| Title Of The Magazine |
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS |
| Year Information |
2024 |
| KeyWord |
Boundary-field interaction network (BFINet), fine-grained boundary information, high-resolution remote sensing (RS) images, irregular agricultural field (AF) delineation |
| Authors |
Hang Zhao, Jiang Long, Miao Zhang, Bingfang Wu, Chenxi Xu, Fuyou Tian, Zonghan Ma |
| Intro |
Current agricultural field (AF) delineation methods
using high-resolution remote sensing (RS) images encounter
two primary challenges: 1) the interactions between boundary
features and field features are often overlooked, resulting in
imprecise field boundaries and 2) the efficacy of delineating
AFs with fuzzy boundaries, irregular shapes, and small sizes in
mountainous and hilly regions necessitates systematic evaluation.
To deal with these challenges, we propose a boundary-field interaction
network, namely, BFINet, leveraging multitask learning
techniques for AF delineation. BFINet comprises two branches:
a core branch for AF delineation and an auxiliary branch
for boundary prediction that furnishes fine-grained boundary
information to enhance geometric feature learning. To model
the interactions between boundary semantics derived from lowand
high-level semantics obtained from the field extraction
branch, we introduce a semantic interaction module (SIM),
facilitating AF identification in complex terrains. A boundary
enhancement module is integrated to refine spatial details of highlevel
semantics, thereby alleviating boundary fuzziness. We also
design a dense multibranch fusion module (DMFM) to augment
the semantic representation of BFINet’s multiscale information
for various fields. Extensive experiments were conducted on
these datasets from Hunan (HN) and Chongqing (CQ) in China,
featuring small AFs with irregular shapes and fuzzy boundaries,
and compared BFINet with five existing AF delineation methods.
Our findings indicate that BFINet excelled in identifying diverse
AFs, achieving superior attribute and geometric accuracies over
competing methods. It effectively delineated AFs with various
sizes and shapes while minimizing interference from other ground
objects. |
| Links To Magazines |
https://doi.org/10.1109/LGRS.2024.3448628 |
English
中文