Biosphere

Retrieval approaches of vegetation traits from imaging spectroscopy data

This slide collection focusses on quantification using regression analysis and RTMs. Following a short introduction about radiance regime of vegetation, we provide an overview about retrieval methods of vegetation bio-geophysical and biochemical traits from imaging spectroscopy data. Retrieval methods can be classified into the following four methodological categories: (1) parametric & (2) nonparametric regressions, (3) RTMs, and (4) hybrid methods. Further, emulation and quantification of uncertainties will be briefly discussed in this lecture.

Regression based mapping of forest aboveground biomass

This tutorial focuses on mapping forest Aboveground Biomass (AGB) from simulated EnMAP imagery. The slide collection provides the theoretical foundation for the tutorial, including general introductions into AGB, how it’s used, and why it’s important, as well as regression-based mapping of AGB using optical remote sensing data. The practical provides hands-on training for working with the EnMAP-Box, including a basic introduction into its functionalities, including built-in tools such as ImageMath, Scatterplot, and the Regression Workflow.

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SAR Handbook

The SAR Handbook: Comprehensive Methodologies for Forest Monitoring and Biomass Estimation is the culmination of a two-year collaboration between NASA SERVIR and SilvaCarbon. Five trainings, led by six SAR subject matter experts, were held at hubs throughout the SERVIR network. The topics of these trainings included SAR basics, SAR for forest change detection, forest height estimation, biomass estimation, mangrove monitoring, and sampling design. Each of these training topics are covered in a SAR Handbook chapter, which includes the theoretical basics and applied exercises. You can download the entire SAR Handbook (PDF) below.

Biomass

Biomass is a crucial parameter in the estimation and quantification of the global carbon cycle. In this lesson the estimation of above ground biomass from SAR data is presented. Several SAR based estimation techniques are introduced and compared to other biomass measurement techniques. Furthermore, numerous application examples of SAR data in biomass estimations on different scale levels are given.

Agriculture

The module “Agricultural Applications with SAR Data” provides information about the potentials and limitations of SAR data for farming activities. Relevant sensor and target parameters affecting the radar backscatter are explained and their influence on the analysis potential is described. Furthermore, several application examples are presented. The lesson is concluded with a comprehensive literature review for further reading.