact happens owing to an increasing need for information exchange processed by those generators of geographic data.