*Article* **A Remote Sensing-Based Approach to Management Zone Delineation in Small Scale Farming Systems**

#### **Davide Cammarano 1,\*,**†**, Hainie Zha 2, Lucy Wilson 3, Yue Li 2, William D. Batchelor 4 and Yuxin Miao 5,\***


Received: 18 September 2020; Accepted: 7 November 2020; Published: 12 November 2020

**Abstract:** Small-scale farms represent about 80% of the farming area of China, in a context where they need to produce economic and environmentally sustainable food. The objective of this work was to define managemen<sup>t</sup> zone (MZs) for a village by comparing the use of crop yield proxies derived from historical satellite images with soil information derived from remote sensing, and the integration of these two data sources. The village chosen for the study was Wangzhuang village in Quzhou County in the North China Plain (NCP) (30◦5155" N; 115◦0206" E). The village was comprised of 540 fields covering approximately 177 ha. The subdivision of the village into three or four zones was considered to be the most practical for the NCP villages because it is easier to manage many fields within a few zones rather than individually in situations where low mechanization is the norm. Management zones defined using Landsat satellite data for estimation of the Green Normalized Vegetation Index (GNDVI) was a reasonable predictor (up to 45%) of measured variation in soil nitrogen (N) and organic carbon (OC). The approach used in this study works reasonably well with minimum data but, in order to improve crop managemen<sup>t</sup> (e.g., sowing dates, fertilization), a simple decision support system (DSS) should be developed in order to integrate MZs and agronomic prescriptions.

**Keywords:** site-specific nutrient management; soil brightness; satellite remote sensing; crop yield; soil fertility; spatial variability
