This paper introduces WaterGPT, a language model designed for complex multimodal tasks
in hydrology. WaterGPT is applied in three main areas:(1) processing and analyzing data …

Deep learning models have achieved great success in water body extraction (WBE) from
remote sensing images. However, the existing deep learning-based extraction methods …

We propose an adaptive fine-tuning algorithm for multimodal large models. The core steps
of this algorithm involve two stages of truncation. First, the vast amount of data is projected …

Surface water body (WB) as one of the world's most critical natural resources, plays a
significant role in forming and sustaining life. Therefore, accurate extraction of WB is …

Automated water body (WB) extraction is one of the hot research topics in the field of remote
sensing image processing. To address the challenges of over-extraction and incomplete …

In recent years, with the intensification of global climate change and the increasing
frequency of natural disasters, flooding has become a widespread concern worldwide. Deep …

Water body extraction from remote sensing images in complex backgrounds is crucial for
environmental monitoring, disaster management, and urban planning. Although existing …

Surface water is of critical importance to the ecosystem, agricultural production and
livelihoods of people in the arid regions of Africa. The surface water is characterized by …

Multispectral remote sensing satellite images exhibit characteristics such as small objects,
complex scenes, significant changes in object scale, and difficulty in distinguishing regions …