Multisensoral Topsoil Mapping in the Semiarid Lake Manyara Region, Northern Tanzania

Abstract

This study pursues the mapping of the distribution of topsoils and surface substrates of the Lake Manyara area of northern Tanzania. The nine soil and lithological target classes were selected through fieldwork and laboratory analysis of soil samples. High-resolution WorldView-2 data, TerraSAR-X intensity data, medium-resolution ASTER spectral bands and indices, as well as ENVISAT ASAR intensity and SRTM-X-derived topographic parameters served as input features. Objects were derived from image segmentation. The classification of the image objects was conducted applying a nonlinear support vector machine approach. With the recursive feature elimination approach, the most input-relevant features for separating the target classes were selected. Despite multiple target classes, an overall accuracy of 71.9% was achieved. Inaccuracies occurred between classes with high CaCO3 content and between classes of silica-rich substrates. The incorporation of different input feature datasets improved the classification accuracy. An in-depth interpretation of the classification result was conducted with three soil profile transects.

Hyper-temporal remote sensing for digital soil mapping: Characterizing soil-vegetation response to climatic variability

“…DSM studies that utilize RS account for temporal variability in different ways and can be 127 generally organized into four categories according to the number of images used: mono-temporal, bi-128 temporal, multi-temporal, and hyper-temporal. 129 7 of bare soils which requires the removal of all non-soil pixels (e.g., vegetation, water) prior to model 137 development (Bachofer et al, 2015;Dutta et al, 2015;Nawar et al, 2015;Shabou et al, 2015). 138…”

State of the Art in Paleoenvironment Mapping for Modeling Applications in Archeology—Summary, Conclusions, and Future Directions from the PaleoMaps Workshop

“…Hence, site location analysis is usually a combination of multi-variate statistics and spatial continuous datasets that have been prepared by advanced GIS applications [31,32]. For example, digital elevation data of different origin and on different scales are utilized to derive topographic indices describing certain processes or characteristics of geomorphologic, geologic, climatic, hydrologic, vegetation or strategic circumstances [33][34][35][36][37][38]. In three case studies from Italy (see Figure 6) and Eastern Africa, we illustrate what DEMs, remotely sensed data, detailed terrain analysis, data mining technologies and geophysical methods tell us about Landscape pattern and how their integration might help to understand, and to reconstruct paleo-landscapes [34,[39][40][41][42].…”

Ten Years of Experience with Scientific TerraSAR-X Data Utilization

“…A smaller share of proposals (12 percent) concentrate on soil mapping. Here, high-resolution X-band data are utilized for top-soil mapping [135], soil surface texture [136] and the investigation of erosion and sedimentation processes [137]. Other proposals assess the impact of ground water extraction [138].…”