Die chronologische Liste zeigt aktuelle Veröffentlichungen aus dem Forschungsbetrieb der Hochschule Weihenstephan-Triesdorf. Zuständig ist das Zentrum für Forschung und Wissenstransfer (ZFW).
In developing countries, data gaps are common and lead to uncertainties in land cover change analysis. This study demonstrates how to mitigate uncertainties in modeling land change in the Ci Kapundung upper water catchment area by comparing the outcomes of two simulation phases. A conventional cellular automata (CA)–Markov model was complemented with a multilayer perceptron (MLP) to project future land cover maps in the study area. The CA–Markov–MLP model results in high uncertainties in forested sites where a data gap is apparent in the input data (land cover maps and driver variables) and parameters. The results show that the model accuracy is improved from 47.90% in the first phase to 81.36% in the second phase. Both first and second phases integrate six demographic–economic and environmental drivers in the modeling, but the second phase also incorporates an updating and backdating analysis to revise the base-maps. This study suggests that uncertainties can be mitigated by linking such base-map revision process with the updating and backdating analyses using remote sensing datasets retrieved at different times.
Visible-Near-Infrared Scanners enable a noninvasive prediction of quality properties of fruit and vegetable based on previously created models. A combination of NIR scanners andmachine learning methods can lead to economic improvements and reduction of food waste by strategies like "first expired, first out" and dynamic pricing. In order to identify parameterscapable of showing dynamic postharvest development, three horticultural products with different postharvest behavior (e. g. strawberry, table grape and mango) were chosen formorphological and statictical analysis. According to the results, a graduation of spectra in correspondence to the day of measurement was noticeable for strawberry regarding the a-value as well as presumingly mass loss for both mango and table grape. Furthermore, a PLS model for the a-values r2cv = 0.80 was developed for strawberries.
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