  Objective: The main objective of this paper is to construct a distributed
clustering algorithm based upon spatial data correlation among sensor nodes and
perform data accuracy for each distributed cluster at their respective cluster
head node. Design Procedure/Approach: We investigate that due to deployment of
high density of sensor nodes in the sensor field, spatial data are highly
correlated among sensor nodes in spatial domain. Based on high data correlation
among sensor nodes, we propose a non -overlapping irregular distributed
clustering algorithm with different sizes to collect most accurate or precise
data at the cluster head node for each respective distributed cluster. To
collect the most accurate data at the cluster head node for each distributed
cluster in sensor field, we propose a Data accuracy model and compare the
results with Information accuracy model. Finding: Simulation results shows that
our propose Data accuracy model collects more accurate data and gives better
performance than Information accuracy model at the cluster head node for each
respective distributed cluster in our propose distributed clustering
algorithm.Morover there exist a optimal cluster of sensor nodes which is
adequate to perform approximately the same data accuracy achieve by a cluster.
Practical Implementation: Measuring humidity and moisture content in an
agricultural field, measuring temperature in physical environment. Inventive
/Novel Idea: A distributed clustering algorithm is proposed based on spatial
data correlation among sensor nodes with Data accuracy model.
