Abstract
Accurate mapping of agricultural fields is needed for many purposes, including irrigation decisions and cadastral management. This paper is concerned with the automated mapping of cropland strips that are common in the North China Plain. These strips are commonly 3–8 m in width and 50–300 m in length, and are separated by small ridges that assist with irrigation. Conventional surveying methods are labor-intensive and time-consuming for this application, and only limited performance is possible with very high resolution satellite images. Small Unmanned Aircraft System (sUAS) images could provide an alternative approach to ridge detection and strip mapping. This paper presents a novel method for detecting cropland strips, utilizing centimeter spatial resolution imagery captured by sUAS flying at low altitude (60 m). Using digital surface models (DSM) and ortho-rectified imagery from sUAS data, this method extracts candidate ridge locations by surface roughness segmentation in combination with geometric constraints. This method then exploits vegetation removal and morphological operations to refine candidate ridge elements, leading to polyline-based representations of cropland strip boundaries. This procedure has been tested using sUAS data from four typical cropland plots located approximately 60 km west of Jinan, China. The plots contained early winter wheat. The results indicated an ability to detect ridges with comparatively high recall and precision (96.8% and 95.4%, respectively). Cropland strips were extracted with over 98.9% agreement relative to ground truth, with kappa coefficients over 97.4%. To our knowledge, this method is the first to attempt cropland strip mapping using centimeter spatial resolution sUAS images. These results have demonstrated that sUAS mapping is a viable approach for data collection to assist in agricultural land management in the North China Plain.
Highlights
Cropland strips are long and narrow agricultural parcels that are common in parts of China and India [1]
This study has investigated the degree to which cropland ridges and strips in the North China Plain (NCP) can be identified from centimeter ground sampling distance (GSD) images acquired by a Small Unmanned Aircraft System (sUAS)
This study reports on an effort to automatically extract typical cropland strips from cm spatial resolution imagery captured by a small UAS mounted on a consumer-level digital camera at one point in time
Summary
Cropland strips are long and narrow agricultural parcels that are common in parts of China and India [1]. Cropland strips are typically separated by ridges that mark ownership or management boundaries and aid in irrigation [3]. The ridges are commonly 30–40 cm in width and 10–20 cm in height. These dimensions aid in efficient use of water during flood irrigation, which has been adopted for more than 90% of cropland in this region [4]. The elongated shapes of the cropland strips, combined with raised ridges between the strips, guide the flow of irrigation water very efficiently. Each cropland strip has a couple of adjacent ridges as its boundary. Cropland ridges have an elongated structure and obvious elevation differences with their surroundings. The linear nature of cropland ridges is similar to roads, which are recognized in images. Road detection methods have strong potential to be used in identifying ridges
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