# Estimating Rice Cropping Area and Analyzing Land Use and Land Cover Changes in Jiangsu Province Using Multispectral Satellite Imagery

## TL;DR

This study uses satellite imagery and machine learning to track rice farming and land use changes in Jiangsu Province from 2018 to 2023, showing a decline in rice fields due to urbanization and climate change.

## Contribution

The study introduces a novel application of random forest machine learning on Google Earth Engine to estimate rice cropping patterns and analyze land use changes in Jiangsu Province.

## Key findings

- Rice cropping areas in Jiangsu decreased by 0.92% from 2018 to 2023, with significant declines in eastern and southern regions.
- Land use changes show a 4.13% reduction in cropland, with much of it converted to built-up areas and water bodies.
- The random forest model achieved 77.33% to 93.55% accuracy in classifying land use, indicating reliable results.

## Abstract

Climate change and growing populations are major challenges for food security. Understanding single-season rice (SSR) growth patterns and how much area changes over time is essential for sustaining rice distribution patterns and ensuring food security. This study utilized ground trothing data with the remote sensing (RS) technique for estimation of the SSR pattern in Jiangsu Province. A total of 1700 rice and 470 non-rice points were collected during the field visit in April–September 2023 across Jiangsu Province. The current study employed advanced machine learning (ML) and the random forest (RF) model using Google Earth Engine (GEE). This study evaluates the SSR cropping area, including the Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), and land use–land cover (LULC) variation from 2018 to 2023 with different satellites. The results of NDVI show an increasing trend with mean values rising from 0.30 in 2018 to 0.42 in 2023. Additionally, higher mean values of LST were noticed in 2020 by 14.4 °C and in 2022 by 14.1 °C. Furthermore, the SSR area has significantly changed, mostly in the eastern and southern regions of Jiangsu Province, from 2018 to 2023. The higher rice cropping area decreased by 1.42% in 2019 compared to 2018, while the total reduction over the 2018–2023 period was 0.92%. Total cultivated crop areas continued to decline because most of the crop areas changed into built-up areas, resulting in a total variation of 2.75% from 2020 to 2023. The overall accuracy of RF model range was 77.33% to 93.55% with a Kappa coefficient of 0.55 and 0.87, indicating moderate to substantial classification agreement across the study period. The results of LULC indicate that the crop area decreased by 4.13% from 2018 to 2023, and major areas were converted into water bodies and built areas. In conclusion, the single-season cropping pattern decreased during the study period, accompanied by a reduction in total cropland area in Jiangsu Province. Therefore, these findings highlight the influence of urbanization and climate change on agricultural land and emphasize adaptive strategies in Jiangsu Province to ensure food security in the face of environmental challenges.