Multi-year time series crop mapping

Download

index.pdf

Date

2020

Author

Teke, Mustaf

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

139
views

70
downloads

Recent automated crop mapping via supervised learning-based methods have demonstrated unprecedented improvement over classical techniques. However, most crop mapping studies are limited to same-year crop mapping in which the present year’s labeled data is used to predict the same year’s crop map. Classification accuracies of these methods degrade considerably in cross-year mapping. Cross-year crop mapping is more useful as it allows the prediction of the following years’ crop maps using previously labeled data. We propose Vector Dynamic Time Warping (VDTW), a novel multi-year classification approach based on the warping of angular distances between phenological vectors. The results prove that the proposed VDTW method is robust to temporal and spectral variations compensating for different farming practices, climate and atmospheric effects, and measurement errors between years. We also describe a method for determining the most discriminative time window that allows high classification accuracies with limited data. We carried out tests of our approach with Landsat 8 time-series imagery from years 2013 to 2015 for classification of corn and cotton in the Harran Plain, and corn, cotton, and soybean in the Bismil Plain of Southeastern Turkey. In addition, VDTW was tested with corn and soybean in Kansas, the US for 2017 and 2018 with the Harmonized Landsat Sentinel data. The VDTW method improved the cross-year overall accuracies by 3% with fewer training samples compared to other state-of-the-art approaches including spectral angle mapper (SAM), dynamic time warping (DTW), time-weighted DTW (TWDTW), random forest (RF), support vector machines (SVM) and deep long short-term memory (LSTM).

Subject Keywords

Phenology., time series, crop mapping, phenology, multi-year classification, dynamic programming

URI

http://etd.lib.metu.edu.tr/upload/12625189/index.pdf
https://hdl.handle.net/11511/45409

Collections

Graduate School of Informatics, Thesis

Suggestions

OpenMETU
Core

Multi-year vector dynamic time warping-based crop mapping Teke, Mustafa; Çetin, Yasemin (2021-03-01) Recent automated crop mapping via supervised learning-based methods have demonstrated unprecedented improvement over classical techniques. Classification accuracies of these methods degrade considerably in cross-year mapping. Cross-year crop mapping is more useful as it allows the prediction of the following years' crop maps using previously labeled data. We propose vector dynamic time warping (VDTW), an innovative multi-year classification approach based on warping of angular distances between phenological...
Multimodal concept detection in broadcast media: KavTan SOYSAL, Medeni; Alatan, Abdullah Aydın; TEKİN, Mashar; ESEN, Ersin; SARACOĞLU, Ahmet; Acar, Banu Oskay; Ozan, Ezgi Can; Ates, Tugrul K.; SEVİMLİ, Hakan; SEVİNÇ, Muge; ATIL, Ilkay; Ozkan, Savas; Arabaci, Mehmet Ali; TANKIZ, Seda; KARADENİZ, Talha; ÖNÜR, Duygu; SELÇUK, Sezin; Alatan, A. Aydin; Çiloğlu, Tolga (Springer Science and Business Media LLC, 2014-10-01) Concept detection stands as an important problem for efficient indexing and retrieval in large video archives. In this work, the KavTan System, which performs high-level semantic classification in one of the largest TV archives of Turkey, is presented. In this system, concept detection is performed using generalized visual and audio concept detection modules that are supported by video text detection, audio keyword spotting and specialized audio-visual semantic detection components. The performance of the p...
Multi target tracking with acoustic power measurements using emitted power density Orguner, Umut (null; 2010-07-29) This paper presents a method to achieve multi target tracking using acoustic power measurements obtained from an acoustic sensor network. We first present a novel concept called emitted power density (EPD) which is an aggregate information state that holds the emitted power distribution of all targets in the scene over the target state space. It is possible to find prediction and measurement update formulas for an EPD which is conceptually similar to a probability hypothesis density (PHD). We propose a Gaus...
Multiple Description Coding of 3D Dynamic Meshes Based on Temporal Subsampling Bici, M. Oguz; Akar, Gözde (2010-01-21) In this paper, we propose a Multiple Description Coding (MDC) method for reliable transmission of compressed time consistent 3D dynamic meshes. It trades off reconstruction quality for error resilience to provide the best expected reconstruction of 3D mesh sequence at the decoder side. The method is based on partitioning the mesh frames into two sets by temporal subsampling and encoding each set independently by a 3D dynamic mesh coder. The encoded independent bitstreams or so-called descriptions are transm...
Compressive sensing imaging at Sub-THz frequency in transmission mode Özkan, Vedat Ali; Menteşe, Yıldız; Takan, Taylan; Şahin, Asaf Behzat; Altan, Hakan (Springer, Dordrecht, 2017-01-01) Due to lack of widespread array imaging techniques in the THz range, point detector applications coupled with spatial modulation schemes are being investigated using compressive sensing (CS) techniques. CS algorithms coupled with innovative spatial modulation schemes which allow the control of pixels on the image plane from which the light is focused onto single pixel THz detector has been shown to rapidly generate images of objects. Using a CS algorithm, the image of an object can be reconstructed rapidly....

Citation Formats

M. Teke, “Multi-year time series crop mapping,” Thesis (Ph.D.) -- Graduate School of Social Sciences. Information Systems., Middle East Technical University, 2020.